TY - JOUR
T1 - On-demand generation of as-built infrastructure information models for mechanised tunnelling from TBM data: a computational design approach
AU - Getuli, Vito
AU - Capone, Pietro
AU - Bruttini, Alessandro
AU - Rahimian, Farzad
PY - 2020/10/21
Y1 - 2020/10/21
N2 - 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.
AB - 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.
U2 - 10.1016/j.autcon.2020.103434
DO - 10.1016/j.autcon.2020.103434
M3 - Article
SN - 0926-5805
VL - 121
SP - 103434
JO - Automation in Construction
JF - Automation in Construction
IS - January 2021
M1 - AUTCON-D-20-00467
ER -