Research article Special Issues

A polygonal topology optimization method based on the alternating active-phase algorithm

  • Received: 28 October 2023 Revised: 17 December 2023 Accepted: 21 December 2023 Published: 29 January 2024
  • We propose a polygonal topology optimization method combined with the alternating active-phase algorithm to address the multi-material problems. During the process of topology optimization, the polygonal elements generated by signed distance functions are utilized to discretize the structural design domain. The volume fraction of each material is considered as a design variable and mapped to its corresponding element variable through a filtering matrix. This method is used to solve a multi-material structural topology optimization problem of minimizing compliance, in which a descriptive model is established by using the alternating active-phase algorithm and the solid isotropic microstructure with penalty theory. This method can accomplish the topology optimization of multi-material structures with complex curve boundaries, eliminate the phenomena of checkerboard patterns and a one-node connection, and avoid sensitivity filtering. In addition, this method possesses fine numerical stability and high calculation accuracy compared to the topology optimization methods that use quadrilateral elements or triangle elements. The effectiveness and feasibility of this method are demonstrated through several commonly used and representative numerical examples.

    Citation: Mingtao Cui, Wennan Cui, Wang Li, Xiaobo Wang. A polygonal topology optimization method based on the alternating active-phase algorithm[J]. Electronic Research Archive, 2024, 32(2): 1191-1226. doi: 10.3934/era.2024057

    Related Papers:

  • We propose a polygonal topology optimization method combined with the alternating active-phase algorithm to address the multi-material problems. During the process of topology optimization, the polygonal elements generated by signed distance functions are utilized to discretize the structural design domain. The volume fraction of each material is considered as a design variable and mapped to its corresponding element variable through a filtering matrix. This method is used to solve a multi-material structural topology optimization problem of minimizing compliance, in which a descriptive model is established by using the alternating active-phase algorithm and the solid isotropic microstructure with penalty theory. This method can accomplish the topology optimization of multi-material structures with complex curve boundaries, eliminate the phenomena of checkerboard patterns and a one-node connection, and avoid sensitivity filtering. In addition, this method possesses fine numerical stability and high calculation accuracy compared to the topology optimization methods that use quadrilateral elements or triangle elements. The effectiveness and feasibility of this method are demonstrated through several commonly used and representative numerical examples.



    加载中


    [1] M. P. Bendsøe, N. Kikuchi, Generating optimal topologies in structural design using a homogenization method, Comput. Methods Appl. Mech. Eng., 71 (1988), 197–224. https://doi.org/10.1016/0045-7825(88)90086-2 doi: 10.1016/0045-7825(88)90086-2
    [2] M. P. Bendsøe, O. Sigmund, Topology Optimization: Theory, Methods and Applications, Berlin, Heidelberg, New York: Springer, 2004. https://doi.org/10.1007/978-3-662-05086-6
    [3] J. D. Deaton, R. V. Grandhi, A survey of structural and multidisciplinary continuum topology optimization: post 2000, Struct. Multidiscip. Optim., 49 (2014), 1–38. https://doi.org/10.1007/s00158-013-0956-z doi: 10.1007/s00158-013-0956-z
    [4] Y. M. Xie, G. P. Steven, A simple evolutionary procedure for structural optimization, Comput. Struct., 49 (1993), 885–896. https://doi.org/10.1016/0045-7949(93)90035-C doi: 10.1016/0045-7949(93)90035-C
    [5] N. P. van Dijk, M. Langelaar, F. van Keulen, Explicit level-set-based topology optimization using an exact Heaviside function and consistent sensitivity analysis, Int. J. Numer. Methods Eng., 91 (2012), 67–97. https://doi.org/10.1002/nme.4258 doi: 10.1002/nme.4258
    [6] Z. Li, L. Wang, T. Lv, A level set driven concurrent reliability-based topology optimization (LS-CRBTO) strategy considering hybrid uncertainty inputs and damage defects updating, Comput. Methods Appl. Mech. Eng., 405 (2023), 115872. https://doi.org/10.1016/j.cma.2022.115872 doi: 10.1016/j.cma.2022.115872
    [7] Z. Li, L. Wang, Z. Luo, A feature-driven robust topology optimization strategy considering movable non-design domain and complex uncertainty, Comput. Methods Appl. Mech. Eng., 401 (2022), 115658. https://doi.org/10.1016/j.cma.2022.115658 doi: 10.1016/j.cma.2022.115658
    [8] Z. Li, L. Wang, X. Geng, A level set reliability-based topology optimization (LS-RBTO) method considering sensitivity mapping and multi-source interval uncertainties, Comput. Methods Appl. Mech. Eng., 419 (2024), 116587. https://doi.org/10.1016/j.cma.2023.116587 doi: 10.1016/j.cma.2023.116587
    [9] M. Cui, H. Chen, J. Zhou, A level-set based multi-material topology optimization method using a reaction diffusion equation, Comput.-Aided Des., 73 (2016), 41–52. https://doi.org/10.1016/j.cad.2015.12.002 doi: 10.1016/j.cad.2015.12.002
    [10] Z. Li, L. Wang, X. Geng, A double-layer mesh-driven robust topology optimization strategy for mechanical metamaterials under size uncertainty, Thin-Walled Struct., 196 (2024), 111439. https://doi.org/10.1016/j.tws.2023.111439 doi: 10.1016/j.tws.2023.111439
    [11] Z. Li, L. Wang, T. Lv, Additive manufacturing-oriented concurrent robust topology optimization considering size control, Int. J. Mech. Sci., 250 (2023), 108269. https://doi.org/10.1016/j.ijmecsci.2023.108269 doi: 10.1016/j.ijmecsci.2023.108269
    [12] L. Wang, Z. Li, K. Gu, An interval-oriented dynamic robust topology optimization (DRTO) approach for continuum structures based on the parametric level-set method (PLSM) and the equivalent static loads method (ESLM), Struct. Multidiscip. Optim., 65 (2022), 150. https://doi.org/10.1007/s00158-022-03236-7 doi: 10.1007/s00158-022-03236-7
    [13] M. Zhou, M. Xiao, Y. Zhang, J. Gao, L. Gao, Marching cubes-based isogeometric topology optimization method with parametric level set, Appl. Math. Model., 107 (2022), 275–295. https://doi.org/10.1016/j.apm.2022.02.032 doi: 10.1016/j.apm.2022.02.032
    [14] M. Cui, M. Pan, J. Wang, P. Li, A parameterized level set method for structural topology optimization based on reaction diffusion equation and fuzzy PID control algorithm, Electron. Res. Arch., 30 (2022), 2568–2599. https://doi.org/10.3934/era.2022132 doi: 10.3934/era.2022132
    [15] M. Cui, C. Luo, G. Li, M. Pan, The parameterized level set method for structural topology optimization with shape sensitivity constraint factor, Eng. Comput., 37 (2021), 855–872. https://doi.org/10.1007/s00366-019-00860-8 doi: 10.1007/s00366-019-00860-8
    [16] M. Zhou, M. Xiao, M. Huang, L. Gao, Multi-material isogeometric topology optimization in multiple NURBS patches, Adv. Eng. Software, 186 (2023), 103547. https://doi.org/10.1016/j.advengsoft.2023.103547 doi: 10.1016/j.advengsoft.2023.103547
    [17] M. Cui, W. Li, G. Li, X. Wang, The asymptotic concentration approach combined with isogeometric analysis for topology optimization of two-dimensional linear elasticity structures, Electron. Res. Arch., 31 (2023), 3848–3878. https://doi.org/10.3934/era.2023196 doi: 10.3934/era.2023196
    [18] Y. Zhong, H. Feng, H. Wang, R. Wang, W. Yu, A bionic topology optimization method with an additional displacement constraint, Electron. Res. Arch., 31 (2023), 754–769. https://doi.org/10.3934/era.2023037 doi: 10.3934/era.2023037
    [19] M. Cui, H. Chen, J. Zhou, F. Wang, A meshless method for multi-material topology optimization based on the alternating active-phase algorithm, Eng. Comput., 33 (2017), 871–884. https://doi.org/10.1007/s00366-017-0503-4 doi: 10.1007/s00366-017-0503-4
    [20] Q. Zhao, C. Fan, F. Wang, W. Qu, Topology optimization of steady-state heat conduction structures using meshless generalized finite difference method, Eng. Anal. Bound. Elem., 119 (2020), 13–24. https://doi.org/10.1016/j.enganabound.2020.07.002 doi: 10.1016/j.enganabound.2020.07.002
    [21] F. J. Bossen, P. S. Heckbert, A pliant method for anisotropic mesh generation, in Proceedings of the 5th International Meshing Roundtable, 63 (1996), 115–126.
    [22] P. O. Persson, G. Strang, A simple mesh generator in MATLAB, SIAM Rev., 46 (2004), 329–345. https://doi.org/10.1137/S0036144503429121 doi: 10.1137/S0036144503429121
    [23] E. Andreassen, A. Clausen, M. Schevenels, B. S. Lazarov, O. Sigmund, Efficient topology optimization in MATLAB using 88 lines of code, Struct. Multidiscip. Optim., 43 (2011), 1–16. https://doi.org/10.1007/s00158-010-0594-7 doi: 10.1007/s00158-010-0594-7
    [24] C. Talischi, G. H. Paulino, A. Pereira, I. F. M. Menezes, PolyMesher: a general-purpose mesh generator for polygonal elements written in Matlab, Struct. Multidiscip. Optim., 45 (2012), 309–328. https://doi.org/10.1007/s00158-011-0706-z doi: 10.1007/s00158-011-0706-z
    [25] C. Talischi, G. H. Paulino, A. Pereira, I. F. M. Menezes, PolyTop: a Matlab implementation of a general topology optimization framework using unstructured polygonal finite element meshes, Struct. Multidiscip. Optim., 45 (2012), 329–357. https://doi.org/10.1007/s00158-011-0696-x doi: 10.1007/s00158-011-0696-x
    [26] Y. X. Jie, X. D. Fu, Y. Liu, Mesh generation for FEM based on centroidal Voronoi tessellations, Math. Comput. Simul., 97 (2014), 68–79. https://doi.org/10.1016/j.matcom.2013.05.014 doi: 10.1016/j.matcom.2013.05.014
    [27] M. Bruggi, Topology optimization with mixed finite elements on regular grids, Comput. Methods Appl. Mech. Eng., 305 (2016), 133–153. https://doi.org/10.1016/j.cma.2016.03.010 doi: 10.1016/j.cma.2016.03.010
    [28] M. Otomori, T. Yamada, K. Izui, S. Nishiwaki, Matlab code for a level set-based topology optimization method using a reaction diffusion equation, Struct. Multidiscip. Optim., 51 (2015), 1159–1172. https://doi.org/10.1007/s00158-014-1190-z doi: 10.1007/s00158-014-1190-z
    [29] F. Cheng, Q. Zhao, L. Zhang, Non‑probabilistic reliability‑based multi‑material topology optimization with stress constraint, Int. J. Mech. Mater. Des., (2023), 1–23. https://doi.org/10.1007/s10999-023-09669-2 doi: 10.1007/s10999-023-09669-2
    [30] X. Li, Q. Zhao, K. Long, H. Zhang, Multi-material topology optimization of transient heat conduction structure with functional gradient constraint, Int. Commun. Heat Mass Transfer, 131 (2022), 105845. https://doi.org/10.1016/j.icheatmasstransfer.2021.105845 doi: 10.1016/j.icheatmasstransfer.2021.105845
    [31] J. Chen, Q. Zhao, L. Zhang, Multi-material topology optimization of thermo-elastic structures with stress constraint, Mathematics, 10 (2022), 1216. https://doi.org/10.3390/math10081216 doi: 10.3390/math10081216
    [32] X. Li, Q. Zhao, H. Zhang, T. Zhang, J. Chen, Robust topology optimization of periodic multi-material functionally graded structures under loading uncertainties, Comput. Model Eng. Sci., 127 (2021), 683–704. https://doi.org/10.32604/cmes.2021.015685 doi: 10.32604/cmes.2021.015685
    [33] Q. Zhao, H. Zhang, T. Zhang, Q. Hua, L. Yuan, W. Wang, An efficient strategy for non-probabilistic reliability-based multi-material topology optimization with evidence theory, Acta Mech. Solida Sin., 32 (2019), 803–821. https://doi.org/10.1007/s10338-019-00121-7 doi: 10.1007/s10338-019-00121-7
    [34] M. Cui, Y. Zhang, X. Yang, C. Luo, Multi-material proportional topology optimization based on the modified interpolation scheme, Eng. Comput., 34 (2018), 287–305. https://doi.org/10.1007/s00366-017-0540-z doi: 10.1007/s00366-017-0540-z
    [35] M. Cui, X. Yang, Y. Zhang, C. Luo, G. Li, An asymptotically concentrated method for structural topology optimization based on the SIMLF interpolation, Int. J. Numer. Methods Eng., 115 (2018), 1175–1216. https://doi.org/10.1002/nme.5840 doi: 10.1002/nme.5840
    [36] M. Cui, P. Li, J. Wang, T. Gao, M. Pan, An improved optimality criterion combined with density filtering method for structural topology optimization, Eng. Optim., 55 (2023), 416–433. https://doi.org/10.1080/0305215X.2021.2010728 doi: 10.1080/0305215X.2021.2010728
    [37] M. P. Bendsøe, O. Sigmund, Material interpolation schemes in topology optimization, Arch. Appl. Mech., 69 (1999), 635–654. https://doi.org/10.1007/s004190050248 doi: 10.1007/s004190050248
    [38] O. Sigmund, Design of multiphysics actuators using topology optimization—Part Ⅱ: Two-material structures, Comput. Methods Appl. Mech. Eng., 190 (2001), 6605–6627. https://doi.org/10.1016/S0045-7825(01)00252-3 doi: 10.1016/S0045-7825(01)00252-3
    [39] T. Gao, W. H. Zhang, A mass constraint formulation for structural topology optimization with multiphase materials, Int. J. Numer. Methods Eng., 88 (2011), 774–796. https://doi.org/10.1002/nme.3197 doi: 10.1002/nme.3197
    [40] M. J. Buehler, B. Bettig, G. G. Parker, Topology optimization of smart structures using a homogenization approach, J. Intell. Mater. Syst. Struct., 15 (2004), 655–667. https://doi.org/10.1177/1045389X04043944 doi: 10.1177/1045389X04043944
    [41] Z. Luo, W. Gao, C. Song, Design of multi-phase piezoelectric actuators, J. Intell. Mater. Syst. Struct., 21 (2010), 1851–1865. https://doi.org/10.1177/1045389X10389345 doi: 10.1177/1045389X10389345
    [42] Z. Kang, L. Y. Tong, Integrated optimization of material layout and control voltage for piezoelectric laminated plates, J. Intell. Mater. Syst. Struct., 19 (2008), 889–904. https://doi.org/10.1177/1045389X07084527 doi: 10.1177/1045389X07084527
    [43] C. F. Hvejsel, E. Lund, Material interpolation schemes for unified topology and multi-material optimization, Struct. Multidiscip. Optim., 43 (2011), 811–825. https://doi.org/10.1007/s00158-011-0625-z doi: 10.1007/s00158-011-0625-z
    [44] R. Tavakoli, S. M. Mohseni, Alternating active-phase algorithm for multimaterial topology optimization problems: a 115-line MATLAB implementation, Struct. Multidiscip. Optim., 49 (2014), 621–642. https://doi.org/10.1007/s00158-013-0999-1 doi: 10.1007/s00158-013-0999-1
    [45] S. Zhou, M. Y. Wang, Multimaterial structural topology optimization with a generalized Cahn-Hilliard model of multiphase transition, Struct. Multidiscip. Optim., 33 (2007), 89–111. https://doi.org/10.1007/s00158-006-0035-9 doi: 10.1007/s00158-006-0035-9
    [46] R. Tavakoli, Multimaterial topology optimization by volume constrained Allen-Cahn system and regularized projected steepest descent method, Comput. Methods Appl. Mech. Eng., 276 (2014), 534–565. https://doi.org/10.1016/j.cma.2014.04.005 doi: 10.1016/j.cma.2014.04.005
    [47] M. Y. Wang, X. Wang, "Color" level sets: a multi-phase method for structural topology optimization with multiple materials, Comput. Methods Appl. Mech. Eng., 193 (2004), 469–496. https://doi.org/10.1016/j.cma.2003.10.008 doi: 10.1016/j.cma.2003.10.008
    [48] Y. Q. Wang, Z. Luo, Z. Kang, N. Zhang, A multi-material level set-based topology and shape optimization method, Comput. Methods Appl. Mech. Eng., 283 (2015), 1570–1586. https://doi.org/10.1016/j.cma.2014.11.002 doi: 10.1016/j.cma.2014.11.002
    [49] X. Guo, W. S. Zhang, J. Zhang, J. Yuan, Explicit structural topology optimization based on moving morphable components (MMC) with curved skeletons, Comput. Methods Appl. Mech. Eng., 310 (2016), 711–748. https://doi.org/10.1016/j.cma.2016.07.018 doi: 10.1016/j.cma.2016.07.018
    [50] W. S. Zhang, W. Y. Yang, J. H. Zhou, D. Li, X. Guo, Structural topology optimization through explicit boundary evolution, J. Appl. Mech., 84 (2017), 011011. https://doi.org/10.1115/1.4034972 doi: 10.1115/1.4034972
    [51] X. Guo, W. S. Zhang, W. L. Zhong, Doing topology optimization explicitly and geometrically - A new moving morphable components based framework, J. Appl. Mech., 81 (2014), 081009. https://doi.org/10.1115/1.4027609 doi: 10.1115/1.4027609
    [52] X. Huang, Y. M. Xie, Bi-directional evolutionary topology optimization of continuum structures with one or multiple materials, Comput. Mech., 43 (2009), 393–401. https://doi.org/10.1007/s00466-008-0312-0 doi: 10.1007/s00466-008-0312-0
    [53] J. E. Bolander, S. Saito, Fracture analyses using spring networks with random geometry, Eng. Fract. Mech., 61 (1998), 569–591. https://doi.org/10.1016/S0013-7944(98)00069-1 doi: 10.1016/S0013-7944(98)00069-1
    [54] M. Yip, J. Mohle, J. E. Bolander, Automated modeling of three-dimensional structural components using irregular lattices, Comput-Aided Civ. Infrastruct. Eng., 20 (2005), 393–407. https://doi.org/10.1111/j.1467-8667.2005.00407.x doi: 10.1111/j.1467-8667.2005.00407.x
    [55] T. A. Poulsen, A simple scheme to prevent checkerboard patterns and one-node connected hinges in topology optimization, Struct. Multidiscip. Optim., 24 (2002), 396–399. https://doi.org/10.1007/s00158-002-0251-x doi: 10.1007/s00158-002-0251-x
    [56] M. Zhou, Y. K. Shyy, H. L. Thomas, Checkerboard and minimum member size control in topology optimization, Struct. Multidiscip. Optim., 21 (2001), 152–158. https://doi.org/10.1007/s001580050179 doi: 10.1007/s001580050179
    [57] C. Talischi, G. H. Paulino, C. H. Le, Honeycomb Wachspress finite elements for structural topology optimization, Struct. Multidiscip. Optim., 37 (2009), 569–583. https://doi.org/10.1007/s00158-008-0261-4 doi: 10.1007/s00158-008-0261-4
    [58] F. Aurenhammer, Voronoi diagrams-a survey of a fundamental geometric data structure, ACM Comput. Surv., 23 (1991), 345–405. https://doi.org/10.1145/116873.116880 doi: 10.1145/116873.116880
    [59] C. Talischi, G. H. Paulino, A. Pereira, I. F. M. Menezes, Polygonal finite elements for topology optimization: A unifying paradigm, Int. J. Numer. Methods Eng., 82 (2010), 671–698. https://doi.org/10.1002/nme.2763 doi: 10.1002/nme.2763
    [60] O. Sigmund, A 99 line topology optimization code written in Matlab, Struct. Multidiscip. Optim., 21 (2001), 120–127. https://doi.org/10.1007/s001580050176 doi: 10.1007/s001580050176
  • Reader Comments
  • © 2024 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(1267) PDF downloads(125) Cited by(3)

Article outline

Figures and Tables

Figures(34)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog