概率逻辑
不确定度分析
帧(网络)
结构工程
不确定度量化
无知
概率方法
阶段(地层学)
发掘
梁(结构)
算法的概率分析
计算机科学
工程类
岩土工程
地质学
人工智能
模拟
机器学习
机械工程
哲学
认识论
古生物学
作者
Jinyan Zhao,Stefan Ritter,Matthew J. DeJong
标识
DOI:10.1016/j.tust.2022.104499
摘要
Current early stage assessment methods for deep excavation induced structural damage have large uncertainty due to modeling idealizations (simplification in analyses) and ignorance (incompleteness of information). This paper implements an elastoplastic two-stage solution of soil-structure-interaction to predict building response to adjacent deep excavations with braced supports. This soil-structure-interaction solution is then used to study the uncertainty in two case studies. A global sensitivity analysis is conducted, which indicates that the prediction of ground movement profiles is the major source of uncertainty in early stage building damage assessment. The uncertainty due to ignorance and idealizations related to structural analysis models also contribute significantly when target buildings are modeled as equivalent beams. However, the use of a 2-dimensional elastic frame structural model, in lieu of an equivalent beam, considerably reduces the assessment uncertainty. Considering the existence of uncertainty, a probabilistic analysis approach is proposed to quantify the uncertainty when predicting potential building damage due to excavation-induced subsidence. A computer program called Uncertainty Quantification in Excavation-Structure Interaction (UQESI) is developed to implement this probabilistic analysis approach.
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