首页> 外文期刊>Journal of Applied Mechanics: Transactions of the ASME >A General Damage Accumulation Model for Multiaxial, Proportional High Cycle Fatigue Loadings With Sines, Crossland and Dang Van Criteria
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A General Damage Accumulation Model for Multiaxial, Proportional High Cycle Fatigue Loadings With Sines, Crossland and Dang Van Criteria

机译:多轴,比例高周疲劳负荷与田园,跨地,凡凡凡标准的一般损伤累积模型

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摘要

In this paper, a key differential equation is proposed to formulate fatigue damage evolution in metallic alloys under multiaxial, multiblock, proportional loadings in high cycle fatigue (HCF) and very high cycle fatigue (VHCF) regimes. This differential equation possesses two main components: one is a stress function to accommodate the adopted fatigue criterion and the other one is a characteristic damage function that serves to capture the HCF response of alloys. Two distinct characteristic damage functions with three different multiaxial fatigue criteria, namely Sines, Crossland, and Dang Van criteria, are examined to develop six (out of many possible) variants of the presented damage accumulation model. As a validation measure, Chaboche's HCF damage model is retrieved as a specific case of the developed formalism. For model parameters identification, an ad hoc two-level identification scheme is designed and numerically verified. It is demonstrated that endurance limit, which is determined from fully reversed HCF tests (i.e., R=-1), can be identified from fatigue tests with positive stress ratio (R > 0), thus making our development quite suitable for specimens prone to buckling under compression. Another salient feature of the devised identification scheme is its capability in extracting model parameters from noisy data.
机译:本文提出了一种关键微分方程,以在高循环疲劳(HCF)和非常高循环疲劳(VHCF)制度下的多轴,多块,比例荷载下金属合金中的疲劳损伤演化。这种微分方程具有两个主要部件:一个是应力功能以适应所采用的疲劳标准,另一个是用于捕获合金的HCF响应的特征损伤功能。两种不同的特征损伤功能,具有三种不同的多轴疲劳标准,即云原,横地和朝外范标准,以开发出现六个(多种可能)损坏累积模型的变种。作为验证措施,作为开发的形式主义的具体情况,检索Chaboche的HCF损伤模型。对于模型参数识别,设计和数值验证了Ad Hoc两级识别方案。结果证明,从完全反转的HCF试验(即,R = -1)中确定的耐久极限可以从阳性应力比(R> 0)鉴定,从而使我们的开发非常适合易于的样品压缩下的屈曲。设计识别方案的另一个突出特征是其在从嘈杂数据中提取模型参数的能力。

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