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

Vito Getuli, Pietro Capone, Alessandro Bruttini, Farzad Rahimian

Research output: Contribution to journalArticlepeer-review

Abstract

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.
Original languageEnglish
Article numberAUTCON-D-20-00467
Pages (from-to)103434
JournalAutomation in Construction
Volume121
Issue numberJanuary 2021
DOIs
Publication statusPublished - 21 Oct 2020

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