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基于可视化计算数字孪生的功能工件快速成型的稳健性优化。

Robustness optimization for rapid prototyping of functional artifacts based on visualized computing digital twins.

作者信息

Xu Jinghua, Liu Kunqian, Wang Linxuan, Guo Hongshuai, Zhan Jiangtao, Liu Xiaojian, Zhang Shuyou, Tan Jianrong

机构信息

State Key Lab of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310058, China.

Key Lab of Advanced Manufacturing Technology of Zhejiang Province, Zhejiang University, Hangzhou 310058, China.

出版信息

Vis Comput Ind Biomed Art. 2023 Feb 27;6(1):4. doi: 10.1186/s42492-023-00131-w.

DOI:10.1186/s42492-023-00131-w
PMID:36847895
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9971427/
Abstract

This study presents a robustness optimization method for rapid prototyping (RP) of functional artifacts based on visualized computing digital twins (VCDT). A generalized multiobjective robustness optimization model for RP of scheme design prototype was first built, where thermal, structural, and multidisciplinary knowledge could be integrated for visualization. To implement visualized computing, the membership function of fuzzy decision-making was optimized using a genetic algorithm. Transient thermodynamic, structural statics, and flow field analyses were conducted, especially for glass fiber composite materials, which have the characteristics of high strength, corrosion resistance, temperature resistance, dimensional stability, and electrical insulation. An electrothermal experiment was performed by measuring the temperature and changes in temperature during RP. Infrared thermographs were obtained using thermal field measurements to determine the temperature distribution. A numerical analysis of a lightweight ribbed ergonomic artifact is presented to illustrate the VCDT. Moreover, manufacturability was verified based on a thermal-solid coupled finite element analysis. The physical experiment and practice proved that the proposed VCDT provided a robust design paradigm for a layered RP between the steady balance of electrothermal regulation and manufacturing efficacy under hybrid uncertainties.

摘要

本研究提出了一种基于可视化计算数字孪生（VCDT）的功能工件快速成型（RP）稳健优化方法。首先建立了方案设计原型RP的广义多目标稳健优化模型，该模型可集成热、结构和多学科知识以实现可视化。为实现可视化计算，采用遗传算法对模糊决策的隶属函数进行优化。进行了瞬态热力学、结构静力学和流场分析，特别是针对具有高强度、耐腐蚀、耐高温、尺寸稳定性和电绝缘特性的玻璃纤维复合材料。通过测量RP过程中的温度及温度变化进行了电热实验。利用热场测量获得红外热像图以确定温度分布。给出了一个轻质带肋人体工程学工件的数值分析以说明VCDT。此外，基于热固耦合有限元分析验证了可制造性。物理实验和实践证明，所提出的VCDT为混合不确定性下电热调节与制造效率的稳定平衡之间的分层RP提供了一种稳健的设计范式。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9505/9971427/4d6995e7b984/42492_2023_131_Fig14_HTML.jpg
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