Random Aggregate Model Research Articles

Meso-Analysis of Recycled Coarse Aggregate Self-Compacting Concrete on the Basis of Random Aggregate Model

The purpose of this paper is to explore the numerical simulation of damage process and results of a new environmentally friendly material, recycled coarse aggregate self-compacting concrete (RCASCC). Random aggregate model of mesoscopic viewpoint was used for the experimental simulation of RCASCC. Results show that the specimens with 50% substitution rate exhibited the best performance among the specimens (i.e., with rates of 25%, 50%, 75%, and 100%). The stress-strain curves after dimensionless treatment were fitted using the uniaxial compressive principal equation of concrete with control parameters a = 0.9 and b = 11, and the fitting degree of the curve was relatively good. Meanwhile, the change process of internal cracking was shown intuitively. The crack expansion process became more obvious in the specimens and beams with a high substitution rate of RCA. The simulation results of the bending process of RCASCC beams analyzed by the concrete damaged plasticity (CDP) model and extended finite element (XFEM) were compared with the test results. Both simulation results validated the applicability of the CDP model and XFEM in the mechanical tests of RCASCC and can provide valuable reference for future research on the mechanical properties of recycled aggregate self-compacting concrete.

Experimental and 3D mesoscopic investigation of uniaxial compression performance on basic magnesium sulfate cement-coral aggregate concrete (BMSC-CAC)

The constitutive relationship of basic magnesium sulfate cement-coral aggregate concrete (BMSC-CAC) under uniaxial compression was investigated using cylindrical specimens. The equal strain monotonic loading method was applied to obtain the stress-strain curves. Mechanical parameters such as elastic modulus ( E c ) and Poisson's ratio( μ ) were calculated. A 3D random aggregate mesoscopic model was used to simulate the failure process and crack propagation . The results show that when the strain approximated to maximum value, BMSC-CAC was rapidly destroyed in the shape of splitting. Compared with ordinary cement, the brittleness of concrete can be effectively improved due to the high toughness of basic magnesium sulfate cement (BMSC). The segmented constitutive equation of BMSC-CAC was given, which could express all of the compression test characteristics. The relative error of the peak stress and strain between the experiments and simulations were small. Analysis of the failure process reveals that damage first appears in the mortar and ITZ of the concrete, with micro-cracks converging into huge oblique cracks through the aggregate.

Numerical simulation of steel corrosion in chloride environment based on random aggregate concrete microstructure model

The corrosion of steel bar in concrete structure under chloride environment is simulated considering the influence of concrete coarse aggregate. Firstly, the random polygonal coarse aggregate is generated, and the meso numerical cross-section of reinforced concrete is obtained. Then, based on Butler-Volmer equation, considering the coupling effect of diffusion and electrochemical corrosion, an electrochemical corrosion model of steel bar is established. Next, the accuracy of the model is verified by existing experimental data. Finally, the relationships between the volume fraction of coarse aggregate and corrosion morphology, steel corrosion quantity and corrosion process are gotten. The results show that the coarse aggregate causes irregular corroded section shape of the steel bar, and there are convexities and concavities on the corroded surface. The coarse aggregate can suppress the steel corrosion. As the volume fraction of coarse aggregate increases, the durations of the non-corrosive stage and the corrosion expansion stage extend.

Mesoscale modelling of recycled aggregate concrete under uniaxial compression of different strain rates

Studying the compressive behaviour of recycled aggregate concrete (RAC) under different strain rates in a mesoscale model is of considerable interest. In the mesoscale model in this paper, RAC is regarded as a five-phase composite material mainly comprising natural aggregates, old interface transition zone (ITZ), old cement mortar, new ITZ and new cement mortar. The existence of pore defects is also considered. Random round aggregates and oval aggregate models of different recycled coarse aggregate replacement rates (0%, 25%, 50%, 75% and 100%) are constructed in the mesoscale RAC model. The uniaxial compressive behaviour of the mesoscale RAC model under different strain rates is numerically simulated. Numerical results show that the material properties of the ITZs have an impact on material damage. The compressive strength of recycled concrete increases with the strain rate, showing dynamic strain rate effects. The dynamic increase in strength is not only due to the material property, but also due to the inertia confinement. A mesoscale model of RAC with 1% porosity is then established to study the influence of initial micro-defects in RAC on its mechanical properties. The numerical results are compared with those of RAC without initial pore defects. These results indicate that the existence of pores considerably affects the formation and development of cracks under static and dynamic uniaxial compressions and weakens the compressive strength of RAC materials.

A Mesoscopic Model for Predicting the Chloride Diffusivity’ Representative Volume Element in Concrete as a Random Composite

Chloride diffusivity is the most crucial factor for evaluating durability and predicting service life of concrete structures exposed to chloride environment. In the present paper, concrete is considered as a random heterogeneous composite of three phases: the aggregates, the matrix, and the interfacial transition zones (ITZ) between them. A mesoscopic model has been established based on the random aggregate model and a numerical model for calculating the chloride diffusivity has been proposed. The influences of aggregate size and the properties of the interfacial transition zones on chloride diffusivity of concrete are also discussed. The chloride diffusivity is size dependent because aggregates are randomly distributed in concrete. The chloride diffusivity under different sizes is analyzed by numerous numerical simulations, and the representative volume element (RVE) of chloride penetration into concrete is researched by the statistical method.

Based on the CT Image Rebuilding the Micromechanics Hierarchical Model of Concrete

Establishing a mesoscopic numerical model to investigate the mechanical properties of concrete has very important significance. This paper considers the random distribution of aggregate in concrete. The aggregate is assumed to be spherical, respectively, to simulate the interface layer as the entity unit or the contact elements. The random aggregate model and the interface model of random aggregate were established. Based on the CT image and the application of MATLAB and MIMICS software, the different characteristics of the concrete model for 3D reconstruction were set up. Through comparative analysis of the advantages and disadvantages of different models, considering the CT number included in the CT images, this paper establishes the reconstruction model, which includes the shape of concrete aggregates, gradation, holes, etc. The analysis results have shown that the model can infer realistic concrete behavior, providing a new approach for studying concrete properties at the mesoscale.

Establishment and Application of Stochastic Mesoscopic Concrete Model

Concrete is a kind of complex multiphase composite material, and the spatial distribution of each component of concrete is random, which has an impact on its physical and mechanical properties. This paper presents algorithms for generating two‐dimensional (2D) and three‐dimensional (3D) arbitrarily graded stochastic concrete aggregate models, graphical format conversion methods, and finite element applications. Aggregate shapes include circular, ellipsoidal, convex polygon, ellipsoidal, and spherical. These models take into account the randomness of appearance, position distribution, and particle size distribution, including the interface transition zone, and the aggregate content can reach a high level. An efficient interference algorithm of ellipsoidal aggregate is proposed, which can reasonably control the thickness of the mortar layer around the aggregate. The corresponding program is compiled by MATLAB to realize the generation of random mesoscopic concrete aggregate geometric model. A graphic format conversion method is provided, which greatly extends the applicability and generality of the random aggregation model. The usefulness of the method in this paper was verified by the mechanical analysis of random aggregate model specimens with different volume fractions and the chloride transport properties of different aggregate shape specimens. In addition, the results of the two cases show that the random aggregate geometry and aggregate content have a great impact on the physical and mechanical properties of concrete, and the randomness of the spatial distribution of aggregates makes the chloride ion transport path and the elastic modulus and Poisson’s ratio of concrete be random. The results of this paper can provide an important research foundation for the study of mesoscopic physical and mechanical properties, gradation theory, and durability of concrete.

Prediction of Concrete Meso-Model Stress-Strain Curve Based on GoogLeNet

Generally, the macro-scopic mechanical properties of heterogeneous composites depend on meso-components’ distribution and mechanical properties, but it is extremely difficult to establish a clear macro-meso relationship expression. To cope with this challenge, for concrete, a strategy based on deep learning was proposed to obtain the stress-strain curves through meso-model image information. First, the GoogLeNet model based on convolutional neural networks was used for image information recognition and extraction. According to the complexity of the stress-strain curve, data preprocessing operations were performed and the corresponding multi-task loss function was designed. The meso-model images in the data set were generated with the random aggregate model based on the Monte Carlo method, and numerical simulation experiments were conducted to obtain the uniaxial compressive stress-strain curve of the corresponding meso-model. Finally, the feasibility of the proposed method was evaluated through training and testing. The training efficiency and prediction accuracy of the GoogLeNet model are better than the AlexNet and ResNet models, and have good generalization ability and robustness.

Analysis of Tensile Strength and Failure Mechanism Based on Parallel Homogenization Model for Recycled Concrete.

In this paper, a parallel homogenization model for recycled concrete was proposed. A new type of finite element method, the base force element method, based on the complementary energy principle and the parallel homogenization model, is used to conduct meso-level damage research on recycled concrete. The stress–strain softening curve and failure mechanism of the recycled concrete under uniaxial tensile load are analyzed using the nonlinear damage analysis program of the base force element method based on the parallel homogenization model. The tensile strength and destructive mechanisms of recycled concrete materials are studied using this parallel homogenization model. The calculation results are compared with the results of the experiments and meso-level random aggregate model analysis methods. The research results show that this parallel homogenization analysis method can be used to analyze the nonlinear damage analysis of recycled concrete materials. The tensile strength, stress–strain softening curve, and crack propagation process of recycled concrete materials can be obtained using the present method.

Multifield coupling study on random aggregate concrete under microwave irradiation

Microwave-assisted concrete aggregate recycling is a new green technology with minute pollution and low energy generation during the heating process. In this study, a random aggregate concrete model is established based on a real industrial microwave heating system. The secondary development of a MATLAB and COMSOL Multiphysics interface is applied to realize a multifield coupled numerical analysis of the electromagnetic field, heat transfer field, and mechanical field of concrete under microwave irradiation. The model is validated by experimental tests. The results show that the dielectric loss is the main factor that influences the concrete temperature variation. Tensile stress and shear stress are generated at the mortar–aggregate interfaces. A high microwave energy input leads to significant temperature and stress gradients between the aggregates and the mortar. Compared to the aggregates, the mortar suffers a larger deformation in a microwave field, finally leadings to its damage. Thus, the investigation of the thermal responses of aggregates and mortars under microwave irradiation will provide reference for the further development of microwave-assisted concrete recycling technology.

Effects of aggregate and interface characteristics on chloride diffusion in concrete based on 3D random aggregate model

The chloride diffusion in concrete with different aggregate volume ratios (AVR) and interfacial transition zone (ITZ) were studied in this paper. According to the finite element method, the 3D concrete model with aggregates and ITZ is modeled, and the chloride diffusion characteristics were numerically simulated and compared with the experimental results. Furthermore, the reasons for the better chloride resistance of nanocomposite concrete are studied. The results show that the established model can well reflect the material properties of concrete and has a good application effect on chloride diffusion. The increase of AVR inhibited the chloride diffusion and there is significant influence on the simulation results when use different AVR to back calculation. However, it is little influence on the simulation results when change the ITZ condition of back calculation. The better chloride diffusion resistance of nanocomposite concrete is mainly due to the improved anti-diffusion properties of the ITZ.

Meso-scale corrosion expansion cracking of ribbed reinforced concrete based on a 3D random aggregate model

Meso-scale corrosion expansion cracking of ribbed reinforced concrete based on a 3D random aggregate model

Mesoscopic study of concrete with random aggregate model using phase field method

In the present work, the phase field method implemented by the user-defined element (UEL) subroutine of commercial finite element software ABAQUS is adopted to investigate the failure pattern and mechanical responses of meso-scale concrete specimens. To build the structure model of meso-scale concrete specimens, the recently proposed random sequential addition (RSA) method is used. With the proposed numerical model, the uniaxial tensile test was carried out as a benchmark test to investigate the influence of several parameters, such as the volume fraction, size, and major axis direction of aggregates on the mechanical responses and failure mode of concrete specimens. Then, two classic examples, namely, a three-point bending (TPB) test and a four-point bending (FPB) test, are investigated with the proposed numerical model. The numerical results from the proposed numerical model indicate that: A higher interfacial transition zone (ITZ) content has an adverse effect on the peak strength of concrete; A negative correlation is shown between major axis direction of aggregates and peak strength of concrete; Intergranular fracture mode is observed, in which the damage areas of concrete are mainly distributed around the ITZ; The linear elastic stiffness and peak strength are almost independent of the aggregate distribution, but the fracture propagation patterns are sensitive to meso-structures of concrete; and numerical results of TPB and FPB tests also indicate that the notch of concrete has non-negligible influences on fracture propagation path, as well as linear elastic stiffness and peak load of concrete specimens.

3‐D base force element method on meso‐damage analysis for recycled concrete

AbstractThe 3‐D base force element method (BFEM) for damage problems is proposed, which is applied to analyze the damage mechanism of recycled aggregate concrete (RAC). A piecewise curve damage constitutive model is given to simulate the constitutive relationships of RAC phases. A spatial random aggregate model of RAC is proposed. 3‐D numerical simulations of RAC under uniaxial mechanical stress are carried out. The macroscopic stress–strain relationship and failure process of RAC under uniaxial stress based on the 3‐D BFEM are obtained. The numerical results show a good consistency with the experimental results. This illustrates that the numerical simulation can reflect the nonlinearity deformation, stress redistribution, and crack propagation process of RAC. In addition, the influence of recycled aggregate replacement percentage on strength and elastic modulus is investigated. The results show that the content proportion of recycled aggregate has a great effect on RAC, which have to be considered in the analysis and the application of RAC.

Three-dimensional meso-scale modelling of failure of steel fiber reinforced concrete at room and elevated temperatures

Steel fiber reinforced concrete (SFRC) is composed of coarse aggregate particles, mortar matrix, fibers, pores and microcracks from the viewpoint of meso-scale. To reflect the mesoscopic characteristics more realistically, a three-dimensional meso-scale model for SFRC was established. In the model, the fibers were explicitly modelled while the concrete matrix was regarded as a tri-phase composite consisting of aggregate, mortar matrix and the interface transition zones (ITZs) between them. Based on the idea of classical random aggregate model for plain concrete, a programme was designed to randomly distribute aggregate particles and steel fibers. The meso-scale numerical model was verified by the good agreement between simulation results and the available test results. The dynamic failure behavior of SFRC at room and elevated temperatures was investigated by utilizing the simulation method. The simulation results indicate that for fiber content no larger than 2% volume, the influence of steel fiber on thermal conduction of SFRC can be ignored. Compared with that of plain concrete, strain rate effect on compressive strength of SFRC is weaker and it would be further decreased under high temperatures. The improvement of SFRC performance induced by steel fiber increases for higher fiber volume fraction whilst decreases with respect to strain rates, regardless of temperature. When the fiber amount is identical, the dynamic compressive strength of SFRC decreases slightly in the case of larger fiber diameter or smaller fiber length.

Three-dimensional mesoscale modeling of concrete with convex aggregate based on motion simulation

Numerical simulation using a mesoscale model is an effective method to determine the complex mechanical behaviors of concrete. Establishing a numerical sample with a mesostructure close to realistic concrete is crucial for mesoscale simulation. This paper presents a heuristic packing algorithm for constructing 3D random aggregate models with high aggregate content. In the algorithm, the aggregate packing problem is considered as a problem of optimizing the potential energy of the mesoscale configuration. In the initial state, all aggregate particles are randomly placed inside the specimen container; then, the particles move in the container according to the proposed motion simulation strategy until a feasible spatial configuration is obtained. The framework is suitable for various types of aggregates, including spherical, ellipsoidal, polyhedral, and mixed-type aggregates, that have a support mapping representation. In this study, numerous samples with different types of aggregates were established, and the influence of the aggregate gradation on the packing density was examined. The results verified the efficiency and robustness of the proposed algorithm.

3D random packing algorithm of ellipsoidal particles based on the Monte Carlo method

The random packing of aggregate particles is an important factor affecting the mechanical properties of concrete at the mesoscopic scale. In the current study, a meso-mechanical pretreatment algorithm is developed to construct the random ellipsoidal aggregate model for the mesoscopic structure of fully graded concrete. The Fuller curve combined with equivalent diameter is adopted to ensure equality between the gradation and content of the random ellipsoidal aggregates and those of the actual geometric aggregates. A ‘removing occupied space’ method is proposed to improve the packing efficiency based on the background grids strategy. A modified search algorithm consisting of rough and fine detection for determining the overlaps is proposed to improve the optimised simulation of the meso-structure of cement-based composites. A random ellipsoidal aggregate model with different aspect ratios of ellipsoid is developed and compared with the existing algorithms to test the efficiency of the new pretreatment algorithm. The effect of the ellipsoidal shape on the random packing fraction is investigated based on the proposed pretreatment algorithm. The pretreatment algorithm proposed greatly improves the efficiency of packing and provides a powerful tool for the realisation of three-dimensional large-scale numerical meso-concrete.

Inverse Analysis of Concrete Meso-constitutive Model Parameters Considering Aggregate Size Effect

Abstract The meso numerical simulation has become an important method to study the characteristics of materials; however, the key to its further application is determining the parameters of meso-constitutive model. Considering that the meso-scale parameters of materials are hard to measure, this paper took into account the aggregate size effect and proposed a meso-parameter identification method by combining random aggregate numerical simulation and genetic algorithm. First, a random aggregate model of concrete was established, and its meso-model parameters were analyzed. The Morris method was used to analyze the sensitivity of meso-component parameters to the macro-responses, and results showed that the elastic modulus of mortar matrix, interface and large aggregates had a great effect on the peak strain and that the elastic modulus, Poisson’s ratio and tensile strength of interface and mortar matrix, as well as the Poisson’s ratio of large aggregates and the elastic modulus of small aggregates all had an effect on the peak stress, among which the interface tensile strength produced the greatest effect. Second, a parametric inversion and optimization function was established. The uniaxial compression numerical simulation test and genetic algorithm were combined to invert the meso-parameters, and results showed that compared with the single-aggregate parameter inversion curve, the multi-aggregate inversion stress-strain curve was much closer to the measured curve. That was because the aggregates of small size had lower elastic modulus, easing the stress concentration at the interface between aggregates and cement stone, and delaying the formation and growth of cracks.

Image Analysis and Functional Data Clustering for Random Shape Aggregate Models

This study presents a random shape aggregate model by establishing a functional mixture model for images of aggregate shapes. The mesoscale simulation to consider heterogeneous properties concrete is the highly cost- and time-effective method to predict the mechanical behavior of the concrete. Due to the significance of the design of the mesoscale concrete model, the shape of the aggregate is the most important parameter to obtain a reliable simulation result. We propose image analysis and functional data clustering for random shape aggregate models (IFAM). This novel technique learns the morphological characteristics of aggregates using images of real aggregates as inputs. IFAM provides random aggregates across a broad range of heterogeneous shapes using samples drawn from the estimated functional mixture model as outputs. Our learning algorithm is fully automated and allows flexible learning of the complex characteristics. Therefore, unlike similar studies, IFAM does not require users to perform time-consuming tuning on their model to provide realistic aggregate morphology. Using comparative studies, we demonstrate the random aggregate structures constructed by IFAM achieve close similarities to real aggregates in an inhomogeneous concrete medium. Thanks to our fully data-driven method, users can choose their own libraries of real aggregates for the training of the model and generate random aggregates with high similarities to the target libraries.

Five-phase sphere equivalent model of recycled concrete and numerical simulation based on the base force element method

Purpose This paper aims to propose the five-phase sphere equivalent model of recycled concrete, which can be used to deduce the theoretical formulas for the Poisson’s ratio and effective elastic modulus. Design/methodology/approach At a mesoscopic level, the equivalent model converts the interfacial layer, which consists of the new interfacial transition zone (ITZ), the old mortar and the old (ITZ), into a uniform equivalent medium. This paper deduces a strength expression for the interfacial transition zone at the microscopic level using the equivalent model and elastic theory. In addition, a new finite element method called the base force element method was used in this research. Findings Through numerical simulation, it was found that the mechanical property results from the five-phase sphere equivalent model were in good agreement with those of the random aggregate model. Furthermore, the proposed model agree on quite well with the available experimental data. Originality/value The equivalent model can eliminate the influence of the interfacial layer on the macroscopic mechanical properties, thereby improving the calculation accuracy and computational efficiency. The proposed model can also provide a suitable model for multi-scale calculations.