Development of a Computer Automated Solution for Steady-State Structural Mechanics Problems

In engineering and scientific research, there is a growing demand for efficient solutions to steady-state structural mechanics problems. This study first reviews the design strategies and recent research advances in multistable mechanical metamaterials. Then, this study establishes the theoretical foundation for the solution, including finite element methods, topology optimization theory, the description of nonlinear mechanical behavior, and stability analysis. Subsequently, this paper develops a modular computer-aided design automation framework, including a user interface layer, core solver, data management module, etc. The experimental results show that the automation solution outperforms traditional methods in key performance indicators such as efficiency, resource utilization, and throughput, with a maximum efficiency of 99.2%, achieving an automated design process with high efficiency, high stability, and low error rate.

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Publication Details

Journal
Procedia Computer Science
Published
2025-01-01
DOI
https://doi.org/10.1016/j.procs.2025.05.066
Primary Topic
Electric Power Systems and Control
Type
article
Field-Weighted Citation Impact
0.00
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article

Development of a Computer Automated Solution for Steady-State Structural Mechanics Problems

Jing Zhang, Sha Liu, Jianye Su, Zhenyu Cai
Procedia Computer Science
Electric Power Systems and Control
article

Development of a Computer Automated Solution for Steady-State Structural Mechanics Problems

Jing Zhang, Sha Liu, Jianye Su, Zhenyu Cai
article en

Abstract

In engineering and scientific research, there is a growing demand for efficient solutions to steady-state structural mechanics problems. This study first reviews the design strategies and recent research advances in multistable mechanical metamaterials. Then, this study establishes the theoretical foundation for the solution, including finite element methods, topology optimization theory, the description of nonlinear mechanical behavior, and stability analysis. Subsequently, this paper develops a modular computer-aided design automation framework, including a user interface layer, core solver, data management module, etc. The experimental results show that the automation solution outperforms traditional methods in key performance indicators such as efficiency, resource utilization, and throughput, with a maximum efficiency of 99.2%, achieving an automated design process with high efficiency, high stability, and low error rate.

Procedia Computer ScienceVol. 262
Dalian University of Technology (CN)
Openalex Percentile: Top 89%
Electric Power Systems and Control
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