QUANTITATIVE RISK ANALYSIS METHODOLOGY FOR THE TRANSPORTATION OF NUCLEAR WASTE
3rd Canadian Nuclear Waste Management Decommissioning and Environmental Restoration - 2016 Sept. 11-14


Presented at:
3rd Canadian Nuclear Waste Management Decommissioning and Environmental Restoration
2016 Sept. 11-14
Location:
Ottawa, Canada
Session Title:
Session M3: Waste Transportation

Authors:
A. McGoey-Smith (Advisian, WorleyParsons Canada)
E. Haack (Advisian, WorleyParsons Canada)
  

Abstract

Transportation of nuclear waste poses risks to human health and safety, and the environment. In quantitative applications risk is defined as a measure of the likelihood and consequences of an adverse event: it is a triple of event, probability and consequences, given the presence of a hazard. Cause-consequence analysis is used to define a set of risk scenarios involving the hazards associated with an accidental spill of nuclear waste from a truck during transportation along public roads. This involves the chain of events linking the primary hazard event, which is a truck collision, to the various risk endpoints which involve hazards to people and the environment and is represented in cause-consequence analysis by an event tree. By combining data on truck collision frequencies and conditional probabilities associated with release and dispersion, the frequencies associated with the risk endpoints are estimated. For the consequence estimation, fate and transport modelling is utilized based on chemical thermodynamics, specifically fugacity modelling. This enables the quantification of the effects of spills of nuclear waste into multiple media such as soils, streams, lakes and groundwater to be analyzed as well as uptake by flora and fauna in a food web. A novel methodology is utilized in this work which integrates discrete tree structures, reliability analysis, Monte Carlo simulation, fate and transport modelling, and food webs. In this representation the explicit quantification of uncertainties is also undertaken. The GoldSim environmental risk and decision tool is used for the computation which combines the aforementioned elements in an integrated way and addition also provides strong graphical capabilities for use communication of system complexity and risk to scientists, engineers, planners and other stakeholders.

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