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Methodology for Voxel-Based Earthwork Modeling

delete2021-10-01
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PRE
AI
M
Muhammad Shoaib Khan
J
Jeonghwan Kim
S
Soohyun Park
S
Soo‐Min Lee
J
Jongwon Seo *
DOI:10.1061/(ASCE)CO.1943-7862.0002137delete
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摘要

摘要

En 中文
Building information modeling (BIM) can facilitate effective three-dimensional (3D) earthwork modeling by furnishing insightful information. An earthwork area is generally represented in a cell-based environment for planning purposes such as allocation plans or equipment plans. However, previous studies utilized conventional methods, which are tedious and time-consuming, to create cell-based representations. Therefore, a method that can be applied to automatically represent earthwork BIM models in a cell-based environment should be developed. To address that research gap, this paper proposes a novel method to develop voxel-based representations of earthwork models. The voxel-based method is parametric, and the size, number, and properties of the voxels can be easily varied. This method, validated for accuracy, rapidly creates a parametric voxel model linked with geotechnical information necessary for earthwork operations. A visual programming tool, Grasshopper, is used to develop an algorithm that can automatically divide the earthwork model into voxels. Finally, experiments are conducted to validate the proposed method using an actual earthwork BIM design. The paper contributes to the existing body of knowledge by proposing a voxel-based earthwork representation and algorithm that automatically create a cell-based 3D environment that is flexible enough to integrate geotechnical parameters. The results indicate that the proposed method will help project engineers, planners, and managers create an optimal-size voxel-based earthwork model with customized geotechnical information.
Keyword:
Building information modeling
Cell-based representation
Voxelization
Visual programming
Earthwork modeling

期刊

J
Journal of Construction Engineering and Management
IF:
5.1
论文数:
5.1K
被引数:
1.4W

机构

H
hanyang university
学者数:
2.9W
论文数: 2.7W
被引数: 36
K
Korea National University of Transportation
学者数:
1.2K
论文数: 1.3K
被引数: 1.5K
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