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Fatigue crack growth spectrum simplification: Facilitation of on-board damage prognosis systems.

机译：疲劳裂纹扩展谱的简化：简化了机载损伤预后系统。

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摘要

Better lifetime predictions of systems subjected to fatigue loading are needed in support of the optimization of the costs of life-cycle engineering. In particular, the climate is especially encouraging for the development of safer aircraft. One issue is that aircraft experience complex fatigue loading and current methods for the prediction of fatigue damage accumulation rely on intensive computational tools that are not currently carried onboard during flight. These tools rely on complex models that are made more difficult by the complicated load spectra themselves. This presents an overhead burden as offline analysis must be performed at an offsite facility. This architecture is thus unable to provide online, timely information for on-board use. The direct objective of this research was to facilitate the real-time fatigue damage assessments of on-board systems with a particular emphasis on aging aircraft.;To achieve the objective, the goal of this research was to simplify flight spectra. Variable-amplitude spectra, in which the load changes on a cycle-by-cycle basis, cannot readily be supported by an onboard system because the models required to predict fatigue crack growth during variable-amplitude loading are too complicated. They are too complicated because variable-amplitude fatigue crack growth analysis must be performed on a cycle-by-cycle basis as no closed-form solution exists. This makes these calculations too time-consuming and requires impractical, heavy onboard systems or offsite facilities.;The hypothesis is to replace a variable-amplitude spectrum with an equivalent constant-amplitude spectrum. The advantage is a dramatic reduction in the complexity of the problem so that damage predictions can be made onboard by simple, fast calculations in real-time without the need to add additional weight to the aircraft. The intent is to reduce the computational burden and facilitate on-board projection of damage evolution and prediction for the accurate monitoring and management of aircraft. A spectrum reduction method was proposed and experimentally validated that reduces a variable-amplitude spectrum to a constant-amplitude equivalent.;The reduction from a variable-amplitude (VA) spectrum to a constant-amplitude equivalent (CAE) was proposed as a two-part process. Preliminary spectrum reduction is first performed by elimination of those loading events shown to be too negligible to significantly contribute to fatigue crack growth. This is accomplished by rainflow counting. The next step is to calculate the appropriate, equivalent maximum and minimum loads by means of a root-mean-square average. This reduced spectrum defines the CAE and replaces the original spectrum. The simplified model was experimentally shown to provide the approximately same fatigue crack growth as the original spectrum.;Fatigue crack growth experiments for two dissimilar aircraft spectra across a wide-range of stress-intensity levels validated the proposed spectrum reduction procedure. Irrespective of the initial K-level, the constant-amplitude equivalent spectra were always conservative in crack growth rate, and were so by an average of 50% over the full range tested. This corresponds to a maximum 15% overestimation in driving force Delta K. Given other typical sources of scatter that occur during fatigue crack growth, a consistent 50% conservative prediction on crack growth rate is very satisfying. This is especially attractive given the reduction in cost gained by the simplification.;We now have a seamless system that gives an acceptably good approximation of damage occurring in the aircraft. This contribution is significant because in a very simple way we now have given a path to bypass the current infrastructure and ground-support requirements. The decision-making is now a lot simpler. In managing an entire fleet we now have a workable system where the strength is in no need for a massive, isolated computational center. The fidelity of the model gives credence because experimental data show that the approximate spectrum model captures the essential spectrum response. The discrepancy between the models is such that an experimental parameter is sufficient to converge the models.;The proposed spectrum reduction procedure significantly mitigates the computational burden and allows for the probabilistic assessment of fatigue in real-time. This, in turn, provides support for crack-growth monitoring systems in facilitation of aircraft prognosis and fleet management.
机译：为了更好地优化生命周期工程的成本，需要对承受疲劳载荷的系统进行更好的寿命预测。特别是，气候对于发展更安全的飞机尤其令人鼓舞。一个问题是飞机会经历复杂的疲劳载荷，并且当前的疲劳损伤累积预测方法依赖于飞行过程中目前尚不携带的大量计算工具。这些工具依赖于复杂的模型，而复杂的模型本身使复杂的载荷谱变得更加困难。由于必须在异地设施执行离线分析，因此这带来了开销负担。因此，该架构无法提供在线及时信息以供车载使用。这项研究的直接目的是促进对机载系统的实时疲劳损伤评估，特别是对老化飞机的评估。为了实现这一目标，本研究的目的是简化飞行谱。车载系统无法轻松支持其中载荷在逐周期变化的可变振幅谱，因为预测可变振幅载荷过程中疲劳裂纹扩展所需的模型太复杂了。它们太复杂了，因为由于不存在封闭形式的解决方案，因此必须逐周期执行可变振幅疲劳裂纹扩展分析。这使得这些计算太费时，并且需要不切实际，笨重的车载系统或异地设施。假设是用等效的恒定振幅频谱代替可变振幅频谱。优点是大大降低了问题的复杂性，因此可以通过简单，快速的实时实时计算来在飞机上进行损坏预测，而无需增加飞机的重量。目的是减轻计算负担，并在机上预测损坏的演变和预测，以便对飞机进行准确的监视和管理。提出了一种频谱减小方法，并通过实验验证了将可变振幅频谱减小到恒定振幅等效量的方法;提出将可变振幅频谱（VA）减小到恒定振幅等效量（CAE）的方法是两个部分过程。首先，通过消除那些被认为太微不足道以至于不能明显促进疲劳裂纹扩展的载荷事件，来进行频谱的初步降低。这是通过雨流量计数来完成的。下一步是通过均方根平均值计算适当的等效最大和最小载荷。减少的频谱定义了CAE，并取代了原始频谱。实验证明了简化的模型可以提供与原始光谱大致相同的疲劳裂纹扩展。；在宽的应力强度水平下，两个不同飞机光谱的疲劳裂纹扩展实验验证了拟议的光谱缩减程序。不管初始的K级如何，等幅等效谱图在裂纹扩展率上始终是保守的，在整个测试范围内平均为50％。这对应于最大的驱动力Delta K高估15％。考虑到疲劳裂纹扩展过程中发生的其他典型散射源，对于裂纹扩展率的一致的50％保守预测非常令人满意。考虑到简化带来的成本降低，这尤其有吸引力。我们现在有了一个无缝系统，可以对飞机中发生的损坏提供近似可接受的良好近似值。这一贡献非常重要，因为我们现在已经以非常简单的方式给出了绕过当前基础架构和地面支持要求的途径。现在，决策更加简单。现在，在管理整个车队时，我们有了一个可行的系统，不需要强大的力量，而无需庞大的隔离计算中心。该模型的保真度具有可信度，因为实验数据表明，近似光谱模型可以捕获基本的光谱响应。模型之间的差异使得实验参数足以使模型收敛。拟议的频谱缩减程序显着减轻了计算负担，并允许对疲劳进行实时概率评估。反过来，这也为裂纹扩展监测系统提供了支持，以促进飞机的预测和机队管理。

著录项

  • 作者

    Adler, Matthew Adam.;

  • 作者单位

    Lehigh University.;

  • 授予单位 Lehigh University.;
  • 学科 Engineering Mechanical.;Engineering Materials Science.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 92 p.
  • 总页数 92
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 机械、仪表工业;工程材料学;
  • 关键词

  • 入库时间 2022-08-17 11:38:29

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