Technical Notes
May 21, 2024

Practical Approach for Data-Efficient Metamodeling and Real-Time Modeling of Monopiles Using Physics-Informed Multifidelity Data Fusion

Publication: Journal of Geotechnical and Geoenvironmental Engineering
Volume 150, Issue 8

Abstract

This paper proposes a practical approach for data-efficient metamodeling and real-time modeling of laterally loaded monopiles using physics-informed multifidelity data fusion. The proposed approach fuses information from one-dimensional (1D) beam-column model analysis, three-dimensional (3D) finite element analysis, and field measurements (in order of increasing fidelity) for enhanced accuracy. It uses an interpretable scale factor–based data fusion architecture within a deep learning framework and incorporates physics-based constraints for robust predictions with limited data. The proposed approach is demonstrated for modeling monopile lateral load–displacement behavior using data from a real-world case study. Results show that the approach provides significantly more accurate predictions compared to a single-fidelity metamodel and a widely used multifidelity data fusion model. The model’s interpretability and data efficiency make it suitable for practical applications.

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Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request. The PIMFNN code is available open-source at https://github.com/autogeolab/PIMFNN/.

Acknowledgments

The second author is supported by the Royal Academy of Engineering under the Research Fellowships scheme.

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Information & Authors

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Go to Journal of Geotechnical and Geoenvironmental Engineering
Journal of Geotechnical and Geoenvironmental Engineering
Volume 150Issue 8August 2024

History

Received: Oct 18, 2023
Accepted: Mar 5, 2024
Published online: May 21, 2024
Published in print: Aug 1, 2024
Discussion open until: Oct 21, 2024

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Lecturer, Dept. of Civil and Environmental Engineering, Univ. of Strathclyde, 75 Montrose St., Glasgow G1 1XJ, UK (corresponding author). ORCID: https://orcid.org/0000-0001-5460-5089. Email: [email protected]
Brian B. Sheil
Laing O’Rourke Associate Professor in Construction Engineering, Dept. of Engineering, Univ. of Cambridge, Trumpington St., Cambridge CB2 1PZ, UK.
Bruno Stuyts
Postdoctoral Researcher, Offshore Wind Infrastructure (OWI)-Lab, Vrije Universiteit Brussel, Pleinlaan 2, Elsene, Brussels 1050, Belgium; Visiting Professor, Geotechnical Laboratory, Ghent Univ., Technologiepark 68, Ghent B-9052, Belgium.

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