火炸药学报2017，Vol.40Issue(3)：53-59,7.DOI:10.14077/j.issn.1007-7812.2017.03.009
基于BKW状态方程的爆轰产物及参数的改进算法
Improved Algorithm of Detonation Products and Parameters Based on the BKW Equation of State
摘要
Abstract
To reduce the difficulty of predicting the detonation products and solving detonation parameters, the equilibrium compositions of detonation products were achieved by linear combination of the basic feasible solutions, which were obtained from the mass conservation equations;and the detonation parameters were further obtained based on equilibrium compositions.The major process was executed as follows: the basic feasible solutions were selected out by the principle of minimum free energy, and the initial solution was given by the principle of largest heat release.The equilibrium compositions of detonation products were linearly searched by uniting the initial solution with the basic feasible solutions, and the above-mentioned operation steps were completed by using self-made program.The parameters of the BKW equation of state were adjusted applying the linear support vector machine (SVM), and its main steps were introduced in detail.The detonation products and parameters of PETN, CL-20 and aluminized explosives were predicted with this method, and after parameter adjustment, it is found that the predicted results and the experimental ones are in better agreement.In comparison with the detonation experiment data of single compound, it is found out that when the BKW equation parameters are adjusted, the energetic materials with more similar percentage of gas fraction in detonation mass to the explosives predicted should be used as the training set of the LS-SVM model.If the detonation parameters of aluminized explosives are predicted, it should use the Al/O ratio close to measured explosive to train the SVM model.关键词
爆炸力学/BKW状态方程/基本可行解/支持向量机/SVM/吉布斯自由能Key words
explosion mechanics/BKW equation of state/basic feasible solution/support vector machine/SVM/Gibbs free energy分类
军事科技引用本文复制引用
何伟平,黄菊,陈厚和,刘晓静,王德堂..基于BKW状态方程的爆轰产物及参数的改进算法[J].火炸药学报,2017,40(3):53-59,7.基金项目
徐州市科技计划社会发展项目(KC15SH064) （KC15SH064）
徐州工业职业技术学院科技基金资助项目(XGY201607) （XGY201607）
