Comparative analysis of porosity coarse-graining techniques for discrete element simulations of dense particulate systems
Comparative analysis of porosity coarse-graining techniques for discrete element simulations of dense particulate systems
复制标题
致密颗粒系统离散元模拟孔隙率粗粒化技术的比较分析
DOI：
10.1007/s40571-021-00402-4
复制
发表时间：
2021
影响因子：
3.3
通讯作者：
Kalderon M
中科院分区：
文献类型：
--
作者：
Kalderon M
离散元法（DEM）是一种在众多应用领域中研究颗粒材料的成熟方法;每个颗粒都单独建模以预测整体行为。然后可以通过使用合适的方法对样品进行平均或粗粒化来提取这种行为。选择适当的粗粒度方法需要在精度和计算成本之间进行折衷，特别是在工业通常需要的大规模模拟中。一些粗粒化的方法已被提出在文献中，这些在这项工作中进行审查和分类。在这方面的贡献，提出了两种新的孔隙度粗粒化策略，包括体素方法，其中的“像素单元”的二次密集网格的实施，采用二进制逻辑的粗粒化和混合方法，其中既利用解析公式和像素。所提出的方法进行了比较与四个粗粒化计划，已在文献中记载，包括粒子质心法，解析方法，一种方法，解决了扩散方程和方法，采用平均使用内核。通过与“精确”分析方法的比较，验证了新方法在二维和三维问题。结果表明，一旦验证，所提出的计划可以近似精确的解决方案相当准确，但是，有一个与体素方法的计算成本很高。这两种方法的精度可以调整，允许用户在精度和计算时间之间做出决定。然后，从“精度”、“光滑度”和“计算成本”三个方面对六种方案进行了详细的比较。最佳参数获得的所有六种方法，粗粒度DEM样本的建议进行了讨论。
The discrete element method (DEM) is a well-established approach to study granular materials in numerous fields of application; each granular particle is modelled individually to predict the overall behaviour. This behaviour can be then extracted by averaging, or coarse graining, the sample using a suitable method. The choice of appropriate coarse-graining method entails a compromise between accuracy and computational cost, especially in the large-scale simulations typically required by industry. A number of coarse-graining methods have been proposed in the literature, and these are reviewed and categorized in this work. Within this contribution, two novel porosity coarse-graining strategies are proposed including a voxel method where a secondary dense grid of “pixel cells” is implemented adopting a binary logic for the coarse graining and a hybrid method where both analytical formulas and pixels are utilized. The proposed methods are compared with four coarse-graining schemes that have been documented in the literature, including the particle centroid method, an analytical method, a method which solves the diffusion equation and an approach which employs averaging using kernels. The novel methods are validated for problems in both two and three dimensions through comparison with the “accurate” analytical method. It is shown that, once validated, both the proposed schemes can approximate the exact solutions quite accurately; however, there is a high computational cost associated with the voxel method. The accuracy of both methods can be adjusted allowing the user to decide between accuracy and computational time. A detailed comparison is then presented for all six schemes considering “accuracy”, “smoothness” and “computational cost”. Optimal parameters are obtained for all six methods, and recommendations for coarse-graining DEM samples are discussed.
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