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Reliability analysis of the solidification cooling of solid rocket motor grain material.
Du, Juan; Li, Yangtian; He, Yun.
Affiliation
  • Du J; College of Statistics and Mathematics, Inner Mongolia University of Finance and Economics, Hohhot, Inner Mongolia, China.
  • Li Y; College of Statistics and Mathematics, Inner Mongolia University of Finance and Economics, Hohhot, Inner Mongolia, China.
  • He Y; College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, China.
PLoS One ; 19(8): e0306208, 2024.
Article in En | MEDLINE | ID: mdl-39163386
ABSTRACT
The reliability of solid rocket motor grain structure during solidification cooling is analyzed. First, a three-dimensional parametric modeling of the grain is carried out by ANSYS finite element software. The dangerous point and dangerous moment can be obtained based on the transient and dynamic thermo-structure coupling under the cooling condition. Moreover, the maximum equivalent strain and temperature values are extracted. Second, a dual neural network model is established based on the probability distribution of the copula function and specific parameters. Finally, the instantaneous reliability during the solidification cooling process of the grain is calculated. Then, the dynamic reliability analysis is realized. The proposed method reduces the computational cost of dynamic reliability of grain structure, demonstrating its applicability in practical engineering problems. Furthermore, comparing the results of the proposed method with the MCS method demonstrates that the proposed method has high computational accuracy.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Neural Networks, Computer Language: En Journal: PLoS One Journal subject: CIENCIA / MEDICINA Year: 2024 Document type: Article Affiliation country: Country of publication:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Neural Networks, Computer Language: En Journal: PLoS One Journal subject: CIENCIA / MEDICINA Year: 2024 Document type: Article Affiliation country: Country of publication: