Please wait a minute...
Frontiers of Mechanical Engineering

ISSN 2095-0233

ISSN 2095-0241(Online)

CN 11-5984/TH

邮发代号 80-975

2019 Impact Factor: 2.448

Frontiers of Mechanical Engineering  2019, Vol. 14 Issue (2): 153-170   https://doi.org/10.1007/s11465-019-0533-2
  本期目录
A regularization scheme for explicit level-set XFEM topology optimization
Markus J. GEISS1, Jorge L. BARRERA1, Narasimha BODDETI2, Kurt MAUTE1()
1. Ann and H.J. Smead Department of Aerospace Engineering Sciences, University of Colorado at Boulder, Boulder, CO 80309-0429, USA
2. Singapore University of Technology and Design, SUTD Digital Manufacturing and Design Centre, Singapore 487372, Singapore
 全文: PDF(4484 KB)   HTML
Abstract

Regularization of the level-set (LS) field is a critical part of LS-based topology optimization (TO) approaches. Traditionally this is achieved by advancing the LS field through the solution of a Hamilton-Jacobi equation combined with a reinitialization scheme. This approach, however, may limit the maximum step size and introduces discontinuities in the design process. Alternatively, energy functionals and intermediate LS value penalizations have been proposed. This paper introduces a novel LS regularization approach based on a signed distance field (SDF) which is applicable to explicit LS-based TO. The SDF is obtained using the heat method (HM) and is reconstructed for every design in the optimization process. The governing equations of the HM, as well as the ones describing the physical response of the system of interest, are discretized by the extended finite element method (XFEM). Numerical examples for problems modeled by linear elasticity, nonlinear hyperelasticity and the incompressible Navier-Stokes equations in two and three dimensions are presented to show the applicability of the proposed scheme to a broad range of design optimization problems.

Key wordslevel-set regularization    explicit level-sets    XFEM    CutFEM    topology optimization    heat method    signed distance field    nonlinear structural mechanics    fluid mechanics
收稿日期: 2018-09-01      出版日期: 2019-04-22
Corresponding Author(s): Kurt MAUTE   
 引用本文:   
. [J]. Frontiers of Mechanical Engineering, 2019, 14(2): 153-170.
Markus J. GEISS, Jorge L. BARRERA, Narasimha BODDETI, Kurt MAUTE. A regularization scheme for explicit level-set XFEM topology optimization. Front. Mech. Eng., 2019, 14(2): 153-170.
 链接本文:  
https://academic.hep.com.cn/fme/CN/10.1007/s11465-019-0533-2
https://academic.hep.com.cn/fme/CN/Y2019/V14/I2/153
Fig.1  
Fig.2  
Fig.3  
Parameter Value
Weak boundary condition penalty Eq. (15) γN= 100/h
Ghost penalty Eq. (13) γG= 0.001
Perimeter penalty weight Eq. (3) w2=0.01
Lower bound of s sL= 3h
Upper bound of s sU= +3h
Target bound of LSF ϕBnd=2h
Filter radius used in 2D rf= 1.6h
Filter radius used in 3D rf= 2.4h
Tab.1  
Parameter Value
Young’s modulus E=2 ×103
Poisson’s ratio ν=0
LS regularization weight w3=0.01
Element edge length h=1.0
Tab.2  
Fig.4  
Fig.5  
Fig.6  
Fig.7  
Fig.8  
Parameter Value
Young’s modulus E=2.0 ×103
Poisson’s ratio ν=0.4
LS regularization weight w3=0.01
Element edge length h=1.0
Tab.3  
Fig.9  
Fig.10  
Fig.11  
Fig.12  
Fig.13  
Fig.14  
Parameter Value
Reynolds number Re=66.0
Fluid density ρ=1.0
LS regularization weight w3=0.05
Element edge length h=0.25
Tab.4  
Fig.15  
Fig.16  
Fig.17  
1 M PBendsøe, OSigmund. Topology Optimization. Berlin: Springer, 2004
2 OSigmund, K Maute. Topology optimization approaches: A comparative review. Structural and Multidisciplinary Optimization, 2013, 48(6): 1031–1055
https://doi.org/10.1007/s00158-013-0978-6
3 J DDeaton, R V Grandhi. A survey of structural and multidisciplinary continuum topology optimization: Post 2000. Structural and Multidisciplinary Optimization, 2014, 49(1): 1–38
https://doi.org/10.1007/s00158-013-0956-z
4 SOsher, J A Sethian. Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations. Journal of Computational Physics, 1988, 79(1): 12–49
https://doi.org/10.1016/0021-9991(88)90002-2
5 SOsher, R Fedkiw. Level Set Methods and Dynamic Implicit Surfaces. Vol. 153. New York: Springer, 2003
6 SOsher, N Paragios. Geometric Level Set Methods in Imaging, Vision, and Graphics. New York: Springer, 2003
7 FGibou, R Fedkiw, SOsher. A review of level-set methods and some recent applications. Journal of Computational Physics, 2018, 353: 82–109
https://doi.org/10.1016/j.jcp.2017.10.006
8 N Pvan Dijk, KMaute, MLangelaar, et al. Level-set methods for structural topology optimization: A review. Structural and Multidisciplinary Optimization, 2013, 48(3): 437–472
https://doi.org/10.1007/s00158-013-0912-y
9 S JOsher, F Santosa. Level set methods for optimization problems involving geometry and constraints I. Frequencies of a two-density inhomogeneous drum. Journal of Computational Physics, 2001, 171(1): 272–288
https://doi.org/10.1006/jcph.2001.6789
10 GAllaire, F Jouve, A MToader. A level-set method for shape optimization. Comptes Rendus Mathématique, 2002, 334(12): 1125–1130 (in French)
https://doi.org/10.1016/S1631-073X(02)02412-3
11 M YWang, X Wang, DGuo. A level set method for structural topology optimization. Computer Methods in Applied Mechanics and Engineering, 2003, 192(1–2): 227–246
https://doi.org/10.1016/S0045-7825(02)00559-5
12 GAllaire, F Jouve, A MToader. Structural optimization using sensitivity analysis and a level-set method. Journal of Computational Physics, 2004, 194(1): 363–393
https://doi.org/10.1016/j.jcp.2003.09.032
13 SWang, M Y Wang. Radial basis functions and level set method for structural topology optimization. International Journal for Numerical Methods in Engineering, 2006, 65(12): 2060–2090
https://doi.org/10.1002/nme.1536
14 ZLuo, M Y Wang, S Wang, et al. A level set-based parameterization method for structural shape and topology optimization. International Journal for Numerical Methods in Engineering, 2008, 76(1): 1–26
https://doi.org/10.1002/nme.2092
15 SKreissl, G Pingen, KMaute. An explicit level set approach for generalized shape optimization of fluids with the lattice Boltzmann method. International Journal for Numerical Methods in Fluids, 2011, 65(5): 496–519
https://doi.org/10.1002/fld.2193
16 N Pvan Dijk, MLangelaar, Fvan Keulen. Explicit level-set-based topology optimization using an exact Heaviside function and consistent sensitivity analysis. International Journal for Numerical Methods in Engineering, 2012, 91(1): 67–97
https://doi.org/10.1002/nme.4258
17 M Jde Ruiter, Fvan Keulen. Topology optimization using a topology description function. Structural and Multidisciplinary Optimization, 2004, 26(6): 406–416
https://doi.org/10.1007/s00158-003-0375-7
18 R BHaber, C S Jog, M P Bendsøe. A new approach to variable-topology shape design using a constraint on perimeter. Structural Optimization, 1996, 11(1): 1–12
https://doi.org/10.1007/BF01279647
19 TYamada, K Izui, SNishiwaki, et al. A topology optimization method based on the level set method incorporating a fictitious interface energy. Computer Methods in Applied Mechanics and Engineering, 2010, 199(45–48): 2876–2891
https://doi.org/10.1016/j.cma.2010.05.013
20 MOtomori, T Yamada, KIzui, et al. Level set-based topology optimisation of a compliant mechanism design using mathematical programming. Mechanical Science, 2011, 2(1): 91–98
https://doi.org/10.5194/ms-2-91-2011
21 JGomes, O Faugeras. Reconciling distance functions and level sets. Journal of Visual Communication and Image Representation, 2000, 11(2): 209–223
https://doi.org/10.1006/jvci.1999.0439
22 BZhu, X Zhang. A new level set method for topology optimization of distributed compliant mechanisms. International Journal for Numerical Methods in Engineering, 2012, 91(8): 843–871
https://doi.org/10.1002/nme.4296
23 CLi, C Xu, CGui, et al. Level set evolution without re-initialization: A new variational formulation. In: Proceedings of 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, (CVPR’05). San Diego: IEEE, 2005, Vol. I, 430–436
24 PCoffin, K Maute. Level set topology optimization of cooling and heating devices using a simplified convection model. Structural and Multidisciplinary Optimization, 2016, 53(5): 985–1003
https://doi.org/10.1007/s00158-015-1343-8
25 MSussman, P Smereka, SOsher. A level set approach for computing solutions to incompressible two-phase flow. Journal of Computational Physics, 1994, 114(1): 146–159
https://doi.org/10.1006/jcph.1994.1155
26 SOsher. Book review: Level set methods and fast marching methods: Evolving interfaces in computational geometry, fluid mechanics, computer vision, and materials science. Mathematics of Computation, 2001, 70(233): 449–451
27 CLi, C Xu, CGui, et al. Distance regularized level set evolution and its application to image segmentation. IEEE Transactions on Image Processing, 2010, 19(12): 3243–3254
https://doi.org/10.1109/TIP.2010.2069690
28 BZhu, X Zhang, SFatikow. Structural topology and shape optimization using a level set method with distance-suppression scheme. Computer Methods in Applied Mechanics and Engineering, 2015, 283: 1214–1239
https://doi.org/10.1016/j.cma.2014.08.017
29 LJiang, S Chen. Parametric structural shape & topology optimization with a variational distance-regularized level set method. Computer Methods in Applied Mechanics and Engineering, 2017, 321: 316–336
https://doi.org/10.1016/j.cma.2017.03.044
30 M,Burger S J. Osher A survey in mathematics for industry a survey on level set methods for inverse problems and optimal design. European Journal of Applied Mathematics, 2005, 16(2): 263–301
https://doi.org/10.1017/S0956792505006182
31 DHartmann, M Meinke, WSchröder. The constrained reinitialization equation for level set methods. Journal of Computational Physics, 2010, 229(5): 1514–1535
https://doi.org/10.1016/j.jcp.2009.10.042
32 JFu, H Li, MXiao, et al. Topology optimization of shell-infill structures using a distance regularized parametric level-set method. Structural and Multidisciplinary Optimization, 2018, 1–14 (in press)
https://doi.org/10.1007/s00158-018-2064-6
33 KCrane, C Weischedel, MWardetzky. Geodesics in heat. ACM Transactions on Graphics, 2013, 32(5): 1–11
https://doi.org/10.1145/2516971.2516977
34 B KCrane, C Weischedel, MWardetzky. The heat method for distance computation. Communications of the ACM, 2017, 60(11): 90–99
https://doi.org/10.1145/3131280
35 SKreissl, K Maute. Levelset based fluid topology optimization using the extended finite element method. Structural and Multidisciplinary Optimization, 2012, 46(3): 311–326
https://doi.org/10.1007/s00158-012-0782-8
36 J ASethian. Fast marching methods. SIAM Review, 1999, 41(2): 199–235
https://doi.org/10.1137/S0036144598347059
37 TWong, S Leung. A fast sweeping method for eikonal equations on implicit surfaces. Journal of Scientific Computing, 2016, 67(3): 837–859
https://doi.org/10.1007/s10915-015-0105-5
38 CDaux, N Moës, JDolbow, et al. Arbitrary branched and intersecting cracks with the extended finite element method. International Journal for Numerical Methods in Engineering, 2000, 48(12): 1741–1760
https://doi.org/10.1002/1097-0207(20000830)48:12<1741::AID-NME956>3.0.CO;2-L
39 T PFries, T Belytschko. The extended/generalized finite element method: An overview of the method and its applications. International Journal for Numerical Methods in Engineering, 2010, 84(3): 253–304
https://doi.org/10.1002/nme.2914
40 AHansbo, P Hansbo. A finite element method for the simulation of strong and weak discontinuities in solid mechanics. Computer Methods in Applied Mechanics and Engineering, 2004, 193(33–35): 3523–3540
https://doi.org/10.1016/j.cma.2003.12.041
41 DMakhija, K Maute. Numerical instabilities in level set topology optimization with the extended finite element method. Structural and Multidisciplinary Optimization, 2014, 49(2): 185–197
https://doi.org/10.1007/s00158-013-0982-x
42 A BTran, J Yvonnet, Q CHe, et al. A multiple level set approach to prevent numerical artefacts in complex microstructures with nearby inclusions within XFEM. International Journal for Numerical Methods in Engineering, 2011, 85(11): 1436–1459
https://doi.org/10.1002/nme.3025
43 EBurman, P Hansbo. Fictitious domain methods using cut elements: III. A stabilized Nitsche method for Stokes’ problem. Mathematical Modelling and Numerical Analysis, 2014, 48(3): 859–874
https://doi.org/10.1051/m2an/2013123
44 BSchott, U Rasthofer, VGravemeier, et al. A face-oriented stabilized Nitsche-type extended variational multiscale method for incompressible two-phase flow. International Journal for Numerical Methods in Engineering, 2015, 104(7): 721–748
https://doi.org/10.1002/nme.4789
45 C H,Villanueva K. Maute CutFEM topology optimization of 3D laminar incompressible flow problems. Computer Methods in Applied Mechanics and Engineering, 2017, 320(Suppl C): 444–473
https://doi.org/10.1016/j.cma.2017.03.007
46 EBurman, S Claus, PHansbo, et al. CutFEM: Discretizing geometry and partial differential equations. International Journal for Numerical Methods in Engineering, 2015, 104(7): 472–501
https://doi.org/10.1002/nme.4823
47 J ANitsche. On a variational principle for the solution of Dirichlet problems under the use of subspaces which are subject to no boundary conditions. Abhandlungen aus dem Mathematischen Seminar der Universität Hamburg, 1971, 36(1): 9–15 (in German)
https://doi.org/10.1007/BF02995904
48 P RAmestoy, A Guermouche, J YL’Excellent, et al. Hybrid scheduling for the parallel solution of linear systems. Parallel Computing, 2006, 32(2): 136–156
https://doi.org/10.1016/j.parco.2005.07.004
49 KSvanberg. The method of moving asymptote—A new method for structural optimization. International Journal for Numerical Methods in Engineering, 1987, 24(2): 359–373
https://doi.org/10.1002/nme.1620240207
50 ASharma, H Villanueva, KMaute. On shape sensitivities with Heaviside-enriched XFEM. Structural and Multidisciplinary Optimization, 2017, 55(2): 385–408
https://doi.org/10.1007/s00158-016-1640-x
51 M JGeiss, K Maute. Topology optimization of active structures using a higher-order level-set-XFEM-density approach. In: Proceedings of 2018 Multidisciplinary Analysis and Optimization Conference, AIAA AVIATION Forum, (AIAA 2018-4053). Atlanta, 2018
https://doi.org/10.2514/6.2018-4053
52 C HVillanueva, KMaute. Density and level set-XFEM schemes for topology optimization of 3-D structures. Computational Mechanics, 2014, 54(1): 133–150
https://doi.org/10.1007/s00466-014-1027-z
53 M JGeiss, N Bodeti, OWeeger, et al. Combined level-set-XFEM-density topology optimization of 4D printed structures undergoing large deformation. Journal of Mechanical Design, 2018 (in press)
https://doi.org/10.1115/1.4041945
54 ASharma, K Maute. Stress-based topology optimization using spatial gradient stabilized XFEM. Structural and Multidisciplinary Optimization, 2018, 57(1): 17–38
https://doi.org/10.1007/s00158-017-1833-y
55 XGuo, W Zhang, WZhong. Explicit feature control in structural topology optimization via level set method. Computer Methods in Applied Mechanics and Engineering, 2014, 272: 354–378
https://doi.org/10.1016/j.cma.2014.01.010
56 SKreissl, G Pingen, KMaute. Topology optimization for unsteady flow. International Journal for Numerical Methods in Engineering, 2011, 87(13): 1229–1253
57 DMakhija, K Maute. Level set topology optimization of scalar transport problems. Structural and Multidisciplinary Optimization, 2015, 51(2): 267–285
https://doi.org/10.1007/s00158-014-1142-7
58 TBorrvall, J Petersson. Topology optimization of fluids in Stokes flow. International Journal for Numerical Methods in Fluids, 2003, 41(1): 77–107
https://doi.org/10.1002/fld.426
59 P DDunning, H Alicia Kim. A new hole insertion method for level set based structural topology optimization. International Journal for Numerical Methods in Engineering, 2013, 93(1): 118–134
https://doi.org/10.1002/nme.4384
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed