On-demand generation of as-built infrastructure information models for mechanised Tunnelling from TBM data: A computational design approach

• Published in: Automation in construction 2021-01, Vol.121, p.103434, Article 103434
• Main Authors: Getuli, Vito, Capone, Pietro, Bruttini, Alessandro, Pour Rahimian, Farzad
• Format: Article
• Language: English
• Subjects: Algorithms; As-built; Automation; BIM; Boring machines; Building management systems; Computational design; Construction; Datasets; Infrastructure; Massive data points; On-demand modelling; TBM Tunnelling
• ISSN: 0926-5805; 1872-7891
• DOI: 10.1016/j.autcon.2020.103434

When dealing with complex curved geometries and massive datasets linked to linear infrastructures, manual generation and maintenance of related multidisciplinary BIM models and documentation are yet to be fully automated. This research focused on the integration of BIM and computational design into an intuitive approach for the generation of as-built models of mechanised tunnelling projects, leveraging the use of the real-time data collected by TBM. A preliminary study of the parameters was conducted to describe the curved geometry of the tunnel, then their mutual alignment was followed by the identification of additional relevant information. To automate the tunnel's BIM-based modelling process, a system of four coupled algorithms was developed and tested with a sample TBM dataset. The results demonstrate how the adoption of computational design methods drastically enhances the modelling process for infrastructure projects, allowing for the on-demand generation of as-built BIM models, reducing time and errors. •Computational design approach for generation of as-built information models of mechanised tunnelling projects•Integration of real-time data from tunnel boring machine and BIM by using coupled algorithms•Computer-aided geometric modelling of mechanised tunnelling•Improving automation in geometric modelling and information content enrichment of tunnelling projects