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Uncertainty Analysis and Expert Judgment in Seismic Hazard Analysis

机译:地震危险性分析中的不确定度分析和专家判断

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The large uncertainty associated with the prediction of future earthquakes is usually regarded as the main reason for increased hazard estimates which have resulted from some recent large scale probabilistic seismic hazard analysis studies (e.g. the PEGASOS study in Switzerland and the Yucca Mountain study in the USA). It is frequently overlooked that such increased hazard estimates are characteristic for a single specific method of probabilistic seismic hazard analysis (PSHA): the traditional (Cornell–McGuire) PSHA method which has found its highest level of sophistication in the SSHAC probability method. Based on a review of the SSHAC probability model and its application in the PEGASOS project, it is shown that the surprising results of recent PSHA studies can be explained to a large extent by the uncertainty model used in traditional PSHA, which deviates from the state of the art in mathematics and risk analysis. This uncertainty model, the Ang–Tang uncertainty model, mixes concepts of decision theory with probabilistic hazard assessment methods leading to an overestimation of uncertainty in comparison to empirical evidence. Although expert knowledge can be a valuable source of scientific information, its incorporation into the SSHAC probability method does not resolve the issue of inflating uncertainties in PSHA results. Other, more data driven, PSHA approaches in use in some European countries are less vulnerable to this effect. The most valuable alternative to traditional PSHA is the direct probabilistic scenario-based approach, which is closely linked with emerging neo-deterministic methods based on waveform modelling.
机译:与未来地震预测相关的巨大不确定性通常被认为是灾害估计增加的主要原因,这是由于一些近期的大规模概率地震灾害分析研究(例如瑞士的PEGASOS研究和美国的尤卡山研究)而导致的。 。人们常常忽略了这种增加的危险估计是概率地震危险分析(PSHA)的单个特定方法的特征:传统的(Cornell–McGuire)PSHA方法在SSHAC概率方法中已达到最高水平。在对SSHAC概率模型及其在PEGASOS项目中的应用进行回顾的基础上,研究表明,最新的PSHA研究的令人惊讶的结果可以在很大程度上解释为传统PSHA中使用的不确定性模型,该模型偏离了状态。数学和风险分析领域。这个不确定性模型是Ang–Tang不确定性模型,它将决策理论的概念与概率性危害评估方法相结合,与经验证据相比,导致对不确定性的高估。尽管专家知识可以成为科学信息的宝贵来源,但将其纳入SSHAC概率方法并不能解决PSHA结果不确定性过高的问题。其他一些受数据驱动的,在某些欧洲国家使用的PSHA方法受此影响的可能性较小。传统PSHA最具价值的替代方法是直接的基于概率方案的方法,该方法与基于波形建模的新兴新确定性方法密切相关。

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