Two steps are continuously performed along the whole QRA process: “communication and consultation” ( Fig. 1.1, 7) and “monitoring, review and update” ( Fig. 1.1, 8). Risk is finally evaluated against the acceptance criteria previously defined ( Fig. 1.1, 6: risk evaluation), and, if needed, risk mitigation measures are taken. Johansen and Rausand provide a short review of such risk metrics. The choice of risk metrics is critical because it directs what kind of information to obtain from the risk analysis. The risk picture is established by considering all the risk contributions of the scenarios analyzed for a specific area of the plant, which, in turn, are obtained through the composition of the related frequencies and damages ( Fig. 1.1, 5: establishing the risk picture). A review of available damage models applied to calculate the spatial distribution of damage (eg, probability of human death) has been carried out by Cozzani and Salzano. A description of many available approaches has been presented by Arunraj and Maiti. The assessment of consequences can be performed using a number of physical-mathematical and empirical models. Quantification of consequences has usually been carried out in terms of losses in production, human health, assets, and environment.
Consequence estimation is used to determine the potential for damage or injury from specific unwanted events. Guidelines in the QRA “Purple Book” report generic loss of containment events and failure frequencies for a number of standard installations such as storage tanks, transport units, pipelines, and loading equipment. One way to retrieve generic failure frequencies and probabilities is to use databases and apply the information in QRA calculations specific plant data should be applied, if available. Crowl and Louvar state that risk analysis basically involves the estimation of accident frequencies and consequences using engineering and mathematical techniques. Įstimation of potential accident frequencies and evaluation of event consequences are central steps for the whole QRA process ( Fig. 1.1, 3: analysis of initiating events, and 4: analysis of consequences). The maximum credible accident scenario analysis method developed by Khan and Abbasi can be used as a criterion to identify credible scenarios among a large number of possibilities.įigure 1.1. Their applicability depends on the project life cycle as well as the amount of information required. As reported by the Center for Chemical Process Safety, several approaches to HAZID may be employed: checklist analysis, what-if analysis, preliminary hazard analysis, fault tree analysis, hazard and operability study, bow-tie analysis, etc. The following step in the development of a QRA is the identification of hazards, which may have several important aims: it may highlight possible malfunctions of the systems, outline top events that are undesired situations, and describe potential scenarios associated with the top events and their consequences.
HRA RISK ENGINE FULL
For this reason, this chapter addresses the integration of QRA by means of human reliability analysis (HRA), which not only assesses the probability of the identified human failure events (HFEs, or failures of functions, systems, or components that are the result of human errors) but also evaluates the influence of underlying factors on human performance.Ī preliminary step ( Fig. 1.1, 1: establishing the context) defines objectives, responsibilities, and methods as well as risk acceptance criteria and deliveries throughout the process and execution plan, to derive full value from the results obtained.
Human and organizational factors often have an important role in the development of a scenario, and their assessment is essential for accurate QRA and effective risk mitigation.
HRA RISK ENGINE SERIES
However, such scenarios may be the result of interaction among a series of elements, which range from the technical to the human and organizational domains. Quantitative risk assessment (QRA) is a consolidated approach to evaluating the risk level of an industrial system, which is traditionally based on the main technical failures leading to potential accident scenarios. Matteini, in Dynamic Risk Analysis in the Chemical and Petroleum Industry, 2016 1 Introduction