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首页> 外文期刊>Journal of Spacecraft and Rockets >Bayesian Analysis of Launch Vehicle Success Rates
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Bayesian Analysis of Launch Vehicle Success Rates

机译：运载火箭成功率的贝叶斯分析

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摘要

In the choosing of a launch vehicle for a given mission or in the determination of insurance coverage and premiums for a given launch, accurate estimates of the probability of success of the different launch vehicles provide important information. There are three general approaches to estimating the probability of launch success. The first is to use a probabilistic risk analysis, decomposing the system into its subsystems and components and estimating the probability of each of the failure modes. The second is to rely on expert judgment about the vehicle's success rate as a whole, without a functional decomposition of the system. The third is to use statistical data about the past performance of the system to estimate the vehicle's success rate. The focus is put on this last approach, using Bayesian probability theory to make better use of vehicle-level performance data. The procedure is demonstrated by an analysis of the success rates of most of the major families of launch vehicles currently in use in the world. A family of launch vehicles includes all variants of a particular type of vehicle from a specific manufacturer, for example, the Delta 2. For vehicles with a small number of launch attempts, the Bayesian approach provides the advantage over classic statistical approaches of yielding estimates of both the mean future frequency of success and the uncertainty about that mean.
机译：在为给定任务选择运载工具或确定给定运载工具的保险范围和保费时，对不同运载工具成功的概率的准确估计可提供重要的信息。有三种通用方法可以估算发射成功的可能性。首先是使用概率风险分析，将系统分解为子系统和组件，并估计每种故障模式的可能性。第二是依靠专家对车辆整体成功率的判断，而不会对系统进行功能分解。第三是使用有关系统过去性能的统计数据来估计车辆的成功率。重点放在最后一种方法上，即使用贝叶斯概率理论更好地利用车辆级性能数据。通过分析目前世界上使用的大多数主要运载火箭系列的成功率，可以证明这一程序。运载火箭系列包括特定制造商提供的特定类型运载工具的所有变体，例如Delta2。对于发射尝试次数较少的运载工具，贝叶斯方法相对于经典的统计方法具有以下优势：未来成功的平均频率和不确定性。

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