...@zju.edu.cn design of experiments design optimization design theory metamodeling multidisciplinary design and optimization product design simulation-based design Accepted Manuscript Not Copyedited Journal of Mechanical Design. Received August 15, 2023; Accepted manuscript posted November 19...

.... In this paper, we integrate the novel Latent Variable Gaussian Process (LVGP) with Sobol' analysis to develop the first metamodel-based mixed-variable GSA method. Through numerical case studies, we validate and demonstrate the effectiveness of our proposed method for mixed-variable problems. Furthermore, while...

... Contributed by the Design Automation Committee of ASME for publication in the J ournal of M echanical D esign . 09 08 2023 20 10 2023 26 10 2023 16 11 2023 design automation metamodeling simulation-based design uncertainty analysis Accepted Manuscript Not Copyedited...

...: chris.hoyle@oregonstate.edu Contributed by the Design Automation Committee of ASME for publication in the J ournal of M echanical D esign . 20 01 2023 23 10 2023 24 10 2023 13 11 2023 design optimization interactive design machine learning metamodeling...

... or design team experiments. 31 08 2022 13 07 2023 14 07 2023 29 08 2023 design of experiments design optimization machine learning metamodeling Directorate for Engineering 10.13039/100000084 1826083 Beyond our main empirical result, our improvements...

...: More Flexible and Effective Metamodeling ,” AIAA J. , 43 ( 6 ), pp. 1306 – 1315 . 10.2514/1.11292 [9] Xu , H. , Zhang , W. , Zhou , N. , Xiao , L. , and Zhang , J. , 2022 , “ An Active Learning Kriging Model With Adaptive Parameters for Reliability Analysis ,” Eng...

... 12 2022 07 07 2023 10 07 2023 16 08 2023 ensemble of surrogate models adaptive weight strategy median metamodeling Ministry of Science and Technology of the People's Republic of China 10.13039/501100002855 2018YFB1700704 National Natural Science Foundation...

... optimization multi-objective optimization Gaussian process acquisition function data-driven design design optimization machine learning metamodeling simulation-based design The distinct treatment of dominated designs adopted by AFs, such as the EEI function and the proposed approach, generates...

... for publication in the J ournal of M echanical D esign . 27 01 2023 23 05 2023 25 05 2023 18 07 2023 time-dependent reliability analysis surrogate model digital twin expansion optimal linear estimation adaptive sampling strategy kriging metamodeling reliability in design...

... ), pp. 399 – 414 . 10.1007/s00158-018-2031-2 [43] Jin , R. , Chen , W. , and Simpson , T. W. , 2001 , “ Comparative Studies of Metamodelling Techniques Under Multiple Modelling Criteria ,” Struct. Multidiscip. Optim. , 23 ( 1 ), pp. 1 – 13 . 10.1007/s00158-001-0160-4 [44...

...Jie Liu; Yue Zhao; Fei Lei; Fei Ding Metamodel technology provides an efficient method to approximate complex engineering design problems. However, the approximation for high-dimensional problems usually requires a large number of samples for most traditional metamodeling methods, which leads...

... side function surrogate model dynamic hybrid sampling hypercube shrinking approximation-based optimal design metamodeling Direct transcription [ 43 ] is a “discretize–then–optimize” approach for DOP, and it transcribes the infinite-dimensional DOP into a large sparse finite-dimensional NLP...

... approximation-based optimal design design optimization machine learning metamodeling multi-objective optimization Two fundamental challenges exist for a complex simulation-based optimization problem: (1) long simulation time and (2) expensive constraints. Finite element analysis (FEA) and other...

... of ASME for publication in the J ournal of M echanical D esign . 02 07 2022 01 02 2023 06 02 2023 17 05 2023 multidisciplinary analysis derivative-based global sensitivity measures multifidelity kriging metamodeling multidisciplinary design and optimization...

... National Laboratories 10.13039/100006234 LDRD approximation-based optimal design design of experiments metamodeling space-filling design 02 04 2022 30 01 2023 02 02 2023 15 03 2023 Tuo et al.’s model is more flexible than the KOH model because each simulation...

.... , 2006 , “ Single- and Multiobjective Evolutionary Optimization Assisted by Gaussian Random Field Metamodels ,” IEEE Trans. Evol. Comput. , 10 ( 4 ), pp. 421 – 439 . 10.1109/TEVC.2005.859463 [20] Gutmann , H. M. , 2001 , “ A Radial Basis Function Method for Global Optimization ,” J...

... interpretation of when maintenance may need to be performed [ 8 , 9 ]. ensemble remaining useful life lithium-ion batteries rolling element bearings machine learning metamodeling 03 07 2022 14 10 2022 29 10 2022 24 11 2022 Contributed by the Design Automation Committee...

... Corresponding author. Email: raminb@uci.edu Contributed by the Design Automation Committee of ASME for publication in the J ournal of M echanical D esign . Gaussian processes calibration multiscale simulations reduced-order model microstructural uncertainties machine learning metamodeling...

... J. Mech. Des. , 135 ( 1 ), p. 011009 . 10.1115/1.4022999 [31] Li , M. , Li , G. , and Azarm , S. , 2008 , “ A Kriging Metamodel Assisted Multi-objective Genetic Algorithm for Design Optimization ,” ASME J. Mech. Des. , 130 ( 3 ), p. 031401 . 10.1115/1.2829879 [32...

... [22] Zhang , J. , Taflanidis , A. A. , and Medina , J. C. , 2017 , “ Sequential Approximate Optimization for Design Under Uncertainty Problems Utilizing Kriging Metamodeling in Augmented Input Space ,” Comput. Methods Appl. Mech. Eng. , 315 , pp. 369 – 395 . 10.1016/j.cma...