A framework for multi-hazards risk aggregation considering risk model maturity levels

Tasneem Bani-Mustafa, Zhiguo Zeng, E. Zio, D. Vasseur
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引用次数: 5

Abstract

Multi-Hazards Risk Aggregation (MHRA) aggregates risk over different risk contributors and provides a final risk index that permits the comparison with safety guidelines to support Decision Making (DM). Maturity of the risk analysis are always different for different risk contributors, resulting in different degrees of confidence on the associated results. The difference in maturity, and the sources of heterogeneity that cause such differences, should be taken into account for supporting a reliable and accurate representation of risk in respect of DM. In this paper, we first propose a hierarchical framework to evaluate the level of maturity of risk assessments in respect of DM. The framework consists of different attributes (uncertainty, conservatism, knowledge and sensitivity) and sub-attributes (availability of data, consistency of data, data reliability, experience, and value ladenness) that are believed to determine the level of maturity of a risk assessment. Evaluation guidelines are pre-defined for facilitating the attributes scoring process. Then, the maturity level is integrated in MHRA by developing a two-dimensional risk aggregation method. Finally, a numerical case study for the MHRA of a Nuclear Power Plant (NPP) is carried out to show the applicability and the plausibility of the methods.
考虑风险模型成熟度的多危害风险聚合框架
多危害风险汇总(MHRA)汇总了不同风险贡献者的风险,并提供了一个最终风险指数,允许与安全指南进行比较,以支持决策(DM)。对于不同的风险贡献者,风险分析的成熟度总是不同的,从而导致对相关结果的置信度不同。成熟度的差异,以及导致这种差异的异质性来源,应该被考虑在内,以支持DM风险的可靠和准确的表示。在本文中,我们首先提出了一个层次框架来评估DM风险评估的成熟度水平。该框架由不同的属性(不确定性、保守性、知识性和敏感性)和子属性(数据的可用性、数据的一致性、数据的可获得性)组成。数据可靠性、经验和价值负担)被认为决定了风险评估的成熟度。评估准则是预先定义的,以方便属性评分过程。然后,通过建立二维风险聚合方法,将成熟度水平集成到MHRA中。最后,以某核电站MHRA为例进行了数值分析,验证了所提方法的适用性和合理性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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