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Dynamic Bayesian Network for Probabilistic Modeling of Tunnel Excavation Processes
Author(s) -
Špačková Olga,
Straub Daniel
Publication year - 2013
Publication title -
computer‐aided civil and infrastructure engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.773
H-Index - 82
eISSN - 1467-8667
pISSN - 1093-9687
DOI - 10.1111/j.1467-8667.2012.00759.x
Subject(s) - dynamic bayesian network , probabilistic logic , bayesian network , computer science , process (computing) , excavation , damages , bayesian inference , tunnel construction , bayesian probability , data mining , engineering , artificial intelligence , structural engineering , geotechnical engineering , law , political science , operating system
A dynamic Bayesian network (DBN) model for probabilistic assessment of tunnel construction performance is introduced. It facilitates the quantification of uncertainties in the construction process and of the risk from extraordinary events that cause severe delays and damages. Stochastic dependencies resulting from the influence of human factors and other external factors are addressed in the model. An efficient algorithm for evaluating the DBN model is presented, which is a modification of the so‐called Frontier algorithm. The proposed model and algorithm are applied to an illustrative case study, the excavation of a road tunnel by means of the New Austrian Tunneling Method.