Methodology for Voxel-Based Earthwork Modeling
Publication: Journal of Construction Engineering and Management
Volume 147, Issue 10
Abstract
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.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are proprietary or confidential in nature and may only be provided with restriction. The available items are data models used in the case studies with the restriction of the algorithm generated.
Acknowledgments
This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (NRF-2019R1A2C2006577) and a Korea Agency for Infrastructure Technology Advancement (KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (National Research for Smart Construction Technology: Grant 20SMIP-A158708-01).
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Received: Nov 5, 2020
Accepted: Apr 27, 2021
Published online: Jul 19, 2021
Published in print: Oct 1, 2021
Discussion open until: Dec 19, 2021
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