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Risk Analysis for Autonomous Underwater Vehicle Operations in Extreme Environments

机译:极端环境下自主水下航行器运行风险分析

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摘要

Autonomous underwater vehicles (AUVs) are used increasingly to explore hazardous marine environments. Risk assessment for such complex systems is based on subjective judgment and expert knowledge as much as on hard statistics. Here, we describe the use of a risk management process tailored to AUV operations, the implementation of which requires the elicitation of expert judgment. We conducted a formal judgment elicitation process where eight world experts in AUV design and operation were asked to assign a probability of AUV loss given the emergence of each fault or incident from the vehicle's life history of 63 faults and incidents. After discussing methods of aggregation and analysis, we show how the aggregated risk estimates obtained from the expert judgments were used to create a risk model. To estimate AUV survival with mission distance, we adopted a statistical survival function based on the nonparametric Kaplan-Meier estimator. We present theoretical formulations for the estimator, its variance, and confidence limits. We also present a numerical example where the approach is applied to estimate the probability that the Autosub3 AUV would survive a set of missions under Pine Island Glacier, Antarctica in January–March 2009.
机译:自主水下航行器(AUV)越来越多地用于探索危险的海洋环境。这种复杂系统的风险评估基于主观判断和专家知识,也基于硬统计。在这里,我们描述了针对AUV业务量身定制的风险管理流程的使用,其实施需要专家的判断。我们进行了正式的判断启发过程,根据汽车的63个故障和事件的生命历史,要求八位世界AUV设计和操作专家确定AUV损失的可能性,以考虑到每个故障或事件的出现。在讨论了汇总和分析方法之后,我们展示了如何使用从专家判断中获得的汇总风险估计来创建风险模型。为了估计AUV生存与任务距离,我们采用了基于非参数Kaplan-Meier估计量的统计生存函数。我们为估计器,其方差和置信度极限提供了理论公式。我们还提供了一个数值示例,其中应用了该方法来估算Autosub3 AUV在2009年1月至3月的南极松岛冰川下进行的一系列任务中存活的可能性。

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