Papers by Keyword: Prediction Model

Abstract: A model of the higher heating value on a dry basis from the proximity analysis of agricultural wastes in Benin has been proposed in this article. This model was developed using agricultural residues such as shea shells and cakes, cotton and soybean stalks, corn cobs and peanut shells identified as part of the implementation of an experimental system. The validity of this model has been established for the Higher Heating Value (HHV) between 18.07 MJ/kg to 25.91 MJ/kg, Volatile Matter rate (%VM) 66.8% to 79.87%, Fixed Carbon rate 13.83% to 29.59%, and Ash content (%Ash) 3.47% to 6.3%. The model has an average absolute error of 2.79% and a bias error of 0.034%, significantly better than the most accurate literature prediction model, which offers a mean absolute error of 5.97% and –4.66% for the bias error. This work presents as well the first data from the proximity analysis of agricultural residues in Benin. These analyzes are carried out using a well-structured methodology that respects the standards and measures of simple random sampling forsample collection. Samples prepared under appropriate conditions are analyzed using standardized protocols for the agricultural wastes studied.

Abstract: The paper presents aspects related to noise pollution due to road traffic in Drobeta Turnu Severin. The main noise sources in Drobeta Turnu Severin are: road transport, railway and industrial activities. Based on the noise level measurement performed to assess the traffic noise over a period of 7 years, namely between 2013 and 2019, on an important road traffic artery in the mentioned city, predictions for its level over the next three years are made, correlating it with the number of cars that are supposed to cross the artery. For this study a road where the equivalent noise level exceeded the limit almost every year, was chosen. For obtaining the correlation between our data we have used the regression method. The noise level depends on the time of day in which the measurements were made but also on the season. Another correlation, between the equivalent noise level, and the number and type of cars was made, for a winter day in 2020, on another important artery, in order to see how much influence these factors have, on the noise level.

Abstract: The article established a modelling that predicted and measured the quenching and pre-stretching stress in 7050 aluminum alloy thick plate in order to make the alloy suitable enough for manufacturing in the aerospace industries. The results show that both the rolling direction component stress and the transverse direction component stress have a “M” distribution along the plate thickness of 7050 aluminum alloy thick plate, but the level is slightly different, but the level is slightly different. The maximum value of quenching residual stress is about 187MPa in the 80mm thick of 7050 plate. Pre-stretching of the heat treated and quenched alloy to 0.5%, 1.0%, 1.5%, 2.0%, 2.5%, 3.0% and 3.5% to reduce the residual stresses. It has been recorded that more than 90% reduction of residual stresses were observed in a pre-stretching rage of 2-3%. Measuring the surface residual stresses of the alloy by ultrasonic methods and measuring the internal residual stresses of the alloy by crack compliance methods. The two methods are used to verify the model. The difference between the measurement and the simulation is within 40MPa. The experimental data of the ultrasonic and the crack compliance methods were found to correspond well with the simulated models. This shows that the simulation model can effectively predict the evolution of residual stress in 7050 aluminum alloy thick plate, and the simulation model can also be reconstructed and inspected through the experimentally measurement.

Abstract: Most of the yachts are comprised of fiberglass reinforced plastics composite materials. This material is expensive and difficult to deal with (It is difficult to burn, and not easy to destroy, more cannot be recycled), the internationally known as field-fill. People accumulation and landfill disposal the old takes up a lot of land resources. Therefore, it is necessary to develop a low cost, recyclable and environmentally friendly yacht to replace the current large number of fiberglass reinforced plastics yachts. The purpose of this study was to explore the advantages of the composite bamboo yacht material as a more cost-effective, sustainable alternative. Applying the theory of the deformation of laminated beam, this study tested a prediction model of the composite bamboo yacht material's the modulus of elasticity values. The prediction model accurately calculated the end product's the modulus of elasticity values according to the single bamboo board's the modulus of elasticity values and its assembling manner, without destroying the material's basic structure and integrity. In sum, the main physical and mechanical properties of the composite bamboo yacht material are obviously beyond regular fiberglass reinforced plastics yacht material. The transverse mechanical properties were obviously enhanced by using the advantage of unidirectional alkali free glass fiber plain cloth and improving the assembly manner. Only 10% of the current market cost at time of publication, a renewable, many environmental advantages, radically has enormous market potential to replace regular fiberglass reinforced plastics yacht material.

Abstract: This article deals with the topic of atmospheric corrosion. Atmospheric corrosion causes damage to nearly 80% of all existing steel structures. The main parameters of atmospheric corrosion are the time of wetness (TOW), air temperature and aggressive corrosive agents such as chlorides, sulfur dioxide and others. Currently, low alloy steels with improved atmospheric corrosion resistance called weathering steels are used for the steel structures located in outdoor environment. A protective layer of corrosion products is created on the steel surface and this layer can reduce continuation of corrosion of steel. The time of wetness together with the effect of aggressive corrosive agents are various for surfaces oriented vertically or horizontally. Experimental tests of atmospheric weathering steel were carried out to monitor the impact of location and position of surface on the different constructions. These tests allow monitoring the development of corrosion products in real exposures. The article presents a part of the research, which includes monitoring the development of the thickness of corrosion products with regard to the position on the structure. Research is developed to refine of prediction models with the aim of improving determination of corrosion losses during the service life of the structure. Second part of these experiments is dedicated to measuring the deposition rate of chlorides. Chlorides have a corrosive impact on the steel surface. Under normal conditions the chlorides does not create suitable environment for the development of a protective layer of corrosion products.

Abstract: Polymer composites are gaining attention due to their superior thermal properties. Especially carbon black /carbon nanotubes/ graphene filled polymer composites are used in energy harvesting, thermal actuators and MEMS. The coefficient of thermal expansion (CTE) is one of the most important properties in the polymer composite. In the present study, thermal expansion of polydimethylsiloxane (PDMS) matrix is filled with carbon black particle of varied volume fraction is modeled. Two-dimensional finite element (FE) model is computed in order to explain the thermal expansion behavior of the polymer composite and same is carried out for ambient to 70 K temperature. A 2D regular arrangement of circular particle packing model is set up and simulated. The FE model predicts that filler geometry has a little effect on the thermal expansion than the percentage of filler in the composite. Thermal expansion of composite is compared with the theoretical model. It shows that the CTE of composite reduces as the filler percentage increase, also gives good agreement in the both models. Hence, it is found that the addition of carbon black to the polymer composite could make it perform significantly better in thermal expansion.

Abstract: Thermal conductivity is an important material property in the energy design process of the buildings. While cement-based materials are the most consumed materials in construction industry, thermal properties of these materials can play a significant role in energy efficiency of the buildings. Cementitious materials with low thermal conductivity can be desirable for using as a part of heat insulation or for thermal bridge calculations. In this study, hydrophobic aerogel granules were used as aggregate and combination of Portland cement and fly ash was considered as the binder in order to achieve a material with low thermal conductivity. Replacement of 50 vol% hardened cement paste (hcp) by aerogel granules led to about 70% reduction in thermal conductivity of air dried samples (from 0.67 W/mK to 0.20 W/mK). However, this reduction was nearly 50% in moist samples submerged in water for three days (from 0.97 W/mK to 0.50 W/mK) due to replacement of air by water in hcp pores, which can be avoided by using hydrophobic agents. The thermal conductivity can be reduced by increasing water-cement ratio as well as aerogel content. This type of composite can be used as cast concrete or on-site 3D printing of wall elements.

Abstract: TWIP steel has the characteristics of high elongation and high tensile strength at room temperature, and therefore it is widely used in the automobile manufacturing industry. Since the grain size has a very important influence on its mechanical properties and corrosion resistance it is significant to study the average grain size of TWIP steel. In this experiment, the specimens were heated to 700~1000°C and preserved for one hour, and the recrystallized structures with different average grain sizes were obtained. All the samples were tested by laser ultrasonic experimental platform and the standard sample was selected. Then the attenuation coefficients of remaining samples were compared with the standard samples by conventional methods. The results showed that the larger the difference between the average grain size of the test sample and the standard sample is, the greater the error of the test will be. The new evaluation model was established by the improved method, and the prediction error was reduced to 5.44~11.61%, which proved the effectiveness of the new method. In addition, laser ultrasonic testing has the advantages of high efficiency and no damage compared with traditional methods.

Abstract: Tool wear is a complex phenomenon, it worsens surface quality, increases power consumption, and causes rejection of machined parts. Tool wear has a direct effect on the quality of the surface finish of the workpiece, dimensional precision and ultimately the cost of the parts produced. In modern automated manufacturing machines, tool monitoring system for automated machines should be capable of operating on-line and interpret the working condition of machining process at a given point in time. Therefore, there is a need to develop a continuous tool monitoring systems that would notify operator the state of tool in order to avoid tool failure or undesirable circumstances. This study therefore uses acoustic emission (AE) sensing techniques, signal processing and Artificial Neural Networks (ANN) frameworks to model and validate the machining process. The AE showed effects of tool breakage and ANN predictions closest to the experimental cutting parameters were obtained. It was also shown that the ANN prediction model obtained is a useful, reliable and quite effective tool for modeling tool wear of carbide tools when working on stainless steel. Thus, the results of the present research can be successfully applied in the manufacturing industry to reduce the time, energy and high experimental costs.

Abstract: Contact lens manufacture requires high accuracy and surface integrity. Surface roughness an important response because it has direct influence toward the part performance and the production cost. Hence, choosing optimal cutting parameters will not only improve the quality measure but also the productivity. This research work is therefore aimed at developing a predictive surface roughness model and investigate a finish cutting conditions of ONSI-56 contact lens polymer with a monocrystalline diamond cutting tool. In this work, a novel surface roughness prediction model, in which the feed rate, cutting speed and depth of cut are considered is developed. This combined process was successfully modeled using a Box–Behnken design (BBD) with response surface methodology (RSM). The effects of feed rate, cutting speed and depth of cut were investigated. Analysis of variance (ANOVA) showed that the proposed quadratic model effectively interpreted the experimental data with coefficients of determination of R² = 0.89 and adjusted R² = 0.84. The worse surface value was obtained at high feedrate and low spindle speed.