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固体火箭发动机药柱材料凝固冷却可靠性分析。

Reliability analysis of the solidification cooling of solid rocket motor grain material.

机构信息

College of Statistics and Mathematics, Inner Mongolia University of Finance and Economics, Hohhot, Inner Mongolia, China.

College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia, China.

出版信息

PLoS One. 2024 Aug 20;19(8):e0306208. doi: 10.1371/journal.pone.0306208. eCollection 2024.

DOI:10.1371/journal.pone.0306208
PMID:39163386
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11335151/
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.

摘要

对固体火箭发动机药柱结构在冷却固化过程中的可靠性进行了分析。首先,利用 ANSYS 有限元软件对药柱进行了三维参数化建模。在冷却条件下,基于瞬态和动态热结构耦合,可以得到危险点和危险时刻,并提取出最大等效应变和温度值。其次,基于 copula 函数的概率分布和具体参数,建立了双神经网络模型。最后,计算了药柱在冷却固化过程中的瞬时可靠性,实现了动态可靠性分析。该方法降低了药柱结构动态可靠性的计算成本,证明了其在实际工程问题中的适用性。此外,将所提方法的结果与 MCS 方法进行比较,表明所提方法具有较高的计算精度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/048f/11335151/9a58c8afe888/pone.0306208.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/048f/11335151/cec20298bd4c/pone.0306208.g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/048f/11335151/356984527742/pone.0306208.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/048f/11335151/87b969b47d8a/pone.0306208.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/048f/11335151/7c1f277a482a/pone.0306208.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/048f/11335151/9a58c8afe888/pone.0306208.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/048f/11335151/cec20298bd4c/pone.0306208.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/048f/11335151/b87afde3c625/pone.0306208.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/048f/11335151/5508f258e24b/pone.0306208.g003.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/048f/11335151/de84e3cd2b0d/pone.0306208.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/048f/11335151/356984527742/pone.0306208.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/048f/11335151/87b969b47d8a/pone.0306208.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/048f/11335151/7c1f277a482a/pone.0306208.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/048f/11335151/9a58c8afe888/pone.0306208.g009.jpg

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