Accurate creep life prediction is necessary for the evaluation of the remaining creep lives of in-service turbine blades and for the design of new turbine blades in aircraft engines. In this study, an integrated computational material engineering methodology for predicting the remaining creep life of in-service turbine blades was developed by taking a microstructural criterion and creep strain criterion into consideration, and combining artificial neural networks with a modified θ projection model to assess the service temperature, stress, degradation time, and existing creep strain. To explore the application of the method and verify its accuracy, the microstructural degradations at different locations of two directionally solidified superalloy DZ125 turbine blades, which were in-service for 300 h and 980 h in different engines, were characterized and quantified. Using these results, the remaining creep life of the microstructures at different locations of the blade was predicted. Finally, these creep life prediction results were experimentally verified using miniature creep test specimens. The development of this new method provides a reference for the design and service evaluation of turbine blades made of directional solidified and single-crystal Ni-based superalloys.

中文翻译：

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ICME框架，用于评估使用镍基高温合金制造的在用涡轮叶片的损伤评估和剩余蠕变寿命

准确的蠕变寿命预测对于评估使用中的涡轮叶片的剩余蠕变寿命以及设计飞机发动机中的新型涡轮叶片很有必要。在这项研究中，通过考虑微观结构准则和蠕变应变准则，并结合人工神经网络和改进的θ，开发了一种用于预测在役涡轮叶片剩余蠕变寿命的综合计算材料工程方法。投影模型来评估使用温度，应力，降解时间和现有的蠕变应变。为了探索该方法的应用并验证其准确性，对两个定向凝固的超级合金DZ125涡轮叶片在不同发动机中分别运行300 h和980 h的不同位置处的微观组织退化进行了表征和量化。使用这些结果，可以预测叶片不同位置的微结构的剩余蠕变寿命。最后，这些蠕变寿命预测结果使用微型蠕变测试样本进行了实验验证。这种新方法的开发为定向凝固和单晶镍基高温合金制成的涡轮叶片的设计和使用评估提供了参考。