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 and effective technologies have been developed 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.
Highlights
The present manuscript proposes a novel finite element analysis (FEA) methodology which is based on the accurate parametric surface model by fitting the actual three-dimensional (3D) feature data. 3D feature data can be detected by many efficient measurement methods, e.g., terrestrial laser scanning (TLS), digital photogrammetry, and radar technology
The accurate parametric model is necessary in the composite structural computation and it is beneficial to improve the reliability and accuracy of the behavior prediction in the FEA progress
This manuscript offers a generic methodology which focuses on the FEA based on the parametric model by approximating 3D actual feature data. 3D actual feature data can be acquired from many efficient measurement methods, e.g., TLS, digital photogrammetry, and radar technology
Summary
The present manuscript proposes a novel finite element analysis (FEA) methodology which is based on the accurate parametric surface model by fitting the actual three-dimensional (3D) feature data. 3D feature data can be detected by many efficient measurement methods, e.g., terrestrial laser scanning (TLS), digital photogrammetry, and radar technology. 3D feature data can be detected by many efficient measurement methods, e.g., terrestrial laser scanning (TLS), digital photogrammetry, and radar technology. This parametric model is realized by approximating the point clouds data from TLS which is an accurate and real-time measurement method. The final goal is to improve the accuracy of finite element (FE) computation results due to geometric model errors, especially in the analysis of structures which have undergone unknowable deformation features. Accurate and fast measurement technologies play important roles in the object acquisition and geometric description. This is a reasonable and feasible solution to improve the accuracy of the geometry in this FEA process
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