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

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

Authors

P. Patlakas

G. Neighbour



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 Mar 29, 2024
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

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