Reliability Assessment of Pile-Founded T-Walls Using Kriging Method
Reliability Assessment of Pile-Founded T-Walls Using Kriging Method
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DOI：
10.1061/9780784484999.032
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发表时间：
2023-07
期刊：
影响因子：
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通讯作者：
L. Zhang;Lei Wang
中科院分区：
文献类型：
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作者：
L. Zhang;Lei Wang
桩基t型墙在防洪中起着至关重要的作用。然而，目前对t型桩基础墙稳定性的研究大多采用确定性方法。然而，土的性质存在许多不确定性，忽视这些不确定性可能会高估t型桩基础墙的安全性。本文采用确定性分析和概率分析相结合的方法，对桩基础t型墙体系的稳定性评价进行了综合研究。在确定性分析中，首先按照传统方法建立了有限差分模型来评价防洪系统的稳定性，得到了不同洪水位下的安全系数。在概率分析中，明确考虑了岩土参数的不确定性。在概率评估中，建立了基于mcs的kriging代理模型，对不同洪涝灾害等级下桩基础t型墙的稳定性进行了预测。基于kriging的代理模型可以用其输入参数逼近有限差分解，提高了概率评估的计算效率。以层状地基上的桩基础t型墙设计为例，验证了该框架的有效性。研究结果可对不同水位下的破坏概率及安全系数进行关键性评价，为风险决策提供依据。
The pile-founded T-walls play a vital role in flood protection. However, most of the current studies on the stability of pile-founded T-walls are performed using a deterministic approach. However, many uncertainties exist in the soil properties, and neglecting these uncertainties might overestimate the safety of the pile-founded T-walls. This paper presents a comprehensive study on the stability assessment of pile-founded T-wall systems using both deterministic analysis and probabilistic analysis. In the deterministic analysis, a finite difference model is first developed to evaluate the stability of the flood protection system following the traditional procedures, in which the factors of safety under different flooding levels are obtained. In probabilistic analysis, the uncertainties in geotechnical parameters are explicitly considered. In the probabilistic assessment, an MCS-based kriging surrogate model is formulated to predict the stability of the pile-founded T-wall under different flooding hazard levels. The kriging-based surrogate model can approximate the finite difference solutions with its input parameters, which improves the computational efficiency of the probabilistic assessment. A case study of the pile-founded T-wall design resting on layered foundation soils is used to demonstrate the effectiveness of the proposed framework. The results can lead to a critical evaluation of the probability of failure in addition to the factor of safety under different flood water levels, which can provide information for risk-informed decision-making.