Automated framework for optimized path-planning for pile foundation drilling machines based on 4D BIM modelling
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Bibliographic Details
Author(s): |
Martina Mellenthin Filardo
(Bauhaus-Universität Weimar)
Rohith Akula (Bauhaus-Universität Weimar) Tino Walther (Bauhaus-Universität Weimar) Hans-Joachim Bargstädt (Bauhaus-Universität Weimar) |
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Medium: | conference paper | ||||
Language(s): | English | ||||
Conference: | IABSE Congress: Structural Engineering for Future Societal Needs, Ghent, Belgium, 22-24 September 2021 | ||||
Published in: | IABSE Congress Ghent 2021 | ||||
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Page(s): | 1949-1956 | ||||
Total no. of pages: | 8 | ||||
DOI: | 10.2749/ghent.2021.1949 | ||||
Abstract: |
While the Building Information Modeling (BIM) method allows accurate information modelling and thus more robust predictions, it often needs to be combined with tasks beyond the model or modelling phase, especially if the goal is a model-based construction phase. This study proposes an optimization workflow for the construction of pile foundations, since they are part of a varying range of building and infrastructure projects. Pile foundation drilling is an extensive construction process, which can be optimized significantly by reducing the execution length through an effective drilling path plan and automated data transfer. This was achieved through the combination of optimization algorithms, which were linked to the 3D BIM model and selected the shortest distance between piles using Ant Colony Optimization (ACO) algorithm, based on the Travelling Salesperson Problem (TSP). Subsequently the script created separate security distance-compliant tours for drilling machines, calculated construction times and converted the resulting paths into schedules, which in turn could be updated to the 3D BIM model to generate a 4D animation of the construction process. The developed optimization framework and script were tested with a construction company focused on special foundations based in Germany. |
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Keywords: |
optimization BIM Building Information Modeling deep foundations Pile Construction Travelling Salesperson Problem TSP Ant Colony Optimization ACO 2-Opt Moves
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Copyright: | © 2021 International Association for Bridge and Structural Engineering (IABSE) | ||||
License: | This creative work is copyrighted material and may not be used without explicit approval by the author and/or copyright owner. |