Analysis of tunnel construction risk

A probabilistic model for estimation of tunnel construction time is developed within this project, using Dynamic Bayesian Networks (DBN). It accounts for the common variability of the construction process and the occurrence of extraordinary events such as cave-in collapses. Different sources of uncertainty are modelled, including the geotechnical conditions and the influence of human factors. Data from tunnels constructed in the past are statistically analysed to serve as an input for the probabilistic modelling. Efficient algorithms for the evaluation of the proposed DBN are developed.

Additionally, models for the prediction of uncertain geotechnical conditions are developed that are used for probabilistic modelling of ground settlements and damages to the buildings due to tunnelling. These models combine a prior knowledge about the geology with measurements of ground behaviour gathered during the construction process.

Dynamic Bayesian Network model for estimation of tunnel construction time – each slice of the DBN represents a 5 m segment of the tunnel. The geotechnical conditions are represented by variables Zone and Ground class; construction process by variables Human factor, geometry, construction Method and unit Time; extraordinary events by Failure mode and Number of failures.

Researchers

Olga Špačková
Daniel Straub
Carles Camós

Funding

Project No. TA01030245 of the Technology Agency of the Czech Republic.
Project No. 103/09/2016 of the Czech Science Foundation.
Project No. 1M0579 (CIDEAS research center) of the Ministry of Education, Youth and Sports of the Czech Republic.
DAAD research grant for doctoral candidates and young scientists.
Bayhost Mobilitätsbeihilfe

Collaborations

Czech Technical University (CTU) in Prague, Fac. Of Civil Engineering.
Arcadis Geotechnika a.s., Prague.
Universitat Politècnica de Catalunya, Barcelona

Publications

Špačková, O., Straub, D., 2013. Dynamic Bayesian network for probabilistic modelling of tunnel excavation process. J. of Computer-Aided Civil and Infrastructure Engineering 28 (1), pp.1-21. Link: http://mediatum.ub.tum.de/doc/1129323/1129323.pdf
Špačková, O., Šejnoha, J., Straub, D., 2013. Probabilistic assessment of tunnel construction performance based on data. Tunnelling and Underground Space Technology 37, pp. 62-78. Link: http://mediatum.ub.tum.de/doc/1145631/1145631.pdf
Camós, C., Molins, C., Špačková, O., Straub, D., 2013. Development of a probabilistic model for the prediction of building damage due to tunneling induced settlements, in: Proc. of 4th Int. Symp. on Geotechnical Safety and Risk (ISGSR2013). Hong Kong.
Špačková, O., Šejnoha, J., Straub, D., 2013. Tunnel construction time and cost estimates: from deterministic to probabilistic approaches. Podzemni stavby Praha 2013, Prague, Czech Republic. Link: https://www.bgu.tum.de/fileadmin/w00cbe/era/Papers/Spackova_et_al-FINAL.pdf
Špačková, O. 2012. Risk management of tunnel construction projects: Modelling uncertainty of construction time (cost) estimates for risk assessment and decision-making. Doctoral thesis, CTU Prague. Link: http://mech.fsv.cvut.cz/wiki/index.php/File:PhD_dissertation_Spackova_2012.pdf
Špačková, O., Šejnoha, J., Straub, D., 2012. Probabilistic assessment of tunnel construction processes using statistical learning to include past experience. Proceedings of EUROCK 2012, Stockholm.
Špačková, O., Straub, D., 2011. Probabilistic risk assessment of excavation performance in tunnel projects using Bayesian networks: a case study. Proceedings of the 3rd International Symposium on Geotechnical Safety and Risk. Bundesanstalt für Wasserbau, München, pp. 651–660. Link: http://vzb.baw.de/e-medien/geotechnical-safety-and-risk-2011/PDF/6%20Practical%20Applications%20and%20Case%20Studies/6_04.pdf