Strength-constrainted Topology Optimization Based on Additive Manufacturing Anisotropy

被引:0
|
作者
He Z. [1 ]
Yang D. [1 ]
Jiang C. [1 ]
Wu Y. [1 ]
Jiang H. [1 ]
机构
[1] State Key Laboratory of Advanced Design and Manufacture for Vehicle Body, Hunan University, Changsha
关键词
additive manufacturing; anisotropic failure strength; bi-directional evolutionary structural optimization(BESO); topology optimization; Tsai-Hill failure coefficient;
D O I
10.3969/j.issn.1004-132X.2022.19.012
中图分类号
学科分类号
摘要
The particularity of additive manufacturing processes leds to the fact that the manufacturing structure exhibited anisotropic mechanics properties. In order to meet the more stringent structural strength design requirements, atopology optimization strategy considering anisotropic strength constraints was proposed based on bi-directional evolutionary structural optimization. The anisotropic Tsai-Hill failure coefficient evaluating additive structural strength was derived, and an objective function containing the constraint of failure coefficient was established by the scale factor. The sensitivity numbers were analyzed in detail, moreover, numerical methods such as sensitivity normalization were used to stabilize the optimization processes. It shows that the proposed method effectively suppresses the high failure risk area, thus, ensures the structural strength, and may obtain better results than that of von-Mesis stress-dependent design under material anisotropic strength assumption. In addition, the optimization results are deeply rely on the variation of anisotropy and the material stacking angle parameters, therefore reasonable tuning will help to optimize structural properties. © 2022 China Mechanical Engineering Magazine Office. All rights reserved.
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页码:2372 / 2380and2393
相关论文
共 29 条
  • [1] ZHU J H, ZHANG W H, XIA L., Topology Optimization in Aircraft and Aerospace Structures Design, Archives of Computational Methods in Engineering, 23, pp. 595-622, (2016)
  • [2] LU Bingheng, Additive Manufacturing-Current Situation and Future, China Mechanical Engineer-ing, 31, 1, pp. 19-23, (2020)
  • [3] MENG L, ZHANG W, QUAN D, Et al., From Topology Optimization Design to Additive Manufacturing: Today's Success and Tomorrow's Roadmap, Archives of Computational Methods in Engineering, 27, pp. 805-830, (2020)
  • [4] ZHU Jihong, ZHOU Han, WANG Chuang, Et al., Status and Future of Topology Optimization for Additive Manufacturing, Aeronautical Manufacturing Technology, 63, 10, pp. 24-38, (2020)
  • [5] YANG K K, ZHU J H, WANG C, Et al., Experimental Validation of 3D Printed Material Behaviors and Their Influence on the Structural Topology Design, Computational Mechanics, 61, pp. 581-598, (2018)
  • [6] ZHU Y Y, TIAN X J, LI J, Et al., The Anisotropy of Laser Melting Deposition Additive Manufacturing Ti-6.5Al-3.5Mo-1.5Zr-0.3Si Titanium Alloy, Materials & Design, 67, pp. 538-542, (2015)
  • [7] ZHANG Anfeng, ZHANG Jinzhi, ZHANG Xiaoxing, Et al., Research Progress in Tissue Regulation and Anisotropy of High-performance Titanium Alloy by Laser Additive Manufacturing, Journal of Netshape Forming Engineering, 11, 4, pp. 1-8, (2019)
  • [8] YANG R J, Chen C J., Stress-based Topology Optimization, Structural and Multidisciplinary Optimization, 12, 2, pp. 98-105, (1996)
  • [9] DUYSINX P, BENDSOE M P., Topology Optimization of Continuum Structures with Local Stress Constraints, International Journal for Numerical Methods in Engineering, 43, pp. 1453-1478, (1998)
  • [10] CHENG G D, GUO X., ε-Relaxed Approach in Structural Topology Optimization, Structural Optimization, 13, 4, pp. 258-266, (1997)