Papers by Keyword: Compressive Strength

Abstract: This study evaluates the impact of replacing natural sand (NS) with quarry waste sand (QWS) or recycled concrete sand (RCS) at varying substitution rates (0%, 25%, 50%, 75%, and 100%). The analyzed properties include Abrams cone slump, superplasticizer demand (SP), rheological and tribological parameters, mechanical strength, capillary water absorption, and shrinkage. The results show that QWS-based concrete exhibits better workability and requires less superplasticizer, whereas RCS-based concrete necessitates a higher admixture dosage. Both QWS sand and RCS sand significantly enhance the rheological and tribological properties of concrete Moreover, QWS sand provides higher mechanical strength than NS sand, with a strength gain of up to 16% at full replacement (100% QWS sand) at 90 days. Conversely, RCS sand reduces compressive strength by 28.6% at 28 days. and negatively affects porosity and capillary water absorption. However, these negative effects are mitigated when the RCS sand replacement is limited to 25%. QWS sand-based concrete exhibits slower shrinkage and reduced deformability compared to NS sand-based concrete. Predictive strength models were established based on experimental parameters, displaying a high correlation coefficient and a low root mean square error. Replacing NS sand with QWS sand or RCS sand reduced production costs, lowered carbon emissions, minimized waste, and preserved natural resources, offering a sustainable approach for concrete applications.

Abstract: The article provides some information about gypsum concrete, its applications, and the advantage of using organic fillers compared to mineral ones. The optimal technology for the production of gypsum concrete mix was determined, and an economically attractive type of organic filler in the form of chopped corn stalks was established. The compressive strength of the resulting material was studied depending on the fraction of crushed stone used. Effective methods for combating shrinkage cracks at the stage of manufacturing prototypes have been identified, which allows increasing the bearing capacity of the samples by 2.5 times. The water resistance and water absorption of the material, as well as their effect on strength, were investigated. As a result of experimental studies, it was found that the optimal concrete compositions with filler fractions of 3-5 and 5-10 mm should be considered 1:1 and 1:1.5 by volume (binder: filler), which can provide sufficient compressive strength (13-23 MPa) for blocks and slabs of internal partitions and good water resistance (0.91-1.0), while having good sound-absorbing properties.

Abstract: The assessment of compressive strength, and air-dry density constitutes essential parameters for evaluating the quality and performance of earthen construction materials. To ascertain these properties, this study investigates the potential application of ultrasonic testing as a non-destructive evaluation technique for earthen materials, including specimens, elements, or structures. The methodology is predicated on the measurement of ultrasonic pulse velocity (UPV), which is affected by various factors such as density, elasticity, and the curing process. By examining the propagation of ultrasonic waves through earthen samples, significant insights can be obtained regarding their drying duration, compressive strength, and density. Compressive strength is a pivotal factor in evaluating the structural integrity of earthen materials. The UPV method provides a non-destructive means to ascertain the compressive strength of earthen samples, thereby serving as a valuable instrument for quality control and assessment of earthen construction materials. Density, another critical property influencing the performance of earthen materials, can also be evaluated using the UPV method. By measuring ultrasonic pulse velocity and analyzing its correlation with density, this non-destructive approach enables rapid and efficient estimation of the compactness and quality of earthen mixtures. The ultrasonic method presents a non-destructive and efficient strategy for determining the compressive strength, and density of various soil compositions. By quantifying pulse velocity and examining its relationship with these properties, substantial insights can be garnered regarding the quality and performance of earthen construction materials. This technique holds the potential to enhance assessment and quality control processes in earthen construction, ultimately contributing to the development of more sustainable and reliable structures utilizing earthen techniques.

Abstract: Sustainable concrete has become more popular due to supplementary cementitious materials (SCMs) that help achieve sustainability. Despite the well-established benefits of these SCMs, the search for substitute materials continues as they become harder to find and adapt to changes with the industry. Concrete performance may be enhanced using bentonite, a commercially available clay mineral that shows promise as an SCM. In the present work, an Artificial Neural Network (ANN) model was developed to predict the compressive strength of cement-based mortar incorporating bentonite as a SCM, by training it on existing data, allowing for better performance and mix design improvement. A comprehensive experimental database comprising test specimens was established. A critical assessment of the collected experimental data suggested that there are several key parameters governing compressive strength gains. The proposed model's parameters, such as weights, biases, and transfer functions, were effectively transformed into a mathematical model that correlates the compressive strength with the key input parameters. An experimental investigation measuring the impact of treating bentonite at various temperatures on compressive strength was also included in the study.The statistical evaluation results indicated that a three-layered Artificial Neural Network model with different hidden neurons could precisely estimate the compressive strength of mortar mixtures modified with bentonite, showing strong agreement with the experimental results. The mortar's compressive strength may be increased by partially replacing cement with calcined bentonite, especially in the initial stages. The type of bentonite and the intended performance determine the appropriate replacement rate and calcination temperature.

Abstract: The aim of this study was to investigate the feasibility of manufacturing typha-based materials with a lime-based binder. For this purpose, three types of lime with different compositions were tested to produce lime-based typha concretes. The mechanical performance (compressive strength and apparent modulus of elasticity) of the materials developed was evaluated as a function of binder content and binder type. Two types of formulations were studied: one with a binder/aggregate ratio of 3, called F3, and the other with a binder/aggregate ratio of 2, called F2. Water absorption kinetics and typha particle size analysis were also studied. The dry density, compressive strength and apparent modulus of elasticity of typha concretes were determined. The results showed a reduction of mechanical performance as the binder/aggregate ratio decreased. The density of typha concretes range from 520 kg/m3to 396 kg/m3. The best mechanical performances were obtained with Thermo Tradical and Earasy binders. When the binder/aggregate ratio was reduced from 3 to 2, stress at 10% strain ranged from 0.6 MPa to 012 MPa and apparent modulus of elasticity from 31.5 MPa to 3.57 MPa. This study showed that binder composition has a significant impact on the mechanical performance of plant-based concretes.

Abstract: This study investigates the relationship between compressive strength and mid-span deflection of reinforced concrete beams, as determined through experimental tests and numerical modelling. Six commonly used concrete classes in Morocco (C10, C15, C20, C25, C30, C35) were prepared and tested to evaluate their mechanical performance. The obtained compressive strength values were incorporated into numerical models created using Robot Structural Analysis software, enabling the simulation of beam behaviour under uniform distributed load. Experimental results confirm that the compressive strength values comply with Moroccan standard NM 10.1.051, and they are strongly influenced by the paste volume and the water–cement (w/c) ratio. Moreover, the presence of superplasticizer helps to maintain workability by prolonging the slump. The findings indicate that mid-span deflection increases with compressive strength, highlighting the close connection between material properties and structural response. This approach demonstrates the value of combining laboratory experimentation with numerical modelling to bridge the gap between academic practice and real-world applications in civil engineering.

Abstract: This study examines how infill percentage and infill pattern affect the compressive strength of 3D-printed High-Density Polyethylene (HDPE) parts using Fused Deposition Modeling (FDM). Specimens were printed with infill densities of 15%, 30%, 60%, and 100% across three patterns: honeycomb, grid, and triangular. Compression tests followed ASTM D695 standards. Results show that compressive strength increases significantly with higher infill percentages, with fully solid (100%) samples reaching up to 43.35 MPa. Among patterns, the honeycomb design consistently outperformed grid and triangular structures due to its efficient stress distribution. At lower infill percentages, pattern choice had a stronger impact, while at higher densities, the infill percentage became the dominant factor. These findings offer practical guidelines for optimizing strength and efficiency in applications such as aerospace, automotive, and healthcare.

Abstract: Accurately predicting the water-binder ratio (W/B ratio) is crucial for achieving rice husk ash supplemented concrete structures' desired strength and durability. This study introduces an innovative approach for W/B ratio prediction, utilizing cutting-edge machine learning algorithms in combination with Explainable Artificial Intelligence (XAI) techniques. The research employs hybrid ensemble learning models, including Random Forest (RF), CATBoost (CB), Whale Optimization Algorithm-optimized RF (RF-WOA), and Moth Flame Optimization-optimized CB (CB-MFOA). The results indicate that these hybridized models significantly outperform the standalone models (RF and CATBoost) and traditional empirical methods (feret’s law, Abram’s law and bolomey’s method), with the CB-MFOA model achieving the highest accuracy, demonstrated by an R-value of 0.9984 during the calibration phase. In the verification phase, the CB model excelled with an R-value of 0.966. In addition to model performance, the study integrates XAI methods to explain the predictions and identify the key factors influencing the w/b ratio. Cement was found to be the most critical variable, enhancing the accuracy of the CB-MFOA model. The findings confirm that the proposed method improves prediction precision and provides engineers with a reliable tool to optimize concrete mix designs, thereby improving the durability and sustainability of concrete. This research contributes to the broader field of concrete technology by advancing the application of AI-based solutions in civil engineering and related fields.

Abstract: This work examines the phase stability during hot corrosion and the compressive strength of the AlCrFeNiCu-Nb high entropy alloy (HEA) produced using laser additive manufacturing, emphasizing its prospective uses in energy materials. The alloy's distinctive composition was chosen for its capacity to endure severe environments, including elevated temperatures and corrosive conditions, essential for energy-related applications. Phase stability was evaluated by X-ray diffraction, demonstrating remarkable preservation of critical phases despite high-temperature oxidation exposure. Compressive strength tests revealed the alloy's exceptional mechanical capabilities, underscoring its significant resistance to deformation. The AlCrFeNiCu-Nb HEA demonstrates significant promise for application in rigorous energy sectors, encompassing components for advanced power generation systems, high-temperature reactors, and corrosive conditions inside energy infrastructure.

Abstract: This study presents a novel approach to optimizing concrete block production by utilizing coconut shells and coconut shell ash as sustainable alternatives to stone dust and cement. Using classical experimental-mathematical modeling and exponential regression analysis, the optimal material proportions and their influence on the mechanical strength of concrete blocks were determined. Chemical composition tests indicated that incinerating coconut shells enhanced key pozzolanic components—silicon oxide, iron oxide, sulfur oxide, and potassium oxide—significantly improving the ash's pozzolanic reactivity and the durability of the concrete mix. The results reveal a critical threshold for incorporating these materials: beyond certain proportions, compressive strength declines. Specifically, strength ranged from 16.14 to 26.77 N/mm² at 100% replacement and from 0.32 to 1.54 N/mm² at 75% replacement. A non-linear regression model based on 42 observation points was developed, with 39 used for model training. The model accurately predicts performance and indicates an ideal mix consisting of 82.58% stone dust, a water–cement ratio of 0.6039, 82.5% cement, 17.5% coconut shell ash, and 17.42% coconut shells. This mix achieved a compressive strength of 3.17 N/mm² after 14 days of curing, exceeding the required 2.9 N/mm². The practical implications of these findings suggest that this mixture is cost-effective, utilizing low-cost coconut shells instead of more expensive materials like cement and stone dust. This approach promotes the use of sustainable materials in concrete production, supports waste management and conservation efforts, and aligns with circular economy practices in construction. Furthermore, the developed non-linear regression model serves as a valuable tool for integrating agricultural byproducts into concrete block production, providing a reliable method for predicting concrete performance and enabling better material selection in future applications. Generally, this study offers recommendations for identifying the optimal concrete block mix, enhancing circular economy practices, and minimizing dependence on non-renewable resources