Study on Shock Initiation Randomness of Energetic Materials on a Macroscopic Scale

Author:

Liu Lan1ORCID,Chen Weidong1,Lu Shengzhuo1,Yu Yanchun2ORCID,Wu Shibo1,Wu Peiwen1

Affiliation:

1. College of Aerospace and Civil Engineering, Harbin Engineering University, Harbin 150001, China

2. School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin 150030, China

Abstract

The shock initiation randomness problem of energetic materials (SIREM) is an important problem in the research field of energetic material safety. With the purposes of solving SIREM on a macroscopic scale and obtaining the statistics, such as the initiation probabilities of energetic materials and the statistical characteristics of the detonation pressure, this paper considers the effect of the randomness of the parameters of the Lee–Tarver equation of reaction rate and the JWL equation of state of energetic materials and the randomness of load intensity parameters—such as fragment shock velocity—on the randomness of the shock initiations of energetic materials. It then decomposes SIREM into an initiation probability problem (IP) and a detonation pressure randomness problem (DPR). Further, with the Back Propagation Neural Networks optimized by the Genetic Algorithm (GABPNN) as the surrogate models of the numerical models of two-phase reactive flow, this paper proposes the approach of solving IP and DPR in turn, adopting Monte Carlo Simulations, which use the calculations of GABPNNs as repeated sampling tests (GABP-MCSs). Finally, by taking the shock initiation randomness problem of Composition B as an applied example, this paper adopts GABP-MCS under the randomness conditions that the means of fragment shock velocities are 1050 m/s and 1000 m/s and that the coefficients of variation (CVs) of BRVs are 0.005, 0.01, 0.015, and 0.02 in order to obtain the initiation probabilities of Composition B and the statistical characteristics, such as the means and CVs of the detonation pressure. It further observes the variation tendencies that these statistics show under various randomness conditions, so as to prove the effectiveness of GABP-MCS in solving SIREM. Therefore, this paper investigates SIREM on a macroscopic scale and proposes a universal technique for solving SIREM by GABP-MCS, in the hope of shedding some light on the SIREM study.

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

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