Probabilistic Structural Mechanics in System and Plant Risk Assessment

Journal of Civil Engineering and Management

2005

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.

Section: Expert Judgement In Modelling Physical Phenomenamentioning

confidence: 99%

“…The action model suggested in this paper can be viewed as a generalisation of the model known as hazard curve. Hazard curves are widely used in QRA [16,17]. It is discussed how to select the action model on the basis of a general approach to QRA known as a classical Bayesian approach (CBA) [18].…”

Section: Introductionmentioning

confidence: 99%

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

Journal of Civil Engineering and Management

2005

“…An evaluation of these probabilities in broad sense includes modelling (prediction) of dynamic loads imposed by the incident blast wave having the characteristics x and, with these dynamic loads, estimation of the probabilities of the damages D 1 themselves (see the two righthand rectangles in Fig). Each probability P(D 1 I x) can be considered as the fragility of the structural system under analysis with respect to the incident blast wave having the characteristics x (see the definition of the fragility of structural and mechanical systems used in QRA, for instance, in [12]).…”

Section: Modelling Uncertainties In Structural Fragility Analysismentioning

confidence: 99%

Probabilistic Framework for Assessing Risks to Structures Stemming From Accidental Explosions

Journal of Civil Engineering and Management

2002

In the paper, an attempt is made to formulate a probabilistic framework for an assessment of risk to structures resulting from accidental vapour cloud explosions (VCEs). This framework is based on the general methodology known in the quantitative risk analysis as the classical Bayesian approach to risk assessment. Attention is centred on the estimation of the annual probabilities of potential damages to structural systems exposed to dangers of VCEs. The paper sets up the mathematical problem of assessing risk to structures related to VCEs and, for the most part, contains discussion on the methodological tasks to be solved in this assessment.

“…QRA has been developed over the past decades as a general methodology for dealing with natural and technological hazards (Sundararajan and Vo, 1995;Kumamoto and Henley, 1996;Ayyub, 2003). A combination of QRA and MAS offers a new possibility of improving the safety of infrastructure components.…”

Section: Introductionmentioning

confidence: 99%

Multiattribute Selection from Alternative Designs of Infrastructure Components for Accidental Situations

Zavadskas

Computer aided Civil Eng

2009

The design of infrastructure systems for "accidental" situations, i.e., abnormal service conditions, may include a comparison of alternative design solutions of system components. These solutions are compared by means of applying a universal methodology known as a multiattribute selection (MAS). The alternative designs are described by a number of attributes that characterize each of them. Failure probability and quantitative measure of the risk are used as safety-related attributes of the alternative designs. This article shows how to carry out the MAS in the presence of epistemic uncertainties in safety-related attributes. Distributions of epistemic uncertainties are specified by means of methods used for quantitative risk assessment. The MAS is carried out as a propagation of these uncertainties. The Monte Carlo simulation is used to propagate uncertainties through the algorithm of MAS. The approach proposed in this article is illustrated by two examples, which consider alternative designs of a protective barrier and alternative sprinkler systems.