Requirements based system level risk modeling

L. Meshkat, S. Cornford, M. Feather
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引用次数: 3

Abstract

Space exploration missions are often characterized by multiple phases and each phase in turn satisfies some objective or requirement. The success of the mission is measured by the degree to which these requirements are satisfied. Missions either aim to demonstrate a new technology, or to obtain new science data or a combination of both of these. During the mission design process, numerous trade studies are conducted between cost, performance and risk. At a very high level, the goal is to maximize the probability of achieving the most science return (or demonstrating the most technology) at the least possible cost. We consider the problem of maximizing this probability by quantifying the degree of importance of each requirement and it's probability of being satisfied. The probability of a requirement being satisfied, in turn, is assessed by finding the aggregate of the probability of all the possible events that could prevent it from being satisfied. We assume a complete list of the requirements, the relevant risk elements and their probability of occurrence and the quantified effect of the risk elements on the requirements. In order to assess the degree to which each requirement is satisfied, we need to determine the effect of the various risk elements on the requirement. The complexity arises due to the fact that various risk elements that effect a requirement in question are not necessarily independent. Moreover, in order to compute the weighted average of the requirements, it's important to take into consideration their dependencies. Therefore we carefully define the relationships between the elements within each category (intra-category) and the elements between the two different categories of risk and requirements (inter-category).
基于需求的系统级风险建模
空间探索任务通常分为多个阶段,每个阶段又依次满足一定的目标或要求。任务的成功是由这些要求得到满足的程度来衡量的。任务的目的要么是展示一项新技术,要么是获取新的科学数据,要么是两者的结合。在特派团设计过程中,在成本、业绩和风险之间进行了许多贸易研究。在一个非常高的层次上,目标是以尽可能少的成本实现最大的科学回报(或展示最多的技术)的可能性最大化。我们通过量化每个需求的重要程度及其被满足的概率来考虑最大化这个概率的问题。一个需求被满足的概率,反过来,是通过找到所有可能阻止它被满足的事件的概率的总和来评估的。我们假设有一个完整的需求列表,相关的风险要素及其发生的概率,以及风险要素对需求的量化影响。为了评估每个需求被满足的程度,我们需要确定各种风险元素对需求的影响。复杂性的产生是由于影响需求的各种风险元素不一定是独立的。此外,为了计算需求的加权平均值,考虑它们的依赖性是很重要的。因此,我们仔细定义每个类别内的元素之间的关系(类别内)和两个不同类别的风险和需求之间的元素(类别间)。
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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