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Title: Model Validation for Automated Building Code Compliance Checking
To allow full automation of building code compliance checking with different building design models and codes/regulations, input building design models need to be automatically validated. Automated architecture, engineering, and construction (AEC) object identification with high accuracy is essential for such validation. For example, in order to check egress requirements, exits of a building (and their presence or absence) need to be identified automatically through object identification. To address that, the authors propose a new AEC object identification algorithm that can identify needed code checking concepts from building design models based on the invariant signatures of AEC objects, which consisted of Cartesian points-based geometry, relative location and orientation, and material mechanical properties. Building design models in industry foundation classes (IFC) format are processed into invariant signatures, which can fully represent the model data and convert them into computable representations to support automated compliance reasoning. A systematic implementation of the above invariant signatures-based object identification algorithm can be used to automatically conduct building design model validation for code compliance checking preparation. An experimental testing on Chapters 4 and 8 of the International Building Code 2015 and a convenience store design model showed the model validation using the proposed identification algorithms successfully validated ceiling and interior door concepts. Comparing to the manual validation used in current practice, this new object identification algorithm is more efficient in supporting model validation for automated building code compliance checking.  more » « less
Award ID(s):
1827733
PAR ID:
10324481
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
Construction Research Congress 2022
Page Range / eLocation ID:
640 to 650
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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