芳香族硝基化合物爆速的定量构效关系预测

doi:10.16265/j.cnki.issn1003-3033.2018.07.006

中国安全科学学报 ›› 2018, Vol. 28 ›› Issue (7): 32-37.doi: 10.16265/j.cnki.issn1003-3033.2018.07.006

芳香族硝基化合物爆速的定量构效关系预测

何培¹, 潘勇^**1 教授, 蒋军成¹ 教授, 周炜² 研究员

1 南京工业大学安全科学与工程学院,江苏南京 210009;
2 交通运输部公路科学研究院,北京 100029

收稿日期:2018-04-18 修回日期:2018-06-13 出版日期:2018-07-28 发布日期:2020-11-25
通讯作者: **潘勇(1981—),男,江苏溧阳人,博士,教授,主要从事危险化学品安全研究。E-mail:yongpannjut@163.com。
作者简介:何培(1994—),女,江苏扬中人,硕士研究生,主要研究方向为化学物质危险特性及其分析鉴定技术。E-mail:952746346@qq.com。
基金资助:
国家自然科学基金资助(21576136,21436006);国家重点研发计划课题项目(2017YFC0804801, 2016YFC0800100)。

Prediction of detonation velocity of nitro aromatic compoundsbased on quantitative structure-property relationship

HE Pei ¹, PAN Yong ¹, JIANG Juncheng¹, ZHOU Wei²

1 College of Safety Science and Engineering,Nanjing Tech University,Nanjing Jiangsu 210009,China;
2 China Academy of Highway Transportation Sciences,Beijing 100029,China

Received:2018-04-18 Revised:2018-06-13 Online:2018-07-28 Published:2020-11-25

摘要/Abstract

摘要： 为提高芳香族硝基化合物爆速的预测精度,提出基于定量结构-性质相关性(QSPR)的芳香族硝基化合物爆速的理论预测方法。应用Dragon软件计算21种芳香族硝基化合物的分子描述符,利用遗传-多元线性回归方法(GA-MLR)从大量描述符中筛选出4个与爆速关系最为密切的分子描述符,建立相应的4参数线性理论预测模型,并采用内部和外部验证方式,验证模型的拟合能力、稳健性和预测能力。结果表明:训练集和测试集的平均绝对误差(AAE)分别为0.048和0.208 km/s,均方根误差(RMSE)分别为0.058和0.302 km/s,所建模型具有较好的稳健性和预测性能。

关键词: 芳香族硝基化合物, 爆速, 定量结构-性质相关性(QSPR), 遗传-多元线性回归方法(GA-MLR), 预测

Abstract: In order to improve the accuracy of predicting detonation velocities of aromatic nitro compounds,a prediction method based on the QSPR principle was worked out.Molecular descriptors of 21 kinds of aromatic nitro compounds were calculated by using the Dragon software and 4 molecular descriptors relating the most closely to the detonation velocity of aromatic nitro compounds were selected from a large number of descriptors through GA-MLR method.A four-parameter linear theory model was built for predicting the velocities,and the degree of fitting,robustness and predictability were verified by means of the internal authentication method and the external validation method.The results demonstrate that the average absolute error (AAE) for the training set and test set is 0.048 and 0.208 km/s respectively,the root mean square error (RMSE) is 0.058 and 0.302 km/s,and that the effectiveness of the proposed method is great.

Key words: nitro aromatic compounds, detonation velocity, quantitative structure-property relationship (QSPR), genetic algorithm-based multiple linear regression (GA-MLR), prediction

中图分类号:

X937

何培, 潘勇, 蒋军成, 周炜. 芳香族硝基化合物爆速的定量构效关系预测[J]. 中国安全科学学报, 2018, 28(7): 32-37.

HE Pei, PAN Yong, JIANG Juncheng, ZHOU Wei. Prediction of detonation velocity of nitro aromatic compoundsbased on quantitative structure-property relationship[J]. China Safety Science Journal, 2018, 28(7): 32-37.

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芳香族硝基化合物爆速的定量构效关系预测

Prediction of detonation velocity of nitro aromatic compoundsbased on quantitative structure-property relationship

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