Capturing and integrating knowledge for managing risks in tunnel works

Abstract

Risk-related knowledge gained from past construction projects is regarded as potentially extremely useful in risk management. This article describes a proposed approach to capture and integrate risk-related knowledge to support decision making in construction projects. To ameliorate the problem related to the scarcity of risks information often encountered in construction projects, Bayesian Belief Networks are used and expert judgment is elicited to augment available information. Particularly, the article provides an overview of judgment-based biases that can appear in the elicitation of judgments for constructing Bayesian Networks and the provisos that can be made in this respect to minimize these types of bias. The proposed approach is successfully applied to develop six models for top risks in tunnel works. More than 30 tunneling experts in the Netherlands and Germany were involved in the investigation to provide information on identifying relevant scenarios than can lead to failure events associated with tunneling risks. The article has provided an illustration of the applicability of the developed approach for the case of "face instability in soft soils using slurry shields."