Actions Imposed on Structures During Man‐made Accidents: Prediction via Simulation‐based Uncertainty Propagation

Abstract

Prediction of mechanical, thermal, and chemical actions induced during man‐made accidents (accidental actions) is of crucial importance to assessing potential damage to structures exposed to these actions. A logical result of such a prediction may be expressed in the form of probabilistic models describing likelihood of occurrence and characteristics of accidental actions. For many types of accidental actions the models are to be selected under the conditions of incomplete knowledge about and/or scarce statistical information on intensities and likelihood of imposition of the actions. This paper proposes a simulation‐based procedure intended for a selection of the probabilistic models under these conditions. The proposed procedure is formulated in the context of the classical Bayesian approach to risk assessment. The main idea of it is that statistical samples necessary for fitting the probabilistic action models can be acquired from a stochastic simulation of accident sequences leading to an imposition of accidental actions. Formally, the stochastic simulation of accidents serves the purpose of propagating uncertainties related to the physical phenomena capable of inducing accidental actions. These uncertainties are quantified in line with the classical Bayesian approach. The simulation‐based procedure can be used for damage assessment and risk studies within the methodological framework provided by the above‐mentioned approach.

Multiattribute Selection from Alternative Designs of Infrastructure Components for Accidental Situations

“…In QRA, the uncertainty related to a model's accuracy is expressed by means of epistemic probability distributions (Zio and Apostolakis, 1996;USNRC, 1997). The epistemic uncertainties related to models 1 to 6 can be propagated by applying a nested loop procedure (Aven and Rettedal, 1998;Vaidogas, 2005Vaidogas, , 2006. The final result of the propagation will be distributions of the epistemic random variablesp f (x i ).…”

First step towards preventing losses due to mechanical damage from abnormal actions: Knowledge-based forecasting the actions

“…Examples of such a simulation, which was performed within the framework of CSA, are provided by Høiset, Hjetager, Tron, and Malo (1997) and Hauptmanns (2001a, b). The present paper follows this simulationoriented approach and takes the position that forecasting AAs should be considered a part of a broader problem of a quantitative risk analysis (QRA) and carried out using knowledge-based methods of QRA (Vaidogas, 2005). They allow using a wider spectrum of diverse knowledge related to AAs than the methods provided by CSA.…”

Dependence of Strength Enhacement on Shock Front Overpressure: The Case of RC Structures

“…which may be subjected to impact or explosive loading. The low probability of occurrence of these loads necessitates a limit state approach to design in which irreversible structural deformation and material damage is acceptable provided that overall structural integrity is maintained (Vaidogas 2005a(Vaidogas , 2005b. The numerical simulation of such structural responses therefore requires the simultaneous consideration of both dynamic material properties and geometrical nonlinearities.…”