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Book ChapterDOI

Quantitative Risk Assessment Methods of Accounting for Probabilistic and Deterministic Data Applied to Complex Systems

TL;DR: This chapter provides a tutorial on accident risk assessment which has been applied to a wide range of legacy weapons and weapon delivery systems and discusses scenario development merging of deterministic and probabilistic calculations uncertainty and facility risk management techniques.
Abstract: Another aspect of understanding the risks of Cold War legacies is through the application of probabilistic safety assessments and probabilistic risk assessments largely aimed at calculating and mitigating the risk and severity of accidents. This chapter provides a tutorial on accident risk assessment which has been applied to a wide range of legacy weapons and weapon delivery systems. It discusses scenario development merging of deterministic and probabilistic calculations uncertainty and facility risk management techniques.
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TL;DR: In this article, the authors applied sensitivity analysis (SA) methods in atmospheric dispersion modeling to the emission dispersion model (EDM) to study the prediction of atmospheric dispersions of NO2 generated by an industrial fire, whose results are useful for fire safety applications.
Abstract: PurposeThe objectives of this paper are the application of sensitivity analysis (SA) methods in atmospheric dispersion modeling to the emission dispersion model (EDM) to study the prediction of atmospheric dispersion of NO2 generated by an industrial fire, whose results are useful for fire safety applications. The EDM is used to predict the level concentration of nitrogen dioxide (NO2) emitted by an industrial fire in a plant located in an industrial region site in Algeria.Design/methodology/approachThe SA was defined for the following input parameters: wind speed, NO2 emission rate and viscosity and diffusivity coefficients by simulating the air quality impacts of fire on an industrial area. Two SA methods are used: a local SA by using a one at a time technique and a global SA, for which correlation analysis was conducted on the EDM using the standardized regression coefficient.FindingsThe study demonstrates that, under ordinary weather conditions and for the fields near to the fire, the NO2 initial concentration has the most influence on the predicted NO2 levels than any other model input. Whereas, for the far field, the initial concentration and the wind speed have the most impact on the NO2 concentration estimation.Originality/valueThe study shows that an effective decision-making process should not be only based on the mean values, but it should, in particular, consider the upper bound plume concentration.

1 citations