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首页> 外文期刊>AIAA Journal >Surrogate Modeling of High-Fidelity Fracture Simulations for Real-Time Residual-Strength Predictions
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Surrogate Modeling of High-Fidelity Fracture Simulations for Real-Time Residual-Strength Predictions

机译:实时残余强度预测的高保真断裂模拟的替代模型

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摘要

A surrogate-model methodology is described for real-time prediction of the residual strength of flight structures with discrete-source damage. Starting with design of experiment, an artificial neural network is developed that takes discrete-source damage parameters as input and then outputs a prediction of the structural residual strength. Target residual-strength values used to train the artificial neural network are derived from three-dimensional finite-element-based fracture simulations. A residual-strength test of a metallic integrally stiffened panel is simulated to show that crack growth and residual strength are determined more accurately in discrete-source damage cases by using an elastic-plastic fracture framework rather than a linear-elastic fracture-mechanics-based method. Improving accuracy of the residual-strength training data would, in turn, improve the accuracy of the surrogate model. When combined, the surrogate-model methodology and high-fidelity fracture simulation framework provide useful tools for adaptive flight technology.
机译:描述了一种替代模型方法,用于实时预测具有离散源损坏的飞行结构的剩余强度。从实验设计开始,开发了一个人工神经网络,该神经网络将离散源损伤参数作为输入,然后输出对结构残余强度的预测。用于训练人工神经网络的目标残余强度值是从基于三维有限元的断裂模拟中得出的。模拟了金属整体加劲板的残余强度测试,结果表明,在离散源损伤情况下,通过使用弹塑性断裂框架而不是基于线性弹性断裂力学的方法,可以更准确地确定裂纹扩展和残余强度方法。剩余强度训练数据的准确性的提高将反过来提高替代模型的准确性。当组合使用时,替代模型方法和高保真裂缝模拟框架为自适应飞行技术提供了有用的工具。

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