The Application of Probabilistic Risk Assessment Techniques to Energy Technologies

Rasmussen, Norman C.

doi:10.1146/annurev.eg.06.110181.001011

Cited by 78 publications

(30 citation statements)

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“…Engineers have come to view risk as a numerical value that is a function of probability and consequences [8]. By contrast, some social scientists view risk as a social construct, not dependent on numerical values, but dependent upon the social situation and conditional knowledge [9].…”

Section: What Is Risk?mentioning

confidence: 99%

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Understanding Risk: Quantification, Perceptions, and Characterization

Meacham

2004

Journal of Fire Protection Engineering

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There is considerable discussion and activity in the fire protection engineering and building regulatory communities related to the use of risk in analysis, design, and regulation. However, understanding risk can be complex, as there are widely varying views as to what risk means, how it can be quantified, how it is perceived, and generally how it can be characterized. This paper presents an overview of key issues that impact the understanding of risk from a variety of perspectives as a resource to better facilitate discussions and agreements in the fire protection engineering and building regulatory communities.

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Section: What Is Risk?mentioning

confidence: 99%

“…Engineers often use what they consider to be a straightforward definition that combines the potential of an undesired consequence with the likelihood that such a consequence will occur [8]. This concept of risk is often represented mathematically as:…”

Section: What Is Risk?mentioning

confidence: 99%

Understanding Risk: Quantification, Perceptions, and Characterization

Meacham

2004

Journal of Fire Protection Engineering

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“…Bazelon (1979) has warned of the potential for "unrecognized value judgments... [to] creep into apparently objective assessments." Rasmussen (1981) and Lowrance (1976) discuss central characteristics of risks which preclude simple utilization of expected values when society faces major risks. (See also Graham, 1981).…”

Section: Comments On Hosticka's Critique Of Risk-and Cost-benefit Anamentioning

confidence: 99%

“…Schulze and Kneese (1981) have produced a seminal work on the philosophical basis of cost-benefit analysis illusti, ating how this technique can be modified to accommodate the principles of ethical systems other than utilitarianism, such as egalitarianism, elitism or libertarianism. In addition, Rasmussen (1981) and Rowe (1977) describe the use of "risk conversion factors" designed to reflect differing public perceptions of risk along several dimensions (e.g., volition, severity, origin, effect manifestation, exposure pattern, controllability, "dread"/familiarity, benefit, and necessity).…”

Section: Comments On Hosticka's Critique Of Risk-and Cost-benefit Anamentioning

confidence: 99%

Reply to hosticka on risk- and cost-benefit analysis

Nemetz

Vining

1982

Policy Sci

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We have read Professor Hosticka's comments on our "Biology-Policy Interface" article with great interest. In essence, Hosticka has concluded that our critical assessment of risk-and cost-benefit analysis is focussed on one narrow area (i.e., deficiencies in the epistemological environment in which the technique is applied) and that we take the inherent value of these techniques for granted. In turn, Hosticka provides a description of other problems which he thinks are more important in the evaluation of cost-benefit analysis as an instrument of social decision making.We are somewhat ambivalent about Hosticka's commentary. On the one hand, he has raised interesting and useful questions concerning the role of risk-and cost-benefit analysis. On the other hand, it is our contention that he has based his case on a critique of how these techniques have been used or misused rather than how they can or should be used. We will divide our remarks into two sections: (i) a reaffirmation of our original thesis, and (ii) a critique of Hosticka's position. Epistemological Issues in Risk-Benefit AnalysisIt was never our intention to provide an exhaustive treatment of all the complexities and problems inherent in the practical application of risk-and cost-benefit analysis; instead, we chose to focus our discussion on one critical and contentious issue deemed worthy of further analysis. Despite Hosticka's comments, the epistemological issues facing risk-benefit analysis pose non-trivial and indeed substantial challenges to the extent to which this methodology can be utilized in the decision-making process. Risk-benefit is the child of the marriage of cost-benefit analysis and probabilistic risk assessment. As such, it is genetically burdened with some of its parents' imperfections. This methodology was the principal focus of our concern.Risk analysis is a relatively new discipline which has gained increasing attention, and a touch of notoriety, especially through its use in the assessment of energy-related catastrophic accidents (see for example, Lewis, 1978; U.S.N.R.C., 1979). Deficiencies in methodology have constrained its usefulness in the resolution of major public policy

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“…However, the expression of the probability of air traffic accident used in this model does not present the true probability of consequence magnitude given the occurrence of causes of accidents. Rasmussen (1981) stated that the calculation of consequence magnitude of accidents will of course depend upon the type of hazard. Hence Bayesian Network (BN) was used to model this shortcoming.…”

Section: Introductionmentioning

confidence: 99%

An Improved Model for Estimating Runway Accident Cost in Nigeria

Oriola¹,

Adekunle²

2016

IJTTE

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This research proposes an improved model for estimating runway accident cost in the aviation industry in Nigeria. Bayesian Network was used to model the probability of consequences of runway accidents and subsequently the cost of the potential consequences. The Bayesian Network was also used to implement causal and diagnostic inference. Market interest rate which incorporates the effect of inflation was included to relax the assumption of constant economic value. The three classes of consequences of runway accidents identified in this study were fatal, serious, and minor. Domain experts were used to obtain relevant Bayesian causes and evidences related to the occurrence of consequence of runway accident. A mathematical equation was developed to solve the Bayesian Network influence diagram to obtain the probability of minor runway accident, serious runway accident and fatal runway accident as 0.7603, 0.1547 and 0.0850 respectively. Consequently, the estimated cost of runway accident (minor, serious and fatal) was $23, 813.52, $20, 052.64 and $772, 856.06 respectively. The Bayesian Network diagnostic inference reveals the close relation of runway accidents in Nigeria aviation sector with aircraft system failure, approach/takeoff procedures, human factors, weather conditions and collision risk.

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The Application of Probabilistic Risk Assessment Techniques to Energy Technologies

Cited by 78 publications

References 1 publication

Understanding Risk: Quantification, Perceptions, and Characterization

Understanding Risk: Quantification, Perceptions, and Characterization

Reply to hosticka on risk- and cost-benefit analysis

An Improved Model for Estimating Runway Accident Cost in Nigeria

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