Methods of quantitative estimation and reduction of uncertainty of the accidental risk in fire explosive facilities

Abstract. Currently, ensuring the industrial safety of hazardous industrial facilities involves – along with conventional oversight – the risk-oriented approach that is significantly more flexible. The procedure of quantitative estimation of an accidental risk for hazardous industrial facilities is essentially one of the procedures of conformity assessment, as it includes the comparison of the risk indicators obtained by means of calculation (or expert assessment) with their standard values. The Aim of the paper is to define the problem of uncertainty that is associated with all the stages of quantitative estimation of an accidental risk, make a brief historical account, analyze its types and sources, describe the approaches employed as part of quantitative estimation of this uncertainty. Currently, it is accepted to identify the terminological, parametric and model types of uncertainty, whose examples are provided in the paper. Analysis shows that a fourth – computational – type should be added, whose contribution in many cases may be considerable. It is shown that, due to a number of circumstances, scalar numbers that are normally used for defining parameter values of the physical-mathematical models of failure processes are in reality mere indicators of the ranges of their value variation. Currently, uncertainties in the values of accidental risk parameters are accounted for using probabilistic and deterministic approaches, as well as fuzzy numbers. Methods. For the purpose of quantitative estimation of uncertainty, the paper employs the method of interval analysis. In the most general case, without using the hypothesis on the behaviour of a parameter value within the range of its possible variation, the parametric uncertainty can be defined with an interval number. In that case, all the required calculations are performed using interval methods. The natural (naive) version of interval analysis has a serious drawback that consists in an unjustified increase of the width of the interval number deduced by means of interval calculations, if one or more input parameters of the model enter into the calculation formula more than once, or the input parameters are functionally interdependent. Modern interval analysis employs methods allowing to alleviate this effect. They are briefly described in this paper. It is shown that if statistical information is available on the behaviour of parameter values within their variation intervals, the results of interval calculations of the accidental risk indicators can be significantly improved. The suggested method of reducing the computational uncertainty of quantitative estimation of the accidental risk in the interval setting is illustrated with a numerical example of risk indicator calculation for the “fireball” accident scenario. The paper sets forth the results of interval calculation of an individual accidental risk for an explosion and fire hazardous facility “reservoir with a flammable liquid” in three ways: a) naive; b) accounting for the effect of parameter correlation; c) additionally, accounting for available statistical information. Conclusions. Interval methods allow not only taking into consideration the presence of uncertainty in the accidental risk parameters, but evaluating it quantitatively. There are efficient methods of alleviating the negative.

industrial safety, accidental risk, parametric uncertainty, interval methods of calculation, minimization of computational uncertainty

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