PSI - Issue 28

Dmitry O. Reznikov et al. / Procedia Structural Integrity 28 (2020) 1360–1368 D.Reznikov, N.Makhutov,O.Yudina / Structural Integrity Procedia 00 (2019) 000–000

1361

2

designed end state

ES 0 ES i

damaged end state i E { N } mathematical mean of the number of victims f N ( x ) probability density function of N per year F N ( x ) cumulative probability distribution function of N per year F U ( x ) cumulative probability distribution function of the economic loss U ; f U ( x ) probability density function of the economic loss f - ( j )

probabilities of the scenarios S ( j ) before the implementation of protective measures probabilities of the scenarios S(j) after the implementation of protective measures

f + ( j )

initiating event economic risk index

IE I e I N IS

the integral society risk index

initial state

disproportionality factor

k dp K lim

limit function cost of human life

L c m - m +

number of failure scenarios before the implementation of protective measures number of failure scenarios after the implementation of protective measures

number of fatalities per year

N

N - ( j ) number of victims under the scenario S ( j ) before the implementation of protective measures N + ( j ) number of victims under the scenario S ( j ) after the implementation of protective measures P ( S i ) probability of realization of the scenario S i P ( f | S i ) conditional probability that the predefined person will be killed due to realization of the scenario S i R e economic risk R I individual risk R i * tolerable individual risk [ R i ] tolerable individual risk limit { R i } broadly acceptable individual risk limit S i scenario i U ( S i ) economic loss associated with scenario i U - ( j ) economic losses expected under the scenario S ( j ) before the protective measures U + ( j ) economic losses expected under the scenario S ( j ) after before the protective measures β policy factor Δ N expected decrease in the number of accident victims after the implementation of protective measures The evolution of a hazardous industrial facility during its life cycle can be represented as a sequence of its time varying states. If it is possible to ensure a transition of the facility from a given initial state (commissioning IS , fig.1) to a given end state (planned decommissioning ES 0 ) than the so-cold success scenario ( S 0 ) is realized. Due to the high level of uncertainty of the system, its functioning is multivariate and is described by a branched scenario tree containing bifurcation points and multiple end states. Due to the fact that the scenario graph of the HIF inevitably includes emergency and catastrophic scenarios, the operation of the HIF is fraught with significant risks for the population, natural environment and economic assets. Management of HIF involves the implementation of special impacts on the system that are focused on directing its evolution along with to the preplanned scenario ( S 0 ) and to prevent the realization of adverse scenarios. In those cases when the risk parameter is considered as the determining factor in the selection of control actions on the system the concept risk based management is used to emphasize that the system is managed according to the risk criterion.