Finite element analysis based on a parametric model by approximating point clouds

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Xu, W.; Neumann, I.: Finite element analysis based on a parametric model by approximating point clouds. In: Remote Sensing 12 (2020), Nr. 3, 518. DOI: https://doi.org/10.3390/rs12030518

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Sum total of downloads: 157




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Abstract: 
Simplified models are widely applied in finite element computations regarding mechanical and structural problems. However, the simplified model sometimes causes many deviations in the finite element analysis (FEA) of structures, especially in the non-designed structures which have undergone unknowable deformation features. Hence, a novel FEA methodology based on the parametric model by approximating three-dimensional (3D) feature data is proposed to solve this problem in the present manuscript. Many significant anci effective technologies have been developeci to detect 3D feature information accurately, e.g., terrestrial laser scanning (TLS), digital photogrammetry, and radar technology. In this manuscript, the parametric FEA model combines 3D point clouds from TLS and the parametric surface approximation method to generate 3D surfaces and models accurately. TLS is a popular measurement method for reliable 3D point clouds acquisition and monitoring deformations of structures with high accuracy and precision. The B-spline method is applied to approximate the measured point clouds data automatically and generate a parametric description of the structure accurately. The final target is to reduce the effects of the model description and deviations of the FEA. Both static and dynamic computations regarding a composite structure are carried out by comparing the parametric and general simplified models. The comparison of the deformation and equivalent stress of future behaviors are reflected by different models. Results indicate that the parametric model based on the TLS data is superior in the finite element computation. Therefore, it is of great significance to apply the parametric model in the FEA to compute and predict the future behavior of the structures with unknowable deformations in engineering accurately.
License of this version: CC BY 4.0 Unported
Document Type: Article
Issue Date: 2020
Appears in Collections:Fakultät für Bauingenieurwesen und Geodäsie

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pos. country downloads
total perc.
1 image of flag of Germany Germany 96 61.15%
2 image of flag of United States United States 21 13.38%
3 image of flag of China China 14 8.92%
4 image of flag of Russian Federation Russian Federation 3 1.91%
5 image of flag of Tanzania, United Republic of Tanzania, United Republic of 2 1.27%
6 image of flag of India India 2 1.27%
7 image of flag of Hungary Hungary 2 1.27%
8 image of flag of Algeria Algeria 2 1.27%
9 image of flag of Czech Republic Czech Republic 2 1.27%
10 image of flag of Denmark Denmark 1 0.64%
    other countries 12 7.64%

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