Robust optimization of structural dynamic characteristics based on adaptive Kriging model and CNSGA

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• 作者：Jin Cheng (1)
  Zhenyu Liu (1)
  Zhenyu Wu (1)
  Xiaogang Li (1)
  Jianrong Tan (1)
  
  1. State Key Lab of Fluid Power Transmission and Control ; Zhejiang University ; Hangzhou ; 310027 ; China
  
• 关键词：Robust optimization ; Structural dynamic characteristics ; Adaptive Kriging model ; Intelligent resampling technology ; Monte Carlo method ; Constrained non ; dominated sorting genetic algorithm
• 刊名：Structural and Multidisciplinary Optimization
• 出版年：2015
• 出版时间：February 2015
• 年：2015
• 卷：51
• 期：2
• 页码：423-437
• 全文大小：2,663 KB
• 参考文献：1. Arendt, PD, Apley, DW, Chen, W (2013) Objective-oriented sequential sampling for simulation based robust design considering multiple sources of uncertainty.. ASME J Mech Des 135: pp. 051005鈥?-10. CrossRef
  2. Asadpoure, A, Tootkaboni, M, Guest, JK (2011) Robust topology optimization of structures with uncertainties in stiffness - Application to truss structures. Comput Struct 89: pp. 1131-1141 CrossRef
  3. Chen, A, Xu, XD (2012) Goal programming approach to solving network design problem with multiple objectives and demand uncertainty.. Expert Syst Appl 39: pp. 4160-4170 CrossRef
  4. Chen, S (2010) Level set based robust shape and topology optimization under random field uncertainties.. Struct Multidisc Optim 41: pp. 507-524 CrossRef
  5. Chen, W, Allen, JK, Mistree, F (1997) A robust concept exploration method for enhancing productivity in concurrent systems design.. Concurr Eng Res Appl 5: pp. 203-217 CrossRef
  6. Chen, W, Allen, JK, Tsui, KL, Mistree, F (1996) A procedure for robust design: minimizing variations caused by noise factors and control factors.. ASME J Mech Des Trans 118: pp. 478-485 CrossRef
  7. Cheng, J, Liu, ZY, Tan, JR (2013) Multiobjective optimization of injection molding parameters based on soft computing and variable complexity method. Int J Adv Manuf Tech 66: pp. 907-916 CrossRef
  8. Choi, JH, Lee, WH, Park, JJ, Youn, BD (2008) A study on robust design optimization of layered plate bonding process considering uncertainties. Struct Multidisc Optim 35: pp. 531-540 CrossRef
  9. Dantzig, BG (1955) Linear programming under uncertainty.. Manage Sci 1: pp. 197-206 CrossRef
  10. De Oliveira, MA, Possamai, O, Dalla Valentina, LVO, Flesch, CA (2013) Modeling the leadership - project performance relation: radial basis function, Gaussian and Kriging methods as alternatives to linear regression. Expert Syst Appl 40: pp. 272-280 CrossRef
  11. Du L, Choi KK, Lee I (2007) Robust design concept in possibility theory and optimization for system with both random and fuzzy input variables. Proceedings of the ASME 2007 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference IDETC/CIE. September 4-7, Las Vegas, Nevada, USA. pp 1183鈥?193
  12. Du, XP (2012) Robust design optimization with bivariate quality characteristics. Struct Multidisc Optim 46: pp. 187-199 CrossRef
  13. Du, X, Chen, W (2000) Towards a better understanding of modeling feasibility robustness in engineering design. ASME J Mech Des Trans 122: pp. 385-394 CrossRef
  14. Du, XP (2004) An integrated framework for optimization under uncertainty using inverse reliability strategy.. ASME J Mech Des 126: pp. 562-570 CrossRef
  15. Du, XP, Sudjianto, A, Huang, B (2005) Reliability-based design with the mixture of random and interval Variables. ASME J Mech Des 127: pp. 1068-1076 CrossRef
  16. Du, XP, Venigella, PK, Liu, D (2009) Robust mechanism synthesis with random and interval variables. Mech Mach Theory 44: pp. 1321-1337 CrossRef
  17. Gu, XG, Sun, GY, Li, GY (2013) A comparative study on multiobjective reliable and robust optimization for crashworthiness design of vehicle structure. Struct Multidisc Optim 48: pp. 669-684 CrossRef
  18. Guo, X, Bai, W, Zhang, WS, Gao, XX (2009) Confidence structural robust design and optimization under stiffness and load uncertainties. Comput Method Appl M 198: pp. 3378-3399 CrossRef
  19. Hu, WW, Azarm, S, Almansoori, A (2013) New approximation assisted multi-objective collaborative robust optimization (new AA-McRO) under interval uncertainty. Struct Multidisc Optim 47: pp. 19-35 CrossRef
  20. Huang, BQ, Du, XP (2007) Analytical robustness assessment for robust design. Struct Multidisc Optim 34: pp. 123-137 CrossRef
  21. Hwang, KH, Lee, KW, Park, GJ (2001) Robust optimization of an automobile rearview mirror for vibration reduction.. Struct Multidisc Optim 21: pp. 300-308 CrossRef
  22. Hwang KH, Park GJ (2005) Development of a robust design process using a new robustness index. Proceedings of the ASME 2005 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference IDETC/CIE2005, September 24-28, Long Beach, California, USA. pp231-241
  23. Jiang, C, Han, X, Guan, FJ, Li, YH (2007) An uncertain structural optimization method based on nonlinear interval number programming and interval analysis method. Eng Struct 29: pp. 3168-3177 CrossRef
  24. Jiang, C, Han, X, Liu, GP (2008a) A sequential nonlinear interval number programming method for uncertain structures.. Comput Method Appl M 197: pp. 4250-4265 CrossRef
  25. Jiang, C, Han, X, Liu, GP (2008b) A nonlinear interval number programming method for uncertain optimization problems. Eur J Oper Res 188: pp. 1-13 CrossRef
  26. Jiang, C, Han, X, Liu, GP (2008c) Uncertain optimization of composite laminated plates using a nonlinear interval number programming method.. Comput Struct 86: pp. 1696-1703 CrossRef
  27. Kang, Z, Luo, YJ, Li, A (2011) On non-probabilistic reliability-based design optimization of structures with uncertain-but-bounded parameters. Struct Saf 33: pp. 196-205 CrossRef
  28. Kitayama S, Yamazaki K (2014) Sequential approximate robust design optimization using radial basis function network. Int J Mech Mater Des. doi:10.1007/s10999-014-9248-z
  29. Kurpati, A, Azarm, S, Wu, J (2002) Constraint handling improvements for multiobjective genetic algorithms. Struct Multidisc Optim 23: pp. 204-213 CrossRef
  30. Lee I, Choi KK, Liu D (2006) Alternative methods for reliability-based robust design optimization including dimension reduction method. Proceedings of the ASME 2006 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference IDETC/CIE. September 10-13 Philadelphia, Pennsylvania, USA. pp 1235-1246
  31. Lee, I, Choi, KK, Liu, D, Gorsich, D (2008a) Inverse analysis method using MPP-based dimension reduction for reliability-based design optimization of nonlinear and multi-dimensional systems. Comput Method Appl M 198: pp. 14-27 CrossRef
  32. Lee I, Choi KK, Liu D, Gorsich D (2008b) Dimension reduction method for reliability-based robust design optimization. Comput Struct 86(13鈥?4):1550鈥?562
  33. Lee, SH, Chen, W, Kwak, BM (2009) Robust design with arbitrary distributions using Gauss-type quadrature formula.. Struct Multidisc Optim 39: pp. 227-243 CrossRef
  34. Li, M, Tang, WC, Yuan, M (2014) Structural dynamic topology optimization based on dynamic reliability using equivalent static loads.. Struct Multidisc Optim 49: pp. 121-129 CrossRef
  35. Liu HP, Maghsoodloo S (2011) Simulation optimization based on Taylor Kriging and evolutionary algorithm. Appl Soft Comput: 3451鈥?462
  36. Luo K, Wang JG, Du XP (2012) Robust mechanism synthesis with truncated dimension variables and interval clearance variables. Mech Mach Theory 57(11):71鈥?3
  37. Luo, YJ, Li, A, Kang, Z (2011) Reliability-based design optimization of adhesive bonded steel-concrete composite beams with probabilistic and non-probabilistic uncertainties. Eng Struct 33: pp. 2110-2119 CrossRef
  38. Maute, K, Weickum, G, Eldred, M (2009) A reduced-order stochastic finite element approach for design optimization under uncertainty.. Struct Saf 31: pp. 450-459 CrossRef
  39. Park, GJ, Lee, TH, Lee, KH, Hwang, KH (2006) Robust design: an overview.. AIAA J 44: pp. 181-191 CrossRef
  40. Park, K, Heo, SJ, Kang, DO, Jeong, JI, Yi, JH, Lee, JH, Kim, KW (2013) Robust design optimization of suspension system considering steering pull reduction. Int J Automot Techn 14: pp. 927-933 CrossRef
  41. Roy, R, Azene, YT, Farrugia, D, Onisa, C, Mehnen, J (2009) Evolutionary multi-objective design optimisation with real life uncertainty and constraints. Cirp Ann-Manuf Techn 58: pp. 169-172 CrossRef
  42. Srivastava, AK, Nema, AK (2012) Fuzzy parametric programming model for multi-objective integrated solid waste management under uncertainty. Expert Syst Appl 39: pp. 4657-4678 CrossRef
  43. Sun GY, Song XG, Baek S, Q Li (2013) Robust optimization of foam-filled thin-walled structure based on sequential Kriging metamodel. Struct Multidisc Optim. doi:10.1007/s00158-013-1017-3
  44. Tang, ZL, P茅riaux, J (2012) Uncertainty based robust optimization method for drag minimization problems in aerodynamics.. Comput Method Appl M 217-220: pp. 12-24 CrossRef
  45. Toal, DJJ, Bressloff, NW, Keane, AJ, Holden, CME (2011) The development of a hybridized particle swarm for kriging hyperparameter tuning. E Optim 43: pp. 675-699 CrossRef
  46. Tootkaboni, M, Asadpoure, A, Guest, JK (2012) Topology optimization of continuum structures under uncertainty - A Polynomial Chaos approach. Comput Method Appl M 201-204: pp. 263-275 CrossRef
  47. Vanderplaats, GN, Moses, F (1973) Structural optimization by methods of feasible directions. Computer Struct 3: pp. 739-755 CrossRef
  48. Wang, GG (2003) Adaptive response surface method using inherited Latin hypercube design points. J Mech Design 125: pp. 210-220 CrossRef
  49. Wang, WM, Peng, YH, Hu, J, Cao, ZM (2009) Collaborative robust optimization under uncertainty based on generalized dynamic constraints network. Struct Multidisc Optim 38: pp. 159-170 CrossRef
  50. Wang, XD, Hirsch, C, Liu, ZY, Kang, S, Lacor, C (2013) Uncertainty-based robust aerodynamic optimization of rotor blades. Int J Numer Meth Eng 94: pp. 111-127 CrossRef
  51. Yao, W, Chen, XQ, Luo, WC, Tooren, MV, Guo, J (2011) Review of uncertainty-based multidisciplinary design optimization methods for aerospace vehicles. Prog Aerosp Sci 47: pp. 450-479 CrossRef
  52. Youn, BD, Choi, KK (2004) A new response surface methodology for reliability-based design optimization. Comput Struct 82: pp. 241-256 CrossRef
  53. Youn BD, Choi KK, Du L, Gorsich D (2007) Integration of possibilitybased optimization and robust design for epistemic uncertainty. ASME J Mech Des 129(8):876鈥?82
  54. Zhang SL, Zhu P, Arendt PD, Chen W (2012) Extended objectiveoriented sequential sampling method for robust design of complex systems against design uncertainty. Proceedings of the ASME International Design Engineering Technical Conferences & Computers and Information in Engineering Conference IDETC/CIE 2012. August 12-15, Chicago, Illinois, USA, pp 1237鈥?246
  55. Zhao, L, Choi, KK, Lee, I (2011) Metamodeling method using dynamic Kriging for design optimization. AAIA Journal 49: pp. 2034-2046 CrossRef
  56. Zhao, L, Choi, KK, Lee, I, Gorsich, D (2013) Conservative surrogate model using weighted Kriging variance for sampling-based RBDO.. ASME J Mech Des 135: pp. 091003鈥?-10. CrossRef
  57. Zhou, YT, Jiang, C, Han, X (2006) Interval and subinterval analysis methods of the structural analysis and their error estimations. Int J Comp Meth-Sing 3: pp. 229-244 CrossRef
  
• 刊物类别：Engineering
• 刊物主题：Theoretical and Applied Mechanics
  Computer-Aided Engineering and Design
  Numerical and Computational Methods in Engineering
  Engineering Design
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1615-1488

文摘

Dynamic characteristics greatly influence the comprehensive performance of a structure. But they are rarely included as objectives in traditional robust optimization of structures. In this study, a robust optimization model including both means and standard deviations of dynamic characteristic indices in the objective and constraint functions is constructed for improving the structural dynamic characteristics and reducing their fluctuations under uncertainty. Adaptive Kriging models are employed for the efficient computation of dynamic characteristics. An intelligent resampling technology is proposed to save computational costs and accelerate convergence of Kriging models, which takes full advantage of the test points for precision verification, the sample points within the local region of the biggest relative maximum absolute error and the near-optimal point to improve the global and local precision of Krigings. The high efficiency of proposed intelligent resampling technology is demonstrated by a numerical example. Finally, an efficient algorithm integrating adaptive Kriging models, Monte Carlo (MC) method, constrained non-dominated sorting genetic algorithm (CNSGA) is proposed to solve the robust optimization model of structural dynamic characteristics. Kriging models are interfaced with MC method to efficiently compute the fitness of individuals during CNSGA. The implementation of proposed methodology is explained in detail and highlighted by the robust optimization of a cone ring fixture with lots of circumferentially distributed holes in a large turbo generator aimed at moving its natural frequencies away from the exciting one. The comparison of the optimized design with the initial one demonstrates that the proposed methodology is feasible and applicable in engineering practice.