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Frontiers of Mechanical Engineering

ISSN 2095-0233

ISSN 2095-0241(Online)

CN 11-5984/TH

Postal Subscription Code 80-975

2018 Impact Factor: 0.989

Front. Mech. Eng.    2021, Vol. 16 Issue (3) : 593-606    https://doi.org/10.1007/s11465-021-0636-4
RESEARCH ARTICLE
Topology optimization of transient problem with maximum dynamic response constraint using SOAR scheme
Kai LONG1(), Xiaoyu YANG1, Nouman SAEED1, Ruohan TIAN1, Pin WEN2, Xuan WANG3
1. State Key Laboratory for Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
2. Hubei Key Laboratory of Theory and Application of Advanced Materials Mechanics, School of Science, Wuhan University of Technology, Wuhan 430070, China
3. Department of Engineering Mechanics, Hefei University of Technology, Hefei 230009, China
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Abstract

This paper proposes a novel method for the continuum topology optimization of transient vibration problem with maximum dynamic response constraint. An aggregated index in the form of an integral function is presented to cope with the maximum response constraint in the time domain. The density filter solid isotropic material with penalization method combined with threshold projection is developed. The sensitivities of the proposed index with respect to design variables are conducted. To reduce computational cost, the second-order Arnoldi reduction (SOAR) scheme is employed in transient analysis. Influences of aggregate parameter, duration of loading period, interval time, and number of basis vectors in the SOAR scheme on the final designs are discussed through typical examples while unambiguous configuration can be achieved. Through comparison with the corresponding static response from the final designs, the optimized results clearly demonstrate that the transient effects cannot be ignored in structural topology optimization.

Keywords topology optimization      solid isotropic material with penalization      transient response      aggregation function      second-order Arnoldi reduction     
Corresponding Author(s): Kai LONG   
Just Accepted Date: 21 June 2021   Online First Date: 03 August 2021    Issue Date: 24 September 2021
 Cite this article:   
Kai LONG,Xiaoyu YANG,Nouman SAEED, et al. Topology optimization of transient problem with maximum dynamic response constraint using SOAR scheme[J]. Front. Mech. Eng., 2021, 16(3): 593-606.
 URL:  
https://academic.hep.com.cn/fme/EN/10.1007/s11465-021-0636-4
https://academic.hep.com.cn/fme/EN/Y2021/V16/I3/593
SOAR procedure
Solve ( K ω2M) q¯1 =F
q1 = q¯1/ q¯12
p1 =0
for i=1, 2, ..., N
Solve (Kω 2M )r =(2ωM )q i+M pi
s=q i
for j=1, 2, ..., i
r=r qi ,r qj
s=s qj ,r qj
endfor
qi +1 = r/ r 2
pi +1 = s/ r 2
endfor
The reduced order basis P={ q1 , q 2, ..., q N}
  
Fig.1  Half-sinusoidal force with various loading times.
Fig.2  Optimized topologies for tL=0.05 s: (a) m=10, V/V0=0.409, j(f)=0.146 m2, and fmax=0.200 m2; (b) m=30, V/V0=0.407, j(f)=0.178 m2, and fmax=0.200 m2; (c) m=50, V/V0=0.406, j(f)=0.185 m2, and fmax=0.200 m2.
Fig.3  Optimized topologies for tL=0.03 s: (a) m=10, V/V0=0.400, j(f)=0.146 m2, and fmax=0.200 m2; (b) m=30, V/V0=0.382, j(f)=0.180 m2, and fmax=0.200 m2; (c) m=50, V/V0=0.406, j(f)=0.185 m2, and fmax=0.200 m2.
Fig.4  Optimized topologies for tL=0.01 s: (a) m=10, V/V0=0.369, j(f)=0.138 m2, and fmax=0.200 m2; (b) m=30, V/V0=0.360, j(f)=0.174 m2, and fmax=0.200 m2; (c) m=50, V/V0=0.360, j(f)=0.183 m2, and fmax=0.200 m2.
Fig.5  Optimized topologies for tL=0.01 s from (a) full analysis and (b) SOAR (N=10), (c) SOAR (N=30), and (d) SOAR (N=50) schemes.
Description of the method V/V0 fmax/m2 Iterations Matlab time/s
Full analysis 0.394 0.18 400 51259.27
SOAR scheme (N=10) 0.399 0.18 400 961.07
SOAR scheme (N=30) 0.400 0.18 400 1248.75
SOAR scheme (N=50) 0.399 0.18 400 1637.57
Tab.1  Comparisons of the optimized results between full analysis and SOAR schemes with various numbers of basis vectors
Fig.6  Rectangular force.
Fig.7  Evolution of volume fraction with different upper bound dynamic responses and the corresponding structural topologies.
Fig.8  Evolution of volume fraction under static and dynamic requirements, with structural topologies inserted.
Fig.9  Time history curves of the maximum dynamic responses under different limits: (a) fmax ≤0.300 m2, (b) fmax ≤0.500 m2, (c) fmax ≤0.700 m2, and (d) fmax ≤0.900 m2.
Fig.10  Load with the interval time t.
Fig.11  Optimized topologies for varying τ: (a) t=0, V/V0=0.332, fmax=0.400 m2, and fs=0.327 m2; (b) t=0.002 s, V/V0=0.314, fmax=0.400 m2, and fs=0.347 m2; (c) t=0.004 s, V/V0=0.263, fmax=0.400 m2, and fs=0.503 m2; (d) t=0.006 s, V/V0=0.246, fmax=0.400 m2, and fs=0.641 m2; (e) t=0.008 s, V/V0=0.246, fmax=0.400 m2, and fs=0.769 m2.
Fig.12  Convergence history of objective and constraint function.
Fig.13  Final designs obtained from (a) full analysis and (b) SOAR (N=30), (c) SOAR (N=40), (d) SOAR (N=50), and (e) SOAR (N=60) schemes.
Description of the method V/V0 fmax/m2 Iterations Maltab time/h
Full analysis 0.181 0.060 400 109.31
SOAR scheme (N=30) 0.203 0.059 400 7.61
SOAR scheme (N=40) 0.200 0.059 400 8.58
SOAR scheme (N=50) 0.198 0.060 400 10.95
SOAR scheme (N=60) 0.197 0.060 400 12.83
Tab.2  Comparison of the optimized results between full analysis and SOAR schemes with various numbers of basis vectors
a0 Parameter defined in Eq. (27)
Ak Weight coefficient in integral operation
B Width of the 3D structure
C Global damping matrix
cM, cK Proportional damping coefficients
cμ Adjustment coefficient
CR Reduced damping matrix
α, δ Parameters in Newmark method
β, η Parameters of the threshold projection
ϕ(f ) A function that replace f(t) to catch the maximum response
Γ Unit vector, of which the concerned DOF is unity while all other components are zeros
Δt Time step
Δ(e, i) Center-to-center distance
E0 Material’s elastic modulus
F Force vector
fmax Peak value of structural dynamic response in the time domain
f Corresponding upper limit
fs Structure response from static analysis
f(t ) A structural behavior function used to measure structural dynamic response
g(t ) Time-varying value
H Height of the structure
Hei Weighting function
ke Elemental stiffness matrix
K ^ Effective stiffness matrix
K Global stiffness matrix
ΚR Reduced stiffness matrix
L Length of the structure
me Elemental mass matrix
M Global mass matrix
MR Reduced mass matrix
Ne Number of total elements
N˜e Neighborhood set of the eth elements
Nt Total step number for discretion of time zone
P Projection matrix
Q ^ Effective load matrix in Newmark method
Q(t) Time-varying force
rmin Circular region of radius
tk Time points in integral operation
tL Loading time
T Thickness of the structure
u(t) Velocity vector
u ˙(t) Displacement vector
u ¨(t) Acceleration vector
V(ρ ) Structural volume
z(t) Reduced solution given in differential Eq. (7)
ρ0 Material’s density
ρe The eth elemental design variable
ρmin Lower bound for ρ
ρ˜ Filtered density
ρ Physical density from the threshold projection
τ Time span between two loading sections
ν Poisson’s ratio
λ(t) An arbitrary vector
μ An aggregation function parameter
ω Circular frequency
  
1 M P Bendsøe, N Kikuchi. Generating optimal topologies in structural design using a homogenization. Computer Methods in Applied Mechanics and Engineering, 1988, 71(2): 197–224
https://doi.org/10.1016/0045-7825(88)90086-2
2 J D Deaton, 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
3 O Sigmund, K Maute. Topology optimization approaches. Structural and Multidisciplinary Optimization, 2013, 48(6): 1031–1055
https://doi.org/10.1007/s00158-013-0978-6
4 Z Chen, K Long, P Wen, et al.. Fatigue-resistance topology optimization of continuum structure by penalizing the cumulative fatigue damage. Advances in Engineering Software, 2020, 150: 102924
https://doi.org/10.1016/j.advengsoft.2020.102924
5 S Zargham, T A Ward, R Ramli, et al.. Topology optimization: A review for structural designs under vibration problems. Structural and Multidisciplinary Optimization, 2016, 53(6): 1157–1177
https://doi.org/10.1007/s00158-015-1370-5
6 A R Díaaz, N Kikuchi. Solution to shape and topology eigenvalue optimization problems using a homogenization method. International Journal for Numerical Methods in Engineering, 1992, 35(7): 1487–1502
https://doi.org/10.1002/nme.1620350707
7 N L Pedersen. Maximization of eigenvalues using topology optimization. Structural and Multidisciplinary Optimization, 2000, 20(1): 2–11
https://doi.org/10.1007/s001580050130
8 J Du, N Olhoff. Topological design of freely vibrating continuum structures for maximum values of simple and multiple eigenfrequencies and frequency gaps. Structural and Multidisciplinary Optimization, 2007, 34(2): 91–110
https://doi.org/10.1007/s00158-007-0101-y
9 Q Li, Q Wu, J Liu, et al.. Topology optimization of vibrating structures with frequency band constraints. Structural and Multidisciplinary Optimization, 2021, 63(3): 1203–1218
https://doi.org/10.1007/s00158-020-02753-7
10 B Niu, J Yan, G Cheng. Optimum structure with homogeneous optimum cellular material for maximum fundamental frequency. Structural and Multidisciplinary Optimization, 2009, 39(2): 115–132
https://doi.org/10.1007/s00158-008-0334-4
11 K Long, D Han, X Gu. Concurrent topology optimization of composite macrostructure and microstructure constructed by constituent phases of distinct Poisson’s ratios for maximum frequency. Computational Materials Science, 2017, 129: 194–201
https://doi.org/10.1016/j.commatsci.2016.12.013
12 Z D Ma, N Kikuchi, H C Cheng. Topological design for vibrating structures. Computer Methods in Applied Mechanics and Engineering, 1995, 121(1‒4): 259–280
https://doi.org/10.1016/0045-7825(94)00714-X
13 C S Jog. Topology design of structures subject to periodic loading. Journal of Sound and Vibration, 2002, 253(3): 687–709
https://doi.org/10.1006/jsvi.2001.4075
14 N Olhoff, J Du. Generalized incremental frequency method for topological design of continuum structures for minimum dynamic compliance subject to forced vibration at a prescribed low or high value of the excitation frequency. Structural and Multidisciplinary Optimization, 2016, 54(5): 1113–1141
https://doi.org/10.1007/s00158-016-1574-3
15 B Niu, X He, Y Shan, et al.. On objective functions of minimizing the vibration response of continuum structures subject to external harmonic excitation. Structural and Multidisciplinary Optimization, 2018, 57(6): 2291–2307
https://doi.org/10.1007/s00158-017-1859-1
16 G H Yoon. Structural topology optimization for frequency response problem using model reduction schemes. Computer Methods in Applied Mechanics and Engineering, 2010, 199(25‒28): 1744–1763
https://doi.org/10.1016/j.cma.2010.02.002
17 H Liu, W Zhang, T Gao. A comparative study of dynamic analysis methods for structural topology optimization under harmonic force excitations. Structural and Multidisciplinary Optimization, 2015, 51(6): 1321–1333
https://doi.org/10.1007/s00158-014-1218-4
18 J Zhu, F He, T Liu, et al.. Structural topology optimization under harmonic base acceleration excitations. Structural and Multidisciplinary Optimization, 2018, 57(3): 1061–1078
https://doi.org/10.1007/s00158-017-1795-0
19 K Long, X Wang, H Liu. Stress-constrained topology optimization of continuum structures subjected to harmonic force excitation using sequential quadratic programming. Structural and Multidisciplinary Optimization, 2019, 59(5): 1747–1759
https://doi.org/10.1007/s00158-018-2159-0
20 B Niu, N Olhoff, E Lund, et al.. Discrete material optimization of vibrating laminated composite plates for minimum sound radiation. International Journal of Solids and Structures, 2010, 47(16): 2097–2114
https://doi.org/10.1016/j.ijsolstr.2010.04.008
21 J Du, N Olhoff. Minimization of sound radiation from vibrating bi-material structures using topology optimization. Structural and Multidisciplinary Optimization, 2007, 33(4‒5): 305–321
https://doi.org/10.1007/s00158-006-0088-9
22 J Du, N Olhoff. Topological design of vibrating structures with respect to optimum sound pressure characteristics in a surrounding acoustic medium. Structural and Multidisciplinary Optimization, 2010, 42(1): 43–54
https://doi.org/10.1007/s00158-009-0477-y
23 C B Dilgen, S B Dilgen, N Aage, et al.. Topology optimization of acoustic mechanical interaction problems: A comparative review. Structural and Multidisciplinary Optimization, 2019, 60(2): 779–801
https://doi.org/10.1007/s00158-019-02236-4
24 B S Kang, G J Park, J S Arora. A review of optimization of structures subjected to transient loads. Structural and Multidisciplinary Optimization, 2006, 31(2): 81–95
https://doi.org/10.1007/s00158-005-0575-4
25 S Min, N Kikuchi, Y Park, et al.. Optimal topology design of structures under dynamic loads. Structural and Multidisciplinary Optimization, 1999, 17(2‒3): 208–218
https://doi.org/10.1007/BF01195945
26 S Turteltaub. Optimal non-homogeneous composites for dynamic loading. Structural and Multidisciplinary Optimization, 2005, 30(2): 101–112
https://doi.org/10.1007/s00158-004-0502-0
27 J P Zhao, C J Wang. Topology optimization for minimizing the maximum dynamic response in the time domain using aggregation functional method. Computers & Structures, 2017, 190: 41–60
https://doi.org/10.1016/j.compstruc.2017.05.002
28 J P Zhao, C J Wang. Dynamic response topology optimization in the time domain using model reduction method. Structural and Multidisciplinary Optimization, 2016, 53(1): 101–114
https://doi.org/10.1007/s00158-015-1328-7
29 J P Zhao, H Yoon, B D Youn. Concurrent topology optimization with uniform microstructure for minimizing dynamic response in the time domain. Computers & Structures, 2019, 222: 98–117
https://doi.org/10.1016/j.compstruc.2019.07.008
30 L Zhao, B Xu, Y Han, et al.. Continuum structural topological optimization with dynamic stress response constraints. Advances in Engineering Software, 2020, 148: 102834
https://doi.org/10.1016/j.advengsoft.2020.102834
31 L Zhao, B Xu, Y Han, et al.. Structural topological optimization with dynamic fatigue constraints subject to dynamic random loads. Engineering Structures, 2020, 205(15): 110089
https://doi.org/10.1016/j.engstruct.2019.110089
32 H Jang, H A Lee, J Y Lee, et al.. Dynamic response topology optimization in the time domain using equivalent static loads. AIAA Journal, 2012, 50(1): 226–234
https://doi.org/10.2514/1.J051256
33 B S Kang, W S Choi, G J Park. Structural optimization under equivalent static loads transformed from dynamic loads based on displacement. Computers & Structures, 2001, 79 (2): 145–154
https://doi.org/10.1016/S0045-7949(00)00127-9
34 W S Choi, G J Park. Structural optimization using equivalent static loads at all time intervals. Computer Methods in Applied Mechanics and Engineering, 2002, 191(19‒20): 2105–2122
https://doi.org/10.1016/S0045-7825(01)00373-5
35 E Kim, H Kim, S Baek, et al.. Effective structural optimization based on equivalent static loads combined with system reduction method. Structural and Multidisciplinary Optimization, 2014, 50(5): 775–786
https://doi.org/10.1007/s00158-014-1080-4
36 B Xu, X Huang, Y M Xie. Two-scale dynamic optimal design of composite structures in the time domain using equivalent static loads. Composite Structures, 2016, 142: 335–345
https://doi.org/10.1016/j.compstruct.2016.01.090
37 M Stolpe. On the equivalent static loads approach for dynamic response structural optimization. Structural and Multidisciplinary Optimization, 2014, 50(6): 921–926
https://doi.org/10.1007/s00158-014-1101-3
38 M Stolpe, A Verbart, S Rojas-Labanda. The equivalent static loads method for structural optimization does not in general generate optimal designs. Structural and Multidisciplinary Optimization, 2018, 58(1): 139–154
https://doi.org/10.1007/s00158-017-1884-0
39 H A Lee, G J Park. Nonlinear dynamic response topology optimization using equivalent static loads method. Computer Methods in Applied Mechanics and Engineering, 2015, 283: 956–970
https://doi.org/10.1016/j.cma.2014.10.015
40 Y C Bai, H S Zhou, F Lei, et al.. An improved numerically-stable equivalent static loads (ESLs) algorithm based on energy-scaling ratio for stiffness topology optimization under crash loads. Structural and Multidisciplinary Optimization, 2019, 59(1): 117–130
https://doi.org/10.1007/s00158-018-2054-8
41 Z Bai, Y Su. Dimension reduction of large-scale second-order dynamical systems via a second-order Arnoldi method. SIAM Journal on Scientific Computing, 2005, 26(5): 1692–1709
https://doi.org/10.1137/040605552
42 X Wang, X B Tang, L Z Mao. A modified second-order Arnoldi method for solving the quadratic eigenvalue problems. Computers & Mathematics with Applications (Oxford, England), 2017, 73(2): 327–338
https://doi.org/10.1016/j.camwa.2016.11.027
43 P Zhou, Y Peng, J Du. Topology optimization of bi-material structures with frequency-domain objectives using time-domain simulation and sensitivity analysis. Structural and Multidisciplinary Optimization, 2021, 63(2): 575–593
https://doi.org/10.1007/s00158-020-02814-x
44 G J Kennedy, J E Hicken. Improved constraint-aggregation methods. Computer Methods in Applied Mechanics and Engineering, 2015, 289: 332–354
https://doi.org/10.1016/j.cma.2015.02.017
45 F Wang, B S Lazarov, O Sigmund. On projection methods, convergence and robust formulations in topology optimization. Structural and Multidisciplinary Optimization, 2011, 43(6): 767–784
https://doi.org/10.1007/s00158-010-0602-y
46 G A da Silva, A T Beck, O Sigmund. Stress-constrained topology optimization considering uniform manufacturing uncertainties. Computer Methods in Applied Mechanics and Engineering, 2019, 344: 512–537
https://doi.org/10.1016/j.cma.2018.10.020
47 G A da Silva, A T Beck, O Sigmund. Topology optimization of compliant mechanisms considering stress constraints, manufacturing uncertainty and geometric nonlinearity. Computer Methods in Applied Mechanics and Engineering, 2020, 365: 112972
https://doi.org/10.1016/j.cma.2020.112972
48 K Svanberg. The method of moving asymptotes—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
49 D Da, L Xia, G Li, et al.. Evolutionary topology optimization of continuum structures with smooth boundary representation. Structural and Multidisciplinary Optimization, 2018, 57(6): 2143–2159
https://doi.org/10.1007/s00158-017-1846-6
50 M Xiao, D Lu, P Breitkopf, et al.. On-the-fly model reduction for large-scale structural topology optimization using principal components analysis. Structural and Multidisciplinary Optimization, 2020, 62(1): 209–230
https://doi.org/10.1007/s00158-019-02485-3
51 M Xiao, D Lu, P Breitkopf, et al.. Multi-grid reduction-order topology optimization. Structural and Multidisciplinary Optimization, 2020, 61(6): 1–23
https://doi.org/10.1007/s00158-020-02570-y
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