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Top-down vs. bottom-up risk assessment: Consistent, contradictory or complimentary?

机译:自上而下与自下而上的风险评估:一致,矛盾或互补?

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Probabilistic risk assessment (PRA) of newly designed space systems is an intricate task due to the uniqueness of each mission's objectives and architecture, and the corresponding lack of relevant data regarding the components and environments. Finding one good source of information is hard enough, but it is even more challenging when multiple, partially relevant sources of information are required or available for the task. Top-down approaches, which are based on analogous systems with well-documented performance records, are usually good at highlighting the challenges in a historical context but the results need to be adjusted when applied to a new design with no or little real flight history. On the other hand, while bottom-up approaches are good at capturing the risk of a system that is comprised of at least some components with demonstrated reliabilities and has a specific design, environment and operational concept, the method is heavily dependent on the analyst to define the failure modes and capture the failures caused by component interaction or by environment hazards such as micrometeoroid and orbital debris (MMOD). This difficulty challenges the completeness of a bottom-up model and makes it difficult to produce bounding risk estimates.
机译:由于每个任务的目标和架构具有独特性,并且相应缺乏有关组件和环境的相关数据,因此,新设计的空间系统的概率风险评估(PRA)是一项复杂的任务。找到一个好的信息源已经很困难了,但是当任务需要或可以使用多个部分相关的信息源时,则更具挑战性。自上而下的方法基于具有良好记录的性能记录的类似系统,通常擅长于突出历史背景下的挑战,但是当将结果应用于没有或只有很少实际飞行历史的新设计时,需要对其结果进行调整。另一方面,虽然自下而上的方法擅长捕获系统的风险,该系统至少包含一些具有已证明的可靠性的组件,并且具有特定的设计,环境和操作概念,但是该方法在很大程度上依赖于分析人员定义故障模式并捕获由组件相互作用或环境危害(如微流星体和轨道碎片(MMOD))引起的故障。这个困难挑战了自下而上模型的完整性,并使得难以产生边界风险估计。

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