A novel method for simulating nuclear explosion with chemical explosion to form an approximate plane wave: Field test and numerical simulation

A nuclear explosion in the rock mass medium can produce strong shock waves,seismic shocks,and other destructive effects,which can cause extreme damage to the underground protection infrastructures.With the increase in nuclear explosion power,underground protection engineering enabled by explosion-proof impact theory and technology ushered in a new challenge.This paper proposes to simulate nuclear explosion tests with on-site chemical explosion tests in the form of multi-hole explosions.First,the mechanism of using multi-hole simultaneous blasting to simulate a nuclear explosion to generate approximate plane waves was analyzed.The plane pressure curve at the vault of the underground protective tunnel under the action of the multi-hole simultaneous blasting was then obtained using the impact test in the rock mass at the site.According to the peak pressure at the vault plane,it was divided into three regions:the stress superposition region,the superposition region after surface reflection,and the approximate plane stress wave zone.A numerical simulation approach was developed using PFC and FLAC to study the peak particle velocity in the surrounding rock of the underground protective cave under the action of multi-hole blasting.The time-history curves of pressure and peak pressure partition obtained by the on-site multi-hole simultaneous blasting test and numerical simulation were compared and analyzed,to verify the correctness and rationality of the formation of an approximate plane wave in the simulated nuclear explosion.This comparison and analysis also provided a theoretical foundation and some research ideas for the ensuing study on the impact of a nuclear explosion.

Improved seismoacoustic analysis model and its application to source parameter inversion of near-surface small-yield chemical explosions

The seismoacoustic analysis method has broad potential applications to source parameter estimation for near-surface explosion events such as industrial explosions and terrorist attacks.In this study,current models were improved by modifying the acoustic model and adopting the Bayesian Markov-chain-Monte-Carlo inversion method.The source parameters of near-surface small-yield chemical explosions were analyzed via the improved seismoacoustic analysis model and by the estimation accuracy of seismoacoustic joint inversion.Estimation and analysis results showed that the improved seismoacoustic analysis model considered ground shock coupling and the impact of explosion products ejecting from the surface so that the improved acoustic impulse relation was more consistent with the measured data than the Ford impulse relation.It is suitable for deep-burial,shallow-burial,and near-surface aerial explosions.Furthermore,trade-off relationships were declined through the application of the improved model to source parameter inversion for near-surface small-yield chemical explosions,and source parameter estimation accuracy was improved.

Analysis and Control Measures of Hazardous Chemical Explosions Based on Fault Tree Analysis

In view of the environmental and safety risks of hazardous chemical explosions in chemical enterprises,the fault tree analysis was used to establish a fault tree model of hazardous chemical explosions and comprehensively analyze the possibility of the explosions.The 34 basic events that caused hazardous chemical explosions were expounded,and the minimum cut and path sets were obtained.The structure importance of basic events were calculated.According to the minimum path sets,the basic events when the accident does not occur were determined,and combined with the sequence of structure importance,the preventive measures for hazardous chemical explosion accidents were proposed.The fault tree model intuitively clarified the correlation between the direct causes of hazardous chemical explosion accidents,and proposed directions for effectively reducing the probability of hazardous chemical explosion accidents in the chemical industry.

Large eddy simulation of spray combustion using flamelet generated manifolds combined with artificial neural networks

In the present work,artificial neural networks(ANN)technique combined with flamelet generated manifolds(FGM)is proposed to mitigate the memory issue of FGM models.A set of ANN models is firstly trained using a 68-species mass fractions in mixture fraction-progress variable space.The ANN prediction accuracy is examined in large eddy simulation(LES)and Reynolds averaged Navier-Stokes(RANS)simulations of spray combustion.It is shown that the present ANN models can properly replicate the FGM table for most of the species mass fractions.The network models with relative error less than 5%are considered in RANS and LES to simulate the Engine Combustion Network(ECN)Spray H flames.Validation of the method is firstly conducted in the framework of RANS.Both non-reacting and reacting cases show the present method predicts very well the trend of spray and combustion process under different ambient temperatures.The results show that FGM-ANN can replicate the ignition delay time(IDT)and lift-off length(LOL)precisely as the conventional FGM method,and the results agree very well with the experiments.With the help of ANN,it is possible to achieve high efficiency and accuracy,with a significantly reduced memory requirement of the FGM models.LES with FGM-ANN is then applied to explore the detailed spray combustion process.Chemical explosive mode analysis(CEMA)approach is used to identify the local combustion modes.It is found that before the spray flame is developed to the steady-state,the high CH_(2)O zone is always associated with ignition mode.However,high CH_(2)O zone together with high OH zone is dominated by the burned mode after the steady-state.The lift-off position is dominated mainly by the diffusion mode.