Automatic Detection of Geometric Errors in Space Boundaries of IFC-BIM Models Using Monte Carlo Ray Tracing Approach

Ying, Huaquan; Lee, Sanghoon

doi:10.1061/(asce)cp.1943-5487.0000878

Cited by 11 publications

(5 citation statements)

References 24 publications

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“…Thus, it must be verified that the assumptions done, and tolerances selected can also be universally applicable to any IFC generation tool. Implementation of more advanced error postprocessing capabilities (as done by Ying and Lee [61,62]) seems a natural evolution. For example, provide auto-adjust capabilities (i.e., to perform different runs in loop by varying the tolerance values until the best configuration is found, i.e., the one with no errors).…”

Section: Conclusion and Next Stepsmentioning

confidence: 99%

Graph-Based Methodology for Multi-Scale Generation of Energy Analysis Models from Ifc

Mediavilla¹,

Elguezabal

Lasarte³

2022

Preprint

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Section: Conclusion and Next Stepsmentioning

confidence: 99%

Graph-Based Methodology for Multi-Scale Generation of Energy Analysis Models from Ifc

Mediavilla¹,

Elguezabal

Lasarte³

2022

Preprint

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“…An AABB tree is a special binary space partitioning tree that indexes geometric primitives (e.g., points, triangles, and polyhedrons) based on their AABBs. It can be fast and easy to build and has proved to be highly efficient in supporting various spatial queries on a large set of geometric primitives (Bergen, 1997; Borrmann et al., 2009; Ying & Lee, 2020). It is generally constructed top‐down in a recursive manner.…”

Section: Proposed Algorithmmentioning

confidence: 99%

“…It is generally constructed top‐down in a recursive manner. A detailed description of the AABB tree creation process can be found in Ying and Lee (2020). Note that to reduce the memory load, all the geometric objects are stored in the leaf nodes only once the tree is completely created.…”

Section: Proposed Algorithmmentioning

confidence: 99%

“…In the architecture, engineering, and construction industry, ray tracing has also been widely used in a simple form for visibility analysis: Given a viewpoint in a 3D space, the objects visible from it can be found by tracing a series of rays from the viewpoint to detect the objects they intersect first. Ying and Lee (2020) developed a ray tracing algorithm to identify all the visible areas of a specific space boundary. In a building indoor reconstruction process, Previtali et al (2018) implemented a raytracing algorithm to distinguish whether holes in a wall plane are real openings (i.e., windows or doors) or just caused by occlusions or clutter during the laser scanning process.…”

Section: Ray Tracing For Visibility Analysismentioning

confidence: 99%

“…However, due to the large size of the scene, specific acceleration techniques like spatial indexing may still be used to speed up the ray tracing process. For example, Ying and Lee (2020) and Fernández et al. (2008) leveraged the AABB tree and kd tree, respectively, to index geometric objects in the target scene.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A two‐stage recursive ray tracing algorithm to automatically identify external building objects in building information models

Ying

Zhou

Degani

et al. 2021

Computer aided Civil Eng

Self Cite

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The internal or external attribute of building information modeling (BIM) objects is vital information for many BIM‐based engineering analyses such as building energy analysis and cost estimation. Unfortunately, such information is often inaccurate, incomplete, or missing entirely in most BIM models. Manually checking, correcting, or inputting this data for large‐scale BIM models can be time‐consuming, laborious, and error‐prone. This study proposes a two‐stage ray tracing algorithm to automatically identify external BIM objects, based on the idea that external objects of a building can be viewed from somewhere outside the building. The first‐stage ray tracing samples viewpoints from the six faces of an offset axis‐aligned bounding box (AABB) of the building and emits a ray for each viewpoint to detect relevant external objects. The second‐stage ray tracing recursively searches for any remaining external objects from the view of the external objects that have been detected in the previous round of ray tracing. Both stages are carefully designed for efficiency. Furthermore, a two‐tier AABB tree is introduced to spatially index building objects on both model and object levels to accelerate relevant geometry operations. The proposed algorithm is validated with one synthetic and two large‐scale real‐world building models. The results show that all the external objects in the three models are accurately and efficiently identified, and the two‐tier spatial indexing and other acceleration techniques improve the algorithm's efficiency significantly.

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Generating second-level space boundaries from large-scale IFC-compliant building information models using multiple geometry representations

Ying

Lee

2021

Automation in Construction

View full text Add to dashboard Cite

Automatic Detection of Geometric Errors in Space Boundaries of IFC-BIM Models Using Monte Carlo Ray Tracing Approach

Cited by 11 publications

References 24 publications

Graph-Based Methodology for Multi-Scale Generation of Energy Analysis Models from Ifc

Graph-Based Methodology for Multi-Scale Generation of Energy Analysis Models from Ifc

A two‐stage recursive ray tracing algorithm to automatically identify external building objects in building information models

Generating second-level space boundaries from large-scale IFC-compliant building information models using multiple geometry representations

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