... sampling methods for creating Kriging surrogate models in seven numerical cases and one real-world engineering case of a cutterhead of a tunnel boring machine. The results show that compared with the other four methods, the proposed sequential sampling method can more quickly and robustly create...

... of ASME 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...

... manner. In this paper, a multi-objective infilling strategy integrating the Kriging model with a two-stage infilling framework is proposed, termed as ATKIS. This method allows exploitation and exploration alternately to pinpoint the infilling solution for improving the Pareto set and avoiding local over...

...); therefore, it can also work well for multiple MPFPs and high-nonlinear problems. To release the computational burden further, the performance function is replaced with the Kriging model, and the well-known U criterion is used for its refinement. In the proposed method, the process of the refinement...

... the metamodel-based GSA method. Note that to attain sufficient accuracy, 1400 initial samples are taken along with ISC applied to confirm R 2 > 0.99 and RAAE < 0.05 for every Kriging model. Furthermore, the fused accuracy assessment indices were taken to be the weighted sum of the reserved PCA...

...Tianzeng Tao; Guozhong Zhao; Shanhong Ren To solve challenging optimization problems with time-consuming objective and constraints, a novel efficient Kriging-based constrained optimization (EKCO) algorithm is proposed in this paper. The EKCO mainly consists of three sampling phases. In phase I...

... method optimally combines the strengths of univariate dimension reduction (UDR) and kriging-based reliability analysis to achieve satisfactory accuracy with an affordable computational cost for HDRA problems. In this paper, we improve the computational efficiency of high-dimensional RBDO by pursuing two...

.... calibration identifiability model updating uncertainty quantification Kriging Gaussian processes Uncertainty is ubiquitous in engineering design. Although recent years have seen a proliferation of research in design under uncertainty [( 1 2 3 4 5 )], the majority of the uncertainty analysis...

.... M. , Korte , J. J. , and Mistree , F. , 2001 , “ Kriging Models for Global Approximation in Simulation-Based Multidisciplinary Design Optimization ,” AIAA J. , 39 ( 12 ), pp. 2233 – 2241 . 10.2514/2.1234 4 Jin , R. , Du , X. , and Chen , W. , 2003 , “ The Use...

... of these methods. For these problems it is important to devise MOGAs that can significantly reduce the number of simulation calls compared to a conventional MOGA. An improved kriging-assisted MOGA, called Circled Kriging MOGA (CK-MOGA), is presented in this paper, in which kriging metamodels are embedded within...

... to iteratively improve the fidelity and efficacy of Kriging models in the context of design decisions. The application of this approach will overcome the potential drawback in surrogate-model-based design optimization, namely, the use of surrogate models may result in suboptimal solutions due to the possible...

...V. Roshan Joseph; Ying Hung; Agus Sudjianto Kriging is a useful method for developing metamodels for product design optimization. The most popular kriging method, known as ordinary kriging, uses a constant mean in the model. In this article, a modified kriging method is proposed, which has...