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Modeling and Analysis of Composite Materials and Structures in Civil Engineering (Second Edition)

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A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Construction and Building Materials".

Deadline for manuscript submissions: closed (30 April 2026) | Viewed by 12116

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Prof. Dr. Yiming Zhang

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1. School of Civil and Transportation Engineering, Hebei University of Technology, Xiping Road 5340, Tianjin 300401, China
2. School of Civil Engineering and Architecture, Zhejiang Sci-Tech University, Hangzhou 310018, China
Interests: multifield research; discontinuity; fracture; rock mechanics; tunnel fires
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Prof. Dr. Linlong Mu

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State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University, Shanghai 200092, China
Interests: suffusion research; CFD-DEM; relative density; fines content; stress transmission mechanisms
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Prof. Dr. Jiale Li

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School of Civil and Transportation Engineering, Hebei University of Technology, Tianjin 300401, China
Interests: research applications of computer vision in traffic engineering; traffic big data analysis; intelligent terminal devices; electric vehicle routing; charging station site optimization; carbon accounting
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Dear Colleagues,

The application of composite materials and structures in civil engineering is becoming increasingly widespread. With their unique mechanical properties, light weight, high strength, corrosion resistance, and durability, they have become key materials for enhancing the performance of civil engineering structures. In particular, the use of composite materials in areas such as bridges, buildings, transportation infrastructure, and seismic reinforcement has shown significant technical advantages and economic benefits. For example, Fiber-Reinforced Polymers (FRPs) are widely used for structural repair and reinforcement, while prestressed composites are applied in the design of bridges and high-rise buildings, effectively extending the lifespan of structures and enhancing their disaster resistance capabilities.

Although the prospects for the application of composite materials in civil engineering are promising, there are still a series of technical challenges in their modeling and analysis. Firstly, composite materials themselves have complex multi-scale characteristics, and the characterization and simulation from microstructure to macro-performance still require further development. Secondly, the heterogeneity, anisotropy, and nonlinear behavior of composite materials make the prediction of their mechanical properties more difficult, raising higher demands for engineering design and structural safety evaluation. In particular, existing models and analysis methods still need to be improved to address real-world conditions in the study of fatigue, damage, and failure mechanisms.

To promote the application and development of composite materials and structures in civil engineering, particularly innovations and advancements in modeling and analysis, we cordially invite scholars, engineers, and researchers from related fields to submit papers. We welcome contributions on topics including, but not limited to, mechanical behavior and performance evaluation of composite materials, multi-scale modeling and simulation, applications of composites in civil structures, damage and fatigue analysis, structural optimization and design, and intelligent design and health monitoring of composites. Of particular interest are data-driven and physics-informed machine learning methods, which, through big data analysis and predictive models, demonstrate great potential in assessing the performance of composite materials and structures, identifying damage, and predicting service life. These methods also show certain advantages in terms of accuracy and computational efficiency. We look forward to discussing the latest research outcomes in this cutting-edge field with you and advancing the wider application of composites in civil engineering.

Prof. Dr. Yiming Zhang
Prof. Dr. Linlong Mu
Prof. Dr. Jiale Li
Guest Editors

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Keywords

composite structures
construction materials
mechanical behavior
modeling and simulations
cement-based materials strength
damage
fatigue
structural performance
machine learning

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Modeling and Analysis of Composite Materials and Structures in Civil Engineering (3rd Edition) in Materials

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Research

16 pages, 5391 KB

Open AccessArticle

Evolution Law of Contact Force Chain Network Structure of Geotechnical Granular Materials Under Unloading Stress Paths

by Gang Wei, Jinshan Tong, Luju Liang, Changfan Yu, Guohui Feng and Xinjiang Wei

Materials 2026, 19(6), 1158; https://doi.org/10.3390/ma19061158 - 16 Mar 2026

Cited by 1 | Viewed by 417

Abstract

Granular materials exhibit complex mechanical behaviors during unloading, yet the underlying micro- and meso-scale mechanisms remain unclear. This study employs a discrete element method to simulate a series of triaxial tests on sand and pebble specimens with varying initial densities under different unloading stress paths. While dense specimens demonstrate strain softening and dilatancy, loose samples exhibit shear contraction. To quantify the underlying fabric evolution, persistent homology (PH) theory is adopted to analyze the particle contact force networks. The results reveal that the average strength of this network correlates strongly with the macroscopic stress–strain response. For dense samples, network strength rapidly increases to a peak coinciding with the deviatoric stress maximum, then gradually decreases with further shear. Crucially, this evolution is path-dependent: the average contact force network strength increases approximately 20% more during unloading in the minor principal stress direction compared to unloading in the major principal stress direction. This quantitative analysis of force chain degradation provides a mechanistic explanation for the observed strain softening, highlighting the dominant role of the unloading stress path. In contrast, loose specimens, which initially lack an obvious force chain network, show negligible microstructural evolution during unloading. Full article

(This article belongs to the Special Issue Modeling and Analysis of Composite Materials and Structures in Civil Engineering (Second Edition))

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30 pages, 10659 KB

Open AccessArticle

Performance Analysis of Artificial Neural Network and Its Optimized Models on Compressive Strength Prediction of Recycled Cement Mortar

by Lin-Bin Li, Guang-Ji Yin, Jing-Jing Shao, Ling Miao, Yu-Jie Lang, Jia-Jia Zhu and Shan-Shan Cheng

Materials 2025, 18(24), 5694; https://doi.org/10.3390/ma18245694 - 18 Dec 2025

Cited by 1 | Viewed by 713

Abstract

In the background of sustainable development in the construction industry, recycled cement mortar (RCM) has emerged as a research hotspot due to its eco-friendly features, where mechanical properties serve as critical indicators for evaluating its engineering applicability. This study proposes an artificial neural network (ANN) model optimized by intelligent algorithms, including the GWO (grey wolf optimizer), PSO (particle swarm optimization), and a GA (genetic algorithm), to predict the compressive strength of recycled mortar. By integrating experimental and prediction data, we establish a comprehensive database with eight input variables, including the water–cement ratio (W/C), cement–sand ratio (C/S), fly ash content (FA), aggregate replacement rate (ARR), and curing age. The predictive performance of neural network models with different database sizes (database 1: experimental data of RCM; database 2: experimental data of RCM and ordinary mortar; database 3: model prediction data of RCM, experimental data of RCM, and ordinary mortar) is analyzed. The results show that the intelligent optimization algorithms significantly enhance the predictive performance of the ANN model. Among them, the PSO-ANN model demonstrates optimal performance, with R² = 0.92, MSE = 0.007, and MAE = 0.0632, followed by the GA-ANN model and the GWO-ANN model. SHAP analysis reveals that the W/C, C/S, and curing age are the key variables influencing the compression strength. Furthermore, the size of the dataset does not significantly influence the computation time for the above models but is primarily governed by the complexity of the optimization algorithms. This study provides an efficient data-driven method for the mix design of RCM and a theoretical support for its engineering applications. Full article

(This article belongs to the Special Issue Modeling and Analysis of Composite Materials and Structures in Civil Engineering (Second Edition))

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10 pages, 2164 KB

Open AccessArticle

3D Printed Beam with Optimized Internal Structure—Experimental and Numerical Approach

by David Juracka, Petr Lehner, Marek Kawulok, David Bujdos and Martin Krejsa

Materials 2025, 18(24), 5512; https://doi.org/10.3390/ma18245512 - 8 Dec 2025

Viewed by 720

Abstract

This article compares the results of numerical and experimental analysis of the mechanical properties of an optimized 3D-printed beam. The samples were subjected to a four-point bending test, and corresponding numerical models were created at the same time. The beams were printed using 3D printing and their weight was reduced by using an internal spatial grid with variable thickness that gradually increases towards the outer walls. This approach allows for effective optimization of material strength while minimizing raw material consumption during production. One of the key findings is the determination of the ultimate strength between fibers, the mode of failure, and the high agreement between the experimental results and the numerical model using the finite element method. The optimized beam achieved nearly 60% weight reduction while maintaining comparable load-bearing capacity. The knowledge gained opens up new possibilities in the field of materials engineering and also makes a significant contribution to the methodology of developing and optimizing these structures using 3D printing technology. Full article

(This article belongs to the Special Issue Modeling and Analysis of Composite Materials and Structures in Civil Engineering (Second Edition))

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17 pages, 6277 KB

Open AccessArticle

Study on Sulfate Migration Behavior of Potassium Magnesium Phosphate Cement Slurry Based on Electro-Pulse-Accelerated Corrosion

by De Xu, Qing Yang, Jianming Yang and Xuexing Hu

Materials 2025, 18(22), 5158; https://doi.org/10.3390/ma18225158 - 13 Nov 2025

Viewed by 560

Abstract

By accelerating the migration of sulfate ions in potassium magnesium phosphate cement (PMPC) paste through an electric field, its sulfate resistance can be quickly evaluated, thereby making up for the defect of long test cycles in existing evaluation methods. Through sulfate concentration analysis, strength tests, microanalysis and theoretical analysis, this paper investigated the SO₄²⁻ migration behavior of PMPC specimens subjected to electro-pulse-accelerated corrosion. The conclusions are as follows: the distribution of SO₄²⁻ concentration c (x, t) in PMPC specimens followed a polynomial pattern with corrosion period t. The surface SO₄²⁻ concentration c (0, t), measured SO₄²⁻ migration depth h₀, and c (x, t) of specimens increased with the t. After 56 days, the c (0, 56 days) and h₀ of the PN containing nickel slag powder and the PS containing silica fume were lower than that of the reference P0. Their calculated SO₄²⁻ migration depth h₀₀ and SO₄²⁻ migration coefficient D were smaller than that of P0. The h₀₀ and D could be estimated based on t due to a logarithmic relationship between t and h₀₀, D. The strength of specimens at the pulse cathode end gradually improved with t. The 56-day strength for P0, PN, and PS specimens increased by 7.14%, 7.94%, and 8.42%, respectively. The research findings provided a theoretical foundation for the application and quality evaluation of PMPC-based material. Full article

(This article belongs to the Special Issue Modeling and Analysis of Composite Materials and Structures in Civil Engineering (Second Edition))

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16 pages, 2829 KB

Open AccessArticle

Axial Compression Behavior of Bamboo Scrimber-Filled Steel Tubular (BSFST) Column Under Different Loading Modes

by Ze Xing, Yang Wei, Kang Zhao, Jinwei Lu, Baoxing Wei and Yu Lin

Materials 2025, 18(15), 3607; https://doi.org/10.3390/ma18153607 - 31 Jul 2025

Viewed by 989

Abstract

Bamboo scrimber is an environmentally friendly biomass building material with excellent mechanical properties. However, it is susceptible to delamination failure of the transverse fibers under compression, which limits its structural performance. To address this problem, this study utilizes steel tubes to encase bamboo scrimber, forming a novel bamboo scrimber-filled steel tubular column. This configuration enables the steel tube to provide effective lateral restraint to the bamboo material. Axial compression tests were conducted on 18 specimens, including bamboo scrimber columns and bamboo scrimber-filled steel tubular columns, to investigate the effects of steel ratio and loading mode (full-section and core loading) on the axial compression performance. The test results indicate that the external steel tubes significantly enhance the structural load-bearing capacity and deformation capacity. Primary failure modes of the composite columns include shear failure and buckling. The ultimate stress and strain of the structure are positively correlated with the steel ratio; as the steel ratio increases, the ultimate stress of the specimens can increase by up to 19.2%, while the ultimate strain can increase by up to 37.7%. The core-loading specimens exhibited superior load-bearing capacity and deformation ability compared to the full-section-loading specimens. Considering the differences in the curves for full-section and core loading, the steel tube confinement coefficient was introduced, and the predictive models for the ultimate stress and ultimate strain of the bamboo scrimber-filled steel tubular column were developed with accurate prediction. Full article

(This article belongs to the Special Issue Modeling and Analysis of Composite Materials and Structures in Civil Engineering (Second Edition))

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19 pages, 3568 KB

Open AccessArticle

Research on the Pavement Performance of Slag/Fly Ash-Based Geopolymer-Stabilized Soil

by Chenyang Yang, Yan Jiang, Zhiyun Li, Yibin Huang and Jinchao Yue

Materials 2025, 18(13), 3173; https://doi.org/10.3390/ma18133173 - 4 Jul 2025

Cited by 3 | Viewed by 1776

Abstract

The road construction sector urgently requires environmentally friendly, low-carbon, and high-performance base materials. Traditional materials exhibit issues of high energy consumption and carbon emissions, making it difficult for them to align with sustainable development requirements. While slag- and fly ash-based geopolymers demonstrate promising application potential in civil engineering, research on their application in road-stabilized soils remains insufficient. To address the high energy consumption and carbon emissions associated with conventional road base materials and to fill this research gap, this study investigated the utilization of industrial solid wastes through slag-based geopolymer and fly ash as stabilizers, systematically evaluating the pavement performance of two distinct soil types. Unconfined compressive strength tests and freeze–thaw cycling tests were conducted to elucidate the effects of stabilizer dosage, fly ash co-stabilization, and compaction degree on mechanical properties. The results demonstrated that the compressive strength of both stabilized soils increased significantly with higher slag-based geopolymer content, achieving peak values of 5.2 MPa (soil sample 1) and 4.5 MPa (soil sample 2), representing a 30% improvement over cement-stabilized soils with identical mix proportions. Fly ash co-stabilization exhibited more pronounced reinforcement effects on soil sample 2. At a 98% compaction degree, soil sample 1 maintained a stable 50% strength enhancement, whereas soil sample 2 displayed a dose-dependent exponential strength increase. Freeze–thaw resistance tests revealed the superior performance of soil sample 1, showing a loss of compressive strength (BDR) of 78% with 8% geopolymer stabilization alone, which improved to 90% after fly ash co-stabilization. For soil sample 2, the BDR increased from 64% to 80% through composite stabilization. This study confirms that slag/fly ash-based geopolymer-stabilized soils not only meet the strength requirements for heavy-traffic subbases and light-traffic base courses, but also demonstrates its great potential as a low-carbon and environmentally friendly material to replace traditional road base materials. Full article

(This article belongs to the Special Issue Modeling and Analysis of Composite Materials and Structures in Civil Engineering (Second Edition))

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17 pages, 3903 KB

Open AccessArticle

Innovative Cross-Shaped SRC Column–RC Slab Connection: Experimental Investigation and Finite Element Analysis of Punching Shear Behavior

by Wei Zhang, Jianyang Xue, Jinjun Xu and Baoxin Li

Materials 2025, 18(13), 3159; https://doi.org/10.3390/ma18133159 - 3 Jul 2025

Cited by 1 | Viewed by 944

Abstract

Flat slab structures are extensively utilized in modern construction owing to their efficient load transfer mechanisms and optimized space utilization. Nevertheless, the persistent issue of brittle punching shear failure at connection zones continues to pose significant engineering challenges. This study proposes an innovative cross-shaped steel-reinforced concrete (SRC) column–slab connection. Through combining test and numerical analyses, the failure mechanisms and performance control principles are systematically analyzed. A refined finite element model incorporating material nonlinearity, geometric characteristics, and interface effects is developed, demonstrating less than 3% error upon test validation. Using the validated model, the influence of key parameters—including concrete strength (C30–C60), reinforcement ratio (ρ = 0.65–1.77%), shear span–depth ratio (λ = 3–6), and limb height-to-thickness ratio (c₁/c₂ = 2–4)—on the punching shear behavior is thoroughly investigated. The results demonstrate that increasing concrete strength synergistically improves both punching shear capacity (by up to 49%) and ductility (by 33%). A critical reinforcement ratio threshold (0.8–1.2%) is identified. When exceeding this range, the punching shear capacity increases by 12%, but reduces ductility by 34%. Additionally, adjusting the shear span–depth ratio enables controlled failure mode transitions and a 24% reduction in punching shear capacity, as well as a 133% increase in displacement capacity. These results offer theoretical support for the design and promotion of this novel structural system. Full article

(This article belongs to the Special Issue Modeling and Analysis of Composite Materials and Structures in Civil Engineering (Second Edition))

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15 pages, 1882 KB

Open AccessArticle

Predicting Rheological Properties of Asphalt Modified with Mineral Powder: Bagging, Boosting, and Stacking vs. Single Machine Learning Models

by Haibing Huang, Zujie Xu, Xiaoliang Li, Bin Liu, Xiangyang Fan, Haonan Ding and Wen Xu

Materials 2025, 18(12), 2913; https://doi.org/10.3390/ma18122913 - 19 Jun 2025

Cited by 1 | Viewed by 1241

Abstract

This study systematically compares the predictive performance of single machine learning (ML) models (KNN, Bayesian ridge regression, decision tree) and ensemble learning methods (bagging, boosting, stacking) for quantifying the rheological properties of mineral powder-modified asphalt, specifically the complex shear modulus (G*) and the phase angle (δ). We used two emulsifiers and three mineral powders for fabricating modified emulsified asphalt and conducting rheological property tests, respectively. Dynamic shear rheometer (DSR) test data were preprocessed using the local outlier factor (LOF) algorithm, followed by K-fold cross-validation (K = 5) and Bayesian optimization to tune model hyperparameters. This framework uniquely employs cross-validated predictions from base models as input features for the meta-learner, reducing information leakage and enhancing generalization. Traditional single ML models struggle to characterize accurately as a result, and an innovative stacking model was developed, integrating predictions from four heterogeneous base learners—KNN, decision tree (DT), random forest (RF), and XGBoost—with a Bayesian ridge regression meta-learner. Results demonstrate that ensemble models outperform single models significantly, with the stacking model achieving the highest accuracy (R² = 0.9727 for G* and R² = 0.9990 for δ). Shapley additive explanations (SHAP) analysis reveals temperature and mineral powder type as key factors, addressing the “black box” limitation of ML in materials science. This study validates the stacking model as a robust framework for optimizing asphalt mixture design, offering insights into material selection and pavement performance improvement. Full article

(This article belongs to the Special Issue Modeling and Analysis of Composite Materials and Structures in Civil Engineering (Second Edition))

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25 pages, 11740 KB

Open AccessArticle

Effects of Stress States and Joint Configurations on Dynamic Mechanical Properties of Rock Masses

by Tingting Liu, Zi Wang, Xuyi Wang, Shenghao Yang, Wenxu Huang and Luyang Ding

Materials 2025, 18(8), 1699; https://doi.org/10.3390/ma18081699 - 9 Apr 2025

Cited by 2 | Viewed by 1292

Abstract

In complex geological environments, the discontinuous dynamic response behavior of jointed rock masses under the coupled effects of in situ stress and transient dynamic disturbances significantly exacerbates the risk of surrounding rock instability. This study establishes three-dimensional numerical models of various jointed rocks under uniaxial–biaxial–triaxial split Hopkinson pressure bar (SHPB) experimental systems through the coupling of the finite difference method (FDM) and discrete element method (DEM). The models adhere to the one-dimensional stress wave propagation assumption and satisfy the dynamic stress equilibrium requirements, demonstrating dynamic mechanical responses consistent with physical experiments. The results reveal that the synergistic–competitive effects between joint configuration and initial pre-compression jointly dominate the dynamic mechanical response of rocks. Multiaxial pre-compression promotes the development of secondary force chain networks, enhances rock impact resistance through multi-path stress transfer mechanisms, significantly improves strain energy storage density during peak stages, and drives failure modes to evolve from macroscopic through-going fractures to localized crushing zones. The spatial heterogeneity of joint configurations induces anisotropic characteristics in principal stress fabric. Single joint systems maintain structural integrity due to restricted weak plane propagation, while cross/parallel joints exhibit geometrically induced synergistic propagation effects, forming differentiated crack propagation paths that intensify frictional and kinetic energy dissipation. Through cross-scale numerical model comparisons, the evolution of force chain fabric, particle displacement distribution, microcrack propagation, and energy dissipation mechanisms were analyzed, unveiling the synergistic regulatory effects of the stress state and joint configuration on the rock dynamic response. This provides a theoretical basis for impact-resistant structure optimization and dynamic instability early warning in deep engineering projects involving jointed surrounding rock. Full article

(This article belongs to the Special Issue Modeling and Analysis of Composite Materials and Structures in Civil Engineering (Second Edition))

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20 pages, 9128 KB

Open AccessArticle

Modeling of Electrical Heating and Cooling for Carbon Textile Reinforced Concrete

by Annette Dahlhoff and Michael Raupach

Materials 2025, 18(5), 1078; https://doi.org/10.3390/ma18051078 - 27 Feb 2025

Viewed by 1157

Abstract

Carbon-textile-reinforced concrete (CTRC) is increasingly being used in the construction industry as a high-performance composite material combining non-metallic textile reinforcement with concrete. Known for its exceptional characteristics such as tensile strength, density, and durability, CTRC also exhibits electrical conductivity, enabling efficient electrical heat generation within building components. This study develops and validates a thermal model to predict the temperature evolution of electrically heated CTRC, incorporating Newton’s law of cooling and Joule’s heating principle. The proposed model segments the temperature development into three distinct phases: heating, constant, and cooling. The temperature calculation accounts for these phases, their boundary conditions, and material-specific parameters, which were determined through laboratory experiments. For the investigated CTRC material combinations, the model accurately predicts temperature profiles, demonstrating strong agreement between experimental and calculated results. Moreover, significant variations in electrical power requirements were observed among the tested materials. The investigated impregnation materials of the carbon textile reinforcement (CTR) significantly influence contact quality and resulting temperature behavior. This research bridges material science and thermal performance, expanding the potential for CTRC use in electrically heated construction solutions. Full article

(This article belongs to the Special Issue Modeling and Analysis of Composite Materials and Structures in Civil Engineering (Second Edition))

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16 pages, 21224 KB

Open AccessArticle

Dynamic Responses and Crack Propagation of Rock with Crossed Viscoelastic Joints Under Blasting Loads

by Chengyang Li, Dongju Jiang, Jinhai Zhao, Tuo Zhang and Renfei Kuang

Materials 2025, 18(3), 548; https://doi.org/10.3390/ma18030548 - 25 Jan 2025

Cited by 5 | Viewed by 1398

Abstract

To investigate the propagation of stress waves in viscoelastic joints under blasting loads, and their impact on crack propagation and dynamic response in rock masses, a numerical model incorporating intersecting viscoelastic joints was developed using LS-DYNA. This study focuses on the influence of various joint geometric parameters, including thickness and angle, on stress wave propagation and damage patterns in rock. The Riedel–Hiermaier–Thoma (RHT) model was employed to simulate the dynamic behavior of rock, while the Poynting–Thomson model was used to describe the viscoelastic properties of the joint fillings. The simulation results provide detailed insights into the principal stress, displacement, and particle vibration velocity around the joints. Based on the stress wave propagation theory, the velocity transmission coefficients were calculated to quantify the attenuation of stress waves across the joints. The findings demonstrate that viscoelastic joint properties significantly affect the damage patterns in the rock mass. Specifically, the area of the crushed zone and the width of cracks on the blasting side are proportional to joint thickness, while crack propagation at the joint tips is governed by differences in principal stress. Moreover, the propagation of vibration velocity is notably weakened at the second joint, highlighting the critical role played by joint characteristics in stress wave dynamics. These results underscore the complex interaction between joint properties and stress wave behavior in rock masses, providing valuable insights for optimizing blasting designs and improving the safety of underground engineering projects. Full article

(This article belongs to the Special Issue Modeling and Analysis of Composite Materials and Structures in Civil Engineering (Second Edition))

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