This paper introduces a digital twin solution for corner fatigue crack growth assessment. The digital twin comprises three core features: (1) diagnosis, (2) prognosis and (3) updating. The diagnosis arm performs remote crack size measurement via strain data collected from strategically identified locations. The prognosis component postulates the fatigue life across both linear-elastic and elasto-plastic loading regimes through a fatigue crack growth power law with the cyclic J-integral, ΔJ, as the crack driving force. Uncertainty in power law parameters, however, may result in differences between the prognosis and observed fatigue life. Hence, the digital twin completes the feedback loop via Bayesian updating of the power law parameters, thereby mirroring its physical counterpart closely. An improved estimation of the remaining useful life follows. The proposed digital twin solution validates against three specimens under constant amplitude loading and a single specimen under variable amplitude loading. The successful application of the approach marks a significant step toward operational digital twins within practical settings.

中文翻译：

---

使用贝叶斯推理的角部疲劳裂纹扩展应变接口数字孪生解决方案


本文介绍了一种用于拐角疲劳裂纹扩展评估的数字孪生解决方案。数字孪生包括三个核心特征：（1） 诊断，（2） 预后和 （3） 更新。诊断臂通过从战略确定的位置收集的应变数据进行远程裂纹尺寸测量。预测组件通过以循环 J 积分 ΔJ 为裂纹驱动力的疲劳裂纹扩展幂律，假设线性弹性和弹塑性载荷状态下的疲劳寿命。然而，幂律参数的不确定性可能导致预后和观察到的疲劳寿命之间存在差异。因此，数字孪生通过幂律参数的贝叶斯更新来完成反馈回路，从而紧密镜像其物理对应物。以下是对剩余使用寿命的改进估计。所提出的数字孪生解决方案在恒定振幅载荷下对三个试样和在可变振幅载荷下对单个试样进行验证。该方法的成功应用标志着在实际环境中向运营数字孪生迈出了重要一步。