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首页> 外文期刊>Comptes rendus. Mecanique >Proper Generalized Decomposition (PGD) for the numerical simulation of polycrystalline aggregates under cyclic loading
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Proper Generalized Decomposition (PGD) for the numerical simulation of polycrystalline aggregates under cyclic loading

机译:适当的广义分解(PGD)用于在循环载荷下的多晶聚集体的数值模拟

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摘要

The numerical modelling of the behaviour of materials at the microstructural scale has been greatly developed over the last two decades. Unfortunately, conventional resolution methods cannot simulate polycrystalline aggregates beyond tens of loading cycles, and they do not remain quantitative due to the plasticity behaviour. This work presents the development of a numerical solver for the resolution of the Finite Element modelling of polycrystalline aggregates subjected to cyclic mechanical loading. The method is based on two concepts. The first one consists in maintaining a constant stiffness matrix. The second uses a time/space model reduction method. In order to analyse the applicability and the performance of the use of a space-time separated representation, the simulations are carried out on a three-dimensional polycrystalline aggregate under cyclic loading. Different numbers of elements per grain and two time increments per cycle are investigated. The results show a significant CPU time saving while maintaining good precision. Moreover, increasing the number of elements and the number of time increments per cycle, the model reduction method is faster than the standard solver. (C) 2017 Academie des sciences. Published by Elsevier Masson SAS.
机译:在过去的二十年中,微观结构规模的材料行为的数值建模已经很大。遗憾的是,常规分辨率方法不能模拟超过数十的装载循环的多晶聚集体,并且由于塑性行为而不会保持定量。该工作介绍了用于分辨对经受循环机械负荷的多晶聚集体的有限元模拟的分辨率的数值求解器的开发。该方法基于两个概念。第一个包括保持恒定的刚度矩阵。第二种使用时间/空间模型减少方法。为了分析适用性和使用空间分离的表示的性能,在循环载荷下的三维多晶聚集体上进行模拟。调查每粒的不同元素和每个周期的两次增量。结果显示了显着的CPU时间,同时保持良好的精度。此外,增加元素数量和每个周期的时间百分比,模型减少方法比标准求解器更快。 (c)2017年Academie Des Sciences。由Elsevier Masson SA出版。

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