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Compressive testing of specimens taken from relatively thin composite plates is difficult, especially due to the occurrence of buckling. To prevent buckling, the central portion of the specimens used for the compression test has smaller dimensions, and the specimens can be guided along their entire length. For these reasons, optical methods, such as digital image correlation (DIC), cannot be used for the compression test and strain rosettes cannot be glued onto the samples to determine Poisson's ratio. In this study, compression tests of a glass fiber-reinforced polymer (GFRP) were conducted using both the ASTM D695 (Boeing version) and a newly proposed method. The new method involves using special specimens that allow T-type rosettes to be bonded to determine Poisson's ratio, whose value of 0.14 was thus determined. SEM images of the failure surfaces were presented and interpreted. A finite element analysis (FEA) of the specimens tested in compression is also presented. The first analyzed case considers the homogeneous and orthotropic composite, loaded with a uniformly distributed force. The normal stress in the central section of the specimen, determined with FEA, has an error of 6.52% compared to that determined experimentally. Additionally, the strain in the center of the strain gauge, determined with FEA, has an error of 4.76% compared to the measured one. In the second case studied with FEA, the sample is loaded with a quasi-concentrated force, which can move in the direction of the symmetry axes of the cross-section, to study the effect of the eccentricity of the compression force on the state of stress. It was shown that the eccentricity of the force has a great influence: the stress distribution in the section of the specimen becomes strongly non-uniform. For a force eccentricity of 0.4 mm in the direction of the OX axis, the minimum stress decreases by 53.7%, and the maximum stress increases by 55.4%. In order to analyze the influence of some manufacturing defects, two other cases were analyzed by FEA, in which it was assumed that the thicknesses of the outer resin layers were modified, making them asymmetrical. For this final FEA, the specimen was considered to be composed of laminates. These results demonstrate the special attention that must be paid to the centric application of force in compression testing. [ABSTRACT FROM AUTHOR]

Syngas produced from glycerol using aqueous phase reforming for nickel-based catalysts with different support materials were tested in a compression ignition (CI) engine. Experiments were conducted using nickel–alumina, nickel–lanthanum (NL), and nickel–ceria catalysts at 1:1, 1:2, 1:3, and 1:4 glycerol–water ratios and temperatures of 240°C, 260°C, and 280°C. The NL catalyst showed the highest syngas and hydrogen yield of 90.58% and 76.42%, respectively, at 1:3 ratio and 260°C. The optimized NL syngas and diesel were tested in a CI engine at 6 to 30 lpm flow rates. At 30 lpm flow, brake thermal efficiency increased by 3.15%, NOx emission was reduced by 21.22%, and smoke lowered significantly compared to diesel. The faster hydrogen combustion in syngas increased the heat release rate and cylinder peak pressure. CO and HC emissions increased at lower loads due to diluted combustion but reduced at higher loads. NL showed the best performance and emissions among the syngases due to higher hydrogen content. In summary, the NL syngas at 30 lpm showed great potential in CI engines by improving combustion and performance and reducing emissions. [ABSTRACT FROM AUTHOR]

Numerical simulations of the cutting process play a key role in manufacturing and cost optimization. Inherent in finite element analysis (FEA) simulations is the correct description of material behavior during machining. For this purpose, various material models are used to describe the behavior of the material in the range of high deformation, high temperature values, and high strain rates. Very often the Johnson–Cook (JC) material model is used for this purpose; however, the correct determination of the material constants of this model is a key aspect. Therefore, this paper presents a procedure for determining the material constants of the JC model using an analytical method based on normalized tensile and compression testing of the material for different strain rates over a wide temperature range. After determining the material constants, the authors conducted numerical simulations of the orthogonal turning of Ti6Al4V titanium alloy using the obtained constants. Validation of the obtained results with those obtained in experimental studies was also carried out. The outcomes demonstrated that the difference between FEM simulation and experimental tests did not exceed 0.02 mm (14%) in the case of chip thickness,. Much smaller differences were obtained for the temperature in the cutting zone, where the maximum difference was about 45 °C (4%). Comparing the components of the cutting force, we found that, in the case of the main cutting force, in most cases, the differences did not exceed 70 N (8%). After the verification of the obtained results, it was also found that the determined material constants of the Johnson–Cook model can be successfully used in FEM modeling of the cutting process of Ti6Al4V titanium alloy for the adopted range of values of technological parameters. [ABSTRACT FROM AUTHOR]

In order to study the difference of bearing capacity between polypropylene fiber reinforced engineered cementitious composite ( PP-ECC) bridge pier and ordinary concrete bridge pier under compressive-bending load, the flexural performance of six PP-ECC bridge piers and two ordinary concrete bridge piers were studied by quasi-static test. Combined with the failure process of PP-ECC bridge pier, the characteristic points of compressive-bending failure of PP-ECC bridge pier were determined. Then, based on the simplified constitutive model of PP-ECC material, the theoretical cracking, yield and ultimate load formulas of PP-ECC bridge pier were derived. The characteristic parameters of the simplified PP-ECC constitutive model were determined by uniaxial tensile and uniaxial compression tests of PP-ECC materials. The calculation results were verified by the experimental results, and the differences of flexural bearing capacity and maximum deformation of piers under different axial compression ratios and PP-ECC zone heights were compared. The results show that after PP-ECC bridge pier is cracked, PP-ECC in the tensile zone still work, and cooperates with the tensile steel bar to participate in the section force. When PP-ECC bridge pier reaches the ultimate load, the crack develops steadily, and there is no large area of concrete spalling in the protective layer of ordinary concrete pier. The maximum deformation of PP-ECC bridge piers under ultimate load are larger than that of ordinary concrete piers, and the increase of axial compression ratio will reduce the deformation capacity of piers. Increasing the height of PP-ECC zone at a higher axial compression ratio, the flexural capacity of the pier increases by 8. 8%. When using the simplified constitutive model to calculate the flexural bearing capacity of PP-ECC bridge pier feature points, the calculation accuracy reaches 0. 86 - 1. 13, and the variance analysis value is small, which has good calculation accuracy. [ABSTRACT FROM AUTHOR]

This study investigates the effects of initial billet size variations on material flow behavior in hot forging processes, aiming to optimize the forging process using validated predictive models. Material and high-temperature compressive tests inform mathematical models, while simulations are conducted via the finite element method (FEM). Results align with the Zener-Hollomon and Cingara-McQueen approaches. The Arrhenius model predicts AISI 1045 steel flow stress with an R² of 0.968 and an average absolute relative error (AARE) of 7.079%. The Cingara-McQueen equation achieves an R² of 0.997 and an AARE of 2.960%. Reducing billets size from 260 mm to 230 mm decreases the material usage by up to 11.5%, while maintaining workpiece integrity. Experimental and simulated loads exhibit an AARE of about 2.69%, thereby indicating potential cost and efficiency improvements in hot forging processes. [ABSTRACT FROM AUTHOR]

The extensive utilization of lithium-ion (Li-ion) batteries within the automotive industry necessitates rigorous measures to ensure their mechanical robustness, crucial for averting thermal runaway incidents and ensuring vehicle safety. This paper introduces an innovative methodology aimed at homogenizing the mechanical response of Li-ion batteries under compression load, using Finite Element Method (FEM) techniques to improve computational efficiency. A novel approach is proposed, involving the selective application of compression loads solely to the Jelly Roll and its casing, achieved by cutting the battery heads. Through this method, distinct mechanical behaviors are identified within the battery force displacement curve: an elastic region, a zone characterized by plastic deformation, and a segment exhibiting densification. By delineating these regions, our study facilitates a comprehensive understanding of the battery's mechanical response under compression. Two battery models were employed in this study: one representing the battery as a solid volume, and another featuring the jelly roll as a solid volume enclosed by a shell representing the casing. The material utilized was LS Dyna MAT24, chosen for its piecewise characteristics' definition, and its validation was primarily conducted through the curve fitting method applied to the force–displacement curve, taking in account the three regions of the compression force behavior. This approach not only optimizes computational resources but also offers insights crucial for enhancing the mechanical stability of Li-ion batteries in automotive applications. [ABSTRACT FROM AUTHOR]

Virtual compression tests based on finite element analysis are representative noninvasive methods to evaluate bone strength. However, owing to the characteristic porous structure of bones, the material obtained from micro‐computed tomography images in the finite‐element model is not uniformly distributed. These characteristics cause differences in the apparent elastic moduli depending on the boundary conditions and affect the accuracy of bone‐strength evaluation. Therefore, this study aimed to evaluate and compare the apparent elastic moduli under various, virtual‐compression and shear‐test boundary conditions. Four, nonuniform models were constructed with increasing model complexity. For representative boundary conditions, two, different, testing directions, and constrained surfaces were applied. As a result, the apparent elastic moduli of the nonuniform model varied up to 55.2% based on where the constrained surface was located in the single‐end‐cemented condition. Additionally, when connectivity in the test direction was lost, the accuracy of the apparent elastic moduli was low. A graphical comparison showed that the equivalent‐stress distribution was more advantageous for analyzing load transferability and physical behavior than the strain‐energy distribution. These results clearly show that the prediction accuracy of the apparent elastic moduli can be guaranteed if the boundary condition on the constraint and loading surfaces of the nonuniform model are applied symmetrically and the connectivity of the elements in the testing direction is well maintained. This study will aid in precision improvement of bone‐strength‐indicator determination for osteoporosis prevention. [ABSTRACT FROM AUTHOR]

The present study focuses on the estimation of uniaxial compressive strength (UCS) in geotechnical projects. UCS is a crucial parameter in designing such projects, and traditional methods of measurement outlined by standards are often time-consuming and cumbersome. Additionally, obtaining standard core samples is always a challenging task in fractured or discontinuous rock masses. To overcome these limitations, alternative techniques such as simple regression (SR), multivariable regression (MVR), and artificial intelligence (AI) have been utilized to estimate UCS based on easily derived geotechnical parameters. While SR and MVR provide simple equations that can be used without the need for complex calculations, AI techniques offer the potential for higher prediction accuracy. However, AI models often require more complex solutions due to their intricate algorithms and computational processes. This makes AI less practical for ongoing geotechnical projects in which simple and quick estimations are often preferred. In this study, both the SR and the MVR models were employed to estimate the UCS using the Schmidt hammer rebound number (RN), density (ρ), porosity (ϕ), and point load index (Is50) as input parameters. Various SR and MVR models were tested, and the best-performing models were selected based on performance indices such as the normalized root mean square error (NRMSE), relative root mean square error (RRMSE), variance accounted for (VAF), efficiency (E), and correlation coefficient (R2). Furthermore, this study proposes a new performance index (PImod) to evaluate the predictive capabilities of the models. This index likely incorporates additional criteria or metrics beyond the aforementioned traditional performance indices. Overall, the equations derived from the regression models in this study offer a simpler and more practical approach for geotechnical practitioners to quickly assess UCS in any given area, providing a useful tool for their work. [ABSTRACT FROM AUTHOR]

The concrete panel of earth-rock dams in cold regions tends to crack due to the combination effect of non-uniform foundation settlement, ice expansion loads, and freeze-thaw damage. In this work, simulations are designed to investigate the effects of freeze-thaw damage degrees on the fracture behavior caused by the partial detachment and ice expansion loads on concrete panels. Results show that the range of detached panels and freeze-thaw damage degree are the dominant factors that affect the overall load-bearing capacity of the panel and the failure cracking modes, whereas the panel slope is a secondary factor. The failure cracking modes are found to be a combination of type II fracture modes, including compression-shear and tension-shear cracking. Besides, with the increase of detachment area and the degree of freezing-thawing damage, the concrete panels are prone to appear bending tension cracks at the bottom and a more serious smeared crack layer at the top. [ABSTRACT FROM AUTHOR]

Concrete compressive strength testing is crucial for construction quality control. The traditional methods are both time-consuming and labor-intensive, while machine learning has been proven effective in predicting the compressive strength of concrete. However, current machine learning-based algorithms lack a thorough comparison among various models, and researchers have yet to identify the optimal predictor for concrete compressive strength. In this study, we developed 12 distinct machine learning-based regressors to conduct a thorough comparison and to identify the optimal model. To study the correlation between compressive strength and various factors, we conducted a comprehensive analysis and selected blast furnace slag, superplasticizer, age, cement, and water as the optimized factor subset. Based on this foundation, grid search and fivefold cross-validation were employed to establish the hyperparameters for each model. The results indicate that the Deepforest-based model demonstrates superior performance compared to the 12 models. For a more comprehensive evaluation of the model's performance, we compared its performance with state-of-the-art models using the same independent testing dataset. The results demonstrate that our model achieving the highest performance (R2 of 0.91), indicating its accurate prediction capability for concrete compressive strength. [ABSTRACT FROM AUTHOR]

With regard to deep mining in metal mines, an investigation into the failure mode of deep fractured rock masses and their corresponding acoustic emission signal characteristics is conducted via uniaxial compression tests. Subsequently, a fractal damage renormalization group mechanical model is developed to explain the behavior of those fractured rock masses. Employing the bonded block model (BBM) numerical simulation method, fracture process in synthetic rock samples is analyzed, thereby validating the efficacy of the mechanical model. The numerical simulations highlight the critical role of fractures expansion in underlying the deterioration of rock mass strength. As the peak load decreases, the fracture fractal dimension increases, leading to a significant 14.2% reduction in compressive strength accompanied by an approximate 8.7% rise in average fracture fractal dimension. A comparative analysis of tetrahedral and voronoi block synthetic rock samples reveals the tetrahedral block samples exhibit a superior ability to depict the fracture behavior of fractured rock masses. Specifically, they offer a more accurate simulation of acoustic emission characteristics and failure modes. Furthermore, variations in the fracture fractal dimension with respect to the hole defect's position are observed, with the maximum value occurring along the vertical axis of the hole defect. This observation underscores the potential utility of visually monitoring deep rock fracture dynamics as an effective mean for quantitatively evaluating fracture damage and strength degradation in deep rock formations. [ABSTRACT FROM AUTHOR]

[Objective] Based on the data of similar material proportions in large-scale model tests of highway tunnels, research on the preparation method of similar materials for large tunnel surrounding rock. Develop a liquid-solid coupling similar material composed of barite powder, quartz sand, white cement, iron powder, silicone oil, and water. [Method] Exploring the influence of different ratios on various physical properties and water rationality of materials through indoor experiments, and the specific ratio results of liquid-solid coupling similar materials were determined. [Result] The experimental results indicate that an increase in the content of white cement will significantly reduce the permeability coefficient of the material, while the binder will significantly affect the elastic modulus and compressive strength of the material, while the content of white cement remains unchanged. In addition, as the proportion of barite powder to white cement in the material gradually increases, the compressive strength of the test material will gradually increase. However, when the content of barite powder and white cement in the material reaches a certain level, the compressive strength of the material may slightly decrease. Increasing the ratio of barite powder to white cement within a certain range can improve the elastic modulus of the material. The shear strength is significantly affected by silicone oil. [Conclusion] Liquid solid coupling similar materials can simulate rock mass materials with different strengths and permeability, making them an ideal similar simulation material. [ABSTRACT FROM AUTHOR]

The abandoned carbonaceous mudstone has caused severe environmental problems such as land occupation and landslides. For the consideration of economic and ecological factors, carbonaceous mudstone soil-rock mixture (CMSRM) is used as an embankment material assessed by California bearing ratio (CBR) and unconfined compression strength (UCS). A series of experiments were conducted to measure the CBR and UCS of the CMSRM with different wet-dry cycles (0, 2, 4, 6 and 8) and different rock contents (0, 20, 40, 60 and 80%). The experimental results were predicted and analysed by a convolutional neural network (CNN). The experiment results show that the CBR and UCS of CMSRM increased at first and then decreased with the increase of rock content and were negatively correlated with wet-dry cycles. The CNN predicted values were highly correlated with the measured values. The CNN model enables variable parameter analysis of the experiment results via deep learning, which provides a new method to the CMSRM embankment road performance prediction. [ABSTRACT FROM AUTHOR]

The associated effects of temperature and steel fiber content on the energy absorption properties of concrete were examined using quasi-static uniaxial compression tests of concrete materials with varied steel fiber contents (0%, 0.5%, 1%, and 1.5%) at various temperatures (20 °C, 200 °C, 400 °C, and 520 °C). The experimental findings demonstrate that steel fibers can greatly boost concrete's ability to absorb energy and that the toughness index rises with steel fiber concentration. The energy absorption capacity of concrete under high-temperature conditions also significantly decreases as temperature rises, and the energy absorption ability of steel fiber concrete under the same temperature is superior to that of plain concrete. The coupled influence factor K of temperature–steel fiber percentage characterizing the energy-absorbing ability of concrete was determined, and the coupled influence law of temperature and steel fiber content on the energy-absorbing capacity of concrete materials was summarized and analyzed on the basis of the experimental data of high-temperature compression. Equivalent equations for steel fiber reinforcing and temperature weakening effects when they are comparable (K = 1) are developed and equivalent parameters for concrete materials are given. [ABSTRACT FROM AUTHOR]

The saturated metasandstone is taken as the research object, and the uniaxial compression characteristics of the saturated metasandstone are simulated by means of the artificially made saturated sandstone samples. By checking the parameters of the Particle Flow Code (PFC) numerical simulation of loading and unloading seepage stress coupling, the effects of the conductivity coefficient, the pipe diameter, the apparent volume of the domain and the time step on the calculation results are analyzed. When PFC is used for numerical simulation of seepage stress coupling, the conductivity coefficient K can be taken as 0.010. When the pipe diameter is 1.0 mm, the apparent volume of the current domain is 1 × 10−6 m³, the water pressure distribution inside the sample is relatively uniform. The influence of time step on the compressive strength and peak strain of the specimen can be almost ignored. Under the action of water pressure, the compressive strength of the intact rock like sample and the rock like sample with cracks decreases, and the compressive strength of the sample decreases gradually with the increase of water pressure. When the inclined angle of fracture is the same, the seepage pressure is the same, and the confining pressure is the same, the compressive strength of the specimen also increases with the increase of the initial axial stress level during unloading. When the confining pressure and the osmotic pressure are the same, the unloading effect makes the crack development of the specimen faster and more complete, the specimen is more fragmented and multiple parallel shear bands develop. [ABSTRACT FROM AUTHOR]

This study explored the influence mechanism on the water resistance of magnesium phosphate repair mortars. The fluidity, setting time, mechanical properties, water resistance, and interfacial bonding strength of red mud–modified magnesium phosphate repair mortars (RMPMs) were systematically investigated. Through capillary absorption tests, the effect of the water-binder ratio (W/B) on the water transfer characteristics was explored, and then the actuating mechanism of capillary porosity and capillary absorption coefficients on water resistance was clarified. The results show that the fluidity and setting time of RMPM increase with the increase of W/B. When W/B increased from 0.18 to 0.20, the compressive strength, flexural strength, strength retention, and interfacial bonding strength of RMPM changed little and decreased linearly. And the interfacial bonding strength of RMPM was significantly reduced after 7 days of water curing. The capillary water absorption of RMPM was linear with the square root of time. The capillary absorption coefficient and capillary porosity of the RMPM increased greatly with increasing W/B when the W/B is between 0.20 and 0.28, while the water resistance, mechanical properties, and interfacial bonding property decreased linearly. Variations in W/B changed the capillary pore characteristics of the RMPM, which in turn affected the mechanical properties, capillary water absorption characteristics, and water resistance. [ABSTRACT FROM AUTHOR]

This article focuses on the compressive yield strength testing of powder metallurgy (PM) copper steels. It highlights the lack of data on compressive yield strength in the standard for PM structural parts and discusses previous testing on PM nickel steel. Concerns about conservative values and a recent testing program that led to the approval of higher values for PM copper steels are also mentioned. The document presents microindentation hardness measurements and microstructures of specific specimens, summarizes the compressive yield strength values, and provides new "typical" values for FC-0205HT and FC-0208HT materials. These values aim to offer design engineers more realistic properties for specifying PM materials. [Extracted from the article]

The main goal of this study is the comparison of different reinforcement architectures on the low-velocity impact behavior of green composites. The study includes the comparison of unidirectional, basket weave, and twill weave flax/PLA composites, they are subjected to unidirectional tensile tests, drop-weight impact tests, and after-impact compression tests. Results show that the unidirectional composite demonstrates superior tensile strength and initial modulus due to reduced fiber crimp, while basket weave exhibits the highest energy absorption capability and strain capacity attributed to its higher fiber–weight ratio and fiber crimp. Unidirectional composite also shows a larger impacted damage area compared to basket weave and twill weave, attributed to its internal architecture. Residual compressive strength across all composites decreased by 40% compared to the reference sample. However, the reduction in stiffness after impact was different, UD/PLA composite stiffness was reduced by 30% while the reduction in BW/PLA and T/PLA composites was about 20%. [ABSTRACT FROM AUTHOR]

For the operative bucket of a 2nd size-group hydraulic excavator, the impact capacity of percussion mechanisms, required for cutting rocks with the compression strength up to 60–80 MPa, is determined. The structure and parameters of hydropercussion mechanisms are chosen. The proposed inter-connection for the hydropercussion mechanisms and the hydraulic power station contains activation valves for each of the mechanisms, and a pressure reducing valve at the inlet. A simulation model of the system of hydropercussion mechanisms is built, and the performance and characteristics of the model are calculated at different rates of power fluids and pressures of the reducing valve. The authors prove the efficiency of the proposed design and connection of hydropercussion mechanisms in the excavator hydraulics and validate the adjustability of the impact capacity of the mechanisms through setting-up of pressure of the reducing valve. [ABSTRACT FROM AUTHOR]

In polar ship hull structural designs, methods based on regulations are considered the most authoritative; however, they tend to be conservative and often exhibit a notable degree of redundancy. This study aims to evaluate the applicability of the empirical formula for ice load assessments by conducting a series of quasi-static indentation tests on scaled hull plates under laboratory-made ice blocks of different scales. The obtained data include ice loads, structural responses, and characteristics of ice pressure distribution. A detailed comparison of various formulas is provided, along with an examination of their differences and errors in comparison to experimental results. The objective of this paper is to offer technical support for ice load forecasting and assessment. [ABSTRACT FROM AUTHOR]

Uniaxial compression tests were conducted on quartz mica schist in a laboratory to study the brittle failure modes of foliated rocks. By focusing on the crack evolution pattern, the failure mechanisms of foliated rocks were investigated by numerical tests based on particle discrete element theory. Furthermore, the effect of fabric on the mechanical anisotropy of foliated rocks was explored. The results indicated that the failure of foliated rocks subjected to uniaxial compression is heavily controlled by the rock fabric, exhibiting complex modes depending on the loading direction, including axial tensile fracture, oblique shear fracture, conical shear fracture, slip shear failure and splitting failure. Cracks initiated in the compressed rocks are induced from the contact surfaces of granular and flaky minerals and from the tips of flaky minerals. The crack initiation of foliated rocks, attributed to the concentration of tensile stress within the rock, responds to the loading direction in terms of the induced mechanism. When α = 90°, 45° and 0°, crack initiation depends on the differences in the mechanical properties of different minerals, the slipping of flaky minerals, and the kinking of flaky minerals, respectively. The formation of primary fracture planes results from tension crack coalescence + shear crack connection (α = 90°), shear crack or tension‒shear composite crack connection (α = 45°), and tension crack coalescence (α = 0°). As the orientation degree of flaky minerals decreases, the failure mode experiences a gradual decrease in sensitivity to the loading direction, and the curve of strength variation with orientation angle changes from U-shaped to shoulder-shaped or wave-shaped, accompanied by a decreasing anisotropy degree of rock strength. [ABSTRACT FROM AUTHOR]

The recommended bearing capacity of medium weathering mudstone foundation is less than the capacity of the rock structure to withstand loads in Southwest China. A comprehensive failure characterization of medium weathering mudstone in Chengdu has been performed including bearing plate test (BPT), binocular vision measurement (BVM) test, uniaxial compressive strength test, trial trench test of shallow rock surface and 3D imaging in this paper. Failure behavior of rock has been modeled with 3D imaging algorithm that utilizes Zhang's calibration method in BVM system combination with trial trench test of shallow rock surface. The bearing capacity of medium weathering mudstone foundation were extracted from uniaxial experiments and BPT-BVM test by fitting relevant material properties to the data. The results revealed that: Bearing capacity of medium weathering mudstone of layered isotropic in Chengdu is undervalued. Specifically, the characteristic load carrying value is in the range 1500–2500 kP, that is 50% higher than in the local standard system. Failure process is different from Hoek–Brown Failure Criterion, presenting a wave peak transfer phenomenon of the increment displacement into the distance. Thus, it can be reduced to that of punching failures for thin bedded structures of Moudstone foundations. Compressive strength of soft rock proves to be main factor limiting the bearing capacity, a clear correlation between the uniaxial compressive strength reduction coefficient and the bearing capacity has been used to establish, leading to the proposal of a load bearing capacity prediction model. [ABSTRACT FROM AUTHOR]

This article compares the two most used strain determination experimental techniques, the strain gauges and the digital image correlation (DIC), which are used here to determine the static Poisson's ratio of rock-like materials under a compressive loading. While the strain gauge technique measures the strains on the small patch of the underlying material on the spot, where the strain gauge is applied, DIC is a novel optical full-field technique that can measure the strains over the entire region of interest of the specimen. The key research question presented in this paper and research significance is to what extent the measurement of Poisson’s ratio is improved by leveraging the richness of the full-field measurements compared to the conventional strain gauge technique. To this purpose, the hypothesis was tested through virtual experiments in which a numerical simulation of a uniaxial compression test with a cylindrical, rock-like sample was created to mimic the strain gauge and DIC measurement techniques, as well as by conducting an actual compression test on a sandstone material. In contrast to conventional strain gauges, novel optical techniques such as stereo DIC proved to be able to capture the macroscopic Poisson coefficient with higher precision, thus reducing the margin of error. [ABSTRACT FROM AUTHOR]

In the exploration of sustainable construction materials, the application of ferronickel slag (FNS) in creating pervious concrete has been investigated, considering its potential to meet the dual requirements of mechanical strength and fluid permeability. To elucidate the statistical properties and models for predicting the performance of FNS-composited pervious concrete with different sizes of aggregates and mixtures, a series of experiments, including 54 kinds of mixtures and three kinds of aggregate, were conducted. The focus was on measuring the compressive strength and the permeability coefficient. The results indicate that the compressive strength of pervious concrete decreases with the increase in aggregate size, while the permeability coefficient increases with the increase in aggregate size. Through normalization, the variability of these properties was quantitatively analyzed, revealing coefficients of variation for the concrete's overall compressive strength and the permeability coefficient at 0.166, 0.132, and 0.150, respectively. Predictive models were developed using machine learning techniques, such as Linear Regression, Support Vector Machines, Regression Trees, and Gaussian Process Regression. These models demonstrated proficiency in forecasting the concrete's compressive strength and permeability coefficient. [ABSTRACT FROM AUTHOR]

Sandy Dolomite is a kind of widely distributed rock. The uniaxial compressive strength (UCS) of Sandy Dolomite is an important metric in the application in civil engineering, geotechnical engineering, and underground engineering. Direct measurement of UCS is costly, time-consuming, and even infeasible in some cases. To address this problem, we establish an indirect measuring method based on the convolutional neural network (CNN) and regression analysis (RA). The new method is straightforward and effective for UCS prediction, and has significant practical implications. To evaluate the performance of the new method, 158 dolomite samples of different sandification grades are collected for testing their UCS along and near the Yuxi section of the Central Yunnan Water Diversion (CYWD) Project in Yunnan Province, Southwest of China. Two regression equations with high correlation coefficients are established according to the RA results, to predict the UCS of Sandy Dolomites. Moreover, the minimum thickness of Sandy Dolomite was determined by the Schmidt hammer rebound test. Results show that CNN outperforms RA in terms of prediction the precision of Sandy Dolomite UCS. In addition, CNN can effectively deal with uncertainty in test results, making it one of the most effective tools for predicting the UCS of Sandy Dolomite. [ABSTRACT FROM AUTHOR]

To reduce the environmental impact of concrete, recycled aggregates are of significant interest. Recycled concrete aggregate (RCA) presents a significant resource opportunity, although its performance as an aggregate in concrete is variable. This study presents a meta-analysis of the published literature to refine the understanding of how the moisture content of RCA, as well as other parameters, affects the compressive strength of concrete. Seven machine learning models were used to predict the compressive strength of concrete with RCA, including linear regression, support vector regression (SVR), and k-nearest neighbors (KNN) as single models, and decision tree, random forest, XGBoost, and LightGBM as ensemble models. The results of this study demonstrate that ensemble models, particularly the LightGBM model, exhibited superior prediction accuracy compared to single models. The LightGBM model yielded the highest prediction accuracy with R2 = 0.94, RMSE = 4.16 MPa, MAE = 3.03 MPa, and Delta RMSE = 1.4 MPa, making it the selected final model. The study, employing feature importance with LightGBM as the final model, identified age, water/cement ratio, and fine RCA aggregate content as key factors influencing compressive strength in concrete with RCA. In an interaction plot analysis using the final model, lowering the water–cement ratio consistently improved compressive strength, especially between 0.3 and 0.4, while increasing the fine RCA ratio decreased compressive strength, particularly in the range of 0.4 to 0.6. Additionally, it was found that maintaining moisture conditions of RCA typically between 0.0 and 0.8 was crucial for maximizing strength, whereas extreme moisture conditions, like fully saturated surface dry (SSD) state, negatively impacted strength. [ABSTRACT FROM AUTHOR]

In order to clarify the relationship between the mechanical properties of coal-rock composite and the loading rate and rock–coal strength ratio, uniaxial compression tests were carried out on coal-rock combinations with three different rock–coal strength ratios at four different loading rates. The rock–coal strength ratio is a ratio of the compression strength of rock to the compression strength of coal. The test results indicate that the relationship between the mechanical properties of coal-rock composite and loading rate is influenced by both the strong and weak components in the composite. The peak stress and elastic modulus mainly depend on the weak component, while the peak strain is determined by both the strong and weak components. For peak stress and elastic modulus, when the weak body is the same, the relationship with loading rate is the same, otherwise it is different. The relationship between the mechanical properties of coal-rock combination and is not affected by the loading rate. The weak body in the coal-rock combination is the main body of damage, and the greater the value of , the more severe the damage. At the same time, the failure mode shows a gradual transition from weak body failure inducing strong body failure to only weak body failure. [ABSTRACT FROM AUTHOR]

In the Chengdu-Chongqing economic circle in China, the recommended bearing capacity of a medium-weathering mudstone foundation is less than the capacity of the rock structure to withstand loads. The aim of this paper was to perform plate loading tests (PLTs) with binocular vision measurement (BVM) to obtain the accurate deformation of the foundation under vertical loading. The results revealed that vertical load–bearing foundations have a failure mode that can be reduced to that of thrust failures for thin bedded structures of mudstone foundations. By analyzing the differences in results between the PLTs and the uniaxial compressive strength tests under the same conditions, a new formalism for calculating foundation-bearing capacity was proposed; there is only a 5% difference compared to in situ tests. The results of this research provide theoretical support and a practical benchmark for the full development of the load-bearing capability of soft red rocks. As the Chengdu-Chongqing economic circle progresses toward the international urban cluster, inevitably, soft rock is used as a foundation retaining layer in the construction of superhigh and super-rise buildings in the region. However, owing to antiquated testing methods and poor intelligibility of the testing equipment, the bearing capacity of such a mass of rock has yet to be fully developed and cannot meet the dual-carbon economic goals and sustainable development of architectural design. Based on this, the study introduces a noncontact method to measure the bearing capacity of soft rock within the traditional method of in situ testing and combines the concept of big data analysis to advance an empirical method for calculating the bearing capacity accurately. Based on the results of this study, the concept of natural foundations can be adopted and the engineering dilemma that the treatment of building foundations cannot be economical and practical can be solved. [ABSTRACT FROM AUTHOR]

This paper presents the details of experimental testing of masonry prisms, which were tested in compression. The experimental program consisted of prisms made with hollow and solid blocks of thickness 100 and 150 mm. Five different proportions of mortars were employed in the casting of these prisms, which included 1:2, 1:3, 1:4, 1:5, and 1:6 by weight. Three prisms were cast and tested using each of these mortar types for each block type. It was found that the failure modes and compressive behaviors of the prisms were not significantly influenced by the mortar types, although these were different for the prisms made of solid and hollow blocks. The deformation behaviors of the prisms in the postpeak region were also different for these block types. The compressive strength of the prisms (fp) varied with the block strength and was not dependent on the block type. All the prisms exhibited typical behaviors of uniaxially compressed prismatic members. An average elastic modulus of 1,720 fp was found for the tested prisms, while Poisson's ratio varied from 0.10 to 0.15. Analytical models for estimating fp and strain corresponding to fp have been proposed for design practice. A new constitutive equation for capturing the falling branch of the stress–strain curve of block masonry prisms has also been proposed. [ABSTRACT FROM AUTHOR]

Take the metamorphic sandstone as the reference object, by making rock like samples with fractures, the conventional triaxial loading and unloading test and PFC numerical simulation of rock like sample with single fracture were conducted, and the effects of the loading path, inclined angle of fracture, axial stress level during unloading, initial confining pressure during unloading on the compressive strength, peak strain and crack propagation evolution of the samples were considered. The compressive strength of the specimen under triaxial unloading is smaller than that under triaxial loading. The peak strain of the specimen under triaxial unloading is also smaller than that under triaxial loading. The specimen is more prone to brittle failure. When the axial stress level is the same during unloading, with the increase of the initial confining pressure during unloading, the difference of the compressive strength of the specimens with different inclined angles of fracture gradually decreases. Under the condition of uniaxial compression and triaxial compression, the failure of all specimens is tensile failure, and the shear failure is the main one during unloading. [ABSTRACT FROM AUTHOR]

The purpose of laboratory tests was to determine the effect of sodium silicate and selected hydrophobic agents on the basic physical parameters and freeze-thaw durability of mortars made with Sorel cement in variable proportions. In order to determine the mortars’ parameters, samples of the dimensions of 4×4×16 cm and boards of the diameters of 1×4×16 cm were prepared. Parameters such as water absorption, capillary absorption, compressive and flexural strength and frost resistance were tested. Mortar supplemented with sodium silicate in the quantity of 2.6% of all components demonstrated the best properties. None of the other hydrophobic agents that were used to mitigate the negative effects of water on Sorel cement mortars demonstrated such positive properties. Flexural strength tests of all mortar batches, performed on cuboid samples and boards of the thickness of 1 cm, demonstrated a similar improvement in strength. The lowest value of compressive strength was recorded for the reference batch at 46.6 MPa, whereas the highest value was recorded for the second batch containing sodium silicate, at 49.8 MPa. During the testing of frost resistance, the lowest reduction of compressive and flexural strength was recorded for the reference mortar and for mortar with sodium silicate. All mortars were varied in the MgO/MgCl2 ratio and the total amount of water, the observed effects may be caused by other variables. However it is possible to notice the positive effect of selected hydrophobic agents. [ABSTRACT FROM AUTHOR]

The FRP reinforcement gained importance due to high tensile strength, high durability and ecological friendliness [1–7]. Its usefulness as the internal or Near Surface Mounted reinforcement in bent concrete elements has already been proven. Though, in terms of the compressive behaviour of the bars and concrete elements incorporating them, there are still few experimental and numerical considerations, especially when high temperatures are considered. This article contains further considerations on the performance of concrete columns with BFRP main reinforcement in fire resistance tests on the basis of previously presented authors’ numerical analyses. Comparative analysis in terms of temperatures, deformations and stresses of concrete columns with BFRP and steel main reinforcement in fire resistance tests is presented by the example of two columns, for which also experimental investigations were performed. Also, a comparative analysis of stress-strain relations for BFRP, steel and concrete at temperatures up to 600◦C is presented. It can be concluded that BFRP bars’ properties are strongly different when compressive and tensile performance is considered, especially at elevated temperatures. Tensile strength was higher for BFRP than steel at room temperature, but along with temperature growth, it came the other way (at around 600◦C). The compressive strength of the BFRP bars was higher than the value for concrete, but only for temperatures lower than 200◦C. [ABSTRACT FROM AUTHOR]

The article presents the results of a detailed experimental campaign including a compressive strength test, three- and four-point bending test (3PBT and 4PBT, respectively) of polymer fiber reinforced concrete with the addition of metakaolin. The comprehensive analysis included three Types of concrete mixture differing in amount and used polymer fibers. It was concluded that polymer fibers did not influence the maximum compressive and flexural tensile strength of concrete. On the other hand, they had a beneficial effect on the ductility, residual and equivalent flexural tensile strengths, and fracture energy of samples. The mixtures of Type 1 and 2 were characterized by softening behaviour but the mixture of Type 3 by soft-hardening behaviour. In the 3PBT, the residual flexural tensile strengths obtained according to EN 14651 did not correspond clearly with equivalent flexural tensile strengths calculated in compliance with RILEM TC 162-TDF. It is noteworthy that the effectiveness and correctness of equations presented in other work of the authors referring to dependencies between deflection, crack and tip mouth opening displacements for the 3PBT were confirmed on samples with different composition and fibers. Based on the 4PBT, the equivalent flexural tensile strengths according to JCI-SF4 standard were calculated and the correlations with the results from 3PBT were defined. [ABSTRACT FROM AUTHOR]

This study aims to determine the needed coefficients for evaluating the uniaxial compressive strength characteristic value for masonry structures made of Laterite Stone (LS) and cement mortar, resulting from experiments conducted in the laboratory evaluating the compressive strengths of the laterite stone and mortar separately in masonry. It proposes calculation coefficients for the completion of Eurocode 6 data that fit the behavior of laterite stone-based masonry. The laterite stone blocks are extracted from three quarries in southern Burkina Faso. The dimensions of the masonry samples tested are 800 mm × 800 mm × 135 mm (±5 mm) with a cement mortar joint of 20 mm (±5 mm) thick. The different failure modes of masonry were also explored. The tests carried out on the masonry showed that the failure is initiated by vertical cracks through the block-mortar interface at a quarter of the width of the walls, generally at 40 to 60% of their maximum strength. The statistical analysis made through a linear regression from the standard model of approximation of the characteristic strength of masonry in Eurocode 6 was used to set out parameters for the empirical relation. The proposed formula considers the intrinsic properties of the block and the mortar, the thickness of the mortar, the dimensions of the masonry block, and the geometry of the masonry itself to evaluate its compression strength. The adequacy between the model and the experimental values is evaluated through the coefficient of determination and the standard error of 0.94 and 0.041 MPa, respectively. [ABSTRACT FROM AUTHOR]

Urban expansion and infrastructure development have exacerbated environmental issues by creating impermeable layers on the earth's surface, resulting in flash floods and reduced groundwater levels. These problems can be alleviated by using pervious concrete to enhance pavement drainage capacities. However, pervious concrete has limited applications due to its lower strength properties, which are attributed to its mix proportions featuring minimal fine aggregate quantities and an open-graded mix. This study examines the impact of incorporating Ground Granulated Blast-furnace Slag (GGBS) as a supplementary cementitious material in pervious concrete on its strength, drainage capabilities, and water absorption. Further, Artificial Neural Networks (ANN) were used to predict the mechanical and permeability properties of pervious concrete mixes with varying GGBS proportions. The study's results indicate that using GGBS as a 35% partial cement replacement with 10 mm aggregates significantly increases compressive and flexural strength by 28% and 20%, respectively. While permeability values were slightly reduced, they remained within acceptable limits for drainage properties. The developed ANN models outperformed the traditional MLR model, serving as a viable substitute logical tool for forecasting strength as well as permeability. Ultimately, adding GGBS to pervious concrete not only enhances strength but also contributes to environmentally friendly construction practices. [ABSTRACT FROM AUTHOR]

The strength of rock under uniaxial compression, commonly known as Uniaxial Compressive Strength (UCS), plays a crucial role in various geomechanical applications such as designing foundations, mining projects, slopes in rocks, tunnel construction, and rock characterization. However, sampling and preparation can become challenging in some rocks, making it difficult to determine the UCS of the rocks directly. Therefore, indirect approaches are widely used for estimating UCS. This study presents two Machine Learning Models, Simple Linear Regression and Step-wise Regression, implemented in Python to calculate the UCS of Charnockite rocks. The models consider Ultrasonic Pulse Velocity (UPV), Schmidt Hammer Rebound Number (N), Brazilian Tensile Strength (BTS), and Point Load Index (PLI) as factors for forecasting the UCS of Charnockite samples. Three regression metrics, including Coefficient of Regression (R2), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE), were used to evaluate and compare the performance of the models. The results indicate a high predictive capability of both models. Notably, the Step-wise model achieved a testing R2 of 0.99 and a training R2 of 0.988 for predicting Charnockite strength, making it the most accurate model. The analysis of the influential factors indicates that UPV plays a significant role in predicting the UCS of Charnockite. [ABSTRACT FROM AUTHOR]

Herein, we conducted a comprehensive statistical assessment of the ultrasonic pulse velocity (UPV) method's effectiveness in predicting concrete strength under diverse conditions, specifically early age, middle age, and high-temperature exposure. The concrete mixtures, with water-to-cement (W/C) ratios of 0.33 and 0.28, were classified as granite aggregate or coal-ash aggregate mixes. Compressive strength and UPV measurements were performed under these conditions, and subsequent statistical analyses treated the identified factors as distinct groups. The results revealed a substantial difference in compressive strength between specimens at early age (average of 13.01) and those at middle age (average of 41.96) and after high-temperature exposure (average of 48.08). Conversely, UPV analysis showed an insignificant difference between the early-age specimens and those after high-temperature exposure. The analysis of the W/C ratio and coarse aggregate demonstrated significant differences (p-value < 0.05) in compressive strength between specimens in middle age and those exposed to high temperatures, excluding the early-age specimens. However, UPV analysis revealed insignificant differences, with p-values of 0.67 and 0.38 between specimens at an early age and post-high-temperature exposure, respectively. Regression analysis identified suitable functions for each scenario, emphasizing the importance of a strength prediction model for concrete after high-temperature exposure, particularly considering the W/C ratio. Since concrete showed statistically different compressive strength, UPV, and strength prediction models in three conditions (early age, middle age, and high temperature), different strength prediction models must be used for the purpose of accurately predicting the strength of concrete. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the interlayer bonding characteristics between double-layered asphalt systems. Three typical asphalt structures were chosen for evaluation. In each case, the bottom layer comprised of a dense graded asphalt concrete (AC-20) while three different asphalt mixtures were applied in surface layer: a dense graded mixture (AC-13), stone mastic asphalt (SMA-13), and open-graded friction course (OGFC-13). The effects of interface morphology, loading, and temperature conditions on interlayer bonding properties were considered. The interlayer shear and tensile strengths of the asphalt systems were tested using 'shear-compression' and 'shear-tensile' loading mode set ups, and the relationship between interface morphology and interlayer bond strength was quantitatively analyzed using 3D laser scanning. In addition, statistical analysis was performed to determine the significance level of each factor, followed by developing and validating prediction models for interlayer bond strength using multivariate nonlinear regression. The results showed that all factors had a significant effect on interlayer bonding performance, with temperature being the most prominent contributing factor. Increasing normal pressure had a positive effect on preventing the attenuation of interlayer shear strength, while an increase in shear stress was found to intensify the degradation of interlayer tensile strength. Moreover, interlocking and ensuring sufficient contact at the layer interface were demonstrated to enhance the interlayer friction effect positively. However, high normal stress could potentially lead to damage at the interface. Finally, the developed prediction models exhibited a high level of accuracy in estimating interlayer bond strengths and were able to explain over 97% and 98% of measured interlayer shear and tensile strengths, respectively. Employing a properly graded surface layer can improve the frictional and contact effects at the layer interface, thereby enhancing the overall interlayer bonding performance. [ABSTRACT FROM AUTHOR]

Compressive strength (CS) is concrete's most important mechanical property, as it plays an important role in setting design criteria. Thus, an accurate and early assessment of the CS of concrete can minimize time, labor, and cost. This paper investigated the ability of the Radial Basis Function (RBF) to handle the prediction of CS. The nonlinearities raised from the novel utilized admixtures between the input variables and output CS is tried to be conducted with the RBF model. In order to make a flexible framework combination of the RBF model with the African Vulture Optimization (AVOA) and Salp Swarm Algorithm (SSA) techniques are considered. The results achieved from the RBF-AVOA model indicated good agreement between the actual and predicted values. The proposed model provides a very accurate HPC compressive strength prediction. In addition, the correlation coefficient R2 is equal to (0.997), and the values of mean absolute error (MAE) (0.1917 MPa), root mean square error (RMSE) (0.937 MPa), and variance account coefficient (VAF) (99.73%) are low. The performance of the RBF-AVOA model, compared to other models, provided the desired advantage and more stable predictions. AVOA plays a key role in modeling results, improving generalization capabilities, avoiding redundant data, and decreasing uncertainty. [ABSTRACT FROM AUTHOR]

Construction and demolition (C&D) wastes are increasing continuously with intensified construction activities worldwide resulting in ecological concerns. Recycling of these waste products into recycled concrete aggregates (RCA) in base and sub-base layers of pavement is one of the solutions for the problem. Thus, the present study is an in-depth investigation of the utilization of the RCA in construction sector containing laboratory tests, microstructural characterization, and economic analysis. The experiment revealed that, for each mix proportion, the maximum dry density decreases and the ideal moisture content increases as the cement percentage is increased. The 7-day average ultimate compressive strength value for natural aggregates (NA) and recycled concrete (RCA) combined with additives met the requirements. The durability index for all the mix proportions was greater than 0.80. Finally, it was found that 17.86% of the material cost was saved with incorporation of RCA (50%)-NA (50%) for the construction of the sub-base layer of the pavement. [ABSTRACT FROM AUTHOR]

High-entropy alloys (HEAs) are new alloy systems that leverage solid solution strengthening to develop high-strength structural materials. However, HEAs are typically cast alloys, which may suffer from large as-cast grains and entrapped porosity, allowing for opportunities to further refine the microstructure in a non-melting near-net shape solid-state additive manufacturing process, additive friction stir deposition (AFSD). The present research compares the microstructure and mechanical behavior of the as-deposited AFSD Al0.35CoCrFeNi to the cast heat-treated properties to assess its viability for structural applications for the first time. Scanning electron microscopy (SEM) revealed the development of fine particles along the layer interfaces of the deposit. Quasi-static and intermediate-rate compression testing of the deposited material revealed a significant strain-rate sensitivity with a difference in yield strength of ~400 MPa. Overall, the AFSD process greatly reduced the grain size for the Al0.35CoCrFeNi alloy and approximately doubled the strength at both quasi-static and intermediate strain rates. [ABSTRACT FROM AUTHOR]

The stability of cemented backfill Is compromised via Hasting disturbances in the two-step stopping method. To obtain the dynamic compressive strength of the backfill quickly and accurately, 40 sets of uniaxial impact experiments with different strain rates were conducted using the separated Hopkinson pressure bar(SHPB). Input parameters included the times and ratio, backfill density, curing age, and average strain rate, while the dynamic compressive strength of the backfill served as the output parameter. A prediction model, optimized using the back propagation neural network (BPNN) based on the logistic chaotic sparrow search algorithm (CSSA), was established and compared with the BPNN optimized by the traditional BPNN and sparrow search algorithm. The results demonstrate that the average relative error of the CSSA-BPNN model Is 4.11%, with fitting correlation coefficients among the predicted and measured values exceeding 0.96, indicating high prediction accuracy. The root- mean-square error of the CSSA-BPNN model is 0.395 0 MPa, the average absolute error is 0.359 2 MPa, and the coefficient of determination Is 0.995 2, all of which outperform the other two prediction models. This enables accurate prediction of the dynamic compressive strength of the backfill, greatly reducing the need for physical experiments and providing a novel approach to the strength design of mine cemented backfill. [ABSTRACT FROM AUTHOR]

Fibre-reinforced sand (FRS) is a multiphase and multiscale geo-material, which is widely used in geotechnical engineering as supporting structure of excavation of underground space and reinforcement of foundation of underground structures, and its strength is determined by the properties of the heterogeneous substances of the FRS and their coupling mechanical responses. In order to investigate the influence of fibre characteristics and mechanical properties on the shear strength of the FRS, according to the microscopic interface slip effect generated by the interaction between sand particles and the interaction between these particles and fibre, the material phase of the FRS is divided to conceptualize a micro cell element of the FRS that is capable of reflecting the internal material characteristic information of the FRS. Moreover, based on the coordinated deformation condition between fibres and sand particles at the microscale and the couple stress theory that is capable of effectively describing the discontinuous mechanical responses at the sand-fibre interface, a mesomechanism-based multiscale Mohr-Coulomb shear strength criterion of the FRS is derived, and the yield locus of the FRS is also drawn on the p plane. Furthermore, a series of FRS samples with different fibre content and fibre length were prepared by adopting the freezing method, and consolidated and drained triaxial compression tests were conducted on these samples to validate the proposed multiscale coupled Mohr-Coulomb shear strength criterion. Results show that the multiscale coupled Mohr-Coulomb shear strength criterion is capable of effectively reproducing and predicting the yield strength of the FRS. The yield locus of the FRS extends outwards as fibre content and fibre length increase. The yield stress of the FRS predicted by the proposed multiscale coupled Mohr-Coulomb shear strength criterion is in good agreement with that of the test result. [ABSTRACT FROM AUTHOR]

The seismically deficient column details in existing reinforced concrete buildings affect the overall behavior of the building depending on the failure type of the column. The purpose of this study is to develop and validate a machine-learning-based prediction model for the column failure modes (shear, flexure–shear, and flexure failure modes). For this purpose, artificial neural network (ANN), K-nearest neighbor (KNN), decision tree (DT), and random forest (RF) models were used considering previously collected experimental data. Using four machine learning methodologies, we developed a classification learning model that can predict the column failure modes in terms of the input variables using the concrete compressive strength, steel yield strength, axial load ratio, height-to-dept aspect ratio, longitudinal reinforcement ratio, and transverse reinforcement ratio. The performance of each machine learning model was compared and verified by calculating the accuracy, precision, recall, F1-Score, and ROC. Based on the performance measurements of the classification model, the RF model has the highest average value for the classification model performance measurements among the considered learning methods and can conservatively predict the shear failure mode. Thus, the RF model can rapidly predict the column failure modes with the simple column details. Additionally, it was demonstrated that the predicted failure modes from the selected model were exactly same as the failure mode determined from a code-defined equation (traditional method). [ABSTRACT FROM AUTHOR]

Cement-based composite is a kind of heterogeneous and discontinuous material. It is not appropriate to conduct stress analysis on a model constructed by continuous mean theory when subjected to external loads. A granular flow model based on discrete element theory is constructed to simulate the dynamic process of cementstabilized macadam during uniaxial compression test in this article. The appropriate contact bonding model is selected, and the contact parameters are calibrated. After the uniaxial compression test in the laboratory, the relative displacement, stress transfer process and crack propagation between aggregate particles in the structure are verified by the results calculated by the model. It can be seen from the research results that the parallel bond model can well reflect the mechanical characteristics of cementstabilized macadam. In the process of the specimen being loaded, the vertical displacement between particles leads to the specimen being compacted, and the horizontal displacement between particles leads to the crack. The displacement angle of cementitious particles in the upper model is larger than that of coarse aggregate. The displacement angle of cementitious particles in the lower model is less than that of coarse aggregate. The particle displacement angle generally shows a decreasing trend. [ABSTRACT FROM AUTHOR]

Rock bursts pose a significant risk to coal mine operation safety. Thus, accurately discriminating coal bursting liabilities is crucial for predicting and preventing rock burst events. To better understand the effects of a varying bedding angle on the crack propagation rule, failure mode and bursting liability level of coal and coal-rock combinations, we propose an optimized machine learning-based model. Additionally, uniaxial compressive tests are conducted using PFC3D software on samples with different bedding angles. The results indicate that, among the nine light gradient boosting machine discriminant models constructed using three data preprocessing methods and three parameter optimization algorithms, the optimal model is identified as the particle swarm optimization-light gradient boosting machine discriminant model based on Z-score standardization method, which exhibits the best stability and has a F1-score of 93.6%. Bedding has a significant impact on the failure modes of two kinds of samples, resulting in an evident bedding effect on their bursting liability. The uniaxial compression strength and bursting energy index of both samples show a reduction-rising trend with an increasing bedding dip angle. However, the bursting liability level of these samples is not affected by 0°C or 90°C bedding dip angle. Therefore, when assessing the bursting liability of samples, the influence of coal seam bedding and its dip angles should be thoroughly considered. [ABSTRACT FROM AUTHOR]

Environmental pollution is a major issue that we are dealing with at the moment. The reuse of industrial waste, which is used as raw materials in other industries such as the construction materials industry, is a beneficial way to reduce pollution. This is possible due to the physical, chemical, and mineralogical properties of industrial waste. Examples of industrial waste that can be used for obtaining new building materials are: fly ash, furnace slag, silica fume, and so on. These wastes were analysed in this study using the following techniques: SEM, XRD, and EDAX. After characterization, the wastes were used as additives in cement-based materials. The following properties of the obtained materials were tested: compression strength, flexural strength, adhesion to the substrate, and shrinkage testing. Based on the results of the tests, the percentages used as waste addition were chosen. [ABSTRACT FROM AUTHOR]

This paper presents the mechanical behavior of thermally sprayed coatings produced using an arc wire coating material. The produced coatings were cut and subjected to strength resistance tests in static and in dynamic loading. The compressive behavior for the strain rates between 0.001 1/s and 2612 1/s was examined. The strain rate sensitivity of the material was recognized in the material during dynamic loading using the SHPB technique. Microstructural observations were made, and properties such as changes in porosity and the microhardness of the coatings tested were examined. A significant reduction in coating porosity was demonstrated after static loading (90%) and dynamic loading (86%). The result of porosity reduction is the strengthening of the coatings through an increase in the microhardness of these coatings after loading in the static test (160 HV 0.3/8) and the dynamic test (278 HV 0.3/8). As a result of the tests, the coatings retain their cohesion and remain consistent. At the same time, they can absorb a significant amount of mechanical energy due to plastic deformation and porosity reduction. The presented results concern a completely new coating material created from a core wire. [ABSTRACT FROM AUTHOR]

This article touches upon the development of dispersed-reinforced concrete components and the improvement of their physical and mechanical properties. They can be used in road and defense structures, bridges, and takeoff and landing zones. Multifunctional micro-reinforced fine-grained concrete compositions have been developed based on basalt fiber, where the limit of compression strength varies from 65.6 to 78.35 MPa, flexural strength from 6.4 to 9.1 MPa, and water permeability from 3.7 to 1.8%. Among the compositions of micro-reinforced concrete with basalt fiber, the best strength result was recorded in the case of 2% basalt fiber and 10% microsilica, with compression and flexural strengths of 78.35 and 9.1 MPa, respectively. The best water absorption result of 1.8% was obtained only with basalt fiber concrete when the fiber content was increased to 3.2%. As a result, the water absorption was reduced by 62% compared to the initial concrete. The increases in flexural and compression strengths were 42.19% and 13.8%, respectively. [ABSTRACT FROM AUTHOR]

Approximately 82% of amputees prefer microprocessor knees (MPKs) to the passive alternatives. However, the cost of these devices makes them inaccessible for many patients. The aim of this research is to develop an affordable MPK that allows for stumble reduction and flexion dampening at a fraction of the cost of similar devices. The GKnee was developed by a sophisticated mathematical model that can effectively calculate geometric configuration and simulate forces transferred through a prosthetic knee at any given point through the gait cycle. With a median error of 6%, the mathematical model was developed to the point of reasonable accuracy for determining component placement and force interactions. The model served as a valuable tool to assist in the iterative design process of the GKnee, influencing component selection for the hydraulic system and frame design. This model was then validated using a compression rig and a mock GKnee prototype. The GKnee was then evaluated for its ability to perform under expected loading conditions, using compression testing and dynamic flexion testing. This research led to the development of a sub USD 500 microprocessor prosthetic, while remaining under 2.27 kg. [ABSTRACT FROM AUTHOR]