检索结果-南通市图书馆

A Bayesian multi-model inference methodology for imprecise momentindependent global sensitivity analysis of rock structures

引用

Journal of Rock Mechanics and Geotechnical Engineering 2024年第3期16卷 840-859页

作者： Akshay Kumar Gaurav Tiwari Department of Civil Engineering Indian Institute of Technology(IIT)KanpurKanpur208016India

Traditional global sensitivity analysis(GsA)neglects the epistemic uncertainties associated with the probabilistic characteristics(*** of distribution type and its parameters)of input rock properties emanating due to the small size of datasets while mapping the relative importance of properties to the model *** paper proposes an augmented Bayesian multi-model inference(BMMI)coupled with GsA methodology(BMMI-GsA)to address this issue by estimating the imprecision in the momentindependent sensitivity indices of rock structures arising from the small size of input *** methodology employs BMMI to quantify the epistemic uncertainties associated with model type and parameters of input *** estimated uncertainties are propagated in estimating imprecision in moment-independent borgonovo’s indices by employing a reweighting approach on candidate probabilistic *** proposed methodology is showcased for a rock slope prone to stress-controlled failure in the Himalayan region of *** proposed methodology was superior to the conventional GsA(neglects all epistemic uncertainties)and Bayesian coupled GsA(B-GsA)(neglects model uncertainty)due to its capability to incorporate the uncertainties in both model type and parameters of *** borgonovo’s indices estimated via proposed methodology provide the confidence intervals of the sensitivity indices instead of their fixed-point estimates,which makes the user more informed in the data collection *** performed with the varying sample sizes suggested that the uncertainties in sensitivity indices reduce significantly with the increasing sample *** accurate importance ranking of properties was only possible via samples of large ***,the impact of the prior knowledge in terms of prior ranges and distributions was significant;hence,any related assumption should be made carefully.

关键词： Bayesian inference Multi-model inference statistical uncertainty Global sensitivity analysis(GsA) borgonovo’s indices Limited data

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：