... on the analysis and experimental results of similarity metrics, a guide to choosing the desirable similarity measures which result in the most accurate and efficient results for the Kriging model with respect to different sample sizes and dimension levels is provided in this paper. kriging surrogate model...

... metamodeling techniques that encompass design of experiments, response surface methodology, Taguchi methods, neural networks, inductive learning, and kriging. We discuss their existing applications in engineering design and then address the dangers of applying traditional statistical techniques to approximate...

... accuracy for optimization when used as global approximations. structural design global approximation spatial correlation metamodels kriging Proceedings of DETC98 1998 ASME Design Engineering Technical Conference September 13-16, 1998, Atlanta, GA R G T . A tio Me of 03 metamodels can produce...

... a single variable function, we compare and contrast the use of response surface models and kriging models for approximating non-random, deterministic computer analyses in robust design with large variances of design variables in a highly nonlinear design space. Our preliminary conclusions are: 1) kriging...

... Abstract In this paper we discuss the performance of different metamodeling techniques in Type II robust design. Five space-filling experimental designs and five correlation functions are compared in their capability for developing accurate kriging models. We observe that in our case study...

... adopts the decoupled formulation and it applies the Kriging technique to quantify the metamodeling uncertainty. The polynomial chaos expansion (PCE) technique is applied to propagate the two types of uncertainties and represent the interdisciplinary consistency constraints. In the optimization approach...

..., then a Kriging model is used to interpolate the LSF values within the rest of the domain so that classification into material or void can be performed. Perceived advantages of the explicit level-set (ELS) approach include alleviating the need for gradients of objectives and constraints, while maintaining...

... that the proposed method can mitigate the effect of both metamodeling uncertainty and design uncertainty, and more efficiently identify the robust solution compared to the one-stage sampling approach that is commonly used in practice. Objective-oriented sequential sampling method Kriging robust design...

...-of-magnitude improvements in metamodel accuracy. Metamodels Kriging Design Optimization Knowledge Variable Fidelity 1 Copyright © 2010 by ASME Proceedings of the ASME 2010 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference IDETC/CIE 2010...

... Surrogate Models Preliminary Design Kriging Multi-Stage Bayesian Surrogates Metamodels Response Surfaces Space-Time Process During the early stages of the design process, designers rarely have accurate models of system behavior, yet the success of their designs depends...

... Kriging Metamodel Maximum Likelihood Estimation Cross-Validation Metamodel Error Assessment The use of kriging models for approximation and metamodel-based design and optimization has been steadily on the rise in the past decade. The widespread usage of kriging models appears...

... Kriging Metamodels Computer Experiments Cross-Validation The use of kriging models for approximation and global optimization has been steadily on the rise in the past decade. The standard approach used in the Design and Analysis of Computer Experiments (DACE) is to use an Ordinary...

... kriging metamodel computer experiment penalized likelihood smoothly clipped absolute deviation (SCAD) fisher scoring algorithm Kriging is a popular metamodeling technique for analysis of computer experiment. However, the likelihood function near the optimum is flat in some situations...

... Support Vector Regression Support Vector Machines Kriging Response Surfaces Metamodels A variety of metamodeling techniques have been developed in the past decade to reduce the computational expense of computer-based analysis and simulation codes. Metamodeling is the process...

... Simulation-Based Design Decision-Based Design Multi-Objective Design Optimization Finite Element Analysis Tradeoff Surrogate model Kriging Coronary Artery Stent Variations associated with stenting systems, artery properties, and doctor skills necessitate a better understanding...

... of Kriging models. A potential drawback of using preference-based surrogate models in simulation based design is that the surrogates may misrepresent the true optima if the model building schemes fail to capture the critical points of interest with enough fidelity or clarity. This work addresses...