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On the utilisation of nonlinear plasticity models in military aircraft fatigue estimation: A preliminary comparison

机译：非线性可塑性模型在军机疲劳评估中的应用：初步比较

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Strain-life methodologies are commonly employed for fatigue estimation in military aircraft structures. These methodologies rely on models describing the elastoplastic response of the material under cycling. Despite the numerous advanced plasticity models proposed and utilised in various engineering problems over the past decades, the Masing model remains a popular choice in fatigue analysis software, mainly due to its simplicity. However, in the case of military aircraft load spectra including scattered overloads the Masing model fails to represent adequately transient cyclic phenomena, such as mean stress relaxation and strain ratcheting. In this study, four well-known constitutive plasticity models have been selected as potential substitutes for the Masing model within a defence organisation in-house developed fatigue analysis software. These models assessed were the well-known Multicomponent Armstrong Frederick Model (MAF) and three of its derivatives: MAF with threshold (MAFT), Ohno-Wang (OW) and MAF with Multiplier (MAFM). The models were calibrated with the use of existing experimental data, obtained from aircraft aluminium alloy tests. Optimisation of the parameters was performed through a genetic algorithm-based commercial software. The models were incorporated in the fatigue analysis software and their performance was evaluated statistically and compared against each other and with the Masing model for a series of different flight load spectra for a military aircraft. The results show that all four models have achieved a drastic improvement in fatigue analysis, with the MAFT model giving a slightly better performance. Crown Copyright (C) 2017 Published by Elsevier Masson SAS. All rights reserved.
机译：应变寿命方法通常用于军用飞机结构的疲劳评估。这些方法依赖于描述材料在循环下的弹塑性响应的模型。尽管在过去的几十年中提出并使用了许多先进的可塑性模型来解决各种工程问题，但是Masing模型仍然是疲劳分析软件中的一种流行选择，主要是因为它的简单性。但是，在包括分散的过载在内的军用飞机载荷谱中，Masing模型无法代表足够的瞬态循环现象，例如平均应力松弛和应变棘轮。在这项研究中，已选择了四个著名的本构模型作为国防组织内部开发的疲劳分析软件中Masing模型的潜在替代品。评估的这些模型是著名的多分量阿姆斯特朗·弗雷德里克模型（MAF）及其三个派生模型：带阈值的MAF（MAFT），Ohno-Wang（OW）和带乘数的MAF（MAFM）。使用从飞机铝合金测试获得的现有实验数据对模型进行了校准。通过基于遗传算法的商业软件对参数进行优化。这些模型被整合到疲劳分析软件中，并对它们的性能进行了统计评估，并与军用飞机一系列不同飞行载荷谱的Masing模型进行了比较。结果表明，所有四个模型在疲劳分析方面均取得了显着改善，而MAFT模型的性能稍好一些。官方版权（C）2017，由Elsevier Masson SAS发布。版权所有。

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