Assessment of long-term deformation of a tunnel in soft rock by utilizing particle swarm optimized neural network

Assessment of long-term deformation of a tunnel in soft rock by utilizing particle swarm optimized neural network

Kovačević, Meho Saša (University of Zagreb)
Bačić, Mario (University of Zagreb)
Gavin, Kenneth (TU Delft Geo-engineering)
Stipanovič, Irina (University of Twente)

2021

The continuous monitoring of long-term performance of tunnels constructed in soft rock masses shows that the rock mass deformations continue after construction, albeit at a rate that reduces with time. This is in contrast with NATM postulates which assume deformation stabilizes shortly after tunnel construction. This paper proposes the prediction of long-term vertical settlement performance of a tunnel in soft rock mass, through the inclusion of a Burger’s creep viscous-plastic constitutive law to model post-construction deformations. To overcome issues related to the complex characterization of this constitutive model, a neural network NetRHEO is developed and trained on a numerically obtained dataset. A particle swarm algorithm is then employed to estimate the most probable rheological parameter set, by utilizing the long-term in-situ monitoring data from several observation points on a real tunnel. The paper demonstrates the potential of the proposed methodology, using displacement measurements of two adjacent tunnels in karstic rock mass in Croatia. The complex interaction of a railway tunnel Brajdica and a road tunnel Pećine, conditioned by the character of the surrounding rock mass as well by the chronology of their construction, was evaluated to predict the future behavior of these tunnels.

Soft rock tunneling
Long-term deformation
Rheological parameters
Neural network
Particle swarm optimization
Tunnel monitoring

http://resolver.tudelft.nl/uuid:8809db36-e5bd-4b4a-b733-fc5958c17e56

https://doi.org/10.1016/j.tust.2021.103838

2021-07-22

0886-7798

Tunnelling and Underground Space Technology, 110

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

journal article

© 2021 Meho Saša Kovačević, Mario Bačić, Kenneth Gavin, Irina Stipanovič