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Using surrogate models to predict nodal results for fatigue risk analysis
International Journal of Fatigue ( IF 5.7 ) Pub Date : 2020-12-29 , DOI: 10.1016/j.ijfatigue.2020.106039
Christopher Thelin , John Salmon , Steven Gorrell , Spencer Bunnell , Gregory Bird , Christopher Ruoti , Evan Selin , Joseph Calogero

Fatigue life analysis and FEA require high computational costs for aerospace models. Goodman diagrams are useful tools for determining the fatigue life of a part, and depend on structural and modal FEA simulations. Surrogate models have been used in fatigue analysis to predict the steady stresses and alternating stresses FEA model for every par node enabling a dynamically-updated Goodman diagram that responds to design parameter changes in real time. This research analyzes a jet engine compressor blade, and compares the accuracy of these nodal surrogate methods to previous surrogate methods where only a single value is predicted for failure analysis. Quantitative data summarizing the error between the single value and full field models are presented for the transonic Purdue blade.



中文翻译:

使用替代模型预测节点结果以进行疲劳风险分析

疲劳寿命分析和有限元分析需要航空模型高昂的计算成本。Goodman图是确定零件疲劳寿命的有用工具,它取决于结构和模态FEA仿真。替代模型已用于疲劳分析中,以预测每个同级节点的稳态应力和交变应力FEA模型,从而实现动态更新的古德曼图,该图可实时响应设计参数的变化。这项研究分析了喷气发动机的压缩机叶片,并将这些节点替代方法的准确性与以前的替代方法进行了比较,在以前的替代方法中,仅预测单个值即可进行故障分析。提出了跨音速普渡叶片的定量数据,总结了单值模型和全场模型之间的误差。

更新日期:2021-01-14
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