부산대학교 도서관

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jlp.2009.08.009 Byline: Jeffrey D. Marx, John B. Cornwell Abstract: As more and more quantitative risk analyses (QRAs) are performed for petrochemical facilities around the world, the variety of techniques used in these analyses continually expands. Although the emphasis is often placed on risk's two constituents, consequence and probability, many of the contributing elements get marginalized, or even lost in the analysis. One such element is the weather data. Changes in wind speed and atmospheric stability affect the size and extent of impact zones, while the different wind directions modify how the impacts are mapped in the area surrounding each release point. Weather data is often defined by three variables (wind speed, atmospheric stability, and wind direction), and is site-specific in nature, with definable probabilities for each triplet combination. Many QRA studies shortcut the quantitative nature of an analysis by condensing the weather data into a small number of combinations, with unpredictable results. By utilizing robust risk mapping techniques, it can be demonstrated that risk contours may be critically dependent on the number of wind speed/stability/direction combinations employed in the analysis. This paper will also demonstrate how a risk assessment can arrive at different conclusions based on the level of weather data detail applied in the analysis. Author Affiliation: Quest Consultants Inc., 908 26th Avenue NW, Norman, OK 73069, USA Article History: Received 11 February 2009; Revised 21 August 2009; Accepted 24 August 2009