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Finite Element Model Updating Method for Radio Telescope Antenna Based on Parameter Optimization with Surrogate Model.

Authors :
Wang, Shuo
Xiang, Binbin
Wang, Wei
Lian, Peiyuan
Zhao, Yongqing
Cui, Hanwei
Lin, Shangmin
Zhou, Jianping
Source :
Applied Sciences (2076-3417); Jul2024, Vol. 14 Issue 13, p5620, 17p
Publication Year :
2024

Abstract

There are deviations between the radio telescope antenna finite element (FE) model, founded on the design stage, and the actual working antenna structure. The original FE model cannot accurately describe the antenna structure deformation characteristics under the environmental load, thereby compromising the accuracy of the active structural compensation. This article proposes an antenna FE model updating method founded on parameter optimization with a surrogate model. The updating method updates the modulus of elasticity parameters of different components of the antenna backup structure (BUS) to obtain finite element analysis (FEA) results consistent with the actual measurement of the antenna reflector surface shape. The surrogate model founded on the multi-quadratic radial basis function (RBF) improves the computational efficiency of FE model updating, replacing the complex and time-consuming finite element analysis and calculation process. This method is implemented on a radio telescope antenna with an aperture of 25 m. The results show a significant reduction in the mismatch between the antenna and the updated FE model. This method's calculation time is significantly reduced compared with the updating method without using the surrogate model, with the RBF surrogate model taking 1% of the time of the finite element model in the FEA calculations. The proposed method can improve the antenna FE model calculation accuracy and significantly enhance the efficiency of FE model updating calculations. Thus, it can offer a reference for antenna engineering practice. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20763417
Volume :
14
Issue :
13
Database :
Complementary Index
Journal :
Applied Sciences (2076-3417)
Publication Type :
Academic Journal
Accession number :
178413945
Full Text :
https://doi.org/10.3390/app14135620