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Inverse Analysis of Material Parameters of Multiple Foam Layers Based on Artificial Neural Network

机译:基于人工神经网络的多泡沫层材料参数逆分析

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Closed cell polymeric foams are widely used in sport and medical equipments. In this study, an artificial neural network (ANN) based inverse finite element (FE) program has been developed and used to predict the nonlinear material properties of EVA foams with multiple layers. A 2-D parametric FE model was developed and validated against experimental data. Systematic data from FE simulations was used to train and validate the ANN model. The accuracy and validity of the ANN method were assessed based on both blind tests and experimental data. Results showed that the proposed artificial neural network model is robust and efficient in predicating the nonlinear parameters of foam materials.
机译:封闭的细胞聚合物泡沫广泛用于运动和医疗设备。在该研究中,已经开发了一种基于人工神经网络(ANN)的逆有限元(FE)程序,并用于预测多层EVA泡沫的非线性材料性质。开发了2-D参数Fe模型并针对实验数据验证。 FE模拟的系统数据用于培训和验证ANN模型。基于盲检测和实验数据评估了ANN方法的准确性和有效性。结果表明,所提出的人工神经网络模型在释放泡沫材料的非线性参数方面具有稳健且有效。

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