کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6479037 | 1428282 | 2017 | 20 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Multiple representation approach to achieve high-performance spatial queries of 3D BIM data using a relational database Multiple representation approach to achieve high-performance spatial queries of 3D BIM data using a relational database](/preview/png/6479037.png)
- We propose a multiple representation scheme for geometries in a database.
- We describe integrated queries to a database for both geometry and other data.
- High-performance spatial queries utilizing octree indexes in a standard SQL
- Demonstrates the effectiveness integrating spatial operations on realistic BIM data.
- Superior spatial query performance using our approach compared to Oracle Spatial
We propose an approach using multiple representations to achieve high-performance spatial queries on 3D BIM data. The geometry data is first stored as a simple polyhedron representation inside a relational database supporting the storage of 3D geometry polyhedra. Additional representations are derived from the main geometry for ready use in many applications such as rule checking. The additional representations include a shape approximation using bounding boxes as the roughest approximation, octree decomposition using non-uniform octree cell size that also serves as a spatial index for the geometry, and its boundary representations by the topological faces that are indexed. The octree decomposition is used for efficient spatial indexing. The octree cells are decoded into a one-dimensional string so that it can be indexed using the ordinary binary tree index supported in the relational database, allowing for high-performance spatial queries. Commonly used spatial queries such as intersection and spatial relation between many objects can be efficiently performed using ordinary SQL queries. Using the proposed method, high performance integrated queries of the complete BIM data that includes its geometry can be achieved. The performance of this approach is validated by comparing identical queries against the same data using the native database supported R-tree indexing and the octree-based indexing. It shows a significant performance improvement that is 8 to 234 times faster and the performance is noticeably more consistent.
Journal: Automation in Construction - Volume 81, September 2017, Pages 369-388