Cook-off experiment on the JH-14C booster explosive with a shell and the relevant numerical simulation

XIAO Youcai; WANG Ruisheng; FAN Chenyang; ZHANG Hong; WANG Zhijun; SUN Yi

doi:10.11883/bzycj-2022-0555

Volume 43 Issue 7

Jul. 2023

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XIAO Youcai, WANG Ruisheng, FAN Chenyang, ZHANG Hong, WANG Zhijun, SUN Yi. Cook-off experiment on the JH-14C booster explosive with a shell and the relevant numerical simulation[J]. Explosion And Shock Waves, 2023, 43(7): 072301. doi: 10.11883/bzycj-2022-0555

Citation:

XIAO Youcai, WANG Ruisheng, FAN Chenyang, ZHANG Hong, WANG Zhijun, SUN Yi. Cook-off experiment on the JH-14C booster explosive with a shell and the relevant numerical simulation[J]. Explosion And Shock Waves, 2023, 43(7): 072301. doi: 10.11883/bzycj-2022-0555

Citation:

XIAO Youcai, WANG Ruisheng, FAN Chenyang, ZHANG Hong, WANG Zhijun, SUN Yi. Cook-off experiment on the JH-14C booster explosive with a shell and the relevant numerical simulation[J]. Explosion And Shock Waves, 2023, 43(7): 072301. doi: 10.11883/bzycj-2022-0555

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Cook-off experiment on the JH-14C booster explosive with a shell and the relevant numerical simulation

doi: 10.11883/bzycj-2022-0555

1.
College of Mechatronic Engineering, North University of China, Taiyuan 030051, Shanxi, China
2.
Xi’an Institute of Electromechanical Information Technology, Xi’an 710065, Shaanxi, China
3.
The 713th Research Institute, China State Shipbuilding Corporation Limited, Zhengzhou 450015, Henan, China
4.
Department of Astronautic Science and Mechanics, School of Astronautics Harbin Institute of Technology, Harbin 150001, Heilongjiang, China

Received Date: 2022-12-12
Rev Recd Date: 2023-05-17

Available Online: 2023-05-17

Publish Date: 2023-07-05

Abstract

Abstract

In order to explore the cook-off response characteristics of the JH-14C booster explosive with a shell under different external temperatures, a set of experimental devices was designed for measuring the cook-off response temperatures at multiple points of the JH-14C booster explosive and for monitoring the deformation of the shell. The explosive temperatures were measured from its edge to its center. The strain-time curves of the shell were recorded by a dynamic strain indicator and a high-temperature strain gauge. The cook-off experiments with the heating rates of 1.0 ℃/min and 3.3 ℃/h were conducted. The temperature was raised at different points of the explosive and the strains at different points of the shell were obtained. The intensity of the shock wave in the process of the slow cook-off experiment is calculated by using the thin-walled cylinder principle, and the violence of the reaction of the JH-14C booster explosive with a shell is quantitatively characterized by using the intensity of blast loading. The response characteristics of the JH-14C booster explosive with a shell in the slow cook-off experiment is revealed. Though the relationship between the shell strain results and the reaction intensities, a method is proposed to describe the reaction level of the JH-14C booster explosive with a shell. Based on the thermodynamics and the chemical reaction of the explosive, the heat conduction model is established. The decomposition reaction of the explosive is described by the Arrhenius equation. A back propagation (BP) neural network is used to invert the heat reaction parameters of the JH-14C booster explosive. Comparison between the experimental and simulated results shows that the presented model can be used to obtain the cook-off response characteristics of the explosive obtained by simulation with high precision. The internal temperature field response of the projectile body is also studied under different heating rates. The results exhibit that the lower the heating rate, the higher the response temperature of the charge and the more intense the reaction. With the decrease of the heating rate, the ignition area of the explosive gradually shifts from the outer edges of both ends to the inside of the explosive.
- JH-14C booster explosive,
- cook-off experiment,
- cook-off response,
- heating rate,
- heat reaction parameter,
- BP neural network

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References(29)

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