Engineering Innovations Volume 12

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Volume 12 of
Engineering Innovations
ISSN print 2813-0995
ISSN web 2813-1002

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Table of Contents

MDNs/FGNs/IFR Synergistic Flame Retardant for Epoxy Resin the Influence of Thermal Degradation Kinetics

Shu Yi Liu, Quan Wang, Zheng Huan Wu

Characterization Study of Wire Arc Additive Manufacturing Layer in Metal Inert Gas Welding Process

Muhammad Ivan Fanani, Renaldi Candra Saputra, Aditya Kurnia Putra, Triyono Triyono

Study on Flexural Performance of Fiber Reinforced Concrete Beams Using Glass Fiber Reinforced Polymer Bars and Steel Rebars

Karri Hemalatha, Darapureddi Ravi Prasad

Modelling and Structural Simulation of Thin-Wall Structure

Akhmat Busori, Ubaidillah Ubaidillah, Eko Prasetya Budiana, Purwadi Joko Widodo

Weight Optimization of the Electric Bus Carbody Structure

Wijianto Wijianto, Giri Fahrezy Istighfarrullah, Agus Dwi Anggono, Taurista Perdana Syawitri

Fabrication of a Potential Difference Measuring Instrument Using a Capacitive Sensor Based on aTmega328 Microcontroller

Anak Agung Ngurah Surya Mahendra Putra, Ni Nyoman Rupiasih, I. Wayan Supardi, Pandit Bhalchandra Vidyasagar

Performance Comparison of Max-Chart and AEWMA-Max Chart in Monitoring Temperature

Alfarizi Pradana Andikaputra Salman, Muhammad Ahsan, Muhammad Mashuri, Kevin Agung Fernanda Rifki

Mode Division Multiplexing Free Space Optical communication System Performance With Aperture Averaging in Atmospheric Turbulence and Various Weather Conditions.

Simbarashe Magidi, Taurayi Pondani

Keywords Index

Authors Index

The original version of this eBook is available on https://www.scientific.net/book/engineering-innovations-vol-12/978-3-0364-1691-5

Engineering Innovations, ISSN: 2813-1002, Vol. 12, pp 1-5

doi: 10.4028/p-8aqyR1

© 2025 The Author(s). Published by Trans Tech Publications Ltd, Switzerland.

Submitted:
2024-07-30

Revised:
2024-09-09

Accepted:
2024-09-09

Online:
2025-01-03

MDNs/FGNs/IFR Synergistic Flame Retardant for Epoxy Resin the Influence of Thermal Degradation Kinetics

The original version of this paper is available on https://www.scientific.net/EI.12.1.pdf

Shu Yi Liu , Quan Wang , Zheng Huan Wu

School of Mechanic and Engineering, Tianjin University of Technology and Education, Tianjin 300222, China

National Mold Product Quality Supervision & Inspection Center, Dongguan Quality Supervision Testing Center, Guangdong, Dongguan, 523841, China

The Key Laboratory of Polymer Processing Engineering of Ministry of Education, South China University of Technology, 510640, China

, wq2001126@163.com, wzh46817@163.com

Keywords: Epoxy resin; Binary synergy; Thermal degradation kinetics; thermal stability.

Abstract

The thermal degradation process of layered molybdenum disulfide nanosheets/flake graphite nanosheets/expanded flame retardants/epoxy resins (MDNs/FGNs/IFR/EP) was analyzed using thermogravimetric analysis. The effect of binary nano layered molybdenum disulfide/flake graphite nanosheets as enhancing flame retardants on thermal stability was studied. The thermal degradation kinetics activation energy of MDNs/FGNs/IFR/EP was calculated using the Coats Redfern method. The mechanism function of MDNs/FGNs/IFR/EP was determined using the Phadnis method, and the thermal degradation mechanism of MDNs/FGNs/IFR/EP was obtained. Binary nano MD/FG helps to improve the thermal stability of EP.

1 Introduction

The original version of this paper is available on https://www.scientific.net/EI.12.1.pdf

Epoxy resin(EP), due to its excellent mechanical and thermal properties, is widely used in industries such as aerospace devices, electronic packaging materials, composite materials, etc.[1] Epoxy resin is flammable, with a limit oxygen index of only and poor thermal stability. Therefore, it is usually necessary to add flame retardants (IFR) to solve this problem.[2] However, the flame retardant efficiency of expansion flame retardants is low, and the carbon layer structure is not dense, so it is often necessary to add synergists to improve their flame retardant efficiency.[3] Squamous graphite has good chemical stability and low thermal expansion coefficient, while molybdenum disulfide has excellent smoke suppression effect.[4] Using binary nano MD/FG as a synergistic flame retardant, the optimal ratio microwave stripping process was employed to prepare binary nano MD/FG, effectively reducing the amount of IFR added and improving the thermal stability of the composite material. Expanded flame retardant is an efficient environmental flame retardant. Its main action mechanism is to form a layer of carbonaceous foam layer on the material surface when the material is subjected to heat. This layer can not only insulate the heat and oxygen, but also inhibit the generation of smoke, so as to achieve the flame retardant effect [5-7]. However, UL94V-0 flame resistance can only be achieved when 30 to IRR is added to the EP. In order to avoid this effect, the use of binary nanocomposites for synergistic flame retardant has been proposed in recent years[8]. When the hexagonal boron nitride and flake graphite are simultaneously stripped, the stripped nano hexagonal boron nitride has good electrical insulation and thermal conductivity, while the graphene has high specific surface area and high temperature resistance [9-10]. Thermal degradation kinetics is an effective method to study the flame retardant property of EP. The thermal stability of EP can be evaluated by studying the mass loss rate and temperature change of EP during the heating process[11]. This article takes MDNs/FGNs/IFR/EP as the research object, and explores the different thermal degradation processes and mechanisms of three materials.

2 Experimental

The original version of this paper is available on https://www.scientific.net/EI.12.1.pdf

2.1 Materials

E51 (618) epoxy resin: Hang Zhou Wulanggang Adhesive Co., Ltd., Hang Zhou, China; Expanded flame retardant (IFR): self-made; Layered Molybdenum Disulfide (MD): Shijiazhuang Dongming New Material Technology Co., Ltd., Shi jia zhuang, China; Squamous graphite (FG): Qingdao Pingdu Fukang graphite mine., Qing dao, China; Sodium dodecyl benzene sulfonate (SDBS): Tianjin Zhiyuan Chemical Reagent Co., Ltd., Tian jin, China; Silane coupling agent (SCA): A-172, Guangzhou Zhongjie Chemical Co., Ltd., Guang zhou, China.

2.2 Preparation of EP/IFR/FGP/h-BN

Place MD and FG in a certain proportion in a small amount of ultrapure water, add ultrapure water to 500 ml , stir at high speed for 15 minutes to evenly disperse, and form a layered MD/FG two-phase suspension. Place it in a microwave reactor, with a microwave power of 600 W for stage 1 and a duration of 20 minutes; The microwave power for Stage 2 is 260 W , with a duration of 2 minutes. After allowing the microwave dried suspension to stand for 24 hours, remove the peeled MD/FG floating on the top layer and completely freeze it in a freezer at . Then, vacuum dry the frozen solid at for 24 hours to obtain MDNs/FGNs composite material. Spray SDBS/anhydrous ethanol and SCA/anhydrous ethanol onto the surfaces of MDNs/FGNs and IFR for modification. The molding formula is shown in Table 1, and MDNs/FGNs/IFR/EP is denoted as EP-1.

Table 1. Formulation of raw materials.

Sample | MDNs(wt%) | FGNs(wt%) | IFR(wt%) | EP(wt%)
EP-1 | 0.5 | 1.5 | 18 | 80

2.3 Thermogravimetric Analysis Test

The Q-50 thermogravimetric analyzer from TA Corporation in the United States was used for testing in a nitrogen atmosphere with a flow rate of . The mass of the sample is . Record the changes of the sample over time from to at heating rates of , and .

2.4 Coats-Redfern Method

By plotting the curve of , the average activation energy Ea of the entire reaction stage can be obtained from the slope, which is

2.5 Phadnis Method

The Phadnis method is a combination of differential and integral methods, which is based on the Arrhenius equation and describes the relationship between chemical reaction rate and temperature. Its expression is:

Integrating equation (2) yields another form:

Substitute the mechanism function into formula (3) in sequence, and plot '(a) against . If the selected mechanism function is appropriate, the plot of (a) against should be a straight line, thus determining the activation energy[13].

3 Results and Discussion

The original version of this paper is available on https://www.scientific.net/EI.12.1.pdf

3.1 Thermal Stability of EP Composites Materials

Figure 1 (a) shows the TG curve of EP-1, which exhibits a single-stage degradation with an inverse " s " shape. Figure 1 (b) shows the DTG curve of EP-1, which has two higher peak tips and one smaller peak tip. Therefore, the decomposition of EP-1 is divided into three stages, with a smaller peak tip appearing at 200-300. Within this temperature range, ammonium polyphosphate in IFR undergoes dehydration reaction under the influence of temperature increase, producing polyphosphate and ammonia gas. The decomposition product is pyrophosphate, which forms a char layer in EP and accelerates its decomposition[14]. The second stage involves the network breakage of large molecules in EP-1, such as epoxy groups, hydroxyl groups, side groups, and cross-linking structures, due to the influence of temperature. This reaction requires a relatively fast reaction rate; The third step is the formation of a carbon layer after the end of macromolecular fracture. As the temperature increases, the carbon layer undergoes thermal decomposition reactions, leading to structural damage and volatilization of carbon elements, ultimately becoming gas and ash[15]. The results showed that the nano layered structure of MDNs/FGNs after microwave exfoliation exhibited good dispersibility in the EP matrix, as well as strong interfacial interactions between MDNs/FGNs and the EP matrix. This played a key role in the gas barrier effect, making it difficult for heat to be transferred to the interior of the EP and slowing down its combustion rate. MDNs/FGNs have the characteristic of being difficult to decompose at high temperatures, playing a role in carbon fixation in the EP matrix.[16]

Fig. 1. TG and DTG curves of EP-1 at different heating rates.

Fig. 1. TG and DTG curves of EP-1 at different heating rates.

3.2 Coats-Redfern Method

Figure 2 shows the fitting curve of EP-1 Coats Redfern method. As the conversion rate increases, the activation energy also increases. The curing of EP-1 is divided into three stages: the first stage is , during which the activation energy gradually increases. This is because EP-1 contains nano layered MDNs with high thermal stability, which belong to high-temperature and non flammable substances; In the second stage, , the activation energy of EP-1 gradually decreases. This is due to the strong covalent bonds and weak van der Waals forces present in each layer of MDNs/FGNs after microwave stripping. Therefore, MDNs/FGNs have a layered special structure, and the nano layered MD/FG crosslinks with the molecular chains in EP. The nano layer blocks the heat release of EP during thermal degradation and effectively inhibits the gas diffusion after the cracking of and molecular chains, increasing the gas phase barrier effect; The third stage is , during which the activation energy suddenly increases because the carbon layer on the surface of EP decomposes. However, due to the presence of C and N elements in the carbon layer, the difficulty of EP thermal decomposition increases.[17]

Fig. 2. Fitting curve of Coats-Redfern method for EP and Its Composites.

Fig. 2. Fitting curve of Coats-Redfern method for EP and Its Composites.

3.3 Confirmation of Mechanism Function of EP-1

For the study of solid-state reaction systems for thermal decomposition reactions of solid substances, there are various expressions for based on the different reaction mechanisms.[18] The mechanism function is sequentially substituted into formula (3), and '(a) is plotted against . If the chosen mechanism function is appropriate, then (a) should be plotted against 1/T as a straight line, thereby determining the activation energy. Finally, by substituting the listed expressions separately, it was found that only when is linearly related to , indicating that the thermal degradation mechanism function of EP-1 is a first-order diffusion reaction, and the effect of reactant concentration on reaction rate follows the first-order reaction kinetics.

Fig. 3. Mechanism function and experimental function.

Fig. 3. Mechanism function and experimental function.

4 Conclusion

The original version of this paper is available on https://www.scientific.net/EI.12.1.pdf

The addition of IFR significantly improves the thermal stability of the composite material. The next step is to investigate the effect of adding different ratios of MDNs/FGNs/on the thermal stability of the composite material.

When the mass fraction ratio of MDNs to FGNs is , it has a good synergistic flame retardant effect on the EP/IFR composite system;

Obtain the activation energies of the three stages of the EP-1 reaction using the Coats Redfern method; .

The Phadnis method was used to determine that the thermal degradation mechanism function of EP-1 is a first-order diffusion reaction, and the effect of reactant concentration on reaction rate follows the first-order reaction kinetics.

References

The original version of this paper is available on https://www.scientific.net/EI.12.1.pdf

Yan, L, Guan, J, Wei, Z, et .al. Combination effect of ADP-intercalated kaolinite and ammonium polyphosphate on simultaneously enhancing the flame retardancy and smoke suppression of epoxy resins J. Journal of Vinyl and Additive Technology, 30(2024): 868-879.

Hu, Z, Shi, T. Application of a piperazine pyrophosphate intumescent flame retardant in thinwalled glass fiber-reinforced polypropylene materials J. Journal of Applied Polymer Science, 40(2023): 1-13.

Yang, X.H, Jiang, S.Y, Zhang, Z.Y, et .al. The preparation of ZIF-67 and its synergistic effect on fire performance of intumescent flame retardant polypropylene J. Journal of Thermal Analysis and Calorimetry, 148(2023): 9547-9560.

Zeng, G.D , Tosin, J.A, Kuang, L, et .al. A tough bio-adhesive inspired by pearl layer and arthropod cuticle structure with desirable water resistance, flame-retardancy, and antibacterial property J. International journal of biological macromolecules, 53(2023): 127669-127669.

Kim N, Bhattacharyya D. Fire reaction and post-fire impact properties of flax fibre reinforced composites containing intumescent flame retardants. Journal of Reinforced Plastics and Composites, 43 (2024):111-126.

Feng MZ, Zhang Z, Wan L, et al. Synthesis and application of novel nitrogen and phosphorus flame retardants for polypropylene. China Plastics. 37 (2023):80-86.

Wang J, Chen L, Li SJ, et al. Research Progress of Chemical Intumescent Flame Retardants. Engineering Plastics application. 50(2022):157-162.

Liu SD, Cui YY. Study on the Performance of Halogen-Free Composite Synergistic Flame Retardant Ethylene-Vinyl Acetate Copolymer. Plastics Science and Technology. 48(2020):37-41.

Hu HL, Xie WB, Li JH. Research Progress of Graphene Synergistic Flame Retardant Polymer Composites Technology & Development of Chemical Industry. 52(2023):26-30.

Wang WR, Zhang JR, Zhang WW, et al. Research Progress on the Application of Hexagonal Boron Nitride in Sample Preparation. Chemical Reagents. 52(2023):26-30.

Xu SJ, Xu ZY, Hou ZM,et al. Flame retardant and thermal degradation behaviors of epoxy resin/dops derivative composites .Materials Reports. 37(2023):259-265.

Juhaina, A,Ahmad ,F,Sameh ,H, et .al. Study the polymerization kinetics of polyaniline by UV-Vis and HPLC and determination of the thermodynamic functions using coats-redfern equation from TGA curves J. Research Journal of Pharmacy and Technology, 14(2021): 4117-4121.

Phadnis, A.B, Deshpande, V.V, Determination of the kinetics and mechanism of a solid-state reaction - a simple approach J. Thermochim.Acta., 62(1683): 361-367.

Sur, K.U, Saha, A, Datta, A, . Synthesis and characterization of stable aqueous dispersions of graphene J. Bulletin of Materials Science, 39(2016): 159-165.

Kamalipour, J, Beheshty, M.H, Zohuriaan, M.M.J. Thermal decomposition kinetic study on one-pack formulations of epoxy resin cured with novel phosphorus-containing flame retardant latent curing agents J. International Journal of Polymer Analysis and Characterization, 28(2023): 596-624.

Dong, L.Y, Hu, C.G, Song, L, et .al. A Large-Area, Flexible, and Flame-Retardant Graphene Paper J. Advanced Functional Materials, 26(2016): 1470-1476.

Du, J, Wu, Z.H, Wang, Q. Exploration of Thermal Degradation Kinetics of Epoxy Resin Composites J. Key Engineering Materials, 6253(2021): 202-206.

Menon, M, Chen, I.W. Bimaterial composites via colloidal rolling techniques 3: Mechanical properties J. Journal of the American Ceramic Society, 82(2010): 3430-3440.

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The original version of this eBook is available on https://www.scientific.net/book/engineering-innovations-vol-12/978-3-0364-1691-5

Engineering Innovations, ISSN: 2813-1002, Vol. 12, pp 7-12

doi: 10.4028/p-e6xqWP

© 2025 The Author(s). Published by Trans Tech Publications Ltd, Switzerland.

Submitted:
2023-11-18

Revised:
2024-05-27

Accepted:
2024-05-27

Online:
2025-01-03

Characterization Study of Wire Arc Additive Manufacturing Layer in Metal Inert Gas Welding Process

The original version of this paper is available on https://www.scientific.net/EI.12.7.pdf

Muhammad Ivan Fanani , Renaldi Candra Saputra , Aditya Kurnia Putra , Triyono

¹Department of Mechanical Engineering, Faculty of Engineering

Sebelas Maret University, Indonesia

@student.uns.ac.id, renaldicandrasaputra@student.uns.ac.id,

adityaputra05@student.uns.ac.id, triyono74@staff.uns.ac.id

Keywords: WAAM, Corrosion rate, Metallography, ER70S-6, Metal inert gas.

Abstract

The advent of innovative, reasonably priced additive manufacturing techniques has been facilitated by the industry 4.0 era. This study aims to characterize the ER70S-6 wire arc additive manufacturing (WAAM) layer in metal inert gas (MIG) as a result of controlled process speed, electrode type, voltage, and weld current using a three-axis automated motion framework. The study approach begins with the design and building of an automated MIG welding motion system, which includes component manufacture, assembly, calibration, and motion path testing. The specified settings modify the speed of the weld probe motion in response to manual welding parameter adjustments. The investigation continues with the characterization of single to four-layers of WAAM to know the corrosion rate, microstructure, and the Vickers hardness. Corrosion testing results showed that the single-layer of WAAM had the lowest corrosion rate, as well as the highest hardness. Whereas the four-layer had the highest corrosion rate and the lowest hardness.

Introduction

The original version of this paper is available on https://www.scientific.net/EI.12.7.pdf

Manufacturing is a process that converts raw resources into finished products. Manufacturing is divided into two categories: conventional manufacturing and modern manufacturing. Conventional manufacturing provides a cost advantage and is more accessible, but it lacks production efficiency. As a result, conventional manufacturing technology must be updated, particularly in modern sectors. Additive manufacturing (AM) is one method for improving conventional manufacturing. This is because AM is versatile, dynamic, and highly adjustable for many industrial applications [1].

AM is a manufacturing process capable of producing parts with complicated geometry for a variety of applications [1]. It can improve product quality without reducing the amount of material used in the machining process. AM can be classed according on the material's usage. Plastic, polymer, and steel are the most prevalent materials used. Wire arc additive manufacturing (WAAM) is a method of AM that produces 3D things by melting wire with an electric arc. The molten wire will be shaped layer by layer until the desired output is achieved [2]. WAAM generally uses three types of machines: MIG (metal inert gas), PAW (plasma arc welding), and TIG (tungsten inert gas) [3].

MIG is one of the WAAM methods that is superior than TIG and PAW. The advantages of the MIG process include the electrode being lured into the torch, the ability to simply change electrode types, and the ability to modify feeding speed. This study seeks to understand the characterization of the WAAM layer in MIG as a result of controlled process speed, electrode type, voltage, and weld current by a three-axis automated motion framework.

Experimental Configuration

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The material employed in this investigation was 10xx carbon steel as a substrate, along with argon gas, which is commonly used in welding. The substrate dimensions were 100 mm by 50 mm by 3 mm . The electrode utilized was the ER70S-6 type, with a diameter of 1.0 mm . The MIG welding procedure uses electric currents of 100 A . Other parameters, such as the voltage and speed of the three-axis automatic motion framework, will be set to constant values. Electrodes for this study are chosen based on market availability and the existing range that can be utilized to weld thin plates of a given thickness. The WPS (welding process specification) states that the lower current limit for low carbon steel plates with a thickness of 3 mm is 100 A . Welding with a current less than 100 A results in an unsteady arc and low penetration. In contrast, the current limit is 110 A , because welding with a current greater than 110 A causes holes in the plate. The design of this tool is depicted in Fig. 1.

Fig. 1. Wire arc additive manufacturing machine with three axis motion.

Fig. 1. Wire arc additive manufacturing machine with three axis motion.

The three-axis automated motion framework employed in this study is powered by an electrical arrangement. CAD software is used to create *stl files. Slic3r will decode the *stl file and create a G-Codes file. G-Codes files will be utilized to move the 3D axis with boards that are incorporated into Arduino. The G-codes detected by Arduino will be scanned by the motor driver. The G-Codes will subsequently be sent from the motor driver to the motor stepper. As the desired design input, the lead screw and ball screw will be rotated to produce motion in all three axes.

Prior to specimen fabrication, motion trajectory testing and refining were performed. The tests performed included straight motion tests, rectangle pattern tests, and backslash motion tests. This test makes use of a pen plotter mechanism, in which the pen is inserted and moved along the motion path according to the desired configuration settings. Time and speed measurements were taken during the motion path testing process using manual welding parameters, which were subsequently incorporated into a welding control program.

The WAAM results of one to four layers will be submitted to corrosion testing. This test employed the three-electrode polarization resistance method to test corrosion. Corrosion test performed with CorrTest CS Studio 6.3 software and CorrTest CS350M EIS hardware. The test used a range of -0.25 V to 0.25 V against corrosion potential ( ) with a scan rate of . Corrosion testing is performed by scanning V values by rotating the potentiodynamic in stages and obtaining voltage (V) and current (A) data, which are then shown on an E-I graph. From this graph plot yielded Tafel constants for the anode and cathode in the form of graph slope and corrosion current ( ), which are in the path of the intersection of the two Tafel constants. The corrosion rate is given using the formula:

The (corrosion rate per year (mpy)) will be translated into millimeters per year (mmpy). In , the constant factor is 0.1288 . measures current density in is the density in represents equivalent weight (g).

To complete the characterization study, metallographic observations and the Vickers hardness test were used to determine the level of surface hardness in each layer. For depicting how it looks microscopically, a solution of alcoholic nitrid acid was utilized. This experiment was carried out with optical microscope. The Vickers hardness test across the layer was performed on the metallographic specimens using a 500gf load. The formula for the number of hardness is as follows:

is the number of Vickers hardness, 1854.4 is a factor constant, is the force in gf, is the indentation's mean diagonal length in .

Results and Discussion

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Corrosion test uses ASTM G59 standard [4]. This test determines the resistance of materials to oxidation when exposed to an external voltage that causes corrosion. Potential corrosion ( ) was calculated using the amount of negative charge produced by the metal in a NaCl solution, which creates chloride ions. These ions will harm the metal surface's protective layer (passive film) due to chloride ions infiltrating tiny cavities. Damage to this protective layer is utilized by the oxygen element around it, resulting in corrosion [5]. The corrosion test results are shown in Fig. 2.

Fig. 2. Corrosion test graph.

Fig. 2. Corrosion test graph.

Polarization curves appear close together on corrosion test graphs. The discrepancy lies in the values of and , as well as the passivity line. Passivation lines with shapes similar to the anodic and cathodic tangents are more corrosion resistant. The corrosion process is caused by an electrochemical reaction between the specimen's surface and an electrolyte solution. From Fig. 2, we carry out the fitting process to determine the and values so that we can obtain the corrosion rate for each specimen according to formula (1). Those data values are determined by the number of negative charges produced. The size of the number shows the material's tendency to oxidize. The maximum value is achieved when WAAM produces the second layer. A low number will tend to corrode more easily, and vice versa. The corrosion current density was
utilized to calculate the corrosion rate desired using the Tafel extrapolation method based on Faraday's law. Corrosion current value ( ) in the Tafel diagram is affected by the form of the curve since it is calculated from the tangent intersection of the curve that transitions from the cathode to the anode or vice versa. As a result, even though the form is nearly identical, changing the trajectory at a different location produces a different . A different causes a varied corrosion rate [6][7]. Comparison of corrosion rates on each layer producing by WAAM is presented in Fig. 3.

Fig. 3. Corrosion rate result.

Fig. 3. Corrosion rate result.

According to Fig. 3, the lowest corrosion rate was found in a single layer of WAAM, at 0.32431 mmpy . The corrosion rate gradually increases as more layers are applied. A four-layer WAAM had the highest corrosion rate, measuring 1.77983 mmpy . It is the result of gasses trapped inside the weld metal due to time lag between the creation of a WAAM layer and the next layer, which causes porosity. The more the porosity, the greater the stress concentration, which is the precursor to the production of pitting corrosion [8]. As shown by Fig. 4, ferrite and pearlite dominate the microstructure phase. This observation was conducted in accordance with the ASTM E407 standard [9]. The addition of the WAAM layer results in a less refined microstructure because the cooling rate reduces while grain size increases. The discrepancy in corrosion resistance was attributed to excessive process heat input and an uneven microstructure, which resulted in variances in grain size and element segregation [10].

Fig. 4. Microstructure observation result.

Fig. 4. Microstructure observation result.

Grain size analysis was thus performed on the WAAM material using the micrographs from Fig. 4. Due of the slower cooling rate, which encourages grain growth. Grain size is often found to grow with increasing distance from the substrate; this is owing to slower cooling rates away from the substrate caused by the heatsink effect [11].

Fig. 5. Vickers hardness test result.

Fig. 5. Vickers hardness test result.

The results of the Vickers hardness test are shown in Fig. 5. This test follows the ASTM E384 standard [12]. The differences in hardness values across WAAM layers are caused by the ferrite density in weld metal [13]. The hardness value decreases with the addition of each subsequent layer. This trend can be attributable to finer grains resulting from rapid cooling [14]. The hardness values increase as the cooling rate rises.

Conclusion

The original version of this paper is available on https://www.scientific.net/EI.12.7.pdf

Wire arc additive manufacturing is a type of additive manufacturing that uses melted wire to create three-dimensional objects. By adapting the three-axis automated motion framework for the WAAM layer characterization study, it is possible to deduce that the corrosion rate increases with the layer's addition. Meanwhile, in the hardness value, the reverse phenomena happens, with the addition of the WAAM layer causing it to decrease. This is influenced by grain size changes caused by a decrease in the cooling rate during the WAAM layering process.

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The original version of this paper is available on https://www.scientific.net/EI.12.7.pdf

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N. Kapustka, C. Conrardy, S. Babu, C. Albright, Effect of GMAW process and material conditions on DP 780 and TRIP 780 welds, Weld. J. (Miami, Fla). 87 (2008) 135-148.

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The original version of this eBook is available on https://www.scientific.net/book/engineering-innovations-vol-12/978-3-0364-1691-5

Engineering Innovations, ISSN: 2813-1002, Vol. 12, pp 13-21

doi: 10.4028/p-yXDMT0

© 2025 The Author(s). Published by Trans Tech Publications Ltd, Switzerland.

Submitted:
2024-07-07

Revised:
2024-08-20

Accepted:
2024-08-22

Online:
2025-01-03

Study on Flexural Performance of Fiber Reinforced Concrete Beams Using Glass Fiber Reinforced Polymer Bars and Steel Rebars

The original version of this paper is available on https://www.scientific.net/EI.12.13.pdf

K. Hemalatha , Dr. D Ravi Prasad *

¹Research Scholar, Structures division, Department of Civil Engineering, National Institute of Technology Warangal,506002, India

Associate Professor, Structures division, Department of Civil Engineering, National Institute of Technology Warangal,506002, India

khema@student.nitw.ac.in, raviprasad@nitw.ac.in

Keywords: PVA fibers, GFRP, Hybrid Reinforced Concrete beams, Flexural capacity, Ductility.

Abstract

Traditionally, reinforced concrete structures are constructed using steel rebars as reinforcement which is more susceptible to reinforcement corrosion in severe exposure conditions. This leads to many disadvantages, like deterioration of concrete, reduction in strength, and increase in maintenance costs, which leads to a decrease in the serviceability of critical infrastructure. Fiber Reinforced Polymer bars are often used as alternative materials for steel bars because they are anticorrosive, exhibit an excellent strength-to-weight ratio and are easy to handle but the main disadvantage is its brittle nature. Hence, the combination of steel and FRP bars was effectively used to augment both flexural capacity and ductility. As the ductility performance of hybrid Reinforcement is lower than conventional reinforced beams, Polyvinyl Alcohol Fibers in volume fraction were added in this investigation. The present investigation aims to determine the flexural capacity of reinforced concrete beams using Glass Fiber Reinforced Polymer (GFRP) bars and Steel bars. The optimum dosage of PVA fibers while evaluating compressive and split tensile strength is observed at in volume fraction. Total six types of concrete beam specimens with and without PVA fibers were experimentally under fourpoint bending test tested such as beams reinforced with only steel bars, only GFRP bars, GFRP and steel bars. From the experimental results, it is observed that inclusion of PVA fibers in proposed beams with hybrid reinforcement enhanced the crack resistance by and ultimate load capacity by when compared with conventional beam.

Introduction

The original version of this paper is available on https://www.scientific.net/EI.12.13.pdf

Reinforced concrete structures with steel rebars are susceptible to corrosion which leads to damage, and reduction in service also leads to high cost of maintenance. Numerous investigations have been carried out to avoid this problem, such as using steel reinforcement coated with epoxy. The presence of epoxy reduces the bond between concrete and steel and the cost shoots up by approximately . An alternative material to steel rebars with the appropriate material characteristics is using Fiber Reinforced Polymer (FRP) rebars which possess high corrosion resistance. These bars possess high tensile strength and high durability. Hence, the concrete structures reinforced with FRP rebar show good performance during their service life. Many studies have been attempted to enhance the flexural capacity [1], and concrete beams using hybrid reinforcement demonstrate a significant improvement in capacity compared to conventional beams. [2] evaluated flexural performance of concrete beams with steel and GFRP bars, and determined that the ultimate moment capacity was more than that of conventional RC beams.
The ultimate capacity in flexure of hybrid RC beams was up to of conventional RC beams . Placing FRP bars at the edges and Steel rebars in the middle shows better performance during service [5] and crack width using hybrid reinforcement with GFRP and steel is reduced compared to concrete beams with FRP bars only [6]. In addition, under service conditions ductility can be increased by applying lower ratio of FRP to steel bars area ( ). The introduction of PVA Fiber in fiber reinforced concrete beams improved ductility significantly [8] when compared with beams without
fiber and also concluded that PVA Fiber showed better results in flexural capacity when compared to Polypropylene fiber [9].
Some studies show an improvement in ductility by when PVA Fibers are used. Experimental investigations indicate that all the concrete grades introducing PVA Fiber exhibited good mechanical characteristics at PVA fiber volume fraction [10,11]. The performance of RC beams using various hybrid reinforcement ratios are studied [12] and concluded that the stiffness of beams with hybrid Reinforcement is higher with a fixed amount of GFRP and varied amount of steel when compared to a fixed amount of steel reinforcement and increased quantity of GFRP.
The design of reinforcement for flexure using Hybrid reinforcement is proposed in [13] and identified that less amount of GFRP is necessary to prevent FRP bar rupture and also suggested two balanced reinforcement ratios to attain steel yielding and crushing of concrete Failure. [14] performed flexural performance of RC beams using BFRP bars, Steel and BFRP, only steel bars and suggested that concrete beams with hybrid reinforcement performance lie amidst of pure BFRP RC beams and RC beams with steel bars.
Flexural study of RC beams using Basalt FRP bars with microfibers improved [15] the flexural capacity and the crack widths less than 0.5 mm at service load. [16] investigated that the flexural capacity of RC beams using GFRP bars and steel bars is 4 to 50 percent higher than Steel Reinforced Concrete beams. The ratio should lie between 1.0 to 2.5 to meet the requirements of ductility and flexural capacity [17].

Research Significance

The original version of this paper is available on https://www.scientific.net/EI.12.13.pdf

In the literature so far, many researchers have focused on ultimate flexural capacity, cracking load, design guidelines, moment-curvature relationships, long-term flexural performance, and the effect of Reinforcement ratio. Equations have been presented in terms of ultimate moment, crack width, and failure modes to reach steel yielding (SY) and concrete crushing (CC). However, there are no studies that give a clear idea of improving both ductility and flexural capacity of RC beams using both GFRP and steel bars and compare with conventional beams made with only steel bars. In this paper, an attempt has been made to examine the PVA fibers influence on flexural and ductility performances on hybrid reinforced concrete beams.

Experimental Program

The original version of this paper is available on https://www.scientific.net/EI.12.13.pdf

Material properties. In the present study, an ordinary Portland cement 53 grade and Class F Fly ash was used as a mineral admixture, locally available River sand, well-graded crushed granite of maximum size 20 mm conforming to IS . Concrete grade M30 was developed as per IS:10262-2019. Fiber details and mechanical characteristics of fiber reinforced concrete are tabulated below in Table 1 and 2. Three specimens for each test were carried out. It was observed that at fiber volume fraction, compressive strength, split tensile strength and modulus of rupture were observed to be maximum. Therefore, the optimum fiber dosage arrived at . In this study, a total of six reinforced concrete beams were experimentally investigated in which two RC beams using steel bars with PVA fibers at a dosage of , two RC beams using GFRP bars and Steel bars with PVA fibers at a dosage of and two RC beams using GFRP bars with PVA fibers at a dosage of in volume fraction.

Methodology. For the preparation of reinforced concrete beams, Glass fiber reinforced polymer bars of 12 mm diameter as per IS 18256: 2023 were adopted in this study which is made up of fiber glass saturated with Epoxy resin under pultrusion process at volume fraction of fibers. The properties of rebars are mentioned in Table 3. The mix proportions are shown in Table 4.

Table 1. PVA Fibers Properties.

S.No | Test | Results
1 | Fiber Type | Bunchy Mono Filaments
2 | Density | 1.29
3 | Length | 6mm
4 | Tensile capacity [MPa] | 1625
5 | Elastic Modulus [GPa] | 43

Table 2. Compressive Strength, Split Tensile Strength and Modulus of Rupture

Mix ID | Compressive Strength (MPa) | % Change | Tensile Strength (MPa) | % Change | MOR (MPa) | % Change
F 0.0 | 34.32 | - | 3.25 | - | 4.20 | -
F 0.125 | 36.41 | +6.09 | 3.98 | +21.8 | 5.32 | +26.7
F 0.25 | 37.29 | +8.65 | 4.21 | +29.54 | 5.72 | +36.2
F 0.375 | 36.3 | +5.76 | 4.13 | +27.08 | 5.35 | +27.4
F 0.5 | 35.5 | +3.43% | 3.84 | +18.15 | 4.70 | +11.9

Note: 1) F 0.0 represents Control Mix without fibers 2) F 0.125 represents mix with PVA fibers 3) F 0.25 represents mix with PVA fibers and similarly followed in all mixes.

Table 3. Mechanical Properties of Steel and GFRP bars

Rebar | Nominal dia (mm) | Weight(gms) | Density(g/cc) | fy (MPa) | fu (MPa) | MOE(GPa)
Steel | 12 | 350 | 7.7 | 505 | 635 | 195
GFRP | 12 | 90 | 2.0 | - | 865 | 45

Note: and represents yield strength and ultimate tensile strength; MOE -Modulus of Elasticity

Table 4. Mix Proportions of M30 Grade Concrete.

Grade | Cement[kg/m³] | Fly Ash [Kg/m³] | FA[Kg/m³] | CA[Kg/m³] | Water [Kg/m³]
M30 | 306.7 | 76.68 | 702.3 | 1301.6 | 132

Note: FA and CA represent Fine Aggregate and Coarse Aggregate respectively
Casting of beams. A total of six reinforced concrete beams of M30 grade were prepared with length 2000 mm , width 150 mm , depth 200 mm and effective cover at 25 mm . Two 8 mm diameter steel bars are provided as hanger bars in the compression zone. Steel stirrups are provided as shown in Fig. 1 and Fig. 2 to secure pure bending behaviour. RC beams with only steel bars and Hybrid reinforcement are designed as under reinforced section where effective reinforcement ratio is less than balanced reinforcement ratio whereas RC beams with only GFRP bars are having effective reinforcement ratio greater than balanced reinforcement [18]. The details are shown in the Table 5 and Table 6.

Table 5. Reinforcement Ratios of RC beams using GFRP and Steel bars.

Beam Type | Main Reinforcement | ρn,E (%) | ρb,E (%) | ρn,F (%) | ρb,F (%)
Hybrid RC beam | Steel | GFRP | 1.09 | 1.93 | 1.83 | 0.695
2φ12 2φ12

Note: and represents nominal and balanced reinforcement ratio in terms of Elastic modulus; and represents nominal and balanced reinforcement ratio in terms of Tensile strength.

Table 6. Test Matrix Details

Beam Type
Main Reinforcement
fck
(N/mm²)
Af (mm²)
As
(mm²)
Af/As
ρf
(Af/bd)
ρs
(As/bd)

Steel
GFRP

F30 0PVA
-
4φ12
30
452.39
-
-
0.018
-

F30 0.25PVA
-
4φ12
30
452.39
-
-
0.018
-

H30 0PVA
2φ12
2φ12
30
226.19
226.19
1
0.009
0.009

H30 0.25PVA
2φ12
2φ12
30
226.19
226.19
1
0.009
0.009

S30 0PVA
4φ12
-
30
-
452.39
-
-
0.018

S30 0.25PVA
4φ12
-
30
-
452.39
-
-
0.018

Note: The first character "S30 or H30 or F30" represents M30 grade Concrete beams reinforced only with steel bars, both steel bars and GFRP bars, only FRP bars; the second character " 0 or 0.25 " represents RC beams with and PVA fibers in Volume fraction; third character PVA refers to PVA fiber content i.e., S30 0PVA represents RC beam with only steel bars and PVA fibers. and represents Area of FRP and Area of Steel bars; and represents reinforcement ratio of FRP and steel bars; and refers width and depth of cross section.

Testing of beams. All the six reinforced concrete beams as shown in Fig. 3 are tested under four-point bending test. The beam is loaded monotonically by a hydraulic jack and the respective load is divided into two equal parts using a steel spreader beam to the test beam. Three linear variable differential transducers were positioned under the pure bending zone. The experimental work was tested using 100 Tonne capacity Universal Testing machine which is applied at a rate of 1.5 mm per minute. The load was applied till the beam failed in flexure. Load at first crack and ultimate, failure modes were observed.

Fig.1. Cross-Section of RC beam

Fig.1. Cross-Section of RC beam

Fig. 1(a). Cross-section details of RC beam using GFRP and Steel bars; Fig. 1(b) Cross-section details of RC beam using GFRP bars; Fig. 1(c) Cross-section details of RC beam using only Steel bars

Fig. 2. Longitudinal Section of RC beam

Fig. 2. Longitudinal Section of RC beam

Fig. 3. Beam test Setup

Fig. 3. Beam test Setup

First Crack load and Ultimate Flexural capacity. From the study, it was observed that RC beams (S30 0PVA, H30 0PVA, F30 0PVA) without fibers undergone first crack at 0.1 to 0.2 Pu (ultimate load) whereas the RC beams (S30 0.25PVA, H30 0.25PVA, F30 0.25PVA) with fibers undergone first crack at 0.2 to 0.35 Pu . This may be due to PVA fibers high tensile strength and high pull-out resistance which delay the appearance of the first crack [19]. This proves that cracking load is directly associated with concrete tensile strength. RC beams with only steel bars sustain a maximum load up to 105 KN , which is lower than the former beams. It is well known that all GFRP beam cracking loads are smaller followed by hybrid reinforcement and conventional beams. Among all other beams, RC beams with hybrid reinforced (GFRP & steel) at dosage of PVA fibers exhibited the highest ductility and it was also observed that cracking load, ultimate load, and ultimate deflection are highest for hybrid reinforced (GFRP & steel) at dosage of PVA Fibers when compared to the conventional beam. The ultimate flexural capacity of F30 0PVA is , F30 0.25 PVA is , H30 0PVA is , H 300.25 PVA is enhanced when compared with conventional beam S30 0PVA.

Table 7. Cracking load, Ultimate Moment, Ductility and Failure modes.

Beam Type | Pcr (KN) | Pu (KN) | Mu (KN-m) | % Increase | μ (Δu/Δy) | Failure Mode
S30 0PVA | 25 | 104.5 | 31.35 | - | 2.2 | SY, CC
S30 0.25PVA | 49 | 121.3 | 36.4 | +16 | 4.9 | SY, CC
H30 0PVA | 22 | 120.6 | 36.19 | +15.4 | 1.7 | SY, CC, FR
H30 0.25PVA | 45 | 145.0 | 43.51 | +38.8 | 3.9 | SY, CC, FR
F30 0PVA | 19 | 138.0 | 41.41 | +32.1 | - | CC
F30 0.25PVA | 30 | 165.6 | 49.69 | +58.5 | 2.1 | CC

Load- Displacement Response and Analysis of Various Failure Stages. To differentiate various stages of failure as shown in Fig. 4, the comparison of Load-Deflection curves for all tested beams with and without PVA Fibers. From the study, it was observed that all RC beams with only steel bars and Hybrid Reinforcement undergo three to four stages from the point of load application to failure of the beam ie., the pre-cracking stage before the first crack appears, the pre-yielding stage after the first crack and before yielding, post yielding stage till ultimate load and Failure stage. RC beams with only GFRP bars undergo linear failure after cracking load which shows brittle failure but the addition of PVA fibers shows pre-yielding and post-yielding stage. From the findings of the study, it was observed that in the first stage, all the RC beams behave linearly until the first crack appears. After the first stage, there is a stiffness reduction in members and an increase in deflection which can be reflected by the degradation of slope. In the second stage the behavior or stiffness of the member is linear which shows stability.
During yielding stage, the deflection of beam varies from 5 mm to 15 mm which is approximately 20 to of the ultimate deflection. During the yielding stage, deflection increases and stiffness decreases even more. Similarly, beams reinforced only with steel or a combination of steel and hybrid reinforcement exhibit proportional behaviour in the third stage. However, beams collapse in the fourth stage when they reach the ultimate strain limits of either GFRP or concrete in the compression zone. Hybrid reinforced concrete beams fail through yielding of steel, crushing of concrete and GFRP rupture. Fig. 4 shows that RC beams with only FRP bars went through two phases in contrast to RC beams with both steel and hybrid reinforcement.
There is comparable variation up to the first crack when comparing S30 0PVA and H30 0PVA. S30 0PVA has more stiffness than H30 0PVA after the first crack and before steel yielding [20]. However, once steel yields H30 0PVA acquires greater stiffness due to the GFRP bars significant involvement in load carrying capacity which is higher than S30 0PVA. S30 0.25PVA and H30 0.25PVA exhibited comparable behaviour as indicated in Table 5, and they both increased their load carrying capacity by when compared to S30 0PVA, the addition of PVA fibers improves ductility by and load capacity by . Out of six specimens evaluated, RC beams with GFRP bars had the highest load capacity whereas control beams having least which is limited to 105 KN only. Therefore, hybrid reinforcement with fibers achieves a balance between load capacity and ductility

Fig. 4. Load-Displacement curves for all Test Specimens

Fig. 4. Load-Displacement curves for all Test Specimens

Crack Propagation. All the tested beams started with a flexural crack at the mid span which is perpendicular to the longitudinal axis of the beams. The first crack was delayed in the conventional and Hybrid reinforced beams and with the increase in load, the number of cracks increased in the pure bending zone till further vertical cracks appeared and eventually flexure shear cracks appeared.
The first crack appeared earlier in pure FRP beams followed by Hybrid Reinforcement and conventional beams. Fig. 5 shows the crack propagation at service load ( 0.7 Pu ). Prior to steel yielding crack formation is similar to both Hybrid reinforced beams and Conventional beams. After Steel yielding there are more cracks in the Hybrid reinforced beam and its propagation is fast. The crack width for pure FRP RC beams is greater and that is expected because of its brittle nature and is less reflected in conventional beams and Hybrid Reinforced beams with PVA fibers.
It can be concluded that hybrid reinforced beam with PVA Fibers flexural capacity is higher than control beams [21]. Ultimately, deflections are similar in both cases as the provision of PVA fibers enhanced cracking load, and ductility due to its bridging effect.

Fig. 5a. Crack Propagation of RC beam using only steel bars(S30 0PVA)

Fig. 5. a. Crack Propagation of RC beam using only steel bars(S30 0PVA)

Fig. 5b. Crack Propagation of RC beam using Hybrid Reinforcement(H30 0PVA)

Fig. 5. b. Crack Propagation of RC beam using Hybrid Reinforcement(H30 0PVA)

Fig. 5c. Crack Propagation of RC beam using only GFRP bars (F30 0PVA)

Fig. 5. c. Crack Propagation of RC beam using only GFRP bars (F30 0PVA)

Fig. 5d. Crack Propagation of RC beam using Steel bars and PVA fibers (S30 0.25PVA)

Fig. 5. d. Crack Propagation of RC beam using Steel bars and PVA fibers (S30 0.25PVA)

Fig. 5e. Crack Propagation of RC beam using Hybrid Reinforcement and PVA fibers (H30 0.25PVA)

Fig. 5. e. Crack Propagation of RC beam using Hybrid Reinforcement and PVA fibers (H30 0.25PVA)

Fig. 5f. Crack Propagation of RC beam using GFRP bars and PVA fibers (F30 0.25PVA)

Fig. 5. f. Crack Propagation of RC beam using GFRP bars and PVA fibers (F30 0.25PVA)

Fig. 5. Crack Propagation of Test Specimens at failure

Conclusions

The original version of this paper is available on https://www.scientific.net/EI.12.13.pdf

The following are the conclusions drawn from the present investigation.

Concrete beams reinforced with GFRP bars alone exhibit higher flexural capacity compared to RC beams using hybrid reinforcement and control beam.

The flexural capacity of hybrid reinforced concrete beams with and without fibers is greater than that of conventional beams.

It was concluded that the proposed RC beam H 300.25 PVA enhanced both Flexural capacity and ductility compared to control beam.

The crack resistance of a conventional beam is greater when compared to F30 0PVA, H30 0PVA whereas the ultimate load capacity is less. That means crack resistance is greater in RC beams when steel bars are replaced whereas ultimate load capacity is greater when GFRP bars are replaced.

Pure GFRP reinforced concrete beams undergo typical failure mode by Concrete Crushing; RC beams made with only steel bars undergo failure by Steel Yielding followed by Concrete Crushing whereas all Hybrid Reinforced beams fail by SY, CC and eventually GFRP bar rupturing, which is the acceptable approach of failure.

The outcome of flexural behavioral studies of all test beams validated the effectiveness of Hybrid Reinforced beams in terms of Flexural capacity, Ductility, Crack resistance when compared to RC beams using only steel bars and only GFRP bars.

References

The original version of this paper is available on https://www.scientific.net/EI.12.13.pdf

Kim, S. & Kim, S. Flexural behavior of concrete beams with steel bar and FRP reinforcement. Journal of Asian Architecture and Building Engineering 18, (2019) 89-97.

Lu, C. H., Li, H., Xu, K., Xuan, G. Y. & Abdullah, W. Experimental study of flexural behavior and serviceability of hybrid concrete beams reinforced by steel and G/BFRP bars. IOP Conf Ser Mater Sci Eng 770, (2020) 012007.

Ge, W., Zhang, J., Cao, D. & Tu, Y. Flexural behaviors of hybrid concrete beams reinforced with BFRP bars and steel bars. Constr Build Mater 87, (2015) 28-37.

Ruan, X., Lu, C., Xu, K., Xuan, G. & Ni, M. Flexural behavior and serviceability of concrete beams hybrid-reinforced with GFRP bars and steel bars. Compos Struct 235, (2020) 111772.

Yinghao, L. & Yong, Y. Arrangement of hybrid rebars on flexural behavior of HSC beams. Compos B Eng 45, (2013) 22-31.

Xingyu, G., Yiqing, D. & Jiwang, J. Flexural behavior investigation of steel-GFRP hybridreinforced concrete beams based on experimental and numerical methods. Eng Struct 206, (2020) 110117.

Liu, S., Wang, X., Ali, Y. M. S., Su, C. & Wu, Z. Flexural behavior and design of underreinforced concrete beams with BFRP and steel bars. Eng Struct 263, (2022) 114386.

LOH, Z. P., MO, K. H., TAN, C. G. & YEO, S. H. Mechanical characteristics and flexural behaviour of fibre-reinforced cementitious composite containing PVA and basalt fibres. Sādhanā 44, (2019) 98.

Shaaban, I. G., Said, M., Khan, S. U., Eissa, M. & Elrashidy, K. Experimental and theoretical behaviour of reinforced concrete beams containing hybrid fibres. Structures 32, (2021) 21432160.

Noushini, A., Samali, B. & Vessalas, K. Flexural toughness and ductility characteristics of polyvinyl-alcohol fibre reinforced concrete (PVA-FRC). in Proceedings of the 8th International Conference on Fracture Mechanics of Concrete and Concrete Structures (eds. J.G.M. Van Mier, G. Ruiz, C. Andrade, R.C. Yu & X.X. Zhang) (OPUS, 2013) 1110-1121.

Said, M., Mustafa, T. S., Shanour, A. S. & Khalil, M. M. Experimental and analytical investigation of high performance concrete beams reinforced with hybrid bars and polyvinyl alcohol fibers. Constr Build Mater 259, (2020) 120395.

Sagar, B. & Sivakumar, M. V. N. Compressive properties and analytical modelling for stressstrain curves of polyvinyl alcohol fiber reinforced concrete. Constr Build Mater 291, (2021) 123192.

Xingyu, G., Yiqing, D. & Jiwang, J. Flexural behavior investigation of steel-GFRP hybridreinforced concrete beams based on experimental and numerical methods. Eng Struct 206, (2020) 110117.

Nguyen, P. D., Dang, V. H. & Vu, N. A. Performance of Concrete Beams Reinforced with Various Ratios of Hybrid GFRP/Steel Bars. Civil Engineering Journal 6, (2020) 1652-1669.

Ge, W., Zhang, J., Cao, D. & Tu, Y. Flexural behaviors of hybrid concrete beams reinforced with BFRP bars and steel bars. Constr Build Mater 87, (2015) 28-37.

Zaki, M., Tobaa, A., Shehata, A., Mohamed, F., Khalef, R., Hagras, Y., Abou-Ali, R., Farag, M., Ghaly, A., Madi, M. and Sayed-Ahmed. Potential advantages of basalt FRP bars compared to carbon FRP bars &amp; conventional steel. Australian Journal of Civil Engineering 19, (2021) 107-122.

LOH, Z. P., MO, K. H., TAN, C. G. & YEO, S. H. Mechanical characteristics and flexural behaviour of fibre-reinforced cementitious composite containing PVA and basalt fibres. Sādhanā 44, (2019) 98.

Hemalatha, K., & D. Ravi Prasad. Numerical analysis on reinforcement ratio of RC beams using FRP and steel rebars. E3S Web of Conferences. Vol. 391. EDP Sciences, 2023.18.

Sijavandi, K., Sharbatdar, M. K. & Kheyroddin, A. Experimental evaluation of flexural behavior of High-Performance Fiber Reinforced Concrete Beams using GFRP and High Strength Steel Bars. Structures 33, (2021) 4256-4268.

Wang, H. & Belarbi, A. Ductility characteristics of fiber-reinforced-concrete beams reinforced with FRP rebars. Constr Build Mater 25, (2011) 2391-2401.

Qu, W., Zhang, X. & Huang, H. Flexural Behavior of Concrete Beams Reinforced with Hybrid (GFRP and Steel) Bars. Journal of Composites for Construction 13, (2009) 350-359.

This ePub file was created using machine-generated methods and automated software to convert the source text into an ePub format and may contain formatting inconsistencies from the original version. Formatting may vary depending on the device used.

Note: Failure Mode SY, CC means the respective beam failed by Steel Yielding followed by Concrete Crushing; failure Mode SY, CC, FR means the respective beam failed by Steel Yielding followed by Concrete Crushing and simultaneously FRP rupture; Failure mode CC means beam failed by Concrete Crushing.

The original version of this eBook is available on https://www.scientific.net/book/engineering-innovations-vol-12/978-3-0364-1691-5

Engineering Innovations, ISSN: 2813-1002, Vol. 12, pp 23-40

doi: 10.4028/p-0XtmNb

© 2025 The Author(s). Published by Trans Tech Publications Ltd, Switzerland.

Submitted:
2023-10-27

Revised:
2024-05-11

Accepted:
2024-05-13

Online:
2025-01-03

Modelling and Structural Simulation of Thin-Wall Structure

The original version of this paper is available on https://www.scientific.net/EI.12.23.pdf

Akhmat Busori , Ubaidillah , Eko Prasetya Budiana , Purwadi Joko Widodo

Mechanical Engineering Department, Faculty of Engineering, Universitas Sebelas Maret, JI. Ir. Sutami 36 A, Kentingan, Surakarta, Central Java 57126, Indonesia

akhmat.busori@inka.co.id, ubaidillah_ft@staff.uns.ac.id,

ekoprasetya@staff.uns.ac.id, purwadijoko@gmail.com

Keywords: thin-walled structure, finite element analysis, transportation.

Abstract

This paper performs a non-linear analysis of a thin-walled structure. This simulation uses the finite element method to calculate actual conditions in a matrix calculation that is visualized. In the finite element method for numerical solutions of elliptic partial differential equations, the stiffness matrix represents the system of linear equations that must be solved to ensure approximate solutions to the differential equations. A plate will be given different stiffener shapes with the same pressure value. There will be two boundary conditions applied at this thin-walled structure, displacement and fixed support will be applied at the side of the plate. The output obtained from this simulation are von mises stress, total deformation, elastic strain and strain energy. Each model of thin-walled structure will have various values of this output. And the outcome of this research will be helpful as the selected design of the best stiffener able to improve the performance of thin-walled structure for design and manufacture of marine and land transportation.

Introduction

The original version of this paper is available on https://www.scientific.net/EI.12.23.pdf

Over time, the development of technology of transportation has increased. This has an impact on people's dependence on the use of the transportation system. People move from one point to another by vehicles for faster mobility. This is clearly seen with the number of vehicle manufactures for land, sea and air are growing rapidly. With this number of vehicles, the probability of accidents and causes of death increases. In view of this, higher demand has been advocated to ensure higher standards of safety in vehicles. The most common cause is a strong impact due to the energy not being properly absorbed by the walls of the vehicle during the collision. This has led to continuous research in designing efficient energy absorbers to dissipate energy during an accident whilst protecting the occupant in the vehicle.

This research focuses on the utilization of thin-walled tubes that are well-known to be effective in absorbing energy. These structures have good toughness and are able to withstand the forces generated during vehicle movement or impact. It is expected that this impact-resistant structure will be able to utilize energy as efficiently as possible by using the minimum mass possible. Thin-walled structures have been shown to have good energy absorption capacity while remaining lightweight. In addition, thin-walled structures using steel tubes have advantages in terms of durability and cost. Over the past decades, substantial efforts have been devoted to investigation into the crushing behaviors of the thin-walled structures through analytical and experimental methods. For example, Alexander first derived an analytical solution to calculate the axial mean crushing force for circular tubes. Wierzbicki and Abramowicz proposed the close form formulas to predict the axial crush response of aluminum thin-walled tubes. The analytical predictions were validated experimentally by Abramowicz and Jones and Langseth and Hopperstad.[1]

Thin-walled structures or tubes have been extensively used as these energy absorbers most commonly exist as either square or circular cross sections Such structures permanently deform to mitigate the crash energy and forces transmitted to the vehicle reducing the decelerations experienced by the occupants. Extensive research has been carried out in improving the energy absorption of such structures due to direct axial impact. However in the context of a vehicle collision, the vehicle's energy absorbers are commonly subjected to both axial and oblique (off-axis) loads.[2]

Many factors, including cost and weight economy, new materials and processes and the growth of powerful methods of analysis have contributed to this growth, and led to the need for a journal which concentrates specifically on structures in which problems arise due to the thinness of the walls. This field includes cold- formed sections, plate and shell structures, reinforced plastics structures and aluminium structures, and is of importance in many branches of engineering.

Research conducted by Xiaohu Dong, Xiaohong Ding, Guojie Li, and Gareth Peter Lewis entitled "Stiffener Layout Optimization of Plate and Shell Structures for Buckling Problem by Adaptive Growth Method" in 2019 revealed problems regarding the vulnerability of thin-walled plate and shell structures to collapse by buckling due to axial pressure or shear load. This research uses the Adaptive Growth Method (AGM). The design results show that AGM is effective for handling buckling problems and AGM is more efficient for achieving a clearer design result problem that includes a compact stiffener distribution compared to the traditional topology design method. To optimize this, a new method will be carried out in this research by conducting a non-linear analysis of the thinwalled structure with the finite element method.[3]

The design calculations required to estimate the strength, stability, and vibration of thin-walled structures are among the most complex problems encountered in structural design. In general, the calculations are limited to solutions of two-dimensional problems in elasticity or plasticity. Computers have been used to develop methods of calculation based on design schemes, which predict with sufficient accuracy the actual performance conditions and characteristics of the structures, for example, the yield of the supporting structure, the presence of stiffening elements, plastic deformation, variable wall thickness, and the formation of cracks.

Based on research of the study by Ali Balaei Sahzabi and Mohsen Esfahanian, it can be concluded that incorporating thin-walled structures in the design of chassis front rails in vehicles can significantly enhance crash safety and improve occupant protection. The optimized design with features such as a bumper beam and notches in the direct beam demonstrated superior performance in terms of energy absorption, plastic deformation, and crash time. This design resulted in reduced injuries to occupants and increased crash duration, making it the most suitable choice for chassis front rails. The study highlights the importance of considering thin-walled structures in vehicle design to enhance crashworthiness and ensure the safety of vehicle occupants.[4]

Thin-Walled Structure

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Definition. Thin-walled structures are generally made of plates with thick materials and small walls. This structure is commonly found at ship hulls which are made up of plate, stiffener, girder and panel structures. The next research in the design of efficient energy absorbers is aimed at absorbing energy during collisions.Commonly, traditional circular and square tubes and conventional honeycomb are heavily utilized as energy absorbers due to their many advantages, such as simple structural configuration, ease of processing and low cost.[5] Internal stresses on the thin-walled structure can cause the structure to deform and displacement. Thin-walled can also perform an elastic buckling analysis of thin-walled structures subjected to longitudinal stress.

The structure being analyzed may be a folded plate system, a stiffened plate or a thin-walled structural member with uniform thickness in the longitudinal direction and simply supported at its ends. The longitudinal edges may be simply supported, clamped or free along the full length of the plate system. The analysis can be done for a number of different buckle half-wavelengths of the structure and the load factor and buckled shape are output for each length. The types of buckling modes calculated include local, distortional and flexural-torsional buckling.

Collision is classified as an accidental load and impact which can occur in various scenarios that lead to remarkable damage. Impact can be described as an applied high-magnitude load in a shorttime period. Involved objects that undergo this load sus-ceptible to experiencing failure as most instruments are designed to withstand gradual energy and load. This statement explicitly clarify the negative effect of impact phenomenon which closely related with failures and casualties.[6]

In marine and ocean structures, this phenomenon is observed to evaluate safety aspects. Nonlinear behavior is expected during its occurrence, for example in ship collision.[7] The design of construction, structure and any arrangement of materials can experience failure when subjected to various loads.[8] The external dynamics of ship collisions have the role as the action in the collision process. When contact between two vessels occurs, dynamic stresses will be generated in the deformable structure because different parameters are applied in each scenario.[9] According to Newton's Third Law about force, for every action, there is an equal and opposite reaction. The statement means that in every interaction, there is a pair of forces acting on the two interacting objects. The size of the force on the first object equals the size of the force on the second object. When the external dynamic causes the action in the collision process, the reaction as the result of the action on a ships structure will be called the internal mechanics of ship collision.[10]

Many factors, including cost and weight economy, new materials and processes and the growth of powerful methods of analysis have contributed to this growth, and led to the need for a journal which concentrates specifically on structures in which problems arise due to the thinness of the walls. This field includes cold- formed sections, plate and shell structures, reinforced plastics structures and aluminium structures, and is of importance in many branches of engineering.[11]

Application on Land and Marine Based Transportation. Three dimensional structural components in which one dimension is small compared to the other two; they include shells, domes, arches, articulated plates, and membrane-type structures. Thin-walled structures have a high loadcarrying capacity, despite their small thickness. They are widely used in the construction industry because of their light weight and economy, particularly for long-span floors in industrial and public buildings and for storage structures for liquids and bulk materials, such as tanks, hoppers, silos, and coal houses. Thin-walled structures are especially suitable for use in constructing exhibition pavilions, concert halls, and sports arenas because the variety of available shapes permits great architectural expression, the covering of wide areas, and flexibility in the choice of construction materials, including steel, aluminum, reinforced concrete, and laminated plastic.[12]

Thin-walled structures comprise an important and growing proportion of engineering construction with areas of application becoming increasingly diverse, ranging from aircraft, bridges, ships and oil rigs to storage vessels, industrial buildings and warehouses.[13]

A method for structural analysis under ship collision was introduced by Paik and Seo.[4] This method was considered as practical technique development for finite element modelling in observing collision and grounding phenomena. The formulation on ship collision was expanded by Liu and Amdahl.[14] Advance developments of impact engineering, especially in ship collision are not independent from the improvement of computational instrument which is considered as good calculation method in estimating structural behavior and material response under various forms of load.[7]

Structural Responses Subjected Applied Loadings

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Strain Energy. Represents the internal energy stored within a material when subjected to loads within its elastic limit. It is also referred to as the work done by a material under load and is commonly known as 'resilience.' The unit of measurement for strain energy is typically expressed in Newtonmeters ( ), Newton-millimeters ( ), kilonewton-meters ( ), or kilonewtonmillimeters ( ).

For strain energy to exhibit its full potential, it is imperative that the material deforms only within its elastic limit. Additionally, it is important to note that the magnitude of strain energy is directly influenced by the applied load.

The Strain Energy Principle is particularly evident in springs, where the material's ability to store and release energy becomes apparent. Notably, when the applied load is removed, the material will return to its original shape, underscoring its resilience.

Loads imposed upon a material can vary in nature and may include gradually applied loads, suddenly applied loads, or impact loads resulting from objects falling from a height.

Resilience, defined as the energy stored within the elastic limit of a material, is denoted as 'u.'

Stress in the material
Young's modulus of material
Volume of the material ( )
Equivalent Elastic Strain. Is a concept used in materials science and mechanics to quantify the amount of strain a material undergoes under an applied load. It is a scalar quantity that represents the total amount of elastic strain energy stored in the material.

Equivalent elastic strain is calculated by taking the square root of the sum of the squares of the normal and shear strains. Mathematically, it is expressed as:

where is the normal or axial strain, is the shear strain, and is the equivalent elastic strain.
The concept of equivalent elastic strain is useful in analyzing the behavior of materials under complex stress states, where the normal and shear strains may be interrelated. By combining the normal and shear strains into a single scalar quantity, the equivalent elastic strain provides a simplified measure of the total deformation energy stored in the material.

Equivalent elastic strain is also used to determine the yield strength and ultimate strength of materials. The yield strength is the stress at which the material begins to undergo plastic deformation, while the ultimate strength is the maximum stress the material can withstand before failure. By analyzing the equivalent elastic strain at different stress levels, engineers can predict the yield and ultimate strength of a material and design structures that can withstand expected loads.

Von-Mises Stress. Is a value used to determine if a given material will yield or fracture. It is mostly used for ductile materials, such as metals. The von Mises yield criterion states that if the von Mises stress of a material under load is equal to or greater than the yield limit of the same material under simple tension then the material will yield.

Fig. 1 illustrate the curve obtained when studying the strain response of the uniaxial tension of a mild steel beam. These will help us understand why von Mises is important. The description of each emphasized point is as with full stop:

Elastic Limit: The elastic limit defines the region where energy is not lost during the process of stressing and straining. That is, the processes that do not exceed the elastic limit are reversible. This limit is also called yield stress. Above that limit, the deformations stop being elastic and start being plastic, and the deformation includes an irreversible part. The stress value of the elastic limit is used here as Sy.

Upper yield and lower yield: When mild steel is in the plastic range and reaches a critical point — called the upper yield limit — it will drop quickly to the lower yield limit, from which deformation happens at constant stress until it starts resisting deformation again.

Rupture stress: Rupture, or fracture, is the separation of an object caused by stress. Therefore, at this point, a fracture of the body is expected. Materials such as mild steel - which have the property of fracturing only after large plastic deformations - are called ductile. The fracture illustrated here is called a ductile fracture. You can recognize a ductile fracture when the diagram has a curve like the one shown below. This means that as the material gets thinner, more pressure is applied until it suddenly breaks at the rupture stress point.

Fig. 1. Stress-strain diagram of mild steel showing critical stages when under uniaxial tension [16]. This diagram is commonly approximated for many materials, as shown in Fig. 2.

Fig. 1. Stress-strain diagram of mild steel showing critical stages when under uniaxial tension [16]. This diagram is commonly approximated for many materials, as shown in Fig. 2.

Fig. 2. Common approximation for the stress-strain plot generalized for all the materials when under unaxial tension [16].

Fig. 2. Common approximation for the stress-strain plot generalized for all the materials when under unaxial tension [16].

The von Mises stress is a criterion for yielding widely used for metals and other ductile materials. It states that a body will yield if the stress components acting on it are greater than this threshold.

The constant k is defined through experiment, and is the stress tensor. Common experiments for defining k are made from uniaxial stress, where the above expression reduces to:

If reaches the simple tension elastic limit, , then the above expression becomes:

Which can be substituted into the first expression:

Or, finally

The von mises stress, , is defined as:

Therefore, the von Mises yield criterion is also commonly rewritten as:

That is, if the von Mises stress is greater than the simple tension yield limit stress, then the material is expected to yield

Total Deformation. typically refers to the overall change in shape or displacement experienced by an object or material when subjected to an external force or load. It is commonly used in the field of mechanics, materials science, and engineering to quantify how much a material or structure has deformed under certain conditions, as shown in Fig. 3.

Total deformation can be broken down into two main components:

Elastic Deformation: This is the reversible deformation that occurs when a material is subjected to a load but returns to its original shape and size once the load is removed. It is often described by Hooke's Law, which states that the deformation is directly proportional to the applied force, assuming the material remains within its elastic limit.
The elastic deformation can be calculated using Hooke's Law, which relates stress ( ) and elastic modulus (E) to strain ( ). The formula is as follows:

is the elastic deformation, is the applied stress, E is the elastic modulus (also known as Young's modulus), L is the original length of the material.
2. Plastic Deformation: This is the permanent, irreversible deformation that occurs in a material beyond its elastic limit. When a material is subjected to a load greater than its elastic limit, it will undergo plastic deformation, resulting in a change in shape that does not fully recover when the load is removed.
To find the total deformation, you would calculate the elastic deformation using Hooke's Law and add it to the measured or known plastic deformation:

The total deformation of an object is the sum of both elastic and plastic deformations. It is typically measured in units such as millimeters, inches, or strain (deformation per unit length).

Total deformation is a critical factor to consider in engineering and design, as it helps engineers and scientists understand how materials and structures respond to loads and how they may change over time due to repeated loading or environmental factors. This understanding is essential for ensuring the safety and reliability of various engineering applications, from building design to the development of materials for various industries.

Fig. 3. Deformation Graph [6].

Fig. 3. Deformation Graph [6].

Research Methodology

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The FEM provides a mathematical model for calculating the real system, easier and cheaper to change than a prototype. However, it remains as an approximate calculating method due to the basic assumptions of the method. Therefore, prototypes are still necessary, but in lower quantity, since the first one can be well approximated to the optimum design.

The general idea of the finite element method is to divide a continuum in a set of small elements interconnected by a range of points called nodes, as ini Fig. 4 shows the meshing process on an object.

Fig. 4. Meshing Process [6].

Fig. 4. Meshing Process [6].

Pre-processing, running and post processing stages in FEA simulation are the steps of the whole process. At this stage, several processes will be carried out, including geometry modelling, meshing, boundary conditions and loads, running and post-processing.

In this research, geometry modeling will be conducted with various stiffener positions, followed by the meshing process. Boundary conditions and loads will then be applied in the subsequent step. The load will be applied to the surface plate, while a fixed support will be applied to the side of the plate. After setting the boundary conditions and load, the analysis will proceed with the solving process. The outputs of this research will include strain energy, elastic strain, von-mises stress, and total deformation. These values will be plotted on graphs to compare each model.

Geometry Modeling

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Fig. 5. Geometry modelling of (a) model 1 (b) model 2 (c) model 3 (d) model 4 (e) model 5 (f) model 6.

Fig. 5. Geometry modelling of (a) model 1 (b) model 2 (c) model 3 (d) model 4 (e) model 5 (f) model 6.

Table 1. Geometry model configuration.

No | Name | Number of Stiffener | Configuration
1 | Model 1 | 2 | Parallel
2 | Model 2 | 3 | Parallel
3 | Model 3 | 2 | Diagonal cross
4 | Model 4 | 2 | Cross
5 | Model 5 | 4 | Cross
6 | Model 6 | 6 | Cross

All geometry model are proceed to meshing process with 10 mm of meshing size

Material Definition

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This thin-walled structure, made up from plate and stiffener. The plate is made from Structural Steel with of area size and has 6 mm of thickness. Same as plate, the stiffener also made from Structural Steel with length adjust the plate and has 6 mm of thickness.

Table 2. Material properties.

Property | Value | Unit
Material Field Variables | Table |
Density | 7,85E-06 | Kg mm^-3
Isotropic Secant Coefficient of Thermal Expansion |  |
Isotropic Elasticity |  |
Derive from | Shear Modulus and Young's Modulus |
Young's Modulus | 2,1E+05 | MPa
Poisson's Ratio | 0,36364 |
Bulk Modulus | 2,5567E+11 | Pa
Shear Modulus | 77000 | MPa
Alternating Stress Mean Stress | Tabular |
Strain-Life Parameters |  |
Tensile Yield Strength | 245 | MPa
Compressive Yield Strength | 245 | MPa
Tensile Ultimate Strength | 400 | MPa
Compressive Ultimate Strength | 0 | Pa

Boundary Conditions and Load

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Fixed Support. Fixed support applied at the side of the plate.

Fig. 6. Fixed support applied on (a) model 1 (b) model 2 (c) model 3 (d) model 4 (e) model 5 (f) model 6.

Fig. 6. Fixed support applied on (a) model 1 (b) model 2 (c) model 3 (d) model 4 (e) model 5 (f) model 6.

Displacement 1. Applied at the corner of the plate

Fig. 7. First displacement applied on (a) model 1 (b) model 2 (c) model 3 (d) model 4 (e) model 5 (f) model 6.

Fig. 7. First displacement applied on (a) model 1 (b) model 2 (c) model 3 (d) model 4 (e) model 5 (f) model 6.

Displacement 2. Applied at the corner of the plate

Fig. 8. Seccond displacement applied on (a) model 1 (b) model 2 (c) model 3 (d) model 4 (e) model 5 (f) model 6.

Fig. 8. Seccond displacement applied on (a) model 1 (b) model 2 (c) model 3 (d) model 4 (e) model 5 (f) model 6.

Preassure Load. 20000 Pascal of pressure load applied at the surface of plate

Fig. 9. 10000 Pa of pressure apllied on top side of (a) model 1 (b) model 2 (c) model 3 (d) model 4 (e) model 5 (f) model 6 (note: the difference in arrow placement is negligible since it represent uniform force across the surface).

Fig. 9. 10000 Pa of pressure apllied on top side of (a) model 1 (b) model 2 (c) model 3 (d) model 4 (e) model 5 (f) model 6 (note: the difference in arrow placement is negligible since it represent uniform force across the surface).

Results and Discussion

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The main purpose of this research is to understand and analyze stress, strain, deformation and strain energy in various stiffener models which are connected to plates that form a thin-walled structure. From these various models it will have different values from different output that can conclude which stiffener has best performance to withstand load. Boundary condition and load applied at all surfaces have the same pressure value and same boundary location. This is following results of this thin-walled structure:

Strain Energy

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Fig. 10. Strain Energy of (a) model 1 (b) model 2 (c) model 3 (d) model 4 (e) model 5 (f) model 6.

Fig. 10. Strain Energy of (a) model 1 (b) model 2 (c) model 3 (d) model 4 (e) model 5 (f) model 6.

Fig. 11. Comparison of strain energy between all stiffener.

Fig. 11. Comparison of strain energy between all stiffener.

This graphic shows model 1 having better performance than 5 other models because of the strain energy occurs from simulation is at 0.6665 mJ followed by model 6 with 0.71565 mJ . This indicates that Model 1 has lower elasticity compared to the other models at a given level of applied load. In many cases, lower elasticity suggests that the material or structure is more resistant to deformation or failure when subjected to a load, which is often considered an indicator of better performance.

Equivalent Elastic Strain

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Fig. 12. Equivalent elastic strain on (a) model 1 (b) model 2 (c) model 3 (d) model 4 (e) model 5 (f) model 6.

Fig. 12. Equivalent elastic strain on (a) model 1 (b) model 2 (c) model 3 (d) model 4 (e) model 5 (f) model 6.

Fig. 13. Comparison of equivalent elastic strain max between all model.

Fig. 13. Comparison of equivalent elastic strain max between all model.

This graphic also shows model 6 having better performance than 5 other models because of the lower equivalent elastic strain maximum that occurs from simulation. Lower equivalent elastic strain means the shape will have less deformation and higher energy storage capacity which on thin-walled application where the dimensional stability and stiffness is regarded as an important aspect, the model 6 performance will be more desirable. For thin-walled structures, minimizing elastic strain is
a key objective for achieving optimal performance. Lower strain translates directly to superior shape retention, preventing unwanted deformations that could compromise functionality. This enhanced rigidity allows the structure to withstand greater loads without excessive deflection, maximizing its load-carrying capacity. Furthermore, in weight-sensitive applications like aerospace engineering, minimizing strain allows for thinner walls without sacrificing performance, leading to lighter and more efficient designs.

Von-Mises Stress

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Fig. 14. Von Misses Stress on (a) model 1 (b) model 2 (c) model 3 (d) model 4
(e) model 5 (f) model 6.

Fig. 14. Von Misses Stress on (a) model 1 (b) model 2 (c) model 3 (d) model 4 (e) model 5 (f) model 6.

Fig. 15. Comparison of equivalent stress max between all model.

Fig. 15. Comparison of equivalent stress max between all model.

Model 6 is having better results than 5 other models because the maximum equivalent stress occurring from simulation is only 27.855 MPa compared to model 3 with 74.656 MPa which is almost 3 times the number. A lower equivalent stress value is generally desirable because it indicates the material experiences less internal pressure under load. This translates to a reduced risk of failure, increased dimensional stability, and potentially allows the material to handle higher loads before exceeding its limits. The linear function of Equivalent Stress vs time for model 6 with a very low slope is expected because of the low area of pressure due to stiffener arrangement.

Total Deformation

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Fig. 16. Total Deformation on (a) model 1 (b) model 2 (c) model 3 (d) model 4
(e) model 5 (f) model 6.

Fig. 16. Total Deformation on (a) model 1 (b) model 2 (c) model 3 (d) model 4 (e) model 5 (f) model 6.

Fig. 17. Comparison of total deformation max between all model.

Fig. 17. Comparison of total deformation max between all model.

The results of total maximum deformation from all 6 models is showing that Model 1 having the poorest results due to limited integrity. Interesting results are shown by model 5 despite having more stiffeners but performed worse than the other. The result is due to the concentration of deformation inside the center point. Minimizing total maximum deformation is generally considered a sign of strong performance in engineering applications. When a structure or material exhibits lower overall deformation under stress, it translates to several benefits. Firstly, it retains its original shape more effectively, crucial for components that need to maintain precise dimensions. Secondly, this minimal deflection improves dimensional accuracy in the final product. Furthermore, a design with lower total deformation often boasts a higher load capacity. The structure can handle greater forces without excessive bending or warping, leading to improved overall stability.

In thin-walled structures, the pursuit of the smallest strain energy, lower elastic strain, lower equivalent stress value, and lower total maximum deformation stems from various performance objectives. Firstly, by minimizing strain energy and elastic strain, these structures optimize material usage, ensuring that the material is utilized efficiently while maintaining structural integrity. This efficiency is crucial for applications where weight reduction is paramount, such as in aerospace and automotive industries, as it allows for lightweight yet robust designs. Additionally, lower elastic strain and equivalent stress values enhance stability, reducing the risk of buckling or deformation under load, which is vital for safety in dynamic or high-stress environments. Moreover, minimizing total maximum deformation improves durability by reducing the strain on the material, thus extending the fatigue life of the structure, particularly in cyclic loading conditions. Lastly, achieving low deformation and strain energy contributes to better dimensional stability and precision, crucial for applications requiring tight tolerances or high accuracy. In essence, optimizing thin-walled structures for these parameters leads to enhanced performance in terms of efficiency, weight reduction, stability, durability, and precision, meeting the demands of industries requiring lightweight, high-performance structures.

Previous research publications in the journal "Computational Modeling and Constructal Design Theory Applied to the Geometric Optimization of Thin Steel Plates with Stiffeners Subjected to Uniform Transverse Load" have shown that despite keeping the same steel volume, dimensions (except thickness), load, and support conditions, all proposed stiffened plates generally have lower central deflection when compared to non-stiffened reference plates. The results that were obtained demonstrate the effectiveness of the proposed method in predicting physical effects accurately. It was also observed that for a fixed amount of weight, stiffened plates are more efficient. Therefore, adequate stiffening is necessary, and welding techniques are also required.[15]

The stiffness and deflections of plates are greatly influenced by the number of transverse stiffeners ( ), number of longitudinal stiffeners ( ), and ratio between height and thickness of stiffeners . It is important to note that an increase in the number of stiffeners does not necessarily result in a reduction in the central deflection of stiffened plates fabricated with the same amount of steel volume. Therefore, it is crucial to conduct geometric evaluations to efficiently use the material when designing and constructing such structures.

Conclusions

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This paper discusses the strengthening effects of thin-walled structure with various stiffeners applied on the top side of the plate with the same pressure and boundary condition. Through the results, following conclusions can be made :

Stiffener number 6 has a better performance between 5 other stiffeners on 3 out of 4 output aspects.

The use of stiffeners in the structural plates can effectively protect the plates from cyclic and impact loading, therefore extend the plate's service time and reduce its maintenance cost

For regular stiffened plates, stiffeners with more number of stiffener provide better performance than the other stiffeners with less arrangement

The optimum number of stiffeners on one configuration in an interesting topic to be further discussed

The listed conclusions will enhance the capability of predicting the structural plates' buckling performance, therefore have wide applicability in any industry that involves design and analysis of constructional plates. The interesting finding that the strengthening effects of an oblique stiffener can be approximated as those of two regular stiffeners aligned along X and Y -direction can be applied in analytical analysis of the stiffened plate.

Future Work

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This research can be extended in a number of ways, including

Investigating the performance of thin-walled structures with different stiffener materials

Optimizing the design of stiffeners for different loading conditions

Developing experimental methods to validate the FEA results

References

The original version of this paper is available on https://www.scientific.net/EI.12.23.pdf

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A. Rio Prabowo, D. Myung Bae, J. Min Sohn, A. Fauzan Zakki, B. Cao, and J. Hyung Cho, "Effects of the rebounding of a striking ship on structural crashworthiness during ship-ship collision," Thin-Walled Structures, vol. 115, pp. 225-239, Jun. 2017, doi: 10.1016/j.tws.2017.02.022.

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"What is Von Mises Stress in FEA? | SimWiki | SimScale." Accessed: Mar. 04, 2024. [Online]. Available:

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Engineering Innovations, ISSN: 2813-1002, Vol. 12, pp 41-48

doi: 10.4028/p-j2BDms

© 2025 The Author(s). Published by Trans Tech Publications Ltd, Switzerland.

Submitted:
2023-10-24

Revised:
2024-05-13

Accepted:
2024-05-13

Online:
2025-01-03

Weight Optimization of the Electric Bus Carbody Structure

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Wijianto , Giri Fahrezy Istighfarrullah , Agus Dwi Anggono and Taurista Perdana Syawitri

¹Department of Mechanical Engineering, Faculty of Engineering, Muhammadiyah University of Surakarta, Indonesia

wijianto@ums.ac.id, girifahrezy28@gmail.com, ada126@ums.ac.id, tps123@ums.ac.id

Keywords: Car body; CAD; Design; Electric Vehicle.

Abstract

Car body is a lightweight construction unit in the form of welded steel construction, has high strength and rigidity against dynamic loading without a fixed change in shape. In this study, the design of the car body bus frame consisted of roof, mascara, side wall, end wall, front part, and underframe. All of these components are designed using Autodesk Inventor Professional 2020 software. The frame material used is SS201. For data retrieval purposes, weight calculations are used in Autodesk Inventor. In the study, we succeeded in making the car body design according to regulations, measuring the weight of the car body, and optimizing the car body. The results showed that with a little optimization on the side wall frame, the weight of the car body bus can be reduced by from the initial weight of 461.5 kg to 407.4 kg without changing its characteristics.

Introduction

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This mode of transportation is largely responsible for the consumption of a large portion of the world's oil reserves over the last few centuries. This sector also makes a large contribution to total greenhouse gas emissions. Most of it is caused by road transportation based on gas-fueled motorbikes. Today, the concept of alternative drivers is becoming increasingly important as a result of climate change and increasing global resource crises. Due to advances in technology, greater attention is now being paid to the concept of battery-powered electric propulsion. In addition, electric vehicles are also believed to be an effective solution for reducing greenhouse gas emissions [1]. The Merah Putih Electric Bus produced by PT Industri Kereta Api (Persero) is one of the superior products of domestic work in terms of electricity-based public transportation. One of the important components of the electric bus is the Car body. Car body is a passenger-filled space structure built with a plate-like frame construction and as an important component in transportation facilities. In accordance with its function, to maintain the safety and comfort of passengers during the journey to stop at their destination. The car body is a monocoque construction unit that integrates with the base frame. The main body of the car body consists of the underframe, flooring, roof, side wall, mascara and end wall [2]. As is the case in the industrial world, vehicles themselves have been regulated in Presidential Regulation no. 55 of 2012 which aims to regulate the technical specifications of the dimensions, engine and carrying capacity of motorized vehicles [3]. However, the main drawback of electric buses lies in their battery life. The battery must provide sufficient power to run the vehicle. The heavier the vehicle, the more power required. Thus, weight reduction must be made to increase battery life, especially in reducing the weight in the car body frame sector [4]. This research is concerned with optimizing and analyzing the bus structure using the Finite Element Method (FEM) under static conditions using ANSYS software [5]. In this study, steel pipe elements are widely used to make bus body frame structures because they cannot only maintain accurate rigidity but also reduce production costs a lot. Bus body geometry is obtained directly from three-dimensional Computer-Aided Design (CAD) files using Autodesk Inventor. After that, weight optimization was carried out on the frame structure of the car body to determine the minimum frame bus weight [6]. The design variable is the position of the steel pipe in the frame structure on the side wall, front frame and end wall.

Literature Review

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In the previous study, Haryanto et al, conducted a study entitled "Optimization of Bus Body Frame Structure for Weight Minimizing with Constraint of Natural Frequency using Adaptive SingleObjective Method". This study discusses the analysis and optimization of the bus frame structure using the Adaptive Single Objective method for the optimization method. Optimization of the bus body frame is carried out using size optimization with variable thickness and with the aim of minimizing the mass of the structure. The software used is ANSYS R18. The material used as the frame of this research bus is Steel. The results showed that by using Adaptive Single Objective method the structural weight of the bus frame can be reduced by up to without a significant effect on the change in the natural frequency of the first 6 orders. This reduction in structural weight is essential for possible improvements in bus design to achieve lower production costs and higher energy efficiency [4].
In research on optimizing the bus frame structure Nandhakumar et al, conducted a study entitled "Weight Optimization and Structural Analysis of An Electric Bus Chassis Frame". In this study Nandhakumar et al. Optimize bus chassis weight using the finite element method. The software used is ANSYS Mechanical 20.0. The materials used as the frame of this research bus are aluminium 6061T6 and aluminium 7075-T6. In this study, the results were obtained in the form of successfully optimizing the weight of the electric bus frame by replacing the material from conventional steel to aluminium alloy. The two types of aluminium alloys selected are aluminium 6061-T6 and aluminium 7075-T6. The results of the analysis show that the optimized electric bus frame using aluminium alloy 7075-T6 has a lighter weight compared to the electric bus frame using conventional steel. In addition, the analysis results also show that the optimized electric bus frame has lower voltage and deformation compared to the electric bus frame that uses conventional steel [7].
The next research analyzed the monocoque type chassis conducted by Wikarta and Yudha with the title "Strength Analysis of Solar Electric Bus Chassis Using Finite Element Method". The purpose of this research is to determine the strength of the frame due to vertical loads, acceleration, braking, and turning conditions. The parameters are Von-Mises stress and safety factor. The chassis is considered safe if its safety factor is more than 1.5. The results show that the chassis is able to withstand vertical loads and acceleration, but is unsafe when subjected to braking and turning. A redesign of the chassis is required to strengthen its structure [8].

Model Car Body Bus

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Car body is a lightweight construction unit in the form of welded steel construction, has high strength and rigidity against dynamic loading without permanent deformation. Car body construction can be either fused construction (monocoque or semi-monocoque) or not fused with the base frame (platform). Carbody consists of Roof, Mascara, Side Wall, End Wall, Front Part, and Underframe [9].

Fig. 1. Car body bus Merah Putih image

Fig. 1. Car body bus Merah Putih image

Table 1.Car body bus specifications

Dimensions
Length | mm | 7.900
Wide | mm | 2.100
High | mm | 3.200
Capacity | seats | 19+1
Frame
Material | SS201
Structure | Semi-monocoque

Figure 1 shows the car body bus used in this study, with specifications that can be seen in Table 1. The bus has a passenger capacity of 19 seats accompanied by 1 special seat for the disabled that can be folded.

Material Car Body Bus

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In this study, the material used for the car body bus was SS201. The material properties of SS201 can be seen in Table 2 [10].

Table 2. Material property SS201

Properties | Value | Dimension
Density | 7.86 | g/cm³
Tensile Yield Strength | 292 | MPa
Tensile Ultimate Strength | 685 | MPa
Young's Modulus | 193-200 | GPa
Poisson's Ratio | 0.27 |

Loading Analysis Simulation

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Simulation The loading analysis in this study was carried out to determine the amount of voltage distribution, maximum voltage value, total deformation, and safety factor of the bus car body under static conditions. This research uses finite element analysis (FEA) software ANSYS Workbench 2021 R2 [11,12].

Convergence Test

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Convergence tests are carried out to ensure that the tests carried out are in a convergent condition. The size variations ranging from 15 mm to 11 mm for convergence tests. The output of the convergence test is the value of Equivalent-stress, total deformation, safety factor, number of elements, and skewness.

Loading on the Car Body

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In testing the strength and safety of a vehicle can be done through two methods. The first method is experimental, but this method is considered less effective and efficient because it requires a long time and costs money, while the second method is simulation. In the simulation method, the car body is subjected to static loading which represents the actual loading. Loading on the car body using vertical loading. Vertical loading is shown in Figure 2.

Fig. 2. Vertical load distribution

Fig. 2. Vertical load distribution

In Figure 2, it shows the vertical load distribution on the car with the wheelbase (L) and the distance of each load to the front wheels. Therefore, the derivative of the equation is obtained as follows:

Where:
Fpt = Force caused by the power train;
Fpf = Force caused by the front passenger;
Fpr = Force caused by rear passenger;
Fl = Force caused by items in the baggage;
Distance of load to the rear wheel;
Distance of load Fpf to front wheel;
lpr = Distance of load Fpr to front wheel;
lpt = Distance of load Fpt to front wheel;
Wheelbase;
Reaction force by the front wheel;
Reaction force by rear wheel.

Safety Factor

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Safety factors are used because of the uncertainty of a load in real conditions so correction factors are needed to ensure that mechanical components are safe in real conditions. The use of safety factors aims to guarantee safety from a mechanical problem. The calculation of the safety factor is as follows:

Where:
SF = safety factor;
yield strength
voltage .

Weight Optimization

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In this study, optimization of the car body bus structure uses optimization of shape and size, where the position of the steel pipe in the frame structure on the side wall of the car body bus becomes a parameter in optimization. With maximum voltage limitation so that it gets the lightest structure.

Optimization Process for Carbody Structure

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In this study, the optimization problem was simplified by considering design variables with iron pipe structures that make up the side wall frame. Iron pipes are used to form the frame structure of side walls, namely U iron pipes. Figure 3 and Figure 4 show the results of optimization of the side wall frame in this research. Optimization is used to reduce the mass of side wall structures in each group.

Fig. 3. Right wall structure after modified

Fig. 3. Right wall structure after modified

Fig. 4. Left wall structure after modified

Fig. 4. Left wall structure after modified

Convergence Test Output

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The convergence test is used to confirm and prove that the car body bus analysis data taken from changing element dimensions is already in a convergent state, with element variations ranging in size from 15 mm to 11 mm .
The output taken is in the form of Equivalent-stress value, total deformation, safety factor, number of elements, and skewness. The output of the convergence test can be seen in Table 3.
Based on the results of the convergence test, the resulting skewness value is 0.06 and the value is classified as very good. The value of the equivalent stress and resulting deformation forms a graph that tends to be linear with an error of no more than . The convergence analysis graph is shown in Figure 5 and Figure 6.

Table 3. Convergence test output

Element | Equivalent Stress (MPa) | Total Deformation (mm) | Element | Skewness Average
15 | 126.4 | 2.472 | 433093 | 0.062
14 | 139.44 | 2.455 | 495287 | 0.063
13 | 138.76 | 2.478 | 654325 | 0.061
12 | 123.56 | 2.497 | 687656 | 0.05
11 | 141.04 | 2.492 | 781952 | 0.043

Fig. 5. Equivalent-stress graph with Element size,

Fig. 5. Equivalent-stress graph with Element size,

Fig. 6. Total deformation graph with Element size

Fig. 6. Total deformation graph with Element size

Based on the convergence test results, the resulting skewness value is 0.06 and the value is classified as very good. The value of the equivalent stress and deformation produced forms a graph that tends to be linear with an error of no more than . This shows that the meshing flow has been well formed so that it can flow the loading evenly. The meshing results produced are classified as convergent, so it is feasible to do the next simulation.

Finite Element Analysis Output

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Equivalent-stress and deformation are taken as design constraints. FEA results obtained for the carbody frame made of U iron pipe with SS201 material and have been optimized on the iron pipe on the side wall frame, front frame and end wall. The results of FEA can be seen in Figure 7 until Figure 10 and have been summarized in Table 4.

Fig. 7. Equivalent stress

Fig. 7. Equivalent stress

Based on the results of the loading simulation that can be seen in Figure 6, there is a maximum force distribution on the roof of 126.36 MPa . This value is still relatively safe because it is far below the yield strength of SS 201 material, which has a strength of 292 MPa . This shows that it is certain that it did not happen at that point. Meanwhile, the underframe has the least force distribution.

Fig. 8. Safety factor

Fig. 8. Safety factor

The resulting safety factor value is 2.31 , which is obtained from the comparison of force distribution with material yield strength. This shows that the component can still accept forces up to 2.31 times before failing or breaking. The resulting safety factor value is still relatively safe because the standard used for bus vehicles, the safety factor must be above 1.5.

Fig. 9. Total Deformation

Fig. 9. Total Deformation

Based on the results of vertical loading, the area that experienced the greatest total deformation was located at the back of the roof, which was rated at 2.4728 mm . While the front underframe experiences the smallest deformation compared to other parts.

Fig. 10. Directional deformation

Fig. 10. Directional deformation

Directional deformation in the direction of the axis due to vertical loading in the direction of the axis ( - ). The results of Z -axis unidirectional deformation showed the highest deformation towards Z at the top of the bus mascara, which was 2.044 mm , besides that there was also Z -direction deformation ( + ) in the chassis underframe located in the air suspension mounting support area, amounting to 0.04 mm .

Table 4. FEA output

Material | SS201
Distribution Force | 126.36 MPa
Total Deformation | 2.472 mm
Directional Deformation | 2.044 mm
Safety Factor | 2.31

Results

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The results of carbody structure optimization use shape and size optimization to determine the minimum structural weight by changing the location and shape of the pipe in each group mentioned in Figures 3 and 4. Structural optimization is proven to reduce the weight of the carbody bus frame. For comparison of initial and optimized conditions on the carbody bus structure can be seen in Table5.

The results showed that by using structural optimization (shape, size) the weight of the carbody bus frame structure can be reduced by from the initial weight of 548.1 kg to 487.27 kg without significant influence. This reduction in structural weight is critical to enable bus designs to achieve lower production costs and also higher energy efficiency.

Table 5. Initial and optimum conditions

Component | Mass (kg) | Reduction (kg)
| Initial | Optimum |
Left wall frame | 177.1 | 152.79 | -24.31
Right wall frame | 177.1 | 169.61 | -7.49
Left wall panel | 53.65 | 39 | -14.65
Right wall panel | 53.65 | 46 | -7.65
Total Mass | 461.5 | 407.4 | -54.1

Conclusion

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The conclusion of the static analysis of the semi-monocoque chassis structure of the electric bus with vertical loading, the loading analysis shows that the semi-monocoque chassis experiences a force distribution of 126.36 MPa , a total deformation of 2.472 mm , the largest Z direction deformation at 2.044 mm , and a safety factor of 2.31 . Optimization of the bus body frame is carried out by optimizing the structure (shape and size) with variable steel pipe positions in the frame structure at the side wall, front frame and end wall with the aim of minimizing the mass of the bus body structure. By optimizing these variables, it is proven that the mass of the bus body frame can be reduced by without having a significant effect on the character of the frame.

Acknowledgements

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Special thanks to The Directorate General of Higher Education, Research and Technology, Ministry of Education, Culture, Research and Technology, Republic of Indonesia for the scholarships contributed in this study.

References

The original version of this paper is available on https://www.scientific.net/EI.12.41.pdf

MR Cagney, Electric Bus Technology, Transport Research Report, Australia, 2017.

Nguyen, T. C., Research on Application of 3D Parametric Software for Design and Shaping of Bus Frame Structure, Applied Mechanics and Materials, 894 (2019) 96-103.

President of the Republic of Indonesia, Peraturan Pemerintah Republik Indonesia Nomor 55 Tahun 2012 Tentang Kendaraan, State Institution of the Republic of Indonesia, 2012.

Haryanto, I., Raharjo, F. A., Kurdi, O., Haryadi, G. D., and Santosa, S. P., Optimization of Bus Body Frame Structure for Weight Minimizing with Constraint of Natural Frequency using Adaptive Single-Objective Method, International Journal of Sustainable Transportation Technology, 1 (2018) 9-14.

Chen, X., and Liu, Y., Finite Element Modeling and Simulation with ANSYS Workbench, CRC Press, Taylor & Francis Group, 2015.

Wang, D., Xie, C., Liu, Y., Xu, W., and Chen, Q., Multi-objective Collaborative Optimization for the Lightweight Design of an Electric Bus Body Frame, Automotive Innovation, vol. 3, no. 3, (2020) 250-259.

Nandhakumar, S., Seenivasan, S., Saalih, A. M., and Saifudheen, M., Weight Optimization and Structural Analysis of an Electric Bus Chassis Frame, Mater Today Proc, vol. 37, (2021) 18241827.

Wirakarta, A., and Yudha, Y. A., Stress Analysis og Solar Electric Bus Chassis Using Finite Element Method, Mechanical Engineering, Institute of Technology Sepuluh November, 2020.

Yao, C., and Yang, M., Research on Lightweight Design and Finite Element Analysis of a 9 Meter Bus Body Frame, J Phys Conf Ser, vol. 1748, (2021)

Callister, Jr. W. D., and Rethwisch, D. G., Materials Science and Engineering, Tenth ed, Wiley, Hoboken, New Jersey, 2018.

Haldankar, M., and Shirahatti, A. M., Finite Element Analysis and Optimization of Commercial Bus Body Structure, International Journal of Engineering and Technical Research, vol. 2 (2014) 175-178.

Chintada, V., Seela, C. R, and Matta, V. R., Modal and Static Analysis of Automotive Chassis Frame by Using FEA, International Journal of Applied Engineering Research, vol. 10 (2015) 19775-19777.

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The original version of this eBook is available on https://www.scientific.net/book/engineering-innovations-vol-12/978-3-0364-1691-5

Engineering Innovations, ISSN: 2813-1002, Vol. 12, pp 49-54

doi: 10.4028/p-r0bO0I

© 2025 The Author(s). Published by Trans Tech Publications Ltd, Switzerland.

Submitted:
2023-11-14

Revised:
2024-04-30

Accepted:
2024-05-08

Online:
2025-01-03

Fabrication of a Potential Difference Measuring Instrument Using a Capacitive Sensor Based on aTmega328 Microcontroller

The original version of this paper is available on https://www.scientific.net/EI.12.49.pdf

Anak Agung Ngurah Surya Mahendra Putra , Ni Nyoman Rupiasih , I Wayan Supardi , Pandit Bhalchandra Vidyasagar

¹Department of Physics, Faculty of Mathematics and Natural Sciences, Udayana University, Kampus Bukit Jimbaran, Badung, Bali, Indonesia 80361

Department of Physics, Savitribai Phule Pune University, Ganeshkhind Rd, Ganeshkhind, Pune, Maharashtra 411007, India

gungde982@gmail.com, *brupiasih@unud.ac.id, supardi@unud.ac.id, prof_pbv@yahoo.com

Keywords: ATmega328; Arduino; Capacitive sensor; Potential difference; PLX-DAQ.

Abstract

A potential difference-measuring instrument using a capacitive sensor based on ATmega328 microcontroller has been successfully designed and implemented. The instrument consists of 2 (two) silver plates as electrodes, INA219 module, Arduino Nano module, LM 2596 module, Organic Light-Emitting Diode (OLED), and 9V 1A (DC) adapter. The electrolyte solution used was KCl solution. The basic principle of the instrument is that the adapter is the input, the electrolyte solution is the source of electrical energy, and the capacitive sensor is the electrode, namely the anode and cathode. The input data is processed by Arduino Nano ATmega328, and the output data is displayed on OLED and automatically saved with format .xlsx. The instrument has been calibrated with a standard electrode, namely the Hanna HI 5414 reference electrode, with an accuracy of . The result indicates that the instrument can be used to measure membrane potential, which replaced the measurement manually.

Introduction

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The development of increasingly advanced technology and information is also followed by many developments in increasingly advanced instruments, one example of which is an electric meter. This instrument is made to make it easier for users to use it, such as in the field of education, for example, electric potential difference experiments. Measurement of potential difference using a voltmeter with two electrodes as conductors, namely the anode and cathode with an electrolyte solution as a source of electrical energy. In electrolyte solutions, positive ions and negative ions will move and collect on the electrode surface [1].

Several studies on membrane potential differences have been carried out, including the influence of UV-C radiation exposure time on ion characteristics and diffusion current density in chitosan membranes [2], the influence of various types of salt on the potential difference of chitosan membranes [3], the influence of electrolyte solutions on ion transport in chitosan membranes [4], and curve studies current-voltage (I-V) characteristics of silver-chitosan nanoparticle composite membranes [5]. In this research, potential difference measurements were carried out using a multimeter and the results of potential difference measurements were recorded one by one. This method of measurement is inefficient and less effective.

Therefore, in this research a potential difference measuring instrument was design and made using capacitive sensor based on ATmega328 microcontroller. Potential difference measurements will be more effective and easily carried out with a digital system, namely using capacitive sensor by using two silver plates connected to INA219 module. The output of this module is received by ATmega328 microcontroller and processed according to the program that has been made in Arduino Integrated Development Environment (IDE) software and measurement results displayed on Organic LightEmitting Diode (OLED) and Microsoft Excel.

The capacitive sensors are usually made of copper, silver, platinum and gold plates by working on the basis of electrical charges that received by the sensor due to changes in plate distance and changes
in cross-sectional area with electrolyte solutions as a source of electrical energy. Electrolyte solutions are solutions that conduct electric current [6].

Capacitive sensors can respond to and evaluate changes in the physical or chemical properties of a material through variations in capacitive values associated with sensor geometry modifications (such as the distance between two capacitor plates/electrodes, overlapping surface area) or the dielectric material (permittivity) [7]. Recently, capacitive sensors have become increasingly popular due to their versatility and suitability for simple and low-cost measurements [8]. Differential capacitive sensor is a type of transducer that shows better rejection of common mode interference for cases of low capacitive variation [9]. Differential capacitive sensors are widely used as position sensors and accelerometers [10,11].

Ion transport across a membrane is a process of moving ions from one chamber to another; this occurs through passive and active transport processes. Each chamber contains the electrolyte solution, which is separated by a membrane and has different concentrations, so according to Fick's law of diffusion, ions from a high concentration will move across the membrane toward a lower concentration. The ions flow affects the flow of electric current in the membrane. The magnitude of the current is related to the voltage and the difference in concentrations of electrolyte solution [12].

The INA219 module is connected to a capacitive sensor so that the INA219 functions as a sensor on the instrument to read DC voltage from the source [13]. Data from the INA219 sensor is processed by Arduino Nano module. Arduino Nano is the brain of the instrument system controller [14]. The processed data is displayed on an Organic Light-Emitting Diode (OLED). OLED is a display with 8 lines per page and 128 pixels per line. Also, it is required LM 2596. The LM 2596 is a step-down module that converts the DC input voltage to DC voltage. Program writing is done with the help of Arduino IDE which is embedded in the Arduino microcontroller.

Methods

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a. System design. The design of the potential difference measuring instrument is shown in Fig. 1.

Fig. 1. The block diagram of the instrument made.

Fig. 1. The block diagram of the instrument made.

Figure 1 shows that the input block consists of an adapter that functions as a voltage source for the Arduino Nano module, a KCl electrolyte solution as a source of electrical energy, and a capacitive sensor as an electrode, namely the anode and cathode, which is connected to INA219. The input data will be processed from analog to digital signal by Arduino Nano. The output data is displayed on OLED via I2C and saved in Excel format .xlsx.
b. Calibration method. The calibration is carried out by determining the relationship between the measurement data of the instrument made and the measurement results using a standard electrode. The standard electrode used is the Hanna HI 5414 reference electrode. This relationship is expressed by the regression equation Eq. (1).

Where Y is the response variable, X is the predictor variable, a is the regression coefficient, and b is the constant. Furthermore, from Eq. (1), the calibration equation can be determined, namely Eq. (2).

Where is the calibrated voltage, Y is the sensor reading, a is the regression coefficient, and b is a constant. Next, Eq. (2) is embedded in the program code of the instrument made, so that the measurements obtained show conformity with the instrument standard.

Result and Discussion

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a. Result. It has been successfully designed and made a potential difference measuring instrument by using a capacitive sensor based on the ATmega328 microcontroller. The instrument consists of 2 silver plates, an INA219 module, an Arduino Nano module, an LM 2596 module, an Organic LightEmitting Diode (OLED), and a 9V 1A (DC) adapter, as shown in Fig. 2.

Fig. 2. The potential difference instrument made.

Fig. 2. The potential difference instrument made.

b. Discussion. The calibration was carried out at a set point of volume in the range of 5 to 15 mL with an increase of 0.1 mL at each set point and at a distance between the two electrodes of 3 cm . The calibration result data is shown on the calibration chart in Fig. 3.

Fig. 3. The calibration graph of the instrument made.

Fig. 3. The calibration graph of the instrument made.

Figure 3 shows an equation with regression coefficient of 0.9675 , a constant of 0.0018 and a coefficient of determination of 0.9829 . The coefficient of determination indicates that the accuracy of the instrument made is . This shows a deviation of measurement between the instruments made and the standard one. So it is necessary to do more measurements to recalibrate the measuring instruments made, and then adding the calibration equations to the program code. The data obtained are displayed on the calibration graph as shown in Fig. 4.

Fig. 4. The recalibration graph of the instruments made.

Fig. 4. The recalibration graph of the instruments made.

Figure 4 shows an equation with a regression coefficient of 0.9935 , a constant of 0.0001 , and a coefficient of determination of 0.9982 . The coefficient of determination obtained shows that the accuracy of the measuring instrument made is . The accuracy was increased by compared to the previous accuracy. Further, the measuring instrument was used to measure the membrane potential of ' chitosan membrane' in various concentrations of KCl electrolyte solution. The data obtained are presented in Table 1.

Table 1. The potential difference data of ' chitosan membrane' in various concentrations of KCl electrolyte solution.

Concentration (mM) | Average Voltage (V)
Room 1 | Room 2 | Design* | Standard**
0.1 | 0.1 | 0.0026 | 0.0026
1 | 0.1 | 0.0068 | 0.0068
10 | 0.1 | 0.0080 | 0.0080
100 | 0.1 | 0.0106 | 0.0106
250 | 0.1 | 0.0116 | 0.0116
500 | 0.1 | 0.0168 | 0.0170
750 | 0.1 | 0.0176 | 0.0176
1000 | 0.1 | 0.0186 | 0.0186

the instrument design; ** the standard instrument.

Table 1 shows the similarity reading results obtained between the measuring instruments made and the standard one. This shows the accuracy of the measuring instrument made. It was also found that the measuring instrument made has several advantages compared to the standard one including, a shorter measurement time required of around 30 minutes, while the standard instrument requires around 100 minutes. The data obtained is automatically saved in excel data format (.xlsx), which is very necessary for the next analysis. Meanwhile, the measurements by using the standard instrument were one by one manually. Table 1 also shows that the greater the difference in solution concentration between the two rooms, the greater the potential difference generated. These results are consistent with published studies. So this result indicates that the instrument made can use to measure membrane potential which replaced the measurement manually.

Conclusion

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In this research, it is reported that a potential difference measuring instrument has been successfully designed and manufactured using a capacitive sensor based on the ATmega328 microcontroller. The measuring instrument consists of two (2) silver plates as electrodes, an INA219 module, an Arduino Nano module, an LM 2596 module, an Organic Light-Emitting Diode (OLED), and a 9 V 1A (DC) adapter. The workings instrument procedures are adapter and KCl electrolyte solution as a source of electrical energy, capacitive sensors as electrodes called anode and cathode, which are connected to INA219. The input data is processed from analog to digital signals by Arduino Nano, and the output data is displayed on the OLED via I2C and saved in Excel format. This instrument has an accuracy of 99.82%.

Acknowledgment

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The author would like to thank all those who have assisted in the research work, especially the Head of the Biophysics Laboratory and the Head of Dept. of Physics, Faculty of Mathematics and Natural Sciences Udayana University, who have provided facilities to conduct this research.

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The original version of this paper is available on https://www.scientific.net/EI.12.49.pdf

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Tritiyatma Hadinugrahaningsih, Rahma Esi Andina, Lingga Restu Munggaran, Yuli Rahmawati, Analysis of Students' Alternative Conceptions about Electrolyte and Non-Electrolyte Solutions Using a Two-Tier Diagnostic Test for Chemistry Teaching Improvement, Universal Journal of Educational Research 8 (2020) 1926-1934

N.N. Rupiasih, Effects of electrolytes on ion transport in Chitosan membranes, Journal of Physics: Conference Series 776 (2016) 012045

Maulida Nirwana Islami, Ni Nyoman Rupiasih, Made Sumadiyasa, I. B. Sujana Manuaba, The Study of Current-Voltage (I-V) Characteristic Curve of Chitosan-Silver Nanoparticle Composite Membrane, Buletin Fisika 19 (2) (2018) 40-45

Xin He, Zhihao Liu, Gengzhe Shen, Xiang He, Jionghong Liang, Yu Zhong, Tianlong Liang, Jie He, Yue Xin, Chi Zhang, Dongdong Ye, Guofa Cai, Microstructured capacitive sensor with broad detection range and long-term stability for human activity detection, npj Flexible Electronics 5 (2021) 17

Siti Balqis Dongoran, Juniastel Rajagukguk, Design and development of water condition measurement in soil using a capacitive based sensor, Journal of Mathematics and Natural Sciences 1 (2021) 1-4

Bayu Jiah Setiawan, Gurum Ahmad Pauzi, Agus Riyanto, Arif Surtono, Design and Build Voltage and Current Monitoring Parameters Device of Rechargeable Batteries in Real-Time Using the INA219 GY-219 Sensor, Journal of Energy, Material, and Instrumentation Technology 4 (2023) 58-71

Rangga Pradana Putra, Yusli Yenni, The Design of Arduino Uno Based Automatic Concrete Maker, JEEMECS 3 (2020) 171-178

Nikhil Sain, Deepesh Sharma, Priya Choudhary, A Review Paper On: Organic Light-Emitting Diode (OLED) Technology And Applications, International Journal of Engineering Applied Sciences and Technology 4 (2020) 587-591

Cekmas Cekdin, Zainuddin Nawawi, Muhammad Faizal, An Effort to Reduce Voltage from DC to DC Converter with a Monolithic Circuit Based on IC LM 2596, Journal of Computational and Theoretical Nanoscience 16 (2019) 5162-5165

Ni Nyoman Rupiasih, W. G. Suharta, Made Sumadiyasa, Maulida Nirwana Islami, The CurrentVoltage Properties of Ch/AgNP Composite Membranes: A Study on the Effect of AgNP Content, IOP Conf. Series: Materials Science and Engineering 515 (2019) 012064

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Engineering Innovations, ISSN: 2813-1002, Vol. 12, pp 55-63

doi: 10.4028/p-C6ITcm

© 2025 The Author(s). Published by Trans Tech Publications Ltd, Switzerland.

Submitted:
2023-12-19

Revised:
2024-04-30

Accepted:
2024-05-01

Online:
2025-01-03

Performance Comparison of Max-Chart and AEWMA-Max Chart in Monitoring Temperature

The original version of this paper is available on https://www.scientific.net/EI.12.55.pdf

Salman Alfarizi P.A , Muhammad Ahsan , Muhammad Mashuri , Kevin Agung Fernanda Rifki

Department of Statistics, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia

s_alfarizi98@yahoo.com, muh.ahsan@its.ac.id*, m_mashuri@statistika.its.ac.id, fernandakevin02@gmail.com

Keywords: Adaptive Exponential Weighted Moving Average Max-Chart (AEWMAM), Control Chart, Statistical Process Control (SPC), Temperature, Univariate, vannamei.

Abstract

Traditional control charts often struggle to simultaneously detect both small and large shifts in process parameters. This study proposes the AEWMA-Max method, an improved variant of the Adaptive Exponentially Weighted Moving Average Max (AEWMAM) chart, to address this challenge in the context of monitoring temperature fluctuations in vannamei shrimp ponds. The research employs a data set containing 26 out-of-control and 64 in-control temperature measurements. AEWMA-Max utilizes a dynamically adjusted smoothing parameter (L) to achieve optimum sensitivity for both subtle and significant deviations from the desired temperature range. Through extensive simulations and comparisons with existing control charts, was identified as the most effective value for this specific application. The proposed AEWMA-Max method demonstrably outperforms traditional charts in detecting both small and large temperature shifts, offering enhanced process control and potentially improved shrimp survival rates.

Introduction

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Ponds are one of the most popular places for cultivation in Indonesia. Ponds are artificial ponds that are usually found in coastal areas and are used as a means of aquaculture [1]. One of the aquaculture commodities that farmers are interested in is the vannamei shrimp (Litopenaeus Vannamei).
Vannamei Shrimp (Litopenaeus Vannamei) is a type of shrimp that has been developed with intensive technology, and the development is carried out only in brackish water media, vannamei has a high tolerance for temperature to live [2]. One of the determining factors for the success of aquaculture in ponds is the water temperature in the pond. Temperature is a water quality parameter that has an important role in the resistance and growth of L. vannamei [3].
Statistical Process Control (SPC) is a technique statistic That Lots used to ensure that something process fulfills certain criteria. SPC themselves is used To identify shift processes quickly and minimize the level of product damage [4]. SPC is a production method to achieve maximum efficiency, productivity, and quality to produce competitive products. The control chart is one of the main techniques in SPC), and is a very useful process monitoring technique [5].
The control chart, originally known as the Shewhart control chart, was a method devised by Walter Andrew Shewhart to increase the robustness of the current transmission system [6]. One of the statistical methods that is often used in solving problems with the quality control of the production process is the control chart. The control chart is a tool used for process monitoring where the process is running from time to time so that you can see the quality of the results of a production process, regardless of whether it is statistically controlled [7]. Control charts are divided into two, namely univariate and multivariate control charts. The univariate control chart is a control chart that uses one quality characteristic. The multivariate control chart is a control chart where more than one quality characteristic is used [8].
The monitoring process is carried out partially, namely on the mean and variability [9]. Several studies on univariate simultaneous control charts to monitor the mean and process variability have been carried out by [10], namely the Max chart which combines the control chart and into a

Click here to enter text.
control chart to monitor the mean and process variability together. The max chart method uses the maximum function for two statistics [11].
The development of the control chart begins by differentiating the two variations that are more effective in detecting small process shifts, namely the Cumulative Sum (CUSUM) control chart by Page in 1954 and the Exponentially Weighted Moving Average (EWMA) control chart by SW Roberts in 1959. Shewhart control chart with data observed at the current time can detect a shift in the process mean or a large variation, while detecting a shift in the process mean or a small variation using the EWMA charts [12]. However, if in production there are small shifts in the mean value, then the Shewhart control chart is not good enough to detect it. Therefore, an EWMA control chart is needed which can overcome the problem of variation in production results when there is a small shift in the mean value of production.
A control chart based on Adaptive EWMA-Max (AEWMAM) is a method of development by combining two methods, namely the Max Chart method [10] with the Adaptive EWMA method of research [13]. On the other hand, the AEWMA control chart is also undergoing development. Considering the AEWMA control chart only works well on small mean shifts but not on large shifts[14]. AEWMA-Max is superior to other existing simultaneous charts in that by detecting small shifts in process parameters it is also good at detecting large shifts [15].
Based on the description of the explanation of the idea above, the researcher proposes to find the best combination of parameters by comparing control charts based on Adaptive exponentially weighted moving average max (AEWMAM) Charts and Max-Charts with real data (temperature) on the vannamei shrimp ponds of CV Air Mas Jaya. This chart is expected to be efficient in controlling the mean and variance simultaneously so that it has better performance.

Related Work

The original version of this paper is available on https://www.scientific.net/EI.12.55.pdf

There are several studies in the literature review that have discussed theory development before and up to the AEWMA-Max chart, here are examples:
The Shewhart control chart with the observed data at the current time is able to detect shifts in the process mean or large variations, while detecting shifts in the process mean or small variations using the AEWMA charts [16].
Several studies on univariate simultaneous control charts to monitor the mean and process variability have been carried out by [17], namely the Max chart which combines the control chart and into a control chart to monitor the mean and process variability together.
In research[16] the application of data to the AEWMA method is good for use on data that has changing characteristics due to the relationship with external factors with a fairly high intensity. In his research, the data used is turbine temperature, turbine failure, and the number of failures in wind generators.
AEWMA schemes are superior to conventional EWMA in the reduction of many adverse effects at fixed States, and the evaluation of multiple graphs using fixed sizes [13]. Research [18] developed an Adaptive Exponentially Weighted Moving Average-Max (AEWMA-Max) control chart which is an extension of the Max chart where the AEWMA technique is applied to Max chart statistics. AEWMAMax is superior to other existing simultaneous charts in that by detecting small shifts in process parameters it is also good at detecting large shifts[19]. On the other hand, the AEWMA control chart is also undergoing development. Considering the AEWMA control chart only works well on small mean shifts but not on large shifts.

Exponentially Weighted Moving Average (AEWMA)

The original version of this paper is available on https://www.scientific.net/EI.12.55.pdf

A control chart based on Adaptive EWMA-Max (AEWMAM) is a method of development by combining two methods, namely the Max Chart method [10] with the Adaptive EWMA method of research [13]. The control chart is able to work well on small and large shifts that are the basis of Adaptive the AEWMAM statistical formula which is defined as follows:

where is a Huber score function which is one of the best functions in providing performance at different shift sizes, and does not completely ignore the previous observation process [13]. The Upper Control Limit (UCL) and the lower control limit on the AEWMAM Control chart can be defined as follows.

Max Chart

The original version of this paper is available on https://www.scientific.net/EI.12.55.pdf

Control chart Max- or Max Chart is a univariate simultaneous control chart that has the function of monitoring process averages and variability in one chart. Given that X denotes certain characteristics of a process, is the average of the process, and is the standard deviation of the process. Given and is the measurement result of X with sample size and i denotes the sample number index is a random sample from a normal distribution with mean and standard deviation with dan by indicating the process is incontrol, besides the process has shifted.
Given and is the average of the i -th sample and is the variance of the i-th sample. Therefore, the simultaneous control chart is formulated as follows:

Where for , the standard normal distribution, . function of . for , the chi-squared distribution with degrees of freedom v .
and are independent because and are also independent, when and and . The advantages of transforming into Ui and becoming Vi are: (1) the distribution of and is independent for the sample size when dan , so that the case of variable sample size can be handled easily; (2) and have the same distribution so that a single control chart can be formed to monitor process averages and variability. In particular, the statistics for the simultaneous control chart are defined as follows:

The value of the test statistic becomes large when the process shifts away from and/or when the process variability increases or decreases. On the other hand, the value decreases when the mean and process variability remain close to their respective target values. So that the control limits are as follows

Thus, the Upper Control Limit (UCL) on the Max chat can be easily determined for various types I error probabilities ( ).

Fig. 1 Detection scheme flowchart using Max Chart

Fig. 1. Detection scheme flowchart using Max Chart

Applying AEWMA-Max Chart on pond temperature data

The original version of this paper is available on https://www.scientific.net/EI.12.55.pdf

Bangkalan is one of the regencies in East Java Province, specifically on Madura Island. This temperature data collection is in the Klampis sub-district, Bator sub-district, where geographically, the Klampis sub-district is located on the coast which is very suitable for vannamei shrimp cultivation. One type of shrimp that has the potential to be developed is vannamei shrimp (Litopenaeus vannamei). This cultivation develops with intensive technology but is limited to the upper middle class (capital intensive) [2]. One of the determining factors for the success of aquaculture in ponds is the temperature of the water in the pond [3]. Temperature is a water quality parameter that has an important role in the development and growth of L. vannamei. There are 2 measurements of temperature in one day, in the morning and the evening. Spreading vannamei shrimp seeds until they are ready for harvest takes approximately 4 months.
Given denotes the quality characteristics of a process with denotes the mean of the process and denotes the standard deviation of the process where denotes the sample number index. AEWMA statistics with smoothing constant are shown in the following equation[20].

with . When the process is in-control, the mean and variance of the AEWMA statistics are

where and denote the mean and variance of the target respectively. If these two values are unknown, they can be estimated using a preliminary sample.
AEWMA-Max chart is an expansion control chart from Max chart by applying the AEWMA technique to Max chart statistics. The AEWMA-Max statistic is defined in the following equation[18].

where is the initial value. and are independent, when and then and .
So that the cumulative Distribution Function (CDF) from Max Chart statistics, which is as follows

Furthermore, the Probability Density Function (PDF) of statistics is the derivative of the shown in the equation.

Using numerical computation, the mean and variance of are as follows

Using numerical computation, the mean and variance of are as follows
,
.
can be distributed with and can be substituted with , so the control limits for the AEWMA-Max chart are as follows.

For increasingly large , the control limits will approach steady-state values, ie

Fig. 2 Detection scheme flowchart using AAEWMA-Max

Fig. 2. Detection scheme flowchart using AAEWMA-Max

Performance evaluation of Max Chart and AEWMA-Max Chart

The original version of this paper is available on https://www.scientific.net/EI.12.55.pdf

In this study, the application assists the process of data input and data processing. Data processing in Excel, namely inputting temperature data for vannamei shrimp ponds at CV Air Mas Jaya, which has been running for about 2 months. As well as data processing in the R program to issue the best combination between Max-Chart and AEWMA-Max on shrimp pond temperature data and find out how out of control the temperature data is in CV Air Mas Jaya vannamei shrimp ponds. In the simulation scenario on Max-Chart and AEWMA-Max, on AEWMA-Max there is a comparison of the best parameter combinations. The following is the parameter table for AEWMA-Max:

Table 1 Lambda and L parameter values used in the AEWMA-Max method

λ | 0.1 | 0.2 | 0.3 | 0.4
k | 2.642 | 2.934 | 3.092 | 3.212

In all scenarios, the best method for monitoring the process is by implementing temperature data which can be seen from the amount of out-of-control data on the control chart graph. Here are the best results on the temperature data in the image below.

Table 2 Amount of data Out of Control and In Control on AEWMA-Max control chart and Max Chart

MAX-Chart | Out of Control | 20
| In Control | 70
AEWMA-MAX (λ=0.1 and L=2.642) | Out of Control | 26
| In Control | 64
AEWMA-MAX (λ=0.2 and L=2.934) | Out of Control | 16
| In Control | 74
AEWMA-MAX (λ=0.3 and L=3.092 | Out of Control | 22
| In Control | 53
AEWMA-MAX (λ=0.4 and L=3.212) | Out of Control | 3
| In Control | 87

The explanation in the table above is as follows, in the temperature data with the Max-Chart method there are 20 data out of control and 70 data in control. In the AEWMA-Max method with and data were out-of-control and the number of data controlled was 64. In the AEWMAMax method with and , the uncontrolled data is 16 and the number of controlled data is 64. In the AEWMA-Max method with and , the data out of control is 22, and the amount of data in control is 53. AEWMA-Max with and , the uncontrolled data is 3 and the number of controlled data is 87 .

The temperature data on shrimp farms CV Air Mas Jaya vannamei tend to decrease in value, then the Max-Chart control chart is not appropriate because the amount of data out-of-control too much and too little data in-control, while the Aewma-Max control chart matches the best combination of parameters with and , with 26 data out-of-control and 64 data in-control. AEWMAMax with and is the best combination of the other two combinations because it has the largest and smallest out-of-control data on the control data, it can be seen that this method is the most suitable and sensitive method for temperature data in shrimp ponds vannamei CV Air Mas Jaya.

Conclusion

The original version of this paper is available on https://www.scientific.net/EI.12.55.pdf

In the cultivation of Litopenaeus vannamei shrimp, water temperature in brackish water ponds plays a crucial role in their resilience and growth. This study sought to optimize temperature monitoring by comparing two control charts: Adaptive Exponentially Weighted Moving Average Max (AEWMAM) and Max-Chart. Our analysis identified the AEWMAM-Max chart with and as the most effective, with 26 out-of-control signals effectively highlighting potential deviations from optimal temperature ranges for shrimp health and growth. This finding contributes to improved precision and timeliness of intervention in shrimp aquaculture, potentially leading to enhanced resilience and productivity in Litopenaeus vannamei cultivation.

References

The original version of this paper is available on https://www.scientific.net/EI.12.55.pdf

Mangampa M, Suwoyo HS. Budidaya udang vaname (Litopenaeus vannamei) teknologi intensif menggunakan benih tokolan. J Ris Akuakultur 2016;5:351-61.

Poernomo A. Teknologi probiotik Untuk Mengatasi Permasalah tambak Udang dan lingkungan Budidaya. Natl. Symp. Dev. an Sci. Technol. Innov. Aquac. Semarang, 2004.

Manan A, Putra FR. Monitoring kualitas air pada tambak pembesaran udang vannamei (Litopenaeus vannamei) di Situbondo, Jawa Timur [Monitoring of water quality on rearing ponds of vannamei shrimp (Litopenaeus vannamei) in Situbondo, Jawa Timur]. J Ilm Perikan Dan Kelaut 2014;6:137-42.

da Costa Quinino R, Lee Ho L, Galindo Trindade AL. Monitoring the process mean based on attribute inspection when a small sample is available. J Oper Res Soc 2015;66:1860-7.

Montgomery DC. Introduction to statistical quality control. John Wiley & Sons; 2020.

Center P. A Brief History. West Electr 2012:22.

Chatterjee K, Koukouvinos C, Lappa A. A new S 2-TEWMA control chart for monitoring process dispersion. Qual Reliab Eng Int 2021;37:1334-54.

Khaw KW, Chew X, Yeong WC, Lim SL. Optimal design of the synthetic control chart for monitoring the multivariate coefficient of variation. Chemom Intell Lab Syst 2019;186:33-40.

Cheng SW, Thaga K. Single variables control charts: An overview. Qual Reliab Eng Int 2006;22:811-20. .

Chen G, Cheng SW. Max chart: combining X-bar chart and S chart. Stat Sin 1998:263-71.

Huang CC. Max control chart with adaptive sample sizes for jointly monitoring process mean and standard deviation. J Oper Res Soc 2014;65:1788-99.

Hussein M, Almorshedi A, Shomran H. The Comparison between Shewhart Control Chart ,Cusum and EWMA. 2013. .

Capizzi G, Masarotto G. An Adaptive Exponentially Weighted Moving Average Control Chart. Technometrics 2003;45:199-207.

Sanusi RA, Mukherjee A, Xie M. A comparative study of some EWMA schemes for simultaneous monitoring of mean and variance of a Gaussian process. Comput Ind Eng 2019; 135: 426-39.

Sanusi RA, Teh SY, Khoo MBC. Simultaneous monitoring of magnitude and time-betweenevents data with a Max-EWMA control chart. Comput Ind Eng 2020;142:106378.

Li H, Deng J, Yuan S, Feng P, Arachchige DDK. Monitoring and identifying wind turbine generator bearing faults using deep belief network and EWMA control charts. Front Energy Res 2021;9:799039.

Chakraborti S, Graham MA. Nonparametric (distribution-free) control charts: An updated overview and some results. Qual Eng 2019;31:523-44.

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Chatterjee K, Koukouvinos C, Lappa A. A joint monitoring of the process mean and variance with a TEWMA-Max control chart. Commun Stat Methods 2022:1-27.

Roberts SW. Control chart tests based on geometric moving averages. Technometrics 2000; 42: 97-101.

This ePub file was created using machine-generated methods and automated software to convert the source text into an ePub format and may contain formatting inconsistencies from the original version. Formatting may vary depending on the device used.

The original version of this eBook is available on https://www.scientific.net/book/engineering-innovations-vol-12/978-3-0364-1691-5

Engineering Innovations, ISSN: 2813-1002, Vol. 12, pp 65-76

doi: 10.4028/p-4A6zQm

© 2025 The Author(s). Published by Trans Tech Publications Ltd, Switzerland.

Submitted:
2024-07-01

Revised:
2024-09-04

Accepted:
2024-09-05

Online:
2025-01-03

Mode Division Multiplexing Free Space Optical communication System Performance With Aperture Averaging in Atmospheric Turbulence and Various Weather Conditions.

The original version of this paper is available on https://www.scientific.net/EI.12.65.pdf

Simbarashe Magidi Taurayi Pondani

Department of Electronic Engineering, Harare Institute of Technology, Zimbabwe

Department of Biomedical Engineering, Harare Institute of Technology, Zimbabwe

smagidi@hit.ac.zw, tpondani@hit.ac.zw

Keywords: Mode division multiplexing, Modified Duo binary Return to Zero, Free space optical, aperture averaging, Bit Error Rate.

Abstract

Due to the serious challenge for mobile operators as a result of spectrum congestion in radio frequency spectrum, free space optical (FSO) communication has been considered a timeous alternative especially for future generation high capacity wireless networks. Although FSO offers advantages such as huge data carrying capacity among others, it suffers from the drawback of atmospheric turbulence and adverse weather conditions. As a mitigation to this problem, mode division multiplexing (MDM) has been another research direction. This paper proposes the design and numerical simulation of a hybrid modified duobinary return to zero (MDRZ) MDM free space optical communication system, which to the best of the authors' knowledge has not been a subject of investigation. The performance metrics used are the bit error rate, quality factor and received optical power. Two modes, HG00 and HG01 were investigated and compared. It has been observed that the BER, Q factor and received power degrades as we increase the beam divergence, FSO transmission distance and data rate. Moreover, the performance gap between clear and moderate weather conditions is more for HG00 than for HG01 for the same considered data rates. The aperture averaging has been shown to be a strong mitigation strategy especially in foggy conditions.

Introduction

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The advantages of free space optical communication such as huge unlicensed spectrum, huge data carrying capacity, easy of deployment and security has motivated its extensive research and applications since the past few decades [1]. Because FSO somehow unifies the features of optical as well as wireless communication, it has attracted special applications from inter-chip connects in modern high speed electronic systems, quick temporal link for disaster recovery or conferences, fiber last mile access link and deep space applications [2]. FSO does not require a fiber cable, but rather a data modulated laser beam is propagated from the transmitter to the receiver via optical telescopes. The transmission of modulated light through the FSO link suffers adversely from prevailing weather conditions and atmospheric turbulence induced loss referred to as scintillation [3]. Absorption occurs due to the presence of atmospheric gases such as oxygen and hydroxyl ions. Since FSO links requires a line of sight and that the transceivers are typically installed on high rise buildings and other structures, misalignment between the transmitter and receiver contributes to pointing error loss [4]. A hybrid polarization division multiplexing (PDM) with wavelength division multiplexing (WDM) and its performance is investigated in [5]
In order to improve the performance of FSO communication, different techniques have been explored in literature among which mode-division multiplexing (MDM), has been another option [6]. In this scheme, a number of channels are transmitted on different modes generated by different mechanisms such as spatial light modulators [7], few mode fibers [8], photonic crystal fibers [9] and optical signal processing among others [10].MODE Division Multiplexing (MDM) is a technique that incorporates multiple spatial optical modes inside an optical waveguide or fiber to increase the capacity of communication channels. In mode division multiplexing, (MDM), multiple spatial optical modes are used inside the waveguide. Thus different data channels can be transmitted simultaneously through
spatial modes in a similar fashion to the common wavelength division multiplexing (WDM) [11]. It basically use the principal of orthogonality of transverse electric (TE) and Transverse magnetic (TM) are well separated when propagating inside an optical waveguide. Hence they do not interfere with each other. This allows for their exploitation as in depended communication channels. Although the earlier application of MDM technology was in chip to chip communication, its usefulness has since expanded to terrestrial FSO communication [12]. Key advantages of MDM technology includes increased data carrying capacity, efficient utilization of the same channel, can be combined with other existing multiplexing technology such as time division multiplexing, frequency division multiplexing and it also offers better utilization of bandwidth among other advantages. Key applications include high capacity optical networks and long distance communication. Despite having these advantages, the main challenges of MDM includes complex signal processing and improvement of channel isolation.

Related Works

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Several works reports on MDM based FSO communication in literature. Modulation schemes plays an integral part of any communication system as it allows for efficient use of the channel bandwidth, power and other available resources. In FSO communication, different modulation schemes have been applied such as on off keying (OOK), differential phase shift keying (DPSK), duobinary and modified duobinary return to zero (MDRZ) [13]. Modeling and investigation of MDM based inter-satellite optical wireless communication (IsOWC) link using OOK based two independent 40 Gbps LG modes of a single laser has been carried out in [14]. The analysis of that system under the impact of pointing error revealed acceptable performance transmission upto rad error angle. The work in [15] reported on the design and simulative modeling of a 2 X 20 Gbps 40 GHz hybrid mode division multiplexing with QAM and DQPSK OFDM radio over free space optical communication system. The performance analysis of the proposed system was carried out based on the error vector magnitude, signal to noise ratio (SNR) and eye diagram. A similar work with OFDM and 4QAM was investigated in more detail in [16]. Another similar work reported on the design and analysis of two independent OFDM based HG01 and HG03 MDM for radio over free space optical communication system [17].
The performance of the WDM in hybrid fiber/free space applied in passive optical networks have been investigated using digital-pulse-position modulation scheme in [18], whereas the dense wavelength division multiplexing with OOK optical communication system was demonstrated in [19]

A performance comparative analysis of an LG mode division based FSO communication system employing polarization shift keying and OOK was investigated in [20] over a maximum link distance of 90 km at 40 Gbps . The influence of different weather conditions was also scrutinized.
The authors in [21] investigated on performance of LP01 and LP11 based MDM FSO communication system with each channel carrying data at a rate of 10 Gbps . Transmission was successful up to a link distance of 8 km with NRZ and RZ modulation schemes. A DPSK based hybrid MDM radio over free space was investigated in clear weather only for a link span of 40 km in [22].

An interesting work reported in [23], investigated on MDM based radio over free space optical communication system using different modulation schemes such as alternate mark inversion, NRZ, return to zero differential phase shift keying (RZ-DPSK) and NRZ-DPSK. Comparative analysis between these different modulation schemes revealed that NRZ-DPSK modulation scheme provided considerably much better results. In [24], dual polarization quadrature phase shift keying (DP-QPSK) polarization shift keying (PoLSK) hybrid modulation scheme was proposed for free space optical transmission system. The system was analyzed at 30 Gbps and 40 Gbps with DP-QPSK and PoLSK respectively under the influence of different weather conditions. In another study [25], a 50 Gbps hybrid polarization division multiplexing (PDM) and optical code division multiplexing was proposed to enhance the capacity of radio over FSO systems. The system was able to achieve a link span of 3.5 km at acceptable BER levels. Most of the works on OOK based MDM FSO communication systems proposed were extended in [26].

Motivated by this short literature review, we note that in all the afore mentioned works, no work has reported on the design and performance analysis of a hybrid modified duobinary return to zero mode division multiplexing free space optical communication system. Further, very few if any of the works available in literature report on the improvement of MDM FSO using aperture averaging. Therefore, in this work, we demonstrate the modeling and analysis of a hybrid MDM-MDRZ based FSO communication system. This work has been carried out with the following objectives: (1) design a hybrid MDRZ-MDM FSO communication system, (2) analyze the performance of such a system in clear and moderate weather conditions and (3) apply aperture averaging to improve the performance of such a system. The rest of the paper is organized as follows: in Sect II the system design has been presented, followed by results and discussion in Sect III. The paper is concluded in Sect IV.

System design

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Fig.1. Design of the proposed MDRZ-MDM FSO transmission system.

Fig.1. Design of the proposed MDRZ-MDM FSO transmission system.

A schematic of the proposed modified duobinary MDM free space optical communication system is illustrated in Fig.1. OptiSystem simulation software has been used to simulate the system. First, the binary information at variable bit rate was generated using the pseudorandom bit generator (PRBS). These information bits were then send to the MDRZ encoder. In the proposed work, we have generated two independent distinct HG modes (HG00 and HG01), each being of the same wavelength of 1550 nm using a spatial laser. The HG modes are mathematically described as [27] [15]:

In Eq.1, the field dependencies on the x and y axis polarizations is denoted by m and n respectively, the beam waist spot size is denoted by . The x -axis and y -axis radii of curvature is represented by and respectively. Finally, and are the Hermite polynomials.

Channel modelling

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The physical medium which links the transmitter and the receiver is hereby considered to be free space. Therefore, while the signal is propagating in this channel, it will be adversely affected by absorption, scattering, atmospheric turbulence losses and frequency selective fading among others losses. The received signal power is be expressed by [28]

In this equation, is the received optical power when the transmitted power is denotes the effective aperture area of the receiving antenna, is the beam divergence angle, L denote the FSO
link and finally is the Exponentiated atmospheric path los which can be expressed be Beer Lambert law as [29]:

Here represent the weather dependent atmospheric losses, which in turn can be obtained from Kim model [30]. Further, the received power can be expressed as

Where denote the PDF of the atmospheric turbulence. In this study, the atmospheric scintillation has been modelled using the log normal turbulence which can be expressed as:

Here, is the Roytov variance, is the refractive index structure, represents the optical wave number, is the operational wavelength, and represents the field irradiance in the absence of turbulence and in presents of turbulence respectively [3], is the mean log intensity. The unconditional probability of error for the MDRZ modulation scheme in free space channel is obtained as:

Where stands for the complimentary error function, represents the SNR PDF of the log normal fading channel.
To generate these distinct modes, a spatial laser was used. This in essence is a combination of a CW laser and a multimode generator. Each distinct mode independently modulate information signal with variable data rate with the aid of Mach-Zehnder modulator (MZM), operating in a push-pull state. Later on, an optical combiner was used to combine these two independent MDRZ modulated signals and then transmitted into free space optical channel with the aid of the transmitting telescope. In the channel, the transmitted signal encounters channel loss, geometric spreading, and scintillation loss due to atmospheric turbulence, as well as different atmospheric conditions such as rain and fog as a result, there is interaction between the molecular constituents of the atmosphere and the photons and thus scattering and attenuation of the propagating beam. Therefore the link equation can be described as [31]

Where and denote the received and transmitted power respectively, and are the transmitter and receiver antenna diameter respectively, is the beam divergence angle, is the FSO link length and denotes the attenuation constant.
At the receiver end, the transmitted signal consisting of two independent MDRZ modulated HG information signals is intercepted using a receiving lens. This is immediately followed by a mode filter, which will allow the selected HG mode to pass and blocks all other modes. Thus in this way, the HG 00 and HG01 information are independently recovered. The signal is then passed to the receiver, which consists firstly of a low pass filter, which filters out any unwanted noise signals. A 3R regenerator is also used for clock and timing recovery. Finally the signal is passed into the BER analyzer, where the performance parameters can be analyzed, such as the bit error rate, quality factor,
eye height and eye opening among other desired parameters. The simulation parameters considered in this work are given in Table 1

Table 1. Simulation parameter values

Parameter | Value
Wavelength | 1550 nm
Transmitter power | 10 dBm
Receiver aperture diameter | 5, 10, 15 cm
Responsivity o PIN photodetector | 0.5 A/W
Dark current of photodiode | 10 nA

Results and Discussion

The original version of this paper is available on https://www.scientific.net/EI.12.65.pdf

In this section, the results of the proposed MDRZ based MDM FSO transmission system is presented and analyzed. The effect of the beam divergence, transmission range and data rate on the FSO system is analyzed in different weather conditions using the BER, Q factor and received optical power as performance metric measures. In Error! Reference source not found., the impact of varying the beam divergence on the performance of the MDRZ-MDM free space optical communication system is analyzed in clear and moderate weather conditions. The transmission distance has been fixed at 4.5 km . it is clear from the results that the beam divergence have got a detrimental effect. As the beam divergence is increased, from 2 mrad to 3.5 mrad , the BER considerably reduces for both channels. However, channel with HG 00 performs better than HG 01. For example in clear weather conditions at a beam divergence of and 3.5 mrad , the BER is and respectively for HG 00 channel, while the BER is and respectively for HG 01 . A similar trend is observed in moderate turbulence conditions.

Fig. 2. Effect of beam divergence on the BER of the MDRZ MDM FSO system.

Fig. 2. Effect of beam divergence on the BER of the MDRZ MDM FSO system.

The BER performance of the proposed system with increasing FSO transmission range for both clear and moderate turbulence is shown in Fig.3. The BER of HG00 channel can be computed as and at transmission distance of 4,5 and 6 km respectively in clear weather conditions. In moderate weather conditions, the BER reduces to , and for the same transmission distance. Similarly, the BER for the HG01 channel can be computed as and in clear weather
conditions which reduces to and 1 at FSO transmission distance of 4, 5 and 6 km respectively. The Q factor performance is shown in Fig.4. From Fig.4, the Q factor is computed as 15.13, 9.26 and 6.11 at FSO transmission distance of 4,5 and 6 km respectively in clear weather conditions for HG 00 mode. In moderate weather conditions, for the same mode, the Q factor degrades to and 2.97. For the HG01 mode, the Q factor is and 4.15 in clear weather conditions, which degrades to and 2.97 in moderate weather conditions at transmission range of 4, 5 and 6 km respectively. These results show that increasing the FSO transmission range has a deteriorating effect on the overall performance of the proposed MDRZ based MDM communication system. Moreover, the performance of HG00 mode is better than that of HG01 mode mainly because HG00 mode is more tolerant multipath fading compared to HG01 [22].

Fig.3. BER as a function of the FSO transmission range.

Fig.3. BER as a function of the FSO transmission range.

Fig.4. Q factor as a function of distance.

Fig.4. Q factor as a function of distance.

Fig.5 Received power as a function of the FSO range.

Fig.5. Received power as a function of the FSO range.

The power performance for the proposed optical communication system is shown in Fig.5. The received optical power for HG00 in clear weather conditions is calculated as and 20.68 dBm at FSO transmission link of 4,5 and 6 km respectively. This degrades in moderate weather conditions to and -23.77 dBm respectively at the same considered link distances. It is interesting to observe that the power performance of the two modes, HG00 and HG01 is the same in all weather conditions. The variation of the Q factor as a function of distance in different weather conditions for the two considered modes has been plotted in Fig.6. The FSO transmission link has been fixed at 4.5 km . for the HG00 mode in clear weather, the Q factor can be computed as 24.85, 14.46 and 11.70 , which degrades in moderate weather conditions to and 6.36 at data rate of 2, 6 and 10 Gbps respectively. For HG 01 , the Q factor can be computed in clear weather conditions as 17.35, 10.02 and 7.93 which degrades in moderate weather conditions to and 4.56 at data rate of 2,6 and 10 Gbps respectively. It is interesting to observe that HG00 mode degrades faster as the data rate is increased compared to HG01 mode. For example, for HG00 mode, the difference in Q factor between clear and moderate weather conditions is and 5.34 at data rates of 2,6 and 10 Gbps . For HG01 mode, the same difference under same conditions can be computed as 7.10, 4.11 and 3.37. That is to say the performance gap between clear and moderate weather conditions is more for HG00 than for HG01 for the same considered data rates.
The clear eye of the received signals for both HG00 and HG01 modes is presented in Fig.7. This demonstrates transportation of both signals of 10 Gbps up to a 4.5 km transmission range over clear weather for the proposed MDRZ modulation based MDM FSO transmission system.

Fig.6. Q factor as function of data rate.

Fig.6. Q factor as function of data rate.

Fig.7. Eye diagram of the received signal for both HG00 and HG01 modes at 4.5 km .

Fig.7. Eye diagram of the received signal for both HG00 and HG01 modes at 4.5 km .

Fig.8. Aperture averaging effects.

Fig.8. Aperture averaging effects.

The aperture averaging effects has been studied for both HG00 and HG01 modes by plotting the Q factor as the aperture has been varied from 8 to 16 cm , shown in Fig.8. As the diameter of the aperture is increased, the Q factor performance improves, with HG00 mode performing better than HG01 mode.

Conclusion

The original version of this paper is available on https://www.scientific.net/EI.12.65.pdf

Since FSO continues to be an integral part of much of the sectors of communication, much investigation is being carried out to improve its performance in atmospheric turbulence and different weather conditions. This paper investigated on the performance of the proposed MDRZ -MDM free space optical communication system in different weather conditions and moderate turbulence conditions. The performance metrics considered are the BER versus the beam divergence and FSO transmission range, the Q factor versus the transmission range and data rate as well as the effects of aperture averaging. For the two considered modes, it has been observed that HG00 mode performs better than HG01 mode and that performance gap between clear and moderate weather conditions is more for HG00 than for HG01 for the same considered data rates.

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The original version of this paper is available on https://www.scientific.net/EI.12.65.pdf

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Keywords Index

A

Adaptive Exponential Weighted Moving Average Max-chart (aewmam) Performance Comparison of Max-Chart and AEWMA-Max Chart in Monitoring Temperature

Aperture Averaging Mode Division Multiplexing Free Space Optical communication System Performance With Aperture Averaging in Atmospheric Turbulence and Various Weather Conditions.

Atmega328; Arduino; Capacitive Sensor; Potential Difference; Plx-daq Fabrication of a Potential Difference Measuring Instrument Using a Capacitive Sensor Based on aTmega328 Microcontroller

B

Bit Error Rate Mode Division Multiplexing Free Space Optical communication System Performance With Aperture Averaging in Atmospheric Turbulence and Various Weather Conditions.

C

Car Body; Cad; Design; Electric Vehicle Weight Optimization of the Electric Bus Carbody Structure

Control Chart Performance Comparison of Max-Chart and AEWMA-Max Chart in Monitoring Temperature

Corrosion Rate Characterization Study of Wire Arc Additive Manufacturing Layer in Metal Inert Gas Welding Process

D

Ductility Study on Flexural Performance of Fiber Reinforced Concrete Beams Using Glass Fiber Reinforced Polymer Bars and Steel Rebars

E

Epoxy Resin; Binary Synergy; Thermal Degradation Kinetics; Thermal Stability MDNs/FGNs/IFR Synergistic Flame Retardant for Epoxy Resin the Influence of Thermal Degradation Kinetics

Er70s-6 Characterization Study of Wire Arc Additive Manufacturing Layer in Metal Inert Gas Welding Process

F

Finite Element Analysis Modelling and Structural Simulation of Thin-Wall Structure

Flexural Capacity Study on Flexural Performance of Fiber Reinforced Concrete Beams Using Glass Fiber Reinforced Polymer Bars and Steel Rebars

Free Space Optical Mode Division Multiplexing Free Space Optical communication System Performance With Aperture Averaging in Atmospheric Turbulence and Various Weather Conditions.

G

Gfrp Study on Flexural Performance of Fiber Reinforced Concrete Beams Using Glass Fiber Reinforced Polymer Bars and Steel Rebars

H

Hybrid Reinforced Concrete Beams Study on Flexural Performance of Fiber Reinforced Concrete Beams Using Glass Fiber Reinforced Polymer Bars and Steel Rebars

M

Metal Inert Gas Characterization Study of Wire Arc Additive Manufacturing Layer in Metal Inert Gas Welding Process

Metallography Characterization Study of Wire Arc Additive Manufacturing Layer in Metal Inert Gas Welding Process

Mode Division Multiplexing Mode Division Multiplexing Free Space Optical communication System Performance With Aperture Averaging in Atmospheric Turbulence and Various Weather Conditions.

Modified Duo Binary Return To Zero Mode Division Multiplexing Free Space Optical communication System Performance With Aperture Averaging in Atmospheric Turbulence and Various Weather Conditions.

P

Pva Fibers Study on Flexural Performance of Fiber Reinforced Concrete Beams Using Glass Fiber Reinforced Polymer Bars and Steel Rebars

S

Statistical Process Control (spc) Performance Comparison of Max-Chart and AEWMA-Max Chart in Monitoring Temperature

T

Temperature Performance Comparison of Max-Chart and AEWMA-Max Chart in Monitoring Temperature

Thin-walled Structure Modelling and Structural Simulation of Thin-Wall Structure

Transportation Modelling and Structural Simulation of Thin-Wall Structure

U

Univariate Performance Comparison of Max-Chart and AEWMA-Max Chart in Monitoring Temperature

V

Vannamei Performance Comparison of Max-Chart and AEWMA-Max Chart in Monitoring Temperature

W

Waam Characterization Study of Wire Arc Additive Manufacturing Layer in Metal Inert Gas Welding Process

Authors Index

A

Ahsan, M. Performance Comparison of Max-Chart and AEWMA-Max Chart in Monitoring Temperature

Anggono, A. Weight Optimization of the Electric Bus Carbody Structure

B

Budiana, E. Modelling and Structural Simulation of Thin-Wall Structure

Busori, A. Modelling and Structural Simulation of Thin-Wall Structure

F

Fanani, M. Characterization Study of Wire Arc Additive Manufacturing Layer in Metal Inert Gas Welding Process

H

Hemalatha, K. Study on Flexural Performance of Fiber Reinforced Concrete Beams Using Glass Fiber Reinforced Polymer Bars and Steel Rebars

I

Istighfarrullah, G. Weight Optimization of the Electric Bus Carbody Structure

L

Liu, S. MDNs/FGNs/IFR Synergistic Flame Retardant for Epoxy Resin the Influence of Thermal Degradation Kinetics

M

Magidi, S. Mode Division Multiplexing Free Space Optical communication System Performance With Aperture Averaging in Atmospheric Turbulence and Various Weather Conditions.

Mashuri, M. Performance Comparison of Max-Chart and AEWMA-Max Chart in Monitoring Temperature

P

Pondani, T. Mode Division Multiplexing Free Space Optical communication System Performance With Aperture Averaging in Atmospheric Turbulence and Various Weather Conditions.

Prasad, D. Study on Flexural Performance of Fiber Reinforced Concrete Beams Using Glass Fiber Reinforced Polymer Bars and Steel Rebars

Putra, A. Characterization Study of Wire Arc Additive Manufacturing Layer in Metal Inert Gas Welding Process; Fabrication of a Potential Difference Measuring Instrument Using a Capacitive Sensor Based on aTmega328 Microcontroller

R

Rifki, K. Performance Comparison of Max-Chart and AEWMA-Max Chart in Monitoring Temperature

Rupiasih, N. Fabrication of a Potential Difference Measuring Instrument Using a Capacitive Sensor Based on aTmega328 Microcontroller

S

Salman, A. Performance Comparison of Max-Chart and AEWMA-Max Chart in Monitoring Temperature

Saputra, R. Characterization Study of Wire Arc Additive Manufacturing Layer in Metal Inert Gas Welding Process

Supardi, I. Fabrication of a Potential Difference Measuring Instrument Using a Capacitive Sensor Based on aTmega328 Microcontroller

Syawitri, T. Weight Optimization of the Electric Bus Carbody Structure

T

Triyono, T. Characterization Study of Wire Arc Additive Manufacturing Layer in Metal Inert Gas Welding Process

U

Ubaidillah, U. Modelling and Structural Simulation of Thin-Wall Structure

V

Vidyasagar, P. Fabrication of a Potential Difference Measuring Instrument Using a Capacitive Sensor Based on aTmega328 Microcontroller

W

Wang, Q. MDNs/FGNs/IFR Synergistic Flame Retardant for Epoxy Resin the Influence of Thermal Degradation Kinetics

Widodo, P. Modelling and Structural Simulation of Thin-Wall Structure

Wijianto, W. Weight Optimization of the Electric Bus Carbody Structure

Wu, Z. MDNs/FGNs/IFR Synergistic Flame Retardant for Epoxy Resin the Influence of Thermal Degradation Kinetics