Special Issues
Table of Content

Computing Technology in the Design and Manufacturing of Advanced Materials

Submission Deadline: 31 August 2025 (closed) View: 4138 Submit to Journal

Guest Editors

Assoc. Prof. Chenglong Guan

Email: guancl@fzu.edu.cn

Affiliation: School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, 350108, China

Homepage:

Research Interests: Multi-physics simulation, Structural-functional integrated design, Curing process of CFRP

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Prof. Lihua Zhan

Email: yjs-cast@csu.edu.cn

Affiliation: Light Alloys Research Institute, Central South University, Changsha, 410083, China

Homepage:

Research Interests: Deformation-performance synergetic manufacturing

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Lec. Youliang Yang

Email: yangyouliang@csu.edu.cn

Affiliation: Light Alloys Research Institute, Central South University, Changsha, 410083, China

Homepage:

Research Interests: Materials modelling

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Postdoc. Ziyao Ma

Email: maziyao@pku.edu.cn

Affiliation: College of Engineering, Peking University, Beijing, 100871, China.

Research Interests: Crystal plasticity, Discrete dislocation dynamics, Cross-scale modelling

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Prof. Bing Wang

Email: b.wang@fzu.edu.cn

Affiliation: School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, 350108, China.

Homepage:

Research Interests: Smart composites, Structural mechanics, Non-destructive testing and evaluation

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Summary

With the trend toward high-performance, lightweight, large-scale, and integrated aerospace components, higher demands are being placed on material systems. Lightweight and high-strength materials, such as aluminum alloys, magnesium alloys, and composite materials, not only offer low density, high strength, and high stiffness but also possess excellent corrosion and wear resistance. Their widespread application is the key to reducing the weight and increasing the payload of aerospace vehicles.


With the advancement of computer technology, computational materials science is becoming an important branch in the field of materials research. It not only addresses the challenges posed by the increasing size and complexity of components, such as high experimental difficulty and cost but also provides guidance through efficient simulation analysis for structural design and process optimization.


Therefore, this special issue focuses on the application of computational materials science in the design and manufacturing of advanced materials (such as aluminum alloys, magnesium alloys, composite materials, etc.).


The following subtopics are the particular interests of this special issue, including but not limited to:

1. Cross-scale modeling of materials.

2. Crystal plasticity modeling of materials.

3. Finite element analysis of multiple physical fields.

4. Structural-functional integrated design.

5. Structural multiscale characterization.

6. Structural health monitoring and prediction.


Keywords

Advanced materials; Cross-scale modelling; Multiphysics calculation; Multiscale characterisation; Health prediction

Published Papers


  • Open Access

    ARTICLE

    Calibration of Elastic-Plastic Degradation Model for 40Cr Steel Applied in Finite Element Simulation of Shear Pins of Friction Pendulum Bearings

    Mianyue Yang, Huasheng Sun, Weigao Sheng
    CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 2749-2761, 2025, DOI:10.32604/cmc.2025.068009
    (This article belongs to the Special Issue: Computing Technology in the Design and Manufacturing of Advanced Materials)
    Abstract The shear pin of the friction pendulum bearing (FPB) can be made of 40Cr steel. In conceptual design, the optimal cut-off point of the shear pin is predetermined, guiding the design of bridges isolated by FPBs to maximize their isolation performance. Current researches on the shear pins are mainly based on linear elastic models, neglecting their plasticity, damage, and fracture mechanical properties. To accurately predict its cutoff behavior, the elastic-plastic degradation model of 40Cr steel is indeed calibrated. For this purpose, the Ramberg-Osgood model, the Bao-Wierzbicki damage initiation criterion, and the linear damage evolution criterion… More >

  • Open Access

    ARTICLE

    Fatigue Life Prediction of Composite Materials Based on BO-CNN-BiLSTM Model and Ultrasonic Guided Waves

    Mengke Ding, Jun Li, Dongyue Gao, Guotai Zhou, Borui Wang, Zhanjun Wu
    CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 597-612, 2025, DOI:10.32604/cmc.2025.067907
    (This article belongs to the Special Issue: Computing Technology in the Design and Manufacturing of Advanced Materials)
    Abstract Throughout the composite structure’s lifespan, it is subject to a range of environmental factors, including loads, vibrations, and conditions involving heat and humidity. These factors have the potential to compromise the integrity of the structure. The estimation of the fatigue life of composite materials is imperative for ensuring the structural integrity of these materials. In this study, a methodology is proposed for predicting the fatigue life of composites that integrates ultrasonic guided waves and machine learning modeling. The method first screens the ultrasonic guided wave signal features that are significantly affected by fatigue damage. Subsequently,… More >

  • Open Access

    ARTICLE

    Application of Various Optimisation Methods in the Multi-Optimisation for Tribological Properties of Al–B4C Composites

    Sandra Gajević, Slavica Miladinović, Jelena Jovanović, Onur Güler, Serdar Özkaya, Blaža Stojanović
    CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 4341-4361, 2025, DOI:10.32604/cmc.2025.065645
    (This article belongs to the Special Issue: Computing Technology in the Design and Manufacturing of Advanced Materials)
    Abstract This paper presents an investigation of the tribological performance of AA2024–B4C composites, with a specific focus on the influence of reinforcement and processing parameters. In this study three input parameters were varied: B4C weight percentage, milling time, and normal load, to evaluate their effects on two output parameters: wear loss and the coefficient of friction. AA2024 alloy was used as the matrix alloy, while B4C particles were used as reinforcement. Due to the high hardness and wear resistance of B4C, the optimized composite shows strong potential for use in aerospace structural elements and automotive brake components. The… More >

  • Open Access

    ARTICLE

    Physics-Informed Gaussian Process Regression with Bayesian Optimization for Laser Welding Quality Control in Coaxial Laser Diodes

    Ziyang Wang, Lian Duan, Lei Kuang, Haibo Zhou, Ji’an Duan
    CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2587-2604, 2025, DOI:10.32604/cmc.2025.065648
    (This article belongs to the Special Issue: Computing Technology in the Design and Manufacturing of Advanced Materials)
    Abstract The packaging quality of coaxial laser diodes (CLDs) plays a pivotal role in determining their optical performance and long-term reliability. As the core packaging process, high-precision laser welding requires precise control of process parameters to suppress optical power loss. However, the complex nonlinear relationship between welding parameters and optical power loss renders traditional trial-and-error methods inefficient and imprecise. To address this challenge, a physics-informed (PI) and data-driven collaboration approach for welding parameter optimization is proposed. First, thermal-fluid-solid coupling finite element method (FEM) was employed to quantify the sensitivity of welding parameters to physical characteristics, including… More >

  • Open Access

    ARTICLE

    Guided Wave Based Composite Structural Fatigue Damage Monitoring Utilizing the WOA-BP Neural Network

    Borui Wang, Dongyue Gao, Haiyang Gu, Mengke Ding, Zhanjun Wu
    CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 455-473, 2025, DOI:10.32604/cmc.2025.060617
    (This article belongs to the Special Issue: Computing Technology in the Design and Manufacturing of Advanced Materials)
    Abstract Fatigue damage is a primary contributor to the failure of composite structures, underscoring the critical importance of monitoring its progression to ensure structural safety. This paper introduces an innovative approach to fatigue damage monitoring in composite structures, leveraging a hybrid methodology that integrates the Whale Optimization Algorithm (WOA)-Backpropagation (BP) neural network with an ultrasonic guided wave feature selection algorithm. Initially, a network of piezoelectric ceramic sensors is employed to transmit and capture ultrasonic-guided waves, thereby establishing a signal space that correlates with the structural condition. Subsequently, the Relief-F algorithm is applied for signal feature extraction,… More >

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