Testing the Effectiveness of Voxels for Structural Analysis

Wedi'i Gadw mewn:
Manylion Llyfryddiaeth
Cyhoeddwyd yn:Algorithms vol. 18, no. 6 (2025), p. 349
Prif Awdur: Gonizzi Barsanti Sara
Awduron Eraill: Nappi, Ernesto
Cyhoeddwyd:
MDPI AG
Pynciau:
Mynediad Ar-lein:Citation/Abstract
Full Text + Graphics
Full Text - PDF
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MARC

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022 |a 1999-4893 
024 7 |a 10.3390/a18060349  |2 doi 
035 |a 3223864753 
045 2 |b d20250101  |b d20251231 
084 |a 231333  |2 nlm 
100 1 |a Gonizzi Barsanti Sara 
245 1 |a Testing the Effectiveness of Voxels for Structural Analysis 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a To assess the condition of cultural heritage assets for conservation, reality-based 3D models can be analyzed using FEA (finite element analysis) software, yielding valuable insights into their structural integrity. Three-dimensional point clouds obtained through photogrammetric and laser scanning techniques can be transformed into volumetric data suitable for FEA by utilizing voxels. When directly using the point cloud data in this process, it is crucial to employ the highest level of accuracy. The fidelity of r point clouds can be compromised by various factors, including uncooperative materials or surfaces, poor lighting conditions, reflections, intricate geometries, and limitations in the precision of the instruments. This data not only skews the inherent structure of the point cloud but also introduces extraneous information. Hence, the geometric accuracy of the resulting model may be diminished, ultimately impacting the reliability of any analyses conducted upon it. The removal of noise from point clouds, a crucial aspect of 3D data processing, known as point cloud denoising, is gaining significant attention due to its ability to reveal the true underlying point cloud structure. This paper focuses on evaluating the geometric precision of the voxelization process, which transforms denoised 3D point clouds into volumetric models suitable for structural analyses. 
653 |a Finite element method 
653 |a Simulation 
653 |a Data processing 
653 |a Deep learning 
653 |a Structural integrity 
653 |a Noise reduction 
653 |a Graph representations 
653 |a Computer aided design--CAD 
653 |a Three dimensional models 
653 |a Approximation 
653 |a Finite element analysis 
653 |a Algorithms 
653 |a Structural analysis 
653 |a Building information modeling 
653 |a Geometric accuracy 
653 |a Cultural resources 
653 |a Photogrammetry 
653 |a Cultural heritage 
700 1 |a Nappi, Ernesto 
773 0 |t Algorithms  |g vol. 18, no. 6 (2025), p. 349 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3223864753/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text + Graphics  |u https://www.proquest.com/docview/3223864753/fulltextwithgraphics/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3223864753/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch