Gaussian Processes enabled model calibration in the context of deep geological disposal
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866918017880817664 |
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| author | Paul, Lennart Urrea-Quintero, Jorge-Humberto Fiaz, Umer Hussein, Ali Yaghi, Hazem Wessels, Henning Römer, Ulrich Stahlmann, Joachim |
| author_facet | Paul, Lennart Urrea-Quintero, Jorge-Humberto Fiaz, Umer Hussein, Ali Yaghi, Hazem Wessels, Henning Römer, Ulrich Stahlmann, Joachim |
| contents | Deep geological repositories are critical for the long-term storage of hazardous materials, where understanding the mechanical behavior of emplacement drifts is essential for safety assurance. This study presents a surrogate modeling approach for the mechanical response of emplacement drifts in rock salt formations, utilizing Gaussian Processes (GPs). The surrogate model serves as an efficient substitute for high-fidelity mechanical simulations in many-query scenarios, including time-dependent sensitivity analyses and calibration tasks. By significantly reducing computational demands, this approach facilitates faster design iterations and enhances the interpretation of monitoring data. The findings indicate that only a few key parameters are sufficient to accurately reflect in-situ conditions in complex rock salt models. Identifying these parameters is crucial for ensuring the reliability and safety of deep geological disposal systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_02576 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Gaussian Processes enabled model calibration in the context of deep geological disposal Paul, Lennart Urrea-Quintero, Jorge-Humberto Fiaz, Umer Hussein, Ali Yaghi, Hazem Wessels, Henning Römer, Ulrich Stahlmann, Joachim Geophysics Data Analysis, Statistics and Probability Deep geological repositories are critical for the long-term storage of hazardous materials, where understanding the mechanical behavior of emplacement drifts is essential for safety assurance. This study presents a surrogate modeling approach for the mechanical response of emplacement drifts in rock salt formations, utilizing Gaussian Processes (GPs). The surrogate model serves as an efficient substitute for high-fidelity mechanical simulations in many-query scenarios, including time-dependent sensitivity analyses and calibration tasks. By significantly reducing computational demands, this approach facilitates faster design iterations and enhances the interpretation of monitoring data. The findings indicate that only a few key parameters are sufficient to accurately reflect in-situ conditions in complex rock salt models. Identifying these parameters is crucial for ensuring the reliability and safety of deep geological disposal systems. |
| title | Gaussian Processes enabled model calibration in the context of deep geological disposal |
| topic | Geophysics Data Analysis, Statistics and Probability |
| url | https://arxiv.org/abs/2409.02576 |