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Determination of elastic properties of a film-substrate system by using the neural networks

机译:利用神经网络确定薄膜-基材系统的弹性

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An inverse method based on artificial neural network (ANN) is presented to determine the elastic properties of films from laser-genrated surface waves. The surface displacement responses are used as the inputs for the ANN model; the outputs of the ANN are the Young's modulus, density, Poisson's ratio, and thickness of the film. The finite element method is used to calculate the surface displacement responses in a film-substrate system. Levenberg Marquardt algorithm is used as numerical optimization to speed up the training process for the ANN model. In this method, the materials parameters are not recovered from the dispersion curves but rather directly from the transient surface displacement. We have also found that this procedure is very efficient for determining the materials parameters of layered systems.
机译:提出了一种基于人工神经网络(ANN)的逆方法,用于确定激光产生的表面波的薄膜弹性特性。表面位移响应用作ANN模型的输入; ANN的输出是杨氏模量,密度,泊松比和薄膜厚度。有限元方法用于计算膜-基底系统中的表面位移响应。 Levenberg Marquardt算法被用作数值优化,以加快ANN模型的训练过程。在这种方法中,材料参数不是从色散曲线中恢复的,而是直接从瞬态表面位移中恢复的。我们还发现,此过程对于确定分层系统的材料参数非常有效。

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