... worst case is smaller than before. Except for AA-MORO's consistency, the proposed approach for the 50-variable case seems to outperform AA-MORO. This improved relative performance with problem size is most likely due to the different balancing of exploring and exploiting the surrogate models. AA-MORO...

...Jeong Woo Park; Ikjin Lee In engineering applications of sampling-based reliability-based design optimization (RBDO), the Monte Carlo simulation (MCS) using a surrogate model of the performance function is mainly used for the probability of failure calculation and sensitivity analysis. However...

...-based and manufacturing constraints. Finally, the model accuracy with frequentist, Bayesian and without MLR-based calibration are compared to true Pareto solutions. Bayesian optimization surrogate modeling multi-objective optimization weighted Tchebycheff Bayesian regression metamodeling stress...

...Yongsu Jung; Kyeonghwan Kang; Hyunkyoo Cho; Ikjin Lee Even though many efforts have been devoted to effective strategies to build accurate surrogate models, surrogate model uncertainty is inevitable due to a limited number of available simulation samples. Therefore, the surrogate model uncertainty...

... uncertainty quantification surrogate modeling simulation-based design Sampling of computer simulations is a well-studied subject in the field of simulation-based design with applications in engineering [ 1 ], biological [ 2 ], and social sciences [ 3 ]. These research efforts have driven...

...Andrew L. Kaminsky; Yi Wang; Kapil Pant Surrogate models can be used to approximate complex systems at a reduced cost and are widely used when data generation is expensive or time consuming. The accuracy of these models is dependent on the samples used to create them. Therefore, proper sample...

...Jie Zhang; Souma Chowdhury; Ali Mehmani; Achille Messac Both global and local error measure metrics were used to assess the accuracy of surrogate models. In this paper, the leave-one-out cross-validation errors at all training points were used as local error measures. When compared with errors...

... model of simulations of multistage assembly processes. At the heart of this approach is a multiple-input-multiple-output surrogate modeling framework that uses a recently developed integrated emulation technique. The unique feature of this technique is that the surrogate models for multiple outputs...

... Power Switch Modules Aeronautic Applications Finite Elements Modeling Surrogate Modeling Lifetime Analysis Structural Reliability One of the current trends in the aircraft industry is the increasing use of electrical systems in replacement of mechanical, hydraulic, and pneumatic ones...

..., and surrogate models to arrive at robust designs on a limited computational budget. The multiobjective formulation used here allows explicit trade-off between the mean and variance of the performance to be carried out. Detailed numerical studies are presented for robust geometric design of a typical compressor...