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Adaptive step-size numerical vibration correlation technique for buckling prediction of thin-walled shells under axial compression and thermal loads.

Authors :
Huang, Lei
Xia, Qiushi
Gao, Tianhe
Wang, Bo
Tian, Kuo
Source :
Multidiscipline Modeling in Materials & Structures (Emerald Group Publishing Limited); 2022, Vol. 18 Issue 4, p635-652, 18p
Publication Year :
2022

Abstract

Purpose: The purpose of this paper is to propose a numerical prediction method of buckling loads for shell structures under axial compression and thermal loads based on vibration correlation technique (VCT). Design/methodology/approach: VCT is a non-destructive test method, and the numerical realization of its experimental process can become a promising buckling load prediction method, namely numerical VCT (NVCT). First, the derivation of the VCT formula for thin-walled structures under combined axial compression and thermal loads is presented. Then, on the basis of typical NVCT, an adaptive step-size NVCT (AS-NVCT) calculation scheme based on an adaptive increment control strategy is proposed. Finally, according to the independence of repeated frequency analysis, a concurrent computing framework of AS-NVCT is established to improve efficiency. Findings: Four analytical examples and one optimization example for imperfect conical-cylindrical shells are carried out. The buckling prediction results for AS-NVCT agree well with the test results, and the efficiency is significantly higher than that of typical numerical buckling methods. Originality/value: The derivation of the VCT formula for thin-walled shells provides a theoretical basis for NVCT. The adaptive incremental control strategy realizes the adaptive adjustment of the loading step size and the maximum applied load of NVCT with Python script, thus establishing AS-NVCT. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15736105
Volume :
18
Issue :
4
Database :
Complementary Index
Journal :
Multidiscipline Modeling in Materials & Structures (Emerald Group Publishing Limited)
Publication Type :
Academic Journal
Accession number :
158675669
Full Text :
https://doi.org/10.1108/MMMS-05-2022-0083