(101c) Benefits of Risk-Based Design through Probabilistic Consequence Modeling

Davis, S. G., GexCon US
Hansen, O., GexCon US
Rogstadkjernet, L., GexCon AS
Brattetrig, A., GexCon US
Berthelsen, I., GexCon AS

As risk is a combination of the probability of an event and its consequences, quantitative risk analyses (QRA) are used in many areas to establish the threshold for intolerable risk. For example, accidental loads (explosion and fire) with an annual probability greater than or equal to 1x10-4 cannot cause the loss of a main safety function or system. In risk management, technical, operational and organizational solutions are chosen primarily to reduce the probability that failures, hazardous situations and accidents will occur, but also to reduce consequences. At the top of the technical safety design, one first identifies all possible hazards. Next, the risk associated with the various hazards are quantified and compared with tolerance criteria through the overall risk process. This, together with other specialized studies, provides the basis for the safety strategy of the organization, where the need of effective risk reducing measures or barriers is evaluated. One main parameter in this process is how to determine the tolerance criteria for major accident and environmental risk. Risk is typically set for: (1) the personnel at the facility, (2) loss of main safety functions, (3) pollution from the facility and (4) damage done to a third party. Major accidents in the past have identified how critical it is to maintain the principal safety functions in order to provide adequate protection during the critical phase of the accident and to avoid escalation.

Probabilistic consequence modeling (fire or explosion) is a powerful tool that can not only evaluate the threshold for intolerable risk, but can also help provide invaluable information required for evaluation of further risk reduction to a level As Low As Reasonably Practicable ? the ALARP principle. For explosions, probabilistic consequence modeling involving CFD provides hundreds of possible leak, atmospheric, ignition and explosion scenarios that determine the resulting explosion loading and drag forces based on the given design. This method can be used to help identify events or series of events that contribute to residual risk, and to evaluate methods for its reduction (reduce probability of unwanted events, reduce inventory, prevent escalation ? safety barriers, deluge, etc.) In addition, this method is used to avoid worst-case scenario design, which in most cases is an unfeasible and costly approach. Simple prescriptive methodologies or risk assessments, may not provide enough detail to evaluate the actual risk at a given facility and may lead to: (1) severe over design and associated costs that has minimal effect on the risk, (2) an improper design that fails to address the actual risk, and in fact may neglect critical events that lead to escalation of the accident, and (3) an inability to asses the effects of mitigation measures. This paper will present cases studying the benefits of risk-based design through probabilistic consequence modeling involving CFD.


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