## Details

Original language | English |
---|---|

Pages (from-to) | 3313-3326 |

Number of pages | 14 |

Journal | Engineering with computers |

Volume | 39 |

Issue number | 5 |

Early online date | 7 Nov 2022 |

Publication status | Published - Oct 2023 |

## Abstract

Risk assessment of earth dams is concerned not only with the probability of failure but also with the corresponding consequence, which can be more difficult to quantify when the spatial variability of soil properties is involved. This study presents a risk assessment for an earth dam in spatially variable soils using the random adaptive finite element limit analysis. The random field theory, adaptive finite element limit analysis, and Monte Carlo simulation are employed to implement the entire process. Among these methods, the random field theory is first introduced to describe the soil spatial variability. Then the adaptive finite element limit analysis is adopted to obtain the bound solution and consequence. Finally, the failure probability and risk assessment are counted via the Monte Carlo simulation. In contrary to the deterministic analysis that only a factor of safety is given, the stochastic analysis considering the spatial variability can provide statistical characteristics of the stability and assess the risk of the earth dam failure comprehensively, which can be further used for guiding decision-making and mitigation. Besides, the effects of the correlation structure of strength parameters on the stochastic response and risk assessment of the earth dam are investigated through parametric analysis.

## Keywords

- Monte Carlo simulation, Random adaptive finite element limit analysis, Random field theory, Risk assessment, Spatial variability

## ASJC Scopus subject areas

- Computer Science(all)
**Software**- Mathematics(all)
**Modelling and Simulation****Engineering(all)**- Computer Science(all)
**Computer Science Applications**

## Cite this

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- RIS

**Probabilistic risk assessment of earth dams with spatially variable soil properties using random adaptive finite element limit analysis.**/ Liao, Kang; Wu, Yiping; Miao, Fasheng et al.

In: Engineering with computers, Vol. 39, No. 5, 10.2023, p. 3313-3326.

Research output: Contribution to journal › Article › Research › peer review

*Engineering with computers*, vol. 39, no. 5, pp. 3313-3326. https://doi.org/10.1007/s00366-022-01752-0

*Engineering with computers*,

*39*(5), 3313-3326. https://doi.org/10.1007/s00366-022-01752-0

}

TY - JOUR

T1 - Probabilistic risk assessment of earth dams with spatially variable soil properties using random adaptive finite element limit analysis

AU - Liao, Kang

AU - Wu, Yiping

AU - Miao, Fasheng

AU - Pan, Yutao

AU - Beer, Michael

N1 - Funding Information: This research is supported by the National Natural Science Foundation of China (No. 41977244 and No. 42007267). The first author is supported by China Scholarship Council (CSC) as a visiting scholar at the Leibniz University Hannover, under grant No. 202006410089. All support are gratefully acknowledged.

PY - 2023/10

Y1 - 2023/10

N2 - Risk assessment of earth dams is concerned not only with the probability of failure but also with the corresponding consequence, which can be more difficult to quantify when the spatial variability of soil properties is involved. This study presents a risk assessment for an earth dam in spatially variable soils using the random adaptive finite element limit analysis. The random field theory, adaptive finite element limit analysis, and Monte Carlo simulation are employed to implement the entire process. Among these methods, the random field theory is first introduced to describe the soil spatial variability. Then the adaptive finite element limit analysis is adopted to obtain the bound solution and consequence. Finally, the failure probability and risk assessment are counted via the Monte Carlo simulation. In contrary to the deterministic analysis that only a factor of safety is given, the stochastic analysis considering the spatial variability can provide statistical characteristics of the stability and assess the risk of the earth dam failure comprehensively, which can be further used for guiding decision-making and mitigation. Besides, the effects of the correlation structure of strength parameters on the stochastic response and risk assessment of the earth dam are investigated through parametric analysis.

AB - Risk assessment of earth dams is concerned not only with the probability of failure but also with the corresponding consequence, which can be more difficult to quantify when the spatial variability of soil properties is involved. This study presents a risk assessment for an earth dam in spatially variable soils using the random adaptive finite element limit analysis. The random field theory, adaptive finite element limit analysis, and Monte Carlo simulation are employed to implement the entire process. Among these methods, the random field theory is first introduced to describe the soil spatial variability. Then the adaptive finite element limit analysis is adopted to obtain the bound solution and consequence. Finally, the failure probability and risk assessment are counted via the Monte Carlo simulation. In contrary to the deterministic analysis that only a factor of safety is given, the stochastic analysis considering the spatial variability can provide statistical characteristics of the stability and assess the risk of the earth dam failure comprehensively, which can be further used for guiding decision-making and mitigation. Besides, the effects of the correlation structure of strength parameters on the stochastic response and risk assessment of the earth dam are investigated through parametric analysis.

KW - Monte Carlo simulation

KW - Random adaptive finite element limit analysis

KW - Random field theory

KW - Risk assessment

KW - Spatial variability

UR - http://www.scopus.com/inward/record.url?scp=85141426141&partnerID=8YFLogxK

U2 - 10.1007/s00366-022-01752-0

DO - 10.1007/s00366-022-01752-0

M3 - Article

AN - SCOPUS:85141426141

VL - 39

SP - 3313

EP - 3326

JO - Engineering with computers

JF - Engineering with computers

SN - 0177-0667

IS - 5

ER -