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Factors Affecting the Shape Parameter in the Weibull Distribution with Respect to Predicting Earliest Failures by SCC

机译:影响Weibull分布形状参数的因素相对于预测SCC预测最早的故障

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The purpose of this discussion is to describe an approach to predicting the earliest failures by corrosion and to compare this with conventional approaches that are largely based on evaluating the mean value of data or on using only engineering judgment. The essence of the approach proposed here involves using a statistical framework typified by the Weibull distribution with its statistical parameters quantified with physical quantities from the seven principal variables that control corrosion: e.g. pH, potential, species, metal composition, metal structure, temperature, and stress. The most important parameter affecting early failures is the shape parameter, beta, as used in the Weibull distribution. The Weibull beta is observed to vary from about unity to about six in most studies but may be somewhat lower and possibly more than 10. Values for beta from similar testing exhibit good agreement. While values for theta and to exhibit intuitively expected patterns, values for beta do not always follow such patterns. While it would be expected for beta to be proportional to stressors, such as temperature, stress, and concentration, this only occurs in about half the cases examined. Applying beta to predictions must be undertaken with great care. Low values of beta in the range of unity are most important since, for example, at a failure probability of 10 .4 the time to failure with a beta =l is 10~(-4) of the mean failure time. This means that for a theta=-10 years, the earliest failure would occur in about half a day. It is shown that the values of beta can be related to terms of physical processes. It is possible to provide reasonable insights into predicting early failures with an approach involving an estimation of theta and taking a conservative value for beta. It is emphasized here that the values of beta are implicit in combinations of the materials, environments and applications. The values of beta are more in the category of cause rather than result.
机译:本讨论的目的是描述通过腐蚀预测最早故障的方法,并将其与主要基于评估数据的平均值或仅使用工程判断的常规值进行比较。此处提出的方法的本质涉及使用Weibull分布的统计框架,其统计参数用来自控制腐蚀的七个主要变量的物理量量化:例如, pH,潜在,物种,金属组合物,金属结构,温度和应力。影响早期故障的最重要参数是形状参数,Beta,如Weibull分布所用。观察到Weibull Beta以在大多数研究中的统一到大约六个,但可能略低,可能超过10.类似测试的β的值表现出良好的一致性。虽然θ的值和直观的预期模式,但是测试的值并不总是遵循这些模式。虽然预期β与压力源成比例,例如温度,应激和浓度,但这只发生在案例中的约一半。必须非常关心地申请预测到预测。统一范围内的β的低值是最重要的,因为例如,在10.4的故障概率下,用β= L失败的时间是平均故障时间的10〜(4)。这意味着对于θ= -10岁,最早的故障将在大约半天内发生。结果表明,β的值可以与物理过程的术语有关。有可能提供合理的见解,以预测预测早期失败,涉及估计θ的方法并为β进行保守值。这里强调的是,在材料,环境和应用程序的组合中隐含测试版的值。 Beta的值更多在原因类别中而不是结果。

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