Data-driven analysis of soil consolidation with prefabricated vertical drains considering stratigraphic variation
In coastal cities such as Hong Kong, rapid reclamation using prefabricated vertical drains (PVDs) is preferred as it can accelerate land supply to meet the urgent demand for houses. A robust PVD design relies on the correct identification of permeable soil layers and accurate delineation of their st...
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sg-ntu-dr.10356-1699152023-08-15T01:52:53Z Data-driven analysis of soil consolidation with prefabricated vertical drains considering stratigraphic variation Wang, Yu Shi, Chao School of Civil and Environmental Engineering Engineering::Civil engineering Stochastic Simulation Risk Management In coastal cities such as Hong Kong, rapid reclamation using prefabricated vertical drains (PVDs) is preferred as it can accelerate land supply to meet the urgent demand for houses. A robust PVD design relies on the correct identification of permeable soil layers and accurate delineation of their stratigraphic connectivity with surrounding drainage boundaries. The current engineering practice often ignores the physical locations of minor drainage boundaries (e.g., sand lenses) in the subsurface stratigraphy and might lead to a false interpretation of potential drainage and consolidation mechanisms. In this study, a data-driven analysis framework that takes stratigraphic uncertainty into consideration is proposed to investigate the spatiotemporal consolidation of PVD-improved ground using sparse site investigation data often encountered in engineering practice. The method adaptively develops multiple geological cross-sections from limited measurements and prior knowledge that is reflected by a single training image. The resulting multiple geological realizations serve as the input for PVD analysis. The proposed data-driven framework allows for a probabilistic evaluation of soil spatiotemporal behavior in terms of the degree of consolidation and future ground settlement. More importantly, the proposed method accurately predicts the spatial distribution of stratigraphic boundaries with quantified uncertainty, which significantly influences the consolidation mechanism. Ministry of Education (MOE) Nanyang Technological University The work described in this paper was supported by a grant from the Research Grant Council of Hong Kong Special Administrative Region (Project no. CityU 11202121), a grant from the Innovation and Technology Commission of Hong Kong Special Administrative Region (Project No: MHP/099/21), and a grant from Shenzhen Science and Technology Innovation Commission (Shenzhen-Hong Kong-Macau Science and Technology Project (Category C) No: SGDX20210823104002020), China. The research was also supported by the Ministry of Education, Singapore, under its Academic Research Fund (AcRF) Tier 1 Seed Funding Grant (Project no. RS03/23) and the Startup grant from Nanyang Technological University. 2023-08-15T01:52:53Z 2023-08-15T01:52:53Z 2023 Journal Article Wang, Y. & Shi, C. (2023). Data-driven analysis of soil consolidation with prefabricated vertical drains considering stratigraphic variation. Computers and Geotechnics, 161, 105569-. https://dx.doi.org/10.1016/j.compgeo.2023.105569 0266-352X https://hdl.handle.net/10356/169915 10.1016/j.compgeo.2023.105569 2-s2.0-85162095156 161 105569 en RS03/23 NTU-SUG Computers and Geotechnics © 2023 Elsevier Ltd. All rights reserved. |
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Engineering::Civil engineering Stochastic Simulation Risk Management Wang, Yu Shi, Chao Data-driven analysis of soil consolidation with prefabricated vertical drains considering stratigraphic variation |
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In coastal cities such as Hong Kong, rapid reclamation using prefabricated vertical drains (PVDs) is preferred as it can accelerate land supply to meet the urgent demand for houses. A robust PVD design relies on the correct identification of permeable soil layers and accurate delineation of their stratigraphic connectivity with surrounding drainage boundaries. The current engineering practice often ignores the physical locations of minor drainage boundaries (e.g., sand lenses) in the subsurface stratigraphy and might lead to a false interpretation of potential drainage and consolidation mechanisms. In this study, a data-driven analysis framework that takes stratigraphic uncertainty into consideration is proposed to investigate the spatiotemporal consolidation of PVD-improved ground using sparse site investigation data often encountered in engineering practice. The method adaptively develops multiple geological cross-sections from limited measurements and prior knowledge that is reflected by a single training image. The resulting multiple geological realizations serve as the input for PVD analysis. The proposed data-driven framework allows for a probabilistic evaluation of soil spatiotemporal behavior in terms of the degree of consolidation and future ground settlement. More importantly, the proposed method accurately predicts the spatial distribution of stratigraphic boundaries with quantified uncertainty, which significantly influences the consolidation mechanism. |
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School of Civil and Environmental Engineering |
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School of Civil and Environmental Engineering Wang, Yu Shi, Chao |
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Article |
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Wang, Yu Shi, Chao |
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Wang, Yu |
title |
Data-driven analysis of soil consolidation with prefabricated vertical drains considering stratigraphic variation |
title_short |
Data-driven analysis of soil consolidation with prefabricated vertical drains considering stratigraphic variation |
title_full |
Data-driven analysis of soil consolidation with prefabricated vertical drains considering stratigraphic variation |
title_fullStr |
Data-driven analysis of soil consolidation with prefabricated vertical drains considering stratigraphic variation |
title_full_unstemmed |
Data-driven analysis of soil consolidation with prefabricated vertical drains considering stratigraphic variation |
title_sort |
data-driven analysis of soil consolidation with prefabricated vertical drains considering stratigraphic variation |
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2023 |
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https://hdl.handle.net/10356/169915 |
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1779156649922002944 |