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| efficient simulation of grain burning surface regression | |
| Liu Youquan; Yin Kangxue; Bao Futing; Liu Yang; Wu Enhua | |
| 2012 | |
| Conference Name | 2012 International Conference on Intelligent System and Applied Material, GSAM 2012 |
| Source | Applied Mechanics and Materials |
| Pages | 314-318 |
| Conference Date | January 13, 2012 - January 15, 2012 |
| Conference Place | Taiyuan, Shanxi, China |
| Indexed Type | EI |
| ISSN | 1660-9336 |
| ISBN | 9783037853689 |
| Department | (1) School of Information Engineering Chang'an University Xi'an China; (2) School of Astronautics Northwestern Polytechnic University Xi'an China; (3) State Key Lab of Computer Science Institute of Software Chinese Academy of Sciences China |
| English Abstract | The computation of grain burning surface regression plays a very important role in the internal ballistic performance evaluation of solid rocket motor, however, the traditional methods such as geometry-based one could not handle the self-intersection and characteristic geometric element disappearing problems. This paper presents an effective and efficient framework to simulate 3D grain burning surface regression with level set method which is combined with Fast Marching technique to constrain the calculation area only around the burning surface. At last, a typical grain example is given by our framework to verify our method's effectiveness and efficiency. © (2012) Trans Tech Publications.; The computation of grain burning surface regression plays a very important role in the internal ballistic performance evaluation of solid rocket motor, however, the traditional methods such as geometry-based one could not handle the self-intersection and characteristic geometric element disappearing problems. This paper presents an effective and efficient framework to simulate 3D grain burning surface regression with level set method which is combined with Fast Marching technique to constrain the calculation area only around the burning surface. At last, a typical grain example is given by our framework to verify our method's effectiveness and efficiency. © (2012) Trans Tech Publications. |
| Keyword | Intelligent Systems Numerical Methods Regression Analysis Rocket Engines Rockets |
| Language | 英语 |
| Content Type | 会议论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/15696 |
| Collection | 中国科学院软件研究所 |
| Recommended Citation GB/T 7714 | Liu Youquan,Yin Kangxue,Bao Futing,et al. efficient simulation of grain burning surface regression[C],2012:314-318. |
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