Determination of the JWL Parameters of Detonation Products Using Adaptive Genetic Algorithm

Cui, Hao; Song, P.; Gu, Xiaoqing; Zhou, Hao; Xing, Boyang; Jiang, Lin; Guo, Rui

doi:10.1002/prep.202000148

Cited by 12 publications

(4 citation statements)

References 30 publications

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“…GA is a search algorithm based on natural selection mechanisms, which essentially define a framework in which human intervention and random information exchange are combined to obtain potentially optimal results. Many studies [30][31][32] have explicitly reached to a conclusion that GA was more efficient in terms of the quality of solution and the ability to find a global optimum than other Optimization algorithm. GA requires only information about the objective function of the problem is solved and is not limited by whether the objective function is continuous or derivable.…”

Section: Optimization Methodsmentioning

confidence: 99%

Rapid optimization method of solid rocket motor propellant with structural strength

Guo,

Xu,

Chen

et al. 2023

Propellants Explo Pyrotec

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To design a solid rocket motor with a high mass ratio, it is necessary to find out the parameters of the grain shape to meet the structural strength under volume loading fraction and initial burning areas conditions. A rapid optimization method for complex grain of solid rocket motors based on parametric modelling and GA‐BP is proposed. Through the sensitivity analysis of the geometric parameters related to the grain, the sensitive parameters are determined. 30 groups of parameters are determined by the mixed horizontal orthogonal test and the learning samples of the neural network are obtained by FEA. The artificial neural network is established based on the FEA results, and the accuracy of the network is verified by 10 groups of test data sampled by the LHS method. The comparison results show that the prediction error of the maximum Von Mises strain is 5.09 %, the prediction error of the volume loading fraction is 0.16 %, and the prediction error of the initial burning surface is 0.865 %. Based on this, the neural network prediction results are optimized as a function of fitness in GA, and the optimization results show that the maximum strain is reduced by 20.41 % while the constraints are satisfied.

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Section: Optimization Methodsmentioning

confidence: 99%

Rapid optimization method of solid rocket motor propellant with structural strength

Guo,

Xu,

Chen

et al. 2023

Propellants Explo Pyrotec

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“…When an explosion occurs, the explosion of explosives is a rapid chemical reaction process. The equation of the state of explosives' detonation products is a complex function that describes the relationship between physical quantities such as pressure, temperature, and density of detonating products after the detonation wavefront [5] . Many different equations of state (EOS) have been proposed to describe the products of an explosion.…”

Section: 1equation Of State For the Explosive Explosionmentioning

confidence: 99%

Numerical Simulation of the Effect of Catalyst on Explosives Detonation Performance

Wei

Wei²

2023

J. Phys.: Conf. Ser.

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Previous studies on the effect of the blast shock wave are mainly based on experiments. However, due to the extremely short duration of the blast shock, usually within several dozen milliseconds, the blast shock wave will have gone from peak to zero, causing a significant impact on the accuracy of experimental results. In recent years, numerical simulation has become an important method to study the effect of the blast. To study the influence of catalysts on the combustion performance of explosives, this paper intends to study the effect of catalysts on the combustion and explosion performance of pyrotechnic explosives. ANSYS workbench finite element analysis software was used to establish a pyrotechnic-rock blasting model to simulate the different effects produced by different catalysts during the combustion of explosives and compare their blasting effects. It is expected to obtain the preparation technology of higher performance nano-combustion catalysts, good performance nano-combustion catalyst system and its microstructure on the catalytic law of energy-containing materials, and to lay an important theoretical foundation for further development of new varieties of fire explosives with excellent comprehensive performance.

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“…Genetic algorithms can be used to calibrate the parameters of the complex forms of material constitutive and equation of state. At present, this method has been applied to calibrate the parameters of the explosive state equation [ 40 , 41 ] and the material constitutive model [ 42 , 43 , 44 ]. The Multiple Population Genetic Algorithm (MPGA) used in this work not only inherits many of the advantages from the standard genetic algorithm (SGA), such as no need for gradient information, strong robustness, good ability to capture global optima, etc.…”

Section: The Constitutive Analysismentioning

confidence: 99%

Dynamic Mechanical Properties of TC11 Titanium Alloys Fabricated by Wire Arc Additive Manufacturing

Tian

Tan

et al. 2022

Materials

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To study the compressive mechanical properties and failure modes of TC11 titanium alloy fabricated by wire arc additive manufacturing (WAAM) technology in a large strain rate range at room temperature, the quasi-static and dynamic compression tests were carried out. In addition, optical microscopy (OM) and scanning electron microscopy (SEM) were employed to observe the metallographic structure and fracture morphology, respectively. The stress–strain curves in the range of 0.001 s−1–4000 s−1, original and post-deformation microstructures, macroscopic damage patterns, and microscopic fracture morphology were obtained at two different loading directions, including the scanning and deposition directions, respectively. In uniaxial compression experiments, the material showed little difference in mechanical properties between the scanning and deposition directions, exhibiting a strain rate strengthening effect. However, the strain rate sensitivity of the material under quasi-static loading conditions is much less than that under dynamic loading conditions. In addition, combining the stress–strain curve with the fracture morphology analysis, the plasticity in the scanning direction is better than in the deposition direction. Based on the experimental results, a modified Johnson–Cook (JC) constitutive model considering strain rate sensitivity and the effect of strain rate on strain hardening was proposed, and the parameters were determined using a Multiple Population Genetic Algorithm (MPGA). The obtained constitutive model is in good agreement with the experimental data, which can provide a reference for the engineering numerical calculation of TC11 titanium alloy for WAAM. This study also provides a fundamental databank for the application and design of WAAM TC11 alloy in the manufacturing of large and complex structural parts.

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Determination of the JWL Parameters of Detonation Products Using Adaptive Genetic Algorithm

Cited by 12 publications

References 30 publications

Rapid optimization method of solid rocket motor propellant with structural strength

Rapid optimization method of solid rocket motor propellant with structural strength

Numerical Simulation of the Effect of Catalyst on Explosives Detonation Performance

Dynamic Mechanical Properties of TC11 Titanium Alloys Fabricated by Wire Arc Additive Manufacturing

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