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首页> 外文期刊>Journal of Mechanical Science and Technology >Prediction assessment and validation of multiscale models for additively manufactured lattice structures under uncertainty
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Prediction assessment and validation of multiscale models for additively manufactured lattice structures under uncertainty

机译：在不确定性下，对多尺度模型进行多尺度模型的预测评估和验证

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摘要

In the design of lattice structures fabricated by additive manufacturing, a multiscale modeling process is usually required to effectively account for fine scale uncertainties. The validation of the multiscale model predictions, on the other hand, is a challenging task. In this research, two prediction assessment approaches, namely the area validation metric and the Kolmogorov-Smirnov test, are presented in a systematic validation pyramid approach with u-pooling method to address this issue. The use of these two approaches are evaluated in terms of being an unbiased decision criterion for the prediction assessment and validation of the multiscale models. The fine scale material and geometry uncertainties are propagated onto homogenized properties using a stochastic upscaling method at each scale of interest. The homogenized model predictions are validated using the experimental data obtained for the lattice structure example fabricated by material extrusion process. The results indicate that the presented approach is capable of effectively validate the predictions of the multiscale models under uncertainty.
机译：在由添加剂制造制造的晶格结构的设计中，通常需要多尺度建模过程来有效地解释为细尺的不确定性。另一方面，多尺度模型预测的验证是一个具有挑战性的任务。在本研究中，两个预测评估方法，即面积验证度量标准和kolmogorov-smirnov测试，以系统验证金字塔方法与U-Pooling方法一起解决，以解决这个问题。根据作为预测评估和多尺度模型的验证的无偏判决决策标准，评估使用这两种方法的使用。使用每种兴趣等级的随机上升方法将细量材料和几何不确定性繁殖到均质化性质上。使用由材料挤出过程制造的晶格结构示例获得的实验数据来验证均质模型预测。结果表明，所提出的方法能够有效地验证在不确定性下多尺度模型的预测。

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