Gardner, P., Rogers, T.J., Lord, C. orcid.org/0000-0002-2470-098X et al. (1 more author) (2018) Sparse Gaussian Process Emulators for surrogate design modelling. Applied Mechanics and Materials, 885. pp. 18-31. ISSN 1660-9336
Abstract
Efficient surrogate modelling of computer models (herein defined as simulators) becomes of increasing importance as more complex simulators and non-deterministic methods, such as Monte Carlo simulations, are utilised. This is especially true in large multidimensional design spaces. In order for these technologies to be feasible in an early design stage context, the surrogate model (oremulator) must create an accurate prediction of the simulator in the proposed design space. Gaussian Processes (GPs) are a powerful non-parametric Bayesian approach that can be used as emulators. The probabilistic framework means that predictive distributions are inferred, providing an understanding of the uncertainty introduced by replacing the simulator with an emulator, known as code uncertainty. An issue with GPs is that they have a computational complexity of O(N3) (where N is the number of data points), which can be reduced to O(NM2) by using various sparse approximations, calculated from a subset of inducing points (where M is the number of inducing points). This paper explores the use of sparse Gaussian process emulators as a computationally efficient method for creating surrogate models of structural dynamics simulators. Discussions on the performance of these methods are presented along with comments regarding key applications to the early design stage.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 Trans Tech Publications, Switzerland. This is an open access article under the CC-BY 4.0 license (https://creativecommons.org/licenses/by/4.0/) |
Keywords: | Gaussian process; Sparse Gaussian process; Kriging; Emulator; Surrogate Modelling. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield) |
Funding Information: | Funder Grant number ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL (EPSRC) EP/N010884/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 27 Feb 2019 10:23 |
Last Modified: | 25 Jun 2023 21:41 |
Published Version: | https://doi.org/10.4028/www.scientific.net/amm.885... |
Status: | Published |
Publisher: | Trans Tech Publications |
Refereed: | Yes |
Identification Number: | 10.4028/www.scientific.net/amm.885.18 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:141998 |
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