Automatic code compliance with multi-dimensional data fitting in a BIM context

Patlakas, P.; Livingstone, A.; Hairstans, R.; Neighbour, G.

Abstract

BIM-based tools can contribute to addressing some of the challenges faced by structural engineering practitioners. A BIM-based framework for the development of components that deliver Automatic Code Compliance (ACC) is presented. The structural design problems that such components solve are categorised as simple, where ACC can be implemented directly, or complex, where more advanced approaches are needed. The mathematical process of Multi-Dimensional Data Fitting (MDDF) is introduced in order for the latter, enabling the compression of complex engineering calculations to a single equation that can be easily implemented into a BIM software engineering package. Proof-of-concept examples are given for both cases: offsite manufactured structural joists are utilised as a non-recursive example, implementing the results obtained in the manufacturer's literature; the axial capacity of metal fasteners in axially loaded timber-to-timber connections are utilised as an example of recursive problems. The MDDF analysis and the implementation in a BIM package of those problems are presented. Finally, the concept is generalised for non-structural aspects at a framework level, and the challenges, implications, and prospects of ACC in a BIM context are discussed.

Citation

Patlakas, P., Livingstone, A., Hairstans, R., & Neighbour, G. (2018). Automatic code compliance with multi-dimensional data fitting in a BIM context. Advanced engineering informatics, 38, 216-231. https://doi.org/10.1016/j.aei.2018.07.002

• Journal Article Type: Article
• Acceptance Date: Jul 6, 2018
• Online Publication Date: Jul 13, 2018
• Publication Date: 2018-10
• Deposit Date: Aug 31, 2018
• Publicly Available Date: Jul 14, 2019
• Journal: Advanced Engineering Informatics
• Print ISSN: 1474-0346
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 38
• Pages: 216-231
• DOI: https://doi.org/10.1016/j.aei.2018.07.002
• Keywords: Artificial Intelligence; Information Systems
• Public URL: http://researchrepository.napier.ac.uk/Output/1245744
• Contract Date: Jul 10, 2018