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首页> 外文期刊>Journal of intelligent material systems and structures >Inversion algorithms for the homogenized energy model for hysteresis in ferroelectric and shape memory alloy compounds
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Inversion algorithms for the homogenized energy model for hysteresis in ferroelectric and shape memory alloy compounds

机译:铁电和形状记忆合金化合物中磁滞的均质能量模型的反演算法

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摘要

Ferroelectric and ferromagnetic materials have the advantage of broadband and dual actuator and sensor capabilities. Ferroelastic compounds such as shape memory alloys have large energy densities and are biocompatible. However, to take full advantage of these properties, it is necessary to employ models and control designs that account for the rate-dependent hysteresis, creep, and constitutive nonlinearities inherent to the materials. Inverse compensation is one technique that achieves this purpose. We present an inversion algorithm based on a binary search of a discretized input grid and apply this to the homogenized energy model for modeling hysteresis. The inversion algorithm is shown to provide a reasonable balance between accuracy and computational speed. Numerical examples are presented for three specific cases of the homogenized energy model.
机译:铁电和铁磁材料具有宽带以及双执行器和传感器功能的优势。铁弹性化合物(例如形状记忆合金)具有大的能量密度,并且具有生物相容性。但是,要充分利用这些特性,有必要采用考虑材料固有的速率相关磁滞,蠕变和本构非线性的模型和控制设计。逆补偿是实现此目的的一种技术。我们提出了一种基于离散化输入网格的二进制搜索的反演算法,并将其应用于均质化的能量模型以对滞后建模。所示的反演算法可在精度和计算速度之间提供合理的平衡。给出了均质能量模型的三种特定情况的数值示例。

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