Investigating the detonation reaction zone structures of high explosives is significant for understanding detonation reaction mechanism.This study employed an integrated approach combining machine learning prediction,...Investigating the detonation reaction zone structures of high explosives is significant for understanding detonation reaction mechanism.This study employed an integrated approach combining machine learning prediction,theoretical calculation,and experimental characterization to determine the detonation reaction zone width of CL-20-based aluminized explosive.In this study,the detonation reaction zone refers to the reaction zone between the von Neumann(VN)peak and sonic point,which usually means the so-called detonation driving zone(DDZ).For the machine learning prediction,an ensemble model integrating Random Forest and Support Vector Regression was developed to predict the reaction zone width using a dataset of 19 publicly available samples.For the theoretical calculation,the Wood-Kirkwood(W-K)detonation theory model was utilized to implement numerical calculation of the reaction zone structures,incorporating chemical reaction kinetics to describe the detonation reaction progress.In experimental characterization,the Photon Doppler Velocimetry(PDV)was applied with LiF as the optical window to measure the particle velocity profile of detonation products and derive the reaction zone width.The results indicate that the reaction zone width values are 0.25 mm,0.28 mm,and 0.26 mm obtained from machine learning prediction,theoretical calculation,and experimental characterization,respectively.The corresponding velocities at the Chapman-Jouguet(CJ)point are 1,938 m/s,2,047 m/s,and 1,982 m/s,respectively.The maximum relative deviation in reaction zone width among three methods is approximately 7.7%,while that for CJ particle velocity is approximately 3.3%.These results from all three methods agree well within engineering error.This validates the effectiveness of integrating machine learning prediction,theoretical calculation and advanced experimental techniques for studying the detonation reaction zone structures of high explosives.This research provides insights into the detonation reaction mechanism and reaction zone characteristics of CL-20-based aluminized explosive.展开更多
为了揭示笼状含能材料六硝基六氮杂异伍兹烷(hexanitrohexaazaisowurtzitane,ε-CL-20)冲击感度各向异性规律,采用低梯度色散校正的反应性力场(reactive force field with low-gradient dispersion corrections,ReaxFF-lg)和分子动力学...为了揭示笼状含能材料六硝基六氮杂异伍兹烷(hexanitrohexaazaisowurtzitane,ε-CL-20)冲击感度各向异性规律,采用低梯度色散校正的反应性力场(reactive force field with low-gradient dispersion corrections,ReaxFF-lg)和分子动力学方法,分别垂直ε-CL-20的6个重要晶面(010)、(110)、(201)、(011)、(111)和(001)进行多尺度冲击加载模拟,考察体系内应力、温度以及化学反应与冲击方向的关联规律。结果表明ε-CL-20具有明显的冲击感度各向异性,6个重要晶面冲击感度强弱顺序为:(010)>(110)>(201)≈(011)>(111)>(001)。垂直于(010)晶面冲击时体系的力-热-化学响应最强、感度最高,垂直于(001)晶面冲击时体系的力-热-化学响应最弱、感度最低。以ε-CL-20不同晶面冲击响应特性为基础,总结了平面层状堆积含能材料的冲击感度各向异性规律,即当冲击方向平行于分子层时冲击感度最高,垂直于分子层时冲击感度最低。展开更多
文摘Investigating the detonation reaction zone structures of high explosives is significant for understanding detonation reaction mechanism.This study employed an integrated approach combining machine learning prediction,theoretical calculation,and experimental characterization to determine the detonation reaction zone width of CL-20-based aluminized explosive.In this study,the detonation reaction zone refers to the reaction zone between the von Neumann(VN)peak and sonic point,which usually means the so-called detonation driving zone(DDZ).For the machine learning prediction,an ensemble model integrating Random Forest and Support Vector Regression was developed to predict the reaction zone width using a dataset of 19 publicly available samples.For the theoretical calculation,the Wood-Kirkwood(W-K)detonation theory model was utilized to implement numerical calculation of the reaction zone structures,incorporating chemical reaction kinetics to describe the detonation reaction progress.In experimental characterization,the Photon Doppler Velocimetry(PDV)was applied with LiF as the optical window to measure the particle velocity profile of detonation products and derive the reaction zone width.The results indicate that the reaction zone width values are 0.25 mm,0.28 mm,and 0.26 mm obtained from machine learning prediction,theoretical calculation,and experimental characterization,respectively.The corresponding velocities at the Chapman-Jouguet(CJ)point are 1,938 m/s,2,047 m/s,and 1,982 m/s,respectively.The maximum relative deviation in reaction zone width among three methods is approximately 7.7%,while that for CJ particle velocity is approximately 3.3%.These results from all three methods agree well within engineering error.This validates the effectiveness of integrating machine learning prediction,theoretical calculation and advanced experimental techniques for studying the detonation reaction zone structures of high explosives.This research provides insights into the detonation reaction mechanism and reaction zone characteristics of CL-20-based aluminized explosive.
文摘为了揭示笼状含能材料六硝基六氮杂异伍兹烷(hexanitrohexaazaisowurtzitane,ε-CL-20)冲击感度各向异性规律,采用低梯度色散校正的反应性力场(reactive force field with low-gradient dispersion corrections,ReaxFF-lg)和分子动力学方法,分别垂直ε-CL-20的6个重要晶面(010)、(110)、(201)、(011)、(111)和(001)进行多尺度冲击加载模拟,考察体系内应力、温度以及化学反应与冲击方向的关联规律。结果表明ε-CL-20具有明显的冲击感度各向异性,6个重要晶面冲击感度强弱顺序为:(010)>(110)>(201)≈(011)>(111)>(001)。垂直于(010)晶面冲击时体系的力-热-化学响应最强、感度最高,垂直于(001)晶面冲击时体系的力-热-化学响应最弱、感度最低。以ε-CL-20不同晶面冲击响应特性为基础,总结了平面层状堆积含能材料的冲击感度各向异性规律,即当冲击方向平行于分子层时冲击感度最高,垂直于分子层时冲击感度最低。
