Reliability analysis of unsaturated slope stability considering SWCC model selection and parameter uncertainties
Reliability analysis of unsaturated slope stability considering SWCC model selection and parameter uncertainties
复制标题
考虑SWCC模型选择和参数不确定性的非饱和边坡稳定性可靠度分析
DOI：
10.1016/j.enggeo.2019.105207
复制
发表时间：
2019-10-03
影响因子：
7.4
通讯作者：
Qi, Xiao-Hui
中科院分区：
文献类型：
--
作者：
Li, Dian-Qing;Wang, Lin;Qi, Xiao-Hui
土-水特征曲线（SWCC）通常通过对有限数量的试验数据拟合指定的参数模型来估计。由于试验数据的缺乏，SWCC估算中的不确定性是不可避免的，包括选择参数模型所产生的不确定性和拟合参数的不确定性。在贝叶斯模型平均（BMA）框架下，提出了一种非饱和边坡可靠度分析方法。所提出的方法帐户，同时，SWCC参数的不确定性和模型选择的不确定性，并允许脱落光对非饱和边坡可靠性分析的影响。通过一个非饱和切坡算例说明了该方法的有效性。结果表明，有限数量的土水混合特性试验数据，明确量化的土水混合特性参数的不确定性提供了更多的洞察土水混合特性的变异性相比，只考虑最佳拟合的试验数据。更重要的是，当只有有限数量的测试数据可用时，模型选择的不确定性可能相当大。在这种情况下，押注于单一模型可能会导致对非饱和边坡破坏概率的不正确估计。相反，所提出的方法提供了一个独立于模型的非饱和边坡破坏概率的估计，是不太敏感的SWCC模型之间的候选池的选择。
Soil-water characteristic curve (SWCC) is usually estimated by fitting a prescribed parametric model to a limited number of test data. Uncertainties in estimated SWCC are unavoidable due to a lack of test data, including uncertainty arising from selecting a parametric model and uncertainty in fitting parameters. This paper develops a reliability analysis approach for unsaturated slope under the Bayesian model averaging (BMA) framework. The proposed approach accounts, simultaneously, for SWCC parameter uncertainty and model selection uncertainty, and allows shedding light on their effects on unsaturated slope reliability analysis. The proposed approach is illustrated through an unsaturated cut slope example. Results show that, with a limited number of SWCC test data, explicit quantification of SWCC parameter uncertainty provides more insights into the variability of SWCC in comparison with only considering the best-fit of test data. More importantly, the model selection uncertainty might be considerably large when only a limited number of test data is available. In such a case, betting on a single model might result in an improper estimate of unsaturated slope failure probability. On the contrary, the proposed approach provides a model-independent estimate of unsaturated slope failure probability that is less sensitive to the selection of SWCC model among the pool of candidates.