A hybrid finite element and surrogate modelling approach for simulation and monitoring supported TBM steering

Ninic, Jelena and Freitag, Steffen and Meschke, Günther (2017) A hybrid finite element and surrogate modelling approach for simulation and monitoring supported TBM steering. Tunnelling and Underground Space Technology, 63 . pp. 12-28. ISSN 0886-7798

[img] PDF - Repository staff only until 24 December 2017. - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Available under Licence Creative Commons Attribution Non-commercial No Derivatives.
Download (4MB)

Abstract

The paper proposes a novel computational method for real-time simulation and monitoring-based predictions during the construction of machine-driven tunnels to support decisions concerning the steering of tunnel boring machines (TBMs). The proposed technique combines the capacity of a process-oriented 3D simulation model for mechanized tunnelling to accurately describe the complex geological and mechanical interactions of the tunnelling process with the computational efficiency of surrogate (or meta) models based on artificial neural networks. The process-oriented 3D simulation model with updated model parameters based on acquired monitoring data during the advancement process is used in combination with surrogate models to determine optimal tunnel machine-related parameters such that tunnelling-induced settlements are kept below a tolerated level within the forthcoming process steps. The performance of the proposed strategy is applied to the Wehrhahn-line metro project in Düsseldorf, Germany and compared with a recently developed approach for real-time steering of TBMs, in which only surrogate models are used.

Item Type: Article
Keywords: Mechanized tunnelling; Finite element method; Parameter identification; Surrogate model; Recurrent neural network; Computational steering; Tunnel boring machine; Monitoring; Settlements; Real-time prediction
Schools/Departments: University of Nottingham, UK > Faculty of Engineering
Identification Number: https://doi.org/10.1016/j.tust.2016.12.004
Depositing User: Eprints, Support
Date Deposited: 05 Jan 2017 13:56
Last Modified: 06 Jan 2017 05:25
URI: http://eprints.nottingham.ac.uk/id/eprint/39633

Actions (Archive Staff Only)

Edit View Edit View