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MANAGEMENT OF COMPLEX LOADING HISTORIES FOR USE IN PROBABILISTIC CREEP-FATIGUE DAMAGE ASSESSMENTS

机译:用于概率蠕变损伤评估的复杂载荷历史的管理

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An approach is outlined for the treatment of stresses in complex three-dimensional components for the purpose of conducting probabilistic creep-fatigue lifetime assessments. For conventional deterministic assessments, the stress state in a plant component is found using thermal and mechanical (elastic) finite element (FE) models. Key inputs are typically steam temperatures and pressures, with the three principal stress components (PSCs) at the assessment location(s) being the outputs. This paper presents an approach which was developed based on application experience with a tube-plate ligament (TPL) component, for which historical data was available. Though both transient as well as steady-state conditions can have large contributions towards the creep-fatigue damage, this work is mainly concerned with the latter. In a probabilistic assessment, the aim of this approach is to replace time intensive FE runs with a predictive model to approximate stresses at various assessment locations. This is achieved by firstly modelling a wide range of typical loading conditions using FE models to obtain the desire stresses. Based on the results from these FE runs, a probability map is produced and input(s)-output(s) functions are fitted (either using a Response Surface Method or Linear Regression). These models are thereafter used to predict stresses as functions of the input parameter(s) directly. This mitigates running an FE model for every probabilistic trial (of which there typically may be more than 104J, an approach which would be computationally prohibitive.
机译:为了进行概率蠕变疲劳寿命评估,概述了一种用于处理复杂三维部件中应力的方法。对于常规的确定性评估,可使用热和机械(弹性)有限元(FE)模型找到工厂组件中的应力状态。关键输入通常是蒸汽温度和压力,其中评估位置的三个主要应力分量(PSC)是输出。本文介绍了一种方法,该方法是基于使用管板韧带(TPL)组件的应用经验而开发的,该方法具有历史数据。尽管瞬态和稳态条件均可对蠕变疲劳损伤做出很大贡献,但这项工作主要涉及后者。在概率评估中,此方法的目的是用预测模型代替耗时的有限元运行,以近似估算各个评估位置的应力。这是通过首先使用有限元模型对各种典型的加载条件进行建模来获得所需的应力来实现的。基于这些有限元运行的结果,生成概率图,并拟合输入/输出函数(使用响应面方法或线性回归)。这些模型随后被用来直接预测应力作为输入参数的函数。这减轻了为每个概率试验(通常可能超过104J)运行有限元模型的方法,这种方法在计算上是令人望而却步的。

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