Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/1467
Title: Increasing automobile crash response metamodel accuracy through adjusted cross validation error based on outlier analysis
Authors: Acar, Erdem
143688
Keywords: outlier
metamodel
automobile
surrogate model
cross validation
crash
Issue Date: 4-Mar-2015
Publisher: Taylor & Francis Ltd
Source: Acar, E. (2015). Increasing automobile crash response metamodel accuracy through adjusted cross validation error based on outlier analysis. International journal of crashworthiness, 20(2), 107-122.
Abstract: Automakers spread on effort to maintain the crashworthiness of vehicle structures while aiming to reduce their weight. Substantial weight savings can be obtained by vehicle redesign through optimisation. Finite element based crashworthiness simulation models have contributed greatly to the optimisation of vehicle structures. These high-fidelity crash simulations may be performed many times during optimisation, thereby making optimisation studies computationally intractable. Metamodels (surrogate models) that can mimic the behaviour of the crash simulation models emerge as a solution to the computational burden. Prediction capability in metamodelling can be improved by combining many different metamodels in the form of an ensemble model. In this paper, approaches based on outlier analysis of cross validation errors are proposed to increase the accuracy of ensemble models constructed for crash response predictions. Full frontal and offset frontal crash response predictions of a c-class passenger car is used for demonstration, and it is found that the proposed approach reduces the metamodelling errors up to 12% and on average by about 4.5%.
URI: https://doi.org/10.1080/13588265.2014.977839
https://hdl.handle.net/20.500.11851/1467
ISSN: 1358-8265
Appears in Collections:Makine Mühendisliği Bölümü / Department of Mechanical Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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