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Title:
efficient simulation of grain burning surface regression
Author: Liu Youquan ; Yin Kangxue ; Bao Futing ; Liu Yang ; Wu Enhua
Source: Applied Mechanics and Materials
Conference Name: 2012 International Conference on Intelligent System and Applied Material, GSAM 2012
Conference Date: January 13, 2012 - January 15, 2012
Issued Date: 2012
Conference Place: Taiyuan, Shanxi, China
Keyword: Intelligent systems ; Numerical methods ; Regression analysis ; Rocket engines ; Rockets
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
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.
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.
Language: 英语
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/15696
Appears in Collections:软件所图书馆_会议论文

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Recommended Citation:
Liu Youquan,Yin Kangxue,Bao Futing,et al. efficient simulation of grain burning surface regression[C]. 见:2012 International Conference on Intelligent System and Applied Material, GSAM 2012. Taiyuan, Shanxi, China. January 13, 2012 - January 15, 2012.
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