Behavior Of Concrete Material Research Articles

Split tensile strength of fiber-reinforced coral aggregate concrete: Deep learning model and experimental validation

Machine learning methods are increasingly becoming an important research field for solving the complex mechanical behavior of concrete materials. A reliable deep learning model was developed based on a dataset consisting of 319 experimental data points to predict the split tensile strength of fiber-reinforced coral aggregate concrete (FRCAC). The feature selection was carried out using correlation analysis, and the neural network structure was optimized by adjusting hyperparameters based on the 10-fold cross-validation (CV). Subsequently, six statistical indicators were employed to evaluate the accuracy and generalization ability of the model. The deep neural network (DNN) model demonstrates excellent performance, with R2, MAE, and MAPE of 0.98, 0.181 MPa, and 0.037 for the training dataset and 0.95, 0.286 MPa, and 0.074 for the test dataset, respectively. Additionally, 24 sets of concrete proportions are designed using the trained DNN model, and the results indicate that the absolute error and relative error between predicted and experimental values are less than 0.4 MPa and 6.8 %, respectively. The feature analysis based on SHapley Additive exPlanations (SHAP) reveals that volume fraction, curing age, water-binder ratio, and the tensile strength of fiber have the highest contribution in estimating the split tensile strength of FRCAC. This research can provide a reference for optimizing the design of FRCAC.

Mechanical Analysis and Optimization of Concrete Structures Based on Advanced Finite Element Method

This article explores the mechanical analysis and optimization problems of concrete structures based on the Advanced Finite Element Method. By integrating advanced numerical techniques with practical engineering cases, this study aims to improve the safety and economy of concrete structure design. Firstly, the paper outlines the limitations of traditional finite element methods in concrete structure analysis, such as insufficient computational accuracy and low computational efficiency. Subsequently, by introducing AFEM, we significantly improved the accuracy and efficiency of the analysis. For example, when simulating a complex bridge structure, AFEM not only reduces the calculation time by about 25%, but also improves the accuracy of stress distribution prediction by more than 10%. In the optimization stage, we utilized the analysis results of AFEM and optimized the material consumption, cross-sectional dimensions, and reinforcement parameters of concrete structures through multi-objective optimization algorithms. A comprehensive data analysis underscores that the optimized concrete structure triumphantly meets all safety performance criteria while achieving a remarkable 12% reduction in material usage. This substantial material savings translates into a substantial 8% decrease in overall construction costs, significantly bolstering the project’s economic feasibility. Moreover, these cost savings not only amplify the project’s profitability but also play a pivotal role in enhancing the structure’s longevity and durability, thereby contributing to its sustainable performance over its entire service life. Furthermore, we delved into the capability of AFEM in simulating intricate phenomena such as the nonlinear behavior of concrete materials, crack propagation patterns, and the intricate interactions between steel reinforcements and concrete. These complex mechanical behaviors are crucial for the safety and stability of structures, and AFEM provides more comprehensive and accurate references for structural design by accurately simulating these behaviors. This article conducts in-depth research on the mechanical analysis and optimization of concrete structures based on AFEM, and demonstrates the significant advantages of AFEM in improving structural safety and economy through specific data. These research results not only provide new theoretical support and practical tools for concrete structure design, but also provide valuable references for future research and application in related fields.

Modeling time-dependent deformation in concrete: A fractional calculus method with finite element implementation

This study presents a novel numerical method to simulate the time-dependent behavior of concrete materials. The deformation response of both traditional and fractional calculus (FC) viscoelastic models is analyzed by the proposed method, in which models’ one-dimensional constitutive relationships are extended to the three-dimensional form. By applying numerical and finite difference methods based on Caputo-type fractional integration, the stress-strain behavior of the FC viscoelastic model is discretized over the time scale. This method exhibits broad application prospects, and can be employed to represent various forms of viscoelastic models. For the concrete material, suitable FC viscoelastic models are developed. To facilitate practical engineering applications of the proposed model, a numerical solution algorithm is implemented in the finite element (FE) analysis through the User-defined Material Mechanical Behavior (UMAT) interface of the commercial FE software ABAQUS. Finally, FE results are compared with the experimental results from several concrete creep tests. The consistency between the FE results and experimental data confirms the effectiveness of the proposed model in describing concrete behavior. The proposed method and model provide theoretical and numerical support for a more profound understanding and simulation of the time-dependent deformation of RC specimens in practical engineering applications.

Time-varying damage evolution of concrete under cyclic disturbance loading- an experimental observation utilizing AE and DIC

Cyclic disturbance loading affects the continuous operation of concrete structures. This study aims to better understand the failure behavior of concrete structures under cyclic disturbance loading. This study combined acoustic emission (AE) and digital image correlation (DIC) technologies to study mechanical failure behavior and damage evolution of concrete materials under cyclic disturbance loading and unloading. The AE event time-frequency characteristics, surface principal strain program, and damage parameters of samples with different cyclic disturbance amplitudes were obtained by theoretical calculation. The results reveal that when minor disturbance amplitudes are applied, the elastic modulus of concrete specimens tends to increase. When the disturbance amplitude is too large, the elastic modulus of the specimens drops, leading to faster specimen failure. The AE characteristic parameters exhibit a Felicity effect after the sample is subjected to a cyclic disturbance loading. Moreover, the larger the amplitude of the disturbance load, the more frequent the low-frequency and high-amplitude events generated during the final rupture, the higher the concentration of the principal strain on the sample's surface, and the wider the crack band distribution. AE energy and Effective crack are consistent in characterizing damage, and the changing trend of these two damage parameters can better reflect the deterioration process of concrete. The research results will provide practical and theoretical insights for safely operating and maintaining concrete structures.

Integration of additive manufacturing, lean and green construction: A conceptual framework

The increasing demand for energy-saving and cleaner production has driven the need for additive manufacturing in the construction industry over the past decade. Additive manufacturing shortens the supply chain of materials and equipment by introducing the concept of just-in-time construction, which is a step towards lean construction. Although additive manufacturing holds significant potential for sustainable construction, several factors, such as the dynamic behavior of fresh concrete material, environmental conditions (temperature and humidity), surface quality, and filament cracking, pose challenges to its practical implementation in large-scale construction projects. This paper aims to develop a conceptual framework by integrating additive manufacturing and lean and green construction to facilitate construction enterprises. The framework shows that lean construction aids in identifying the wasteful activities found in the construction 3D printing and provides a strategic way to minimize such activities using various lean tools in order to ensure sustainable construction. Moreover, this integrated framework provides additive manufacturing experts with a strategic approach to addressing the challenges encountered in the construction 3D printing process by leveraging lean construction tools. The utilization of lean construction tools to address additive manufacturing challenges has the potential to enhance the sustainability of additive manufacturing.

Research on rheological behavior of fresh concrete single-cylinder pumping based on SPH-DEM

In contrast to traditional approaches to simulating fresh concrete, the model applied here allows issues such as liquid phase and the motion of sub-scale particles to be considered. The rheological behavior of fresh concrete materials was investigated, and the slump test and pumping process of fresh concrete were simulated by combining the smooth particle hydrodynamics coupled with discrete element method. Based on Bi-viscosity model and Bingham model, linear and nonlinear fitting of rheometer data and the derivation equations were educing. Bi-viscosity model and the Bingham model were compared in slump test. The results show that the Bi-viscosity model is more accurate in simulation, and the error percentage is less than 10%. The Bi-viscosity model was used to simulate and predict the results of slump experiment, and the influence of rheological parameters on the slump velocity and shape was obtained. The simulation analysis model of concrete single-cylinder pumping is established, and the experimental and simulation analysis models are compared. The results show that the SPH-DEM pumping pressure prediction is very close to the experimental results.

Mechanical and Fracture Behavior of Concrete Material Derived from CDA, Crumb Rubber Particles and Inclusion of Basalt Fiber

Mechanical and Fracture Behavior of Concrete Material Derived from CDA, Crumb Rubber Particles and Inclusion of Basalt Fiber

Meso-scale analysis on the effect of coarse aggregate properties on the creep behaviors of concrete based on the 3D particle-based method

Coarse aggregate, as the main component of concrete, has a significant influence on its behaviors. In this work, a 3D particle-based method was utilized to investigate the effect of coarse aggregate properties on the creep behaviors of concrete at a meso-scale level, in which concrete was composed of mortar, coarse aggregate, and interfacial transition zone (ITZ). Firstly, cluster-based modules for aggregate were generated based on the real aggregate geometry obtained by 3D scanning, and then, the developed aggregates were randomly distributed in the model according to the specified aggregate gradation and content. Then, the Burger model, a linear viscoelastic-plastic model, was employed to define the contact mechanical characteristics of mortar and ITZ. Meanwhile, the linear parallel bond model, a linear elastic bonding interface with dimensions that can transmit forces and moments, was utilized to describe the contact bonds between balls in the aggregate. On this basis, the effects of coarse aggregate properties (i.e., surface topography, shape, gradation, content, and elastic modulus) on the concrete creep were studied quantitatively. The results show that the coarser the surface topography of aggregate, the smaller creep. Also, with the increase in the content or elastic modulus of coarse aggregate, concrete creep showed a decreasing trend. In addition, the constraint action of the aggregate can be illustrated by the displacement fields. Overall, the 3D particle-based proposed in this work can provide an effective tool to explain the creep behavior of concrete materials from the meso-scale.

Two-Dimensional Mesoscale Finite Element Modeling of Concrete Damage and Failure

Methodologies are developed for analyzing failure initiation and crack propagation in highly heterogeneous concrete mesostructures. Efficient algorithms are proposed in Python to generate and pack geometric features into a continuous phase. The continuous phase represents the mortar matrix, while the aggregates and voids of different sizes represent the geometric features randomly distributed within the matrix. The cohesive zone model (CZM) is utilized to investigate failure initiation and crack propagation in mesoscale concrete specimens. Two-dimensional zero-thickness cohesive interface elements (CIEs) are generated at different phases of the concrete mesostructure: within the mortar matrix, aggregates, and at the interfacial transition zone (ITZ). Different traction–separation laws (TSL) are assigned to different phases to simulate potential crack paths in different regions of the mesoscale concrete specimen. The mesoscale finite element simulations are verified using experimental results from the literature, with a focus on implementing mixed-mode fracture and calibrating its corresponding parameters with respect to the experimental data. In addition, the current study addresses the limited exploration of void effects in mesoscale concrete simulations. By investigating voids of diverse sizes and volume fractions, this research sheds light on their influence on the mechanical behavior of concrete materials. The algorithms for generating cohesive interface elements and concrete microstructures are described in detail and can be easily extended to more complex states. This methodology provides an effective tool for the mesostructural optimization of concrete materials, considering specific strength and toughness requirements.

Characterizing fatigue damage behaviors of concrete beam specimens in varying amplitude load

In this paper, the random and nonlinear mechanical characteristics of the composition distribution of concrete in each phase are investigated to solve the difficulty of fatigue damage test of concrete beam specimens under variable amplitude loading. A three-dimensional (3D) concrete composite random aggregate meso-model of concrete beam specimens is built with Digimat as a composite modeling tool. Subsequently, the bending-tensile strength and fatigue life of the model under four-point bending loading is analyzed and calculated using Abaqus finite element analysis model based on the concrete elastic-plastic damage criterion. The mechanical behaviors of concrete materials under static load failure, multistage fatigue loading, and random fatigue loading are studied. Finally, compared with the test results, the following conclusions are obtained. The random aggregate model and elastoplastic damage mechanics model of concrete composite constructed by concrete in Abaqus and Digimat can better describe the geometric and distribution characteristics of composite structure and aggregate in concrete beams and the mechanical behavior of fatigue and static load failure. The difference is 4.08 % with the experimental results, which verifies the validity and reliability of the numerical simulation model, and the fatigue life of concrete beams under random loading Sra and Srb is 1622 and 164 times, respectively. The research results have certain guiding significance and reference value for accurate calculation of bending and tensile strength of concrete beams under specified raw material and mix ratio and prediction of fatigue damage cracking in airport cement concrete pavement structure.

Experimental study on the size effect on the equation of state of concretes under shock loading

Adopting the classical theory of hydrocodes, the constitutive relations of concretes are separated into an equation of state (EoS) which describes the volumetric behavior of concrete material and a strength model which depicts the shear properties of concrete. The experiments on the EoS of concrete is always challenging due to the technical difficulties and equipment limitations, especially for the specimen size effect on the EoS. Although some researchers investigate the shock properties of concretes by fly-plate impact tests, the specimens used in their tests are usually in one size. In this paper, the fly-plate impact tests on concrete specimens with different sizes are performed to investigate the size effect on the shock properties of concrete materials. The mechanical background of the size effect on the shock properties are revealed, which is related to the lateral rarefaction effect and the deviatoric stress produced in the specimen. According to the tests results, the modified EoS considering the size effect on the shock properties of concrete are proposed, which the bulk modulus of concrete is unpredicted by up to 20% if size effects are not accounted for.

Development of Mesoscale Simulation Approach of Concrete Material and Structural Behavior with Physical Damages with RBSM

Development of Mesoscale Simulation Approach of Concrete Material and Structural Behavior with Physical Damages with RBSM

Modeling and Simulation of the Hysteretic Behavior of Concrete under Cyclic Tension-Compression Using the Smeared Crack Approach.

Concrete structures under wind and earthquake loads will experience tensile and compressive stress reversals. It is very important to accurately reproduce the hysteretic behavior and energy dissipation of concrete materials under cyclic tension-compression for the safety evaluation of concrete structures. A hysteretic model for concrete under cyclic tension-compression is proposed in the framework of smeared crack theory. Based on the crack surface opening-closing mechanism, the relationship between crack surface stress and cracking strain is constructed in a local coordinate system. Linear loading-unloading paths are used and the partial unloading-reloading condition is considered. The hysteretic curves in the model are controlled by two parameters: the initial closing stress and the complete closing stress, which can be determined by the test results. Comparison with several experimental results shows that the model is capable of simulating the cracking process and hysteretic behavior of concrete. In addition, the model is proven to be able to reproduce the damage evolution, energy dissipation, and stiffness recovery caused by crack closure during the cyclic tension-compression. The proposed model can be applied to the nonlinear analysis of real concrete structures under complex cyclic loads.

Strain Rate Influences on Concrete and Steel Material Behavior, State-of-the-Art Review

Strain Rate Influences on Concrete and Steel Material Behavior, State-of-the-Art Review

Mechanical performance of Bio-Inspired Gyroid and Primitive concrete structures under combined compression and torsion Loads: A discrete element method study

Bioinspired lightweight Primitive and Gyroid structures are two well-known TPMS (triply periodic minimal surface) cellular structures. These structures have been shown to possess high specific strength and energy absorption capacity, and thus hold great promise for a range of prefabricated civil engineering applications. As a result, concrete cellular TPMS structures have garnered the attention of researchers. However, prior to this study, no investigation has been carried out on the mechanical properties and failure patterns of concrete Primitive and Gyroid structures under coupled compressive and torsional loads. This lack of knowledge on the behaviour of these structures can lead to safety concerns in construction projects. To better understand the mechanical behaviour of Primitive and Gyroid structures under combined compression and torsion, the discrete element method (DEM) is adopted to simulate the TPMS structures. Both linear contact and nonlinear softbond contact models are utilized to simulate the brittle mechanical behaviour of concrete material. After validating the DEM parameters using published experimental data, the DEM models are subjected to coupled compressive and torsional loads to study their compressive and torsional bearing capacity and cracking patterns. The results indicate that the Primitive based structures outperform the Gyroid based structures in terms of both compressive and torsional resistance. The study is the world's first to reveal that a compressive load enhances the ultimate torsional bearing capacity of TPMS structures, but a torsional load reduces their compressive bearing capacity. Additionally, the loading conditions have little impact on the cracking patterns of the four TPMS structures.

A novel approach in forecasting compressive strength of concrete with carbon nanotubes as nanomaterials

The evolution of nanotechnology in cementitious concrete can be used to enhance the mechanical behavior of concrete and other materials. Thus, the utilization of carbon nanotubes (CNTs) in the concrete cementitious industry will deliver important remedial measures for generating an eco-friendly environment with multifunctional properties. In addition, planning and conducting experimental tests for different samples and testing at varying ages is laborious, time taking and expensive. Consequently, the prediction model looks necessary. Because of the complex nature of contemporary construction materials, empirical and statistical approaches do not work well for such materials; thus, machine learning approaches were utilized for this study. Thus, the process of forecasting concrete strength (CS) can be accelerated by employing soft machine learning (ML) techniques. Moreover, the ensemble of the models is also done for an accurate estimation of the CS with the Python Jupyter Notebook. Decision tree (DT), multilayer perceptron neuron network (MLPNN), and support vector machine (SVM) were utilized as individual approaches. These individual ML models then ensemble with two approaches namely bagging and boosting with twenty sub models. The outcome of the model depicts a robust performance by showing significant correlations (R2) as compared to individual ML. Data points with 282 having contribution factors (e.g., curing (days), cement (kg/m3), water to binder (w/b), fine aggregate (kg/m3), nanomaterial as carbon nanotubes (%), coarse aggregate (kg/m3), and CS were used as input parameters for ML modeling. To ensure that each model is as accurate as possible, cross-validation (CV) with K-folding and statistical error analysis (i.e., MAE, MAE, and RMSE) was utilized. The result reveals that the ensemble algorithm with bagging and boosting give robust correlation R2 ranging from 0.9 to 0.95. Moreover, DT with Ada-boost yields a strong R2 of about 0.93. Similarly, ensemble model of SVM and MLPNN with boosting depicts R2 = 0.93 and 0.94 respectively. K-fold cross-validation confirms the model’s accuracy with minimal statistical error. Also, statistical checks reveal that the ensemble model provides an increase in the overall performance by showing minimal error as compared to standalone method.

Finite element modeling of precast reinforced concrete wall with dual boundary elements under lateral load

This study aimed to stimulate the structural behaviour of the precast wall PC with dual boundary elements under constant axial load and incremental lateral load in terms of displacement control and assess its response based on the load–displacement response, stiffness degradation and modes of failure using Abaqus Software and validate the result of the tested specimen. Two approaches were used for defining the interaction between the steel reinforcement and the surrounding concrete where the high-stress regions are. Friction and cohesive behaviour using traction separation law were employed to define the interaction between the interfaces of the PC wall and post-cast concrete boundary elements. Furthermore, this study primarily focused on the nonlinear behaviour of concrete and steel materials, the bond-slip behaviour between concrete-to-steel interface, the interaction between precast and post-cast concrete interfaces, and load and boundary conditions. The concrete damage plasticity model was adopted to simulate the concrete behaviour and the cohesive and frictional behaviour to model the interaction between precast and post-cast concrete interfaces. The findings show that the initial response of both FE models agreed well with test rested specimen. However, Model I exhibited a stiffer response up to the yielding point. Furthermore, both FE models continued to exhibit ductile response, showing that the right-hand side post-cast cornet boundary element didn’t experience total crushing at the bottom right concrete.

Numerical Modeling of Interface Bond Behavior Between Hybrid Steel-PVA Fiber-Reinforced Engineered Cementitious Composite and Concrete

This paper presents a numerical study on interfacial behavior between hybrid steel and polyvinyl-alcohol fiber-reinforced engineered cementitious composite (HSP-ECC) and concrete. Concrete damage plasticity (CDP) model was used to define the mechanical behavior of HSP-ECC and concrete materials. Interfacial behavior was simulated for as-cast and sandblasted surfaces by adopting traction-separation constitutive model. Key interface parameters were determined by calibration of finite element (FE) modeling results with experimental results. The FE modeling results illustrated the reliability and efficiency of the proposed numerical approach in the prediction of interface bond behaviors between HSP-ECC and concrete for different degrees of surface roughness.

Polymorphic Uncertain Structural Analysis: Challenges in Data‐Driven Inelasticity

AbstractThis contribution addresses polymorphic uncertainty quantification within structural analysis of reinforced concrete structures composed of heterogeneous concrete and reinforcement (e.g. steel bars or carbon fibres). The macroscopic material behaviour of concrete is strongly dependent on the mesoscopic heterogeneities, which are considered by multiscale modelling. The heterogeneous mesoscopic material behaviour is characterized by representative volume elements (RVE) and the transition of scales is carried out by utilizing numerical homogenization methods.The concept of data‐driven computational mechanics enables material model free finite element analyses directly based on material data sets, overcoming the necessity of assumptions in material modelling. This approach mainly consists in assigning a stress‐strain state, which leads to a minimum of an objective function and fulfils equilibrium as well as compatibility constraints of every integration point. Inelastic material behaviour is taken into account through the definition of local data sets containing only data set states which are consistent with respect to the past local history . The realistic modelling of structures requires the consideration of data uncertainty. Generalized polymorphic uncertainty models are utilized in order to take variability, imprecision, inaccuracy and incompleteness of material data into account by combining aleatoric and epistemic uncertainty models.In this contribution, a computationally efficient approach for the consideration of data sets containing uncertain stress‐strain states within data‐driven analysis based on information reduction measurements is presented. Due to generalization, the approach is applicable to various aleatoric, epistemic and polymorphic uncertainty models. The identification of admissible local data sets for taking inelastic material behaviour into account within data‐driven analysis is realized by an energy based history parametrization which is extended to uncertain data. An approach for the efficient selection of these local data sets is presented and challenges in data‐driven inelasticity, particularly in the use case of polymorphic uncertain analyses of concrete structures, are pointed out.

The Effect of Elevated Temperatures on the Behavior of Concrete Material

Abstract: The purpose of this study was to provide an overview of the effect of elevated temperature on the behavior of concrete materials. The effects of elevated temperatures on the properties of common portland cement concretes and manufacturing materials are summarized. The effect of elevated temperature on conventional concrete, GGBS concrete and BFS concrete is considered and the performance is compared with the strength of conventional concrete. Concrete in case of an unexpected fire, the properties of the concrete will change after the fire. The building must be designed to withstand high temperatures and also mainly fire. When exposed to high temperatures, such as during a fire, the mechanical properties of concrete such as strength, modulus of elasticity and volume stability are significantly reduced. Concrete structure is exposed to high temperatures, it degrades in many different ways, such as color, compressive strength, elasticity, and high temperature affects concrete density and surface appearance