A reduced order model framework suitable for geotechnical problems [dataset]

Ouyang, Mao (Durham University, UK); Knappett, Jonathan (University of Oxford, UK); Coombs, William M. (Durham University, UK); Petalas, Alexandors (Durham University, UK); Brown, Michael (University of Dundee, UK); Augarde, Charles E. (Durham University, UK); Alagha, Ahmed (University of Dundee, UK)

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A reduced order model framework suitable for geotechnical problems [dataset] Open Access

Data-driven methods are of increasing popularity for solving problems in geotechnics, offering as they do, the possibility of high-fidelity results without the effort of a detailed deterministic numerical analysis (e.g. using finite elements). A wide range of approaches fall under the heading of Reduced Order Models (ROMs) which are created by processing data generated from high-fidelity models. The quality of these ROMs, and the computational cost of their construction, themselves depend heavily on the architecture chosen. In this study, we introduce a set of efficient frameworks for data-driven ROMs that can be applied to geotechnics problems in general. Our approach employs autoencoders and/or principal component analysis to reduce data dimensionality and to extract latent representations, followed by a Deep Operator Network (DeepONet) to learn nonlinear behaviour within this latent space. The architectures are demonstrated on the problem of the prediction of spatio-temporal responses in soil consolidation, and we demonstrate that the proposed efficient ROM architectures accurately predict responses for a range of problem specifications. The proposed framework provides a versatile methodology for large-scale complex geotechnical modelling applications.

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Resource type: Dataset
Contributors: Creator: Ouyang, Mao ¹
Augarde, Charles E. ¹
Coombs, William M. ¹
Petalas, Alexandors ¹
Knappett, Jonathan ²
Brown, Michael ³
Alagha, Ahmed ³

¹ Durham University, UK
² University of Oxford, UK
³ University of Dundee, UK
Funder: Engineering and Physical Sciences Research Council
Research methods
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Subject: Geotechnical engineering
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Identifier: ark:/32150/r1k930bx126
doi:10.15128/r1k930bx126
Rights: Creative Commons Attribution 4.0 International (CC BY)
Publisher: Durham University
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