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Parameter identification of Bouc-Wen model for vacuum packed particles based on genetic algorithm

机译:基于遗传算法的真空包装粒子Bouc-Wen模型的参数识别

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This paper investigates cylindrical samples made of vacuum packed particles. Such structures are composed of granular media placed in a hermetic encapsulation where, in the final stage, a partial vacuum is generated. The main advantage of such a structure is that the under pressure value makes it possible to control the global physical properties of granular systems. Materials with various grains are analyzed in the paper. A modified Bouc-Wen hysteresis model is adopted to describe the nonlinear properties of the tested specimens. To identify the model parameters, a genetic algorithm is applied. The proposed model is found to be in good agreement with the experimental data. (C) 2018 Politechnika Wroclawska. Published by Elsevier B.V. All rights reserved.
机译:本文研究了由真空填充颗粒制成的圆柱形样品。 这种结构由放置在气密封装中的粒状介质组成,其中在最终阶段,产生部分真空。 这种结构的主要优点是下压力值使得可以控制粒状系统的全局物理性质。 在纸上分析了具有各种晶粒的材料。 采用改进的BOUC-WEN滞后模型来描述测试标本的非线性性质。 为了识别模型参数,应用了一种遗传算法。 发现拟议的模型与实验数据很好。 (c)2018 Politechnika Wroclawska。 由elsevier b.v出版。保留所有权利。

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