Large scale blast emulator based explosive gas loading methods for structures and recent advances in experimental studies

This paper discusses the methods of utilizing acetylene-air mixture explosion for blast loading realization and its related experimental implementations, as well as the numerical simulation on comparison of dynamite explosion and acetylene-air mixture explosion based on LS-DYNA nonlinear explicit dynamic codes. The characteristic parameters of shock wave, such as over pressure and arriving time with respect to propagation distance, are compared for different blast cases. Then, the blast heat based equivalent principle and modified index of scale distance for gas explosion is proposed from the point view of energy conservation. The analysis results show that the Euler algorithm is useful for the numerical simulation of shock wave propagation caused by acetylene-air mixture explosion, and the results are in good accordance with the prediction results through different empirical formulations. With the increasing of propagation distance, the relative error between the two explosion methods is shown to be decreased. As a result, the explosive acetylene-air mixture can be used to conditionally realize the explosion effect of traditional chemical dynamites, such as TNT explosives. The results establish a theoretical foundation for using such explosive gas material in generating shock wave loadings based on the large scale blast emulator facility. At last, some preliminary test results on Tension Membrane structure, scaled steel frame structure and model energy resources structure are summarized based on this blast test method

Numerical Investigation on Improving the Computational Efficiency of the Material Point Method

Based on the basic theory of the material point method (MPM), the factors affecting the computational efficiency are analyzed and discussed, and the problem of improving calculation efficiency is studied. This paper introduces a mirror reflection boundary condition to the MPM to solve axisymmetric problems; to improve the computational efficiency of solving large deformation problems, the concept of "dynamic background domain (DBD)" is also proposed in this paper. Taking the explosion and/or shock problems as an example, the numerical simulation are calculated, and the typical characteristic parameters and the CPU time are compared. The results show that the processing method introducing mirror reflection boundary condition and MPM with DBD can improve the calculation efficiency of the corresponding problems, which, under the premise of ensuring its calculation accuracy, provide useful reference for further promoting the engineering application of this method

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

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

Stochastic Material Point Method for Analysis in Non-Linear Dynamics of Metals

A stochastic material point method is proposed for stochastic analysis in non-linear dynamics of metals with varying random material properties. The basic random variables are parameters of equation of state and those of constitutive equation. In conjunction with the material point method, the Taylor series expansion is employed to predict first- and second-moment characteristics of structural response. Unlike the traditional grid methods, the stochastic material point method does not require structured mesh; instead, only a scattered cluster of nodes is required in the computational domain. In addition, there is no need for fixed connectivity between nodes. Hence, the stochastic material point method is more suitable than the stochastic method based on grids, when solving dynamics problems of metals involving large deformations and strong nonlinearity. Numerical examples show good agreement between the results of the stochastic material point method and Monte Carlo simulation. This study examines the accuracy and convergence of the stochastic material point method. The stochastic material point method offers a new option when solving stochastic dynamics problems of metals involving large deformation and strong nonlinearity, since the method is convenient and efficient