Finite Element Analysis based on A Parametric Model by Approximating Point Clouds
- verfasst von
- Wei Xu, Ingo Neumann
- 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.
- Organisationseinheit(en)
-
Geodätisches Institut
- Typ
- Artikel
- Journal
- Remote sensing
- Band
- 12
- Anzahl der Seiten
- 26
- ISSN
- 2072-4292
- Publikationsdatum
- 05.02.2020
- Publikationsstatus
- Veröffentlicht
- Peer-reviewed
- Ja
- ASJC Scopus Sachgebiete
- Erdkunde und Planetologie (insg.)
- Elektronische Version(en)
-
https://doi.org/10.3390/rs12030518 (Zugang:
Offen)
https://doi.org/10.15488/9896 (Zugang: Offen)
