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Probability of infancy problems for space launch vehicles

机译:太空运载工具婴儿期问题的可能性

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This paper addresses the treatment of 'infancy problems' in the reliability analysis of space launch systems. To that effect, we analyze the probability of failure of launch vehicles in their first five launches. We present methods and results based on a combination of Bayesian probability and frequentist statistics designed to estimate the system's reliability before the realization of a large number of launches. We show that while both approaches are beneficial, the Bayesian method is particularly useful when the experience base is small (i.e. for a new rocket). We define reliability as the probability of success based on a binary failureo failure event. We conclude that the mean failure rates appear to be higher in the first and second flights (≈1/3 and 1/4, respectively) than in subsequent ones (third, fourth and fifth), and Bayesian methods do suggest that there is indeed some difference in launch risk over the first five launches. Yet, based on a classical frequentist analysis, we find that for these first few flights, the differences in the mean failure rates over successive launches or over successive generations of vehicles, are not statistically significant (i.e. do not meet a 95% confidence level). This is true because the frequentist analysis is based on a fixed confidence level (here: 95%), whereas the Bayesian one allows more flexibility in the conclusions based on a full probability density distribution of the failure rate and therefore, permits better interpretation of the information contained in a small sample. The approach also gives more insight into the considerable uncertainty in failure rate estimates based on small sample sizes.
机译:本文介绍了空间发射系统可靠性分析中“婴儿期问题”的处理方法。为此,我们分析了运载工具在前五次发射中失败的可能性。我们基于贝叶斯概率和频度统计数据的组合提出了一些方法和结果,旨在估计在实现大量发射之前系统的可靠性。我们表明,虽然两种方法都是有益的,但当经验基础较小时(即对于新火箭而言),贝叶斯方法特别有用。我们将可靠性定义为基于二进制故障/无故障事件的成功概率。我们得出的结论是,第一次和第二次飞行的平均故障率似乎分别更高(分别约为1/3和1/4),而随后的几次(第三次,第四次和第五次)则更高,而贝叶斯方法的确表明确实存在与前五次发射相比,发射风险有所不同。但是,根据经典的频常论者的分析,我们发现对于前几次飞行,连续发射或连续几代车辆的平均故障率差异在统计上并不显着(即,不满足95%的置信度) 。之所以如此,是因为频繁性分析基于固定的置信度(此处为95%),而贝叶斯分析则基于失败率的完整概率密度分布,在结论中具有更大的灵活性,因此可以更好地解释风险。小样本中包含的信息。该方法还可以使您更深入地了解基于小样本量的故障率估计中的相当大的不确定性。

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