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- W2383784148 abstract "On the basis of finite element data,artificial neural network was established,and the interpolation prediction of stress and strain response in the head of solid propellant was made. Taking artificial neural network output,the maximum Mises stress at the splicing band σ and the maximum Mises strain of the circular arc at top of the stress-releaser e1and e2,as target function,the stress-releaser structure of propellant gain was optimized using the genetic algorithm.And an optimized design scheme was obtained.The results show that the non-linear relationship between the stress and strain in the head of the propellant gain and the size of stress-releaser can be reflected by the trained artificial neural network effectively,and that Multi-objective optimization design scheme has obvious optimization effect and is more feasible than the single objective optimization design scheme. The method can provide reference for the design of stress-releaser of propellant gain." @default.
- W2383784148 created "2016-06-24" @default.
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- W2383784148 date "2014-01-01" @default.
- W2383784148 modified "2023-09-25" @default.
- W2383784148 title "Optimization design for the stress-releaser of solid propellant gain based on genetic algorithm and neural network" @default.
- W2383784148 hasPublicationYear "2014" @default.
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