Finite Element Model Updating of Axisymmetric Structures

Creating the most accurate numerical models with the same dynamic behavior as real structures plays an important role in the development process of various facilities. This article deals with the use of experimental methods, particularly experimental modal analysis (EMA), scanning, detection, spectral analysis, and mechanical testing in combination with the optimization techniques of the ANSYS 2024 R1 software to calibrate numerical models of axisymmetric structures. The proposed methodology was tested on a steel pipe whose geometric and material properties were both available. Within the updating of finite element models (FEMU) with one or two design variables, the influence of the range of feasible values on the accuracy of the observed parameters was examined. The updating process led to the acquisition of such a pipe model, which natural frequencies differed by less than 1.5% from the results estimated in EMA, and its weight also differed only minimally. The proposed methodology was then used for the FEMU of a pressure vessel whose contour was obtained by a 3D scanning method; material properties were investigated, and all wall thicknesses, i.e., eleven design variables, were unknown and thus determined by an iterative optimization technique. Using the Multi-Objective Genetic Algorithm (MOGA) method, the dimensions of the vessel were first updated for their shell model and subsequently for the 3D model. The resulting natural frequencies of the model with applied internal pressures of 0 bar, 40 bar, and 80 bar differed from those estimated experimentally by less than 1.2%.

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Publication Details

Journal
Applied Sciences
Published
2025-10-24
DOI
https://doi.org/10.3390/app152111407
Primary Topic
Structural Health Monitoring Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Finite Element Model Updating of Axisymmetric Structures

Jaroslav Briančin, Pavol Lengvarský, Martin Hagara, Lenka Hagarová
Applied Sciences
Structural Health Monitoring Techniques
article

Finite Element Model Updating of Axisymmetric Structures

Jaroslav Briančin, Pavol Lengvarský, Martin Hagara, Lenka Hagarová
article en

Abstract

Creating the most accurate numerical models with the same dynamic behavior as real structures plays an important role in the development process of various facilities. This article deals with the use of experimental methods, particularly experimental modal analysis (EMA), scanning, detection, spectral analysis, and mechanical testing in combination with the optimization techniques of the ANSYS 2024 R1 software to calibrate numerical models of axisymmetric structures. The proposed methodology was tested on a steel pipe whose geometric and material properties were both available. Within the updating of finite element models (FEMU) with one or two design variables, the influence of the range of feasible values on the accuracy of the observed parameters was examined. The updating process led to the acquisition of such a pipe model, which natural frequencies differed by less than 1.5% from the results estimated in EMA, and its weight also differed only minimally. The proposed methodology was then used for the FEMU of a pressure vessel whose contour was obtained by a 3D scanning method; material properties were investigated, and all wall thicknesses, i.e., eleven design variables, were unknown and thus determined by an iterative optimization technique. Using the Multi-Objective Genetic Algorithm (MOGA) method, the dimensions of the vessel were first updated for their shell model and subsequently for the 3D model. The resulting natural frequencies of the model with applied internal pressures of 0 bar, 40 bar, and 80 bar differed from those estimated experimentally by less than 1.2%.

Applied SciencesVol. 15(21)
Technical University of Košice (SK), Institute of Geotechnics of the Slovak Academy of Sciences (SK)
Slovenská Akadémia Vied, Ministerstvo školstva, vedy, výskumu a športu Slovenskej republiky, Vedecká Grantová Agentúra MŠVVaŠ SR a SAV
Openalex Percentile: Top 68%
Structural Health Monitoring Techniques
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