- ISSN 0258-2724
- CN 51-1277/U
- EI Compendex
- Scopus
- Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
- Chinese S&T Journal Citation Reports
- Chinese Science Citation Database
| Citation: | YOU Jigang, ZHU Jun, DANG Pei, GUO Yukun, ZHANG Jinbin, WU Jianlin. Fast Three-Dimensional Printing for Terrain Models Based on Improved K-Dimensional Tree Spatial Segmentation[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20240183
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In view of the problems of low efficiency and high cost associated with current three-dimensional (3D) printing methods for fabricating physical terrain models, a rapid printing method for terrain models based on improved K-dimensional (KD) tree spatial segmentation was proposed, aiming to enhance printing efficiency and reduce material consumption. First, the correlation between digital terrain model features and 3D printing parameters was analyzed to establish a rule set of spatial segmentation constraints. Subsequently, an improved KD tree model integrating dimension adaptation and size constraints was constructed, overcoming the rigid limitations of positions and dimensions in traditional segmentation and achieving refined segmentation for the terrain model and effective removal of underground sections. Building upon this foundation, a rapid spatial segmentation algorithm incorporating a greedy strategy was designed. This algorithm maximized the hollowed-out volume of the base by pursuing locally optimal segments. Micro terrain areas were integrated by means of regional clustering to optimize the sub-block segmentation results. For each terrain unit after segmentation, a rapid prototyping method based on block-based parallel and inverted printing was proposed. Fine support structures at four corners prevented model distortion while enabling substantial base hollowing and reducing material consumption and printing time. Finally, an experimental environment was established; case experiments and analysis were carried out; five typical disaster terrain data, including earthquakes, wildfires, floods, landslides, and debris flows, were selected for printing validation under conditions of varying resolutions and spatial scales. Research results demonstrate that the proposed method effectively overcomes the rigid limitations of traditional segmentation and the problem of model sagging distortion in fused deposition modeling. Across cases of the five disaster types, the approach achieves an average reduction of 17.69% in 3D printing time and 28.98% in material consumption. This facilitates rapid and low-cost physical terrain model printing with high applicability across diverse terrains.
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