Calculation for Primary Combustion Characteristics of Boron-Based Fuel-Rich Propellant Based on BP Neural Network | Zendy

Wu Wan'e | Zendy; Zhu Zuoming | Zendy

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Calculation for Primary Combustion Characteristics of Boron-Based Fuel-Rich Propellant Based on BP Neural Network

Author(s) -

Wu Wan'e,

Zhu Zuoming

Publication year - 2012

Publication title -

journal of combustion

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.45

H-Index - 18

eISSN - 2090-1968

pISSN - 2090-1976

DOI - 10.1155/2012/635190

Subject(s) - ammonium perchlorate , propellant , boron , combustion , polybutadiene , materials science , backpropagation , range (aeronautics) , artificial neural network , nuclear engineering , process engineering , computer science , environmental science , chemistry , composite material , engineering , organic chemistry , artificial intelligence , copolymer , polymer

A practical scheme for selecting characterization parameters of boron-based fuel-rich propellant formulation was put forward; a calculation model for primary combustion characteristics of boron-based fuel-rich propellant based on backpropagation neural network was established, validated, and then was used to predict primary combustion characteristics of boron-based fuel-rich propellant. The results show that the calculation error of burning rate is less than ±7.3%; in the formulation range (hydroxyl-terminated polybutadiene 28%–32%, ammonium perchlorate 30%–35%, magnalium alloy 4%–8%, catocene 0%–5%, and boron 30%), the variation of the calculation data is consistent with the experimental results

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