Physics-Based Surrogate Modeling Using Response Correction

Slawomir Koziel and Leifur Leifsson
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Slawomir Koziel: Reykjavik University, Engineering Optimization & Modeling Center
Leifur Leifsson: Iowa State University, Department of Aerospace Engineering

Chapter Chapter 12 in Simulation-Driven Design by Knowledge-Based Response Correction Techniques, 2016, pp 211-243 from Springer

Abstract: Abstract The surrogate modeling and response correction techniques considered in this book were mostly discussed in the context of design optimization. In such a setup, the primary purpose of the surrogate is to ensure good local alignment with the high-fidelity model, whereas global accuracy of the model is not of a major concern. In a more general setting, i.e., global or quasi-global modeling, the surrogate is to be valid within a larger portion of the design space. This is important for creating multiple-use library models and applications such as statistical analysis, uncertainty quantification, or global optimization. This chapter describes approaches to quasi-global surrogate modeling using physics-based surrogates and response correction techniques. Formulation of the modeling problem is followed by a discussion of global modeling using space mapping, and space mapping enhanced by function approximation layers, as well as surrogate modeling with the shape-preserving response prediction. Finally, feature-based modeling for statistical design is described. The chapter ends with summary and discussion.

Keywords: Characteristic Point; Lift Coefficient; Training Point; Kriging Interpolation; Nominal Design (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-30115-0_12

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DOI: 10.1007/978-3-319-30115-0_12

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