Multisource information fusion for safety risk assessment in complex projects considering dependence and uncertainty

连接词(语言学) 风险分析(工程) 新颖性 风险评估 云计算 计算机科学 Sobol序列 可靠性工程 工程类 计量经济学 灵敏度(控制系统) 数学 计算机安全 业务 哲学 神学 电子工程 操作系统
作者
Kai Guo,Limao Zhang
出处
期刊:Risk Analysis [Wiley]
被引量:3
标识
DOI:10.1111/risa.17651
摘要

The success of tunneling projects is crucial for infrastructure development. However, the potential leakage risk is particularly challenging due to the inherent uncertainties and fuzziness involved. To address this demanding challenge, a hybrid approach integrating the copula theory, cloud model, and risk matrix, is proposed. The dependence of multiple risk-related influential factors is explored by the construct of the copula-cloud model, and the diverse information is fused by applying the risk matrix to gain a crisp risk result. A case study is performed to test the applicability of the proposed approach, in which a risk index system consisting of nine critical factors is developed and Sobol-enabled global sensitivity analysis (GSA) is incorporated to investigate the contributions of different factors to the risk magnitude. Key findings are as follows: (1) Risk statuses of the studied three tunnel sections are perceived as under grade I (safe), II (low-risk), and III (medium-risk), respectively, and the waterproof material aspect is found prone to deteriorating the tunnel sections. Furthermore, the proposed approach allows for a better understanding of the trends in the risk statuses of the tunnel sections. (2) Strong interactions between influential factors exist and exert impacts on the final risk results, proving the necessity of studying the factor dependence. (3) The developed neutral risk matrix presents a strong robustness and displays a higher recognition capacity in risk assessment. The novelty of this research lies in the consideration of the dependence and uncertainty in multisource information fusion with a hybrid copula-cloud model, enabling to perform a robust risk assessment under different risk matrices with varying degrees of risk tolerance.
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