Probabilistic analysis of highly nonlinear models by adaptive sparse polynomial chaos: transient infiltration in unsaturated soil

Polynomial chaos expansion (PCE) is widely adopted in geotechnical engineering as a surrogate model for probabilistic analysis. However, the traditional low-order PCE may be unfeasible for unsaturated transient-state models due to the high nonlinearity. In this study, a temporal-spatial surrogate mo...

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Main Authors: Yang, Hao-qing, Yan, Yipu, Wei, Xin, Shen, Zhichao, Chen, Xiaoying
Other Authors: School of Civil and Environmental Engineering
Format: Article
Language:English
Published: 2023
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Online Access:https://hdl.handle.net/10356/168993
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1689932023-06-26T06:19:17Z Probabilistic analysis of highly nonlinear models by adaptive sparse polynomial chaos: transient infiltration in unsaturated soil Yang, Hao-qing Yan, Yipu Wei, Xin Shen, Zhichao Chen, Xiaoying School of Civil and Environmental Engineering Engineering::Civil engineering Unsaturated Soil Rainfall Polynomial chaos expansion (PCE) is widely adopted in geotechnical engineering as a surrogate model for probabilistic analysis. However, the traditional low-order PCE may be unfeasible for unsaturated transient-state models due to the high nonlinearity. In this study, a temporal-spatial surrogate model of adaptive sparse polynomial chaos expansions (AS-PCE) is established based on hyperbolic truncation with stepwise regression as surrogate models to improve computational efficiency. The uncertainty of pore water pressure of an unsaturated slope under transient-state rainfall infiltration considering hydraulic spatial variability is studied. The saturated coefficient of permeability ks is chosen to be spatial variability to account for the soil hydraulic uncertainty. The effects of location and time and the performances of AS-PCE are investigated. As rainfall goes on, the range of the pore pressure head becomes larger and the spatial variability of ks has little influence in the unsaturated zone with high matric suction. The pore pressure head under the water table suffers more uncertainty than it in the unsaturated zone. The R2 in the high matric suction zone has a trend of rising first and then falling. Except for the high matric suction zone, the R2 rise over time and they are almost 1 at the end of the time. It can be concluded that the AS-PCE performs better for low matric suction and positive pore pressure head and the fitting effect gradually increases as the rainfall progresses. The quartiles and at least up to second statistical moments can be characterized by the AS-PCE for transient infiltration in unsaturated soil slopes under rainfall. 2023-06-26T06:19:17Z 2023-06-26T06:19:17Z 2023 Journal Article Yang, H., Yan, Y., Wei, X., Shen, Z. & Chen, X. (2023). Probabilistic analysis of highly nonlinear models by adaptive sparse polynomial chaos: transient infiltration in unsaturated soil. International Journal of Computational Methods. https://dx.doi.org/10.1142/S0219876223500068 0219-8762 https://hdl.handle.net/10356/168993 10.1142/S0219876223500068 2-s2.0-85150699501 en International Journal of Computational Methods © 2023 World Scientific Publishing Company. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Civil engineering
Unsaturated Soil
Rainfall
spellingShingle Engineering::Civil engineering
Unsaturated Soil
Rainfall
Yang, Hao-qing
Yan, Yipu
Wei, Xin
Shen, Zhichao
Chen, Xiaoying
Probabilistic analysis of highly nonlinear models by adaptive sparse polynomial chaos: transient infiltration in unsaturated soil
description Polynomial chaos expansion (PCE) is widely adopted in geotechnical engineering as a surrogate model for probabilistic analysis. However, the traditional low-order PCE may be unfeasible for unsaturated transient-state models due to the high nonlinearity. In this study, a temporal-spatial surrogate model of adaptive sparse polynomial chaos expansions (AS-PCE) is established based on hyperbolic truncation with stepwise regression as surrogate models to improve computational efficiency. The uncertainty of pore water pressure of an unsaturated slope under transient-state rainfall infiltration considering hydraulic spatial variability is studied. The saturated coefficient of permeability ks is chosen to be spatial variability to account for the soil hydraulic uncertainty. The effects of location and time and the performances of AS-PCE are investigated. As rainfall goes on, the range of the pore pressure head becomes larger and the spatial variability of ks has little influence in the unsaturated zone with high matric suction. The pore pressure head under the water table suffers more uncertainty than it in the unsaturated zone. The R2 in the high matric suction zone has a trend of rising first and then falling. Except for the high matric suction zone, the R2 rise over time and they are almost 1 at the end of the time. It can be concluded that the AS-PCE performs better for low matric suction and positive pore pressure head and the fitting effect gradually increases as the rainfall progresses. The quartiles and at least up to second statistical moments can be characterized by the AS-PCE for transient infiltration in unsaturated soil slopes under rainfall.
author2 School of Civil and Environmental Engineering
author_facet School of Civil and Environmental Engineering
Yang, Hao-qing
Yan, Yipu
Wei, Xin
Shen, Zhichao
Chen, Xiaoying
format Article
author Yang, Hao-qing
Yan, Yipu
Wei, Xin
Shen, Zhichao
Chen, Xiaoying
author_sort Yang, Hao-qing
title Probabilistic analysis of highly nonlinear models by adaptive sparse polynomial chaos: transient infiltration in unsaturated soil
title_short Probabilistic analysis of highly nonlinear models by adaptive sparse polynomial chaos: transient infiltration in unsaturated soil
title_full Probabilistic analysis of highly nonlinear models by adaptive sparse polynomial chaos: transient infiltration in unsaturated soil
title_fullStr Probabilistic analysis of highly nonlinear models by adaptive sparse polynomial chaos: transient infiltration in unsaturated soil
title_full_unstemmed Probabilistic analysis of highly nonlinear models by adaptive sparse polynomial chaos: transient infiltration in unsaturated soil
title_sort probabilistic analysis of highly nonlinear models by adaptive sparse polynomial chaos: transient infiltration in unsaturated soil
publishDate 2023
url https://hdl.handle.net/10356/168993
_version_ 1772826842277871616