Using meta-models as fast and accurate predictors of a reconfigurable mould system

Esben T. Christensen*, Alexander I J Forrester, Erik Lund, Esben Lindgaard

*Corresponding author for this work

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

Abstract

In this paper methods from the meta- or surrogate modeling literature are used to build models for predicting the response of a reconfigurable mould system. The proposed methods are difference methods constructed from the methods kriging and proper orthogonal decomposition (POD) together with a spline-based coarse model. Four different models, namely kriging and POD with kriging of the coefficients in global and local variants, are compared in terms of accuracy and numerical efficiency on data sets of different sizes. It is shown that the POD methods are vastly superior for the treated problem.

Original languageEnglish
Title of host publicationAdvanced Manufacturing
Volume2B-2015
PublisherAmerican Society of Mechanical Engineers
Publication date1 Jan 2015
ISBN (Electronic)9780791857366
DOIs
Publication statusPublished - 1 Jan 2015
EventASME 2015 International Mechanical Engineering Congress and Exposition, IMECE 2015 - Houston, United States
Duration: 13 Nov 201519 Nov 2015

Conference

ConferenceASME 2015 International Mechanical Engineering Congress and Exposition, IMECE 2015
Country/TerritoryUnited States
CityHouston
Period13/11/201519/11/2015
SponsorAmerican Society of Mechanical Engineers (ASME)

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