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STATISTICAL MODELING FOR LOW CYCLE FATIGUE

机译:低循环疲劳的统计建模

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Low cycle fatigue (LCF) is a common loading condition experienced by structural components. LCF is usually defined as the fatigue cycles to failure are less than 10~5. In order to certify and qualify a material for an application that requires high reliability for operation and safety, fundamental material properties must be experimentally investigated and validated. The well documented strain-life approach serves as the underlying experimental method for the investigation herein. The purpose of this paper is to investigate the statistical variability and appropriately model that variability for life in LCF. Specifically, the variability associated with the median behavior in a strain-life graph for data is examined. The ensuing analyses are based on data for a cold-rolled, low carbon, extra deep drawing steel; ASTM A969. ASTM A969 is intended for applications where extremely severe drawing or forming is envisioned. The probability distribution functions considered for characterizing the LCF life are taken from a generalized Weibull distribution function that empirically incorporates load history and damage accumulation. The strain-life computation employs the standard Coffin-Manson relationship.
机译:低循环疲劳(LCF)是结构部件经历的常见负载条件。 LCF通常定义为失效的疲劳循环小于10〜5。为了认证和符合需要高可靠性的应用的材料,需要高可靠性和安全性,必须通过实验调查和验证基本材料特性。良好记录的应变 - 寿命方法用作本文研究的基础实验方法。本文的目的是探讨统计变异性和适当的模型,即LCF的寿命变化。具体地,检查与菌株 - 寿命图中的中值行为相关的可变性被检查用于数据的数据图。随后的分析基于冷轧,低碳,额外的深层钢钢数据; ASTM A969。 ASTM A969旨在设想极其严重的绘图或成形的应用。考虑用于表征LCF寿命的概率分布函数是从经验融合负载历史和损坏累积的广义威布尔分布函数中的。应变寿命计算采用标准棺材曼森关系。

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