Name
Title | ||
|---|---|---|
A Fast And Accurate Gpu Based Method On Simulating Energy Deposition For Beam-Target Coupling With Granular Materials |
Abstract | ||
|---|---|---|
The simulation of beam energy transfer and medium dynamics is essential in nuclear studies and designs involving the beam loading on targets. Although the existing methods are relatively mature in simulating the thermohydrodynamics of a solid or liquid target coupled with an energetic beam, they may not be entirely applicable to a complex porous medium such as granular materials with massive discrete elements. In this study, a GPU (Graphics Processing Unit) based discrete energy deposition simulation method is proposed for the thermohydrodynamical simulation of granular flow targets with beam-grain coupling. The results of physical validations show that a significant improvement in accuracy was achieved by our method compared to the equivalent homogenization method which just simplified the granular medium to a whole block. This method provides a more accurate alternative solution to the problem of calculating energy deposition on grains. Although the method is computationally intensive, it can be synchronously executed with the granular dynamics simulation owing to the powerful parallel computing capability of GPUs. Thus, the studies on the dynamical and thermal behaviors of beam-grain coupling can be conducted in a relatively fast and precise way. (C) 2021 Elsevier B.V. All rights reserved. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.cpc.2021.108104 | COMPUTER PHYSICS COMMUNICATIONS |
Keywords | DocType | Volume |
Beam-target coupling, Granular materials, Energy deposition, Synchronous computing, GPU | Journal | 269 |
ISSN | Citations | PageRank |
0010-4655 | 0 | 0.34 |
References | Authors | |
0 | 11 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuan Tian | 1 | 0 | 0.34 |
| Ping Lin | 2 | 0 | 0.68 |
| Hanjie Cai | 3 | 0 | 0.34 |
| Yaling Zhang | 4 | 0 | 0.34 |
| Qiong Yang | 5 | 0 | 0.34 |
| Meiling Qi | 6 | 0 | 0.34 |
| Guanghui Yang | 7 | 0 | 0.34 |
| Xiaofei Gao | 8 | 0 | 0.34 |
| Xiaolong Chen | 9 | 0 | 0.34 |
| Lei Yang | 10 | 0 | 0.34 |
| Qingguo Zhou | 11 | 103 | 29.48 |