ABSTRACT:

A method for risk-based design is described in this paper. Probabilistic methods of analysis are applied to stress modelling to determine the probability of exceeding a given depth of failure. Suggestions are provided for dealing with geotechnical uncertainty. The understanding of aleatory variability can be improved by collecting more data and improving the quality of data through training and quality control. Stress and model uncertainty remains a challenge in geotechnical engineering. Some degree of subjective engineering judgment will therefore always be required in geotechnical design.

Acceptance criteria then need to be defined in terms of safety and economic risk. Corporate risk matrices can be used for assessing the risk in terms of the probability and consequence. International safety benchmarking and safety milestones should be considered. The cost of rehabilitation of tunnels and the financial losses due to lost production are assessed using the model. A typical risk matrix is used to evaluate the level of risk. Different types of excavations have different risk profiles based on the potential impact on production.

1 INTRODUCTION

By its nature, rock engineering is subject to a great deal of uncertainty and variability (Hadjigeorgiou and Harrison, 2011; Brown, 2012; Contreras and Ruest, 2016), which need to be taken into account in the design process and in the management of rock-related risks.

Variability is a property of nature and is a measure of the change in rock mass characteristics over time and space. The variability can be described with statistics and the probabilities related to variability can be interpreted as a frequency of occurrence. Uncertainty is a state of mind and is a product of our lack of knowledge, which can be reduced with more measurement and improved understanding. Probabilities related to uncertainty are best interpreted as a degree-of-belief. Uncertainties include measurement errors, insufficient data, sampling bias, stress state uncertainty, and model uncertainty. The understanding of variability can be improved by collecting more data and improving the quality of data through training and quality control. Stress and model uncertainty remain a challenge in rock engineering. Some degree of subjective engineering judgement will therefore always be required in geotechnical design.

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