Guest Editors
Prof. Xujiang Chao
Email: xchao_me@nwpu.edu.cn
Affiliation: School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an, China
Homepage:
Research Interests: computational mechanics; mechanical metamaterials data-driven & ML
Prof. Wenlong Tian
Email: tianwenlong_me@nwpu.edu.cn
Affiliation: School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an, China
Homepage:
Research Interests: thermal conductivity; composites; numerical simulation; mechanical properties
Prof. Peng Wang
Email: wangpeng0919@dhu.edu.cn
Affiliation: College of Textiles, Donghua University, Shanghai, 201620, China
Homepage:
Research Interests: mechanical metamaterials; impact dynamics; textile composites
Dr. Jian Ge
Email: gejian@mail.nwpu.edu.cn
Affiliation: School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an, China
Homepage:
Research Interests: multiscale simulation; composites; homogenization methods; mechanical properties
Summary
Advanced materials and structures, such as composites, metamaterials, and multifunctional alloys, are increasingly critical in modern engineering applications, ranging from aerospace and energy systems to biomedical devices. However, their complex mechanical behaviorsgoverned by multiscale interactions, nonlinear thermoelasticity, and progressive damage mechanismspose significant challenges for accurate modeling and prediction. Traditional computational mechanics approaches, including molecular dynamics, finite element methods, and representative volume element (RVE) modeling, have provided foundational insights but often face limitations in efficiency or scalability when addressing multiphysics coupling or large-scale structural responses. Recent advances in data-driven techniques, high-performance computing, and multiscale simulation frameworks offer transformative opportunities to overcome these barriers, enabling precise predictions of material properties and failure mechanisms while accelerating the design of optimized microstructures.
This Special Issue seeks cutting-edge research on computational mechanics methodologies for advanced materials and structures, with emphasis on theoretical innovations, numerical algorithms, and machine learning-enhanced simulations. Topics of interest include but are not limited to: molecular dynamics for defect evolution, multiscale finite element modeling, RVE generation and homogenization techniques, thermo-mechanical property prediction, and damage/fracture behavior analysis. We welcome contributions integrating computational approaches with experimental validation, as well as studies leveraging AI/ML for surrogate modeling, inverse design, or uncertainty quantification. By bridging gaps across scales and disciplines, this issue aims to advance the frontier of computational mechanics for next-generation materials and their engineering applications.
Keywords
computational mechanics, advanced materials, multiscale modelling, representative volume element (RVE), damage mechanics, data-driven simulation
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