离散元法
欧拉路径
有限元法
计算流体力学
计算机科学
灵活性(工程)
计算科学
联轴节(管道)
统计物理学
CFD-DEM公司
比例(比率)
一套
多尺度建模
机械工程
拉格朗日
航空航天工程
物理
工程类
数学
应用数学
机械
统计
热力学
历史
计算化学
考古
化学
量子力学
作者
Bernhard Peters,Maryam Baniasadi,Mehdi Baniasadi,Xavier Besseron,Alvaro Antonio Estupinan Donoso,Mohammad Mohseni
出处
期刊:Particuology
[Elsevier]
日期:2019-06-01
卷期号:44: 176-193
被引量:33
标识
DOI:10.1016/j.partic.2018.04.005
摘要
The extended discrete element method (XDEM) multi-physics and multi-scale simulation platform is being developed at the Institute of Computational Engineering, the University of Luxembourg. The platform is an advanced multi-physics simulation technology that combines flexibility and versatility to establish the next generation of multi-physics and multi-scale simulation tools. For this purpose, the simulation framework relies on coupling various predictive tools based on an Eulerian and Lagrangian approach. The Eulerian approach represents the wide field of continuum models; the Lagrangian approach is perfect for characterising discrete phases. Continuum models thus include classical simulation tools, such as computational fluid dynamics simulation and finite element analysis, while an extended configuration of the classical discrete element method addresses the discrete (e.g., particulate) phase. Apart from predicting the trajectories of individual particles, XDEM-suite extends the application of the XDEM to estimating the thermodynamic state of each particle using advanced and optimised algorithms. The thermodynamic state may include temperature and species distributions due to chemical reaction and external heat sources. Hence, coupling these extended features with either computational fluid dynamics simulation or finite element analysis opens a wide range of applications as diverse as pharmaceuticals, agriculture, food processing, mining, construction and agricultural machinery, metals manufacturing, energy production and systems biology.
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