A comprehensive risk assessment system for probabilistic problems (original) (raw)
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Treatment of Uncertainties in Probabilistic Risk Assessment
System Reliability [Working Title]
Probabilistic risk assessment (PRA), sometimes called probabilistic safety analysis, quantifies the risk of undesired events in industrial facilities. However, one of the weaknesses that undermines the credibility and usefulness of this technique is the uncertainty in PRA results. Fault tree analysis (FTA) and event tree analysis (ETA) are the most important PRA techniques for evaluating system reliabilities and likelihoods of accident scenarios. Uncertainties, as incompleteness and imprecision, are present in probabilities of undesired events and failure rate data. Furthermore, both FTA and ETA traditionally assume that events are independent, assumptions that are often unrealistic and introduce uncertainties in data and modeling when using FTA and ETA. This work explores uncertainty handling approaches for analyzing the fault trees and event trees (method of moments) as a way to overcome the challenges of PRA. Applications of the developed frameworks and approaches are explored in illustrative examples, where the probability distributions of the top event of fault trees are obtained through the propagation of uncertainties of the failure probabilities of basic events. The application of the method of moments to propagate uncertainty of log-normal distributions showed good agreement with results available in the literature using different methods.
Applications of Probabilistic Risk Assessments: The Selection of Appropriate Tools1
Risk Analysis, 1991
Probabilistic risk assessment (PRA) is an important methodology for assessing the risks of complex technologies. This paper discusses the strengths and weaknesses of PRA. Its application is explored in three different settings: adversarial policy processes, regulatory/licensing procedures, and plant safety audits. It is concluded that PRA is a valuable tool for auditing safety precautions of existing or planned technologies, especially when it is carried out as an interactive process involving designers and plant personnel who are familiar with actual, everyday operations. PRA has not proven to be as well-suited in providing absolute risk estimates in public-policy debates concerning the acceptability of a technology, or for the licensing and regulatory procedures. The reasons for this are discussed.
Utility Experience Performing Probabilistic Risk Assessment for Operational Planning
2007 International Conference on Intelligent Systems Applications to Power Systems, 2007
EPRI has developed a Probabilistic Risk/Reliability Assessment (PRA) method under Power Delivery Reliability Initiative, which has been successfully implemented by various energy companies in planning studies of growing complexity. Unlike the traditional deterministic contingency analysis, PRA combines a probabilistic measure of the likelihood of undesirable events with a measure of the consequence of the events (that is, the impact) into a single reliability index-Probabilistic Reliability Index (PRI). EPRI internally developed the PRI program that uses contingency analysis results as well as the transmission facility outage information as input to compute and graphically display the reliability indices. This paper presents an application of PRI program to study the transmission network of New York Power Authority (NYPA). This work has demonstrated that the PRA method significantly improves the ability of conducting effective transmission operational planning. The paper represents the collaborative effort between EPRI and NYPA.
Uncertainty Analysis using Probabilistic Estimates in Risk Assessment
Journal of Pharmaceutical Negative Results, 2023
Monte Carlo Simulation (MCS) was applied as a decision-making model to quantify the level of project risk based on risk factors taken from expert opinions and literature studies. The model classifies the datasets of a construction project into one of the five classes such as tolerable, low, medium, high and intolerable level of risk. As agreed, the probability of risk (RP) and the impact of risk (RI) were selected as the inputs for assessing the level of risk (RL). MCS tools have been widely utilized to deal with the inherent variability in construction systems and is a very useful technique for modeling and analyzing real-world systems. The objective of this paper is to evaluate the use of MCS to quantify project risk. Consequently, risk assessment using MCS to represent risk RP and RI is carried out. Using the Monte Carlo method, the risk on processes (R2), construction error (R4) and process delay (R6), low productivity (R8), quality issues (R12), and technical problem (R13) were evaluated in a LOW-HIGH risk range, while the MEDIUM-HIGH risk was contributed by processes (R1), inexperienced project management team (R3), design errors (R5), construction errors (R7), inexperienced site workers (R9), site accidents (R10). At 95% certainty, the highest risk on the project was contributed by construction error (R7) and delay in delay (R11), with a mean value of 56%, followed by risk on design error, R5 (55.8%), risk on inexperienced workers, R9 (47%), and risk on inexperienced project management team, R3 (46.5%).
Total efficient risk priority number (TERPN): a new method for risk assessment
Journal of Risk Research, 2017
Safety is one of the most important issues in modern industrial plants and industrial activities. The Safety Engineering role is to ensure acceptable safety levels of production systems, not only to respect local laws and regulations, but also to improve production efficiency and to reduce manufacturing costs. For these reasons, the choice of a proper model for risk assessment is crucial. In this context, the present research aims to propose a new method, called Total Efficient Risk Priority Number (TERPN), able to classify risks and identify corrective actions in order to obtain the highest risk reduction with the lowest cost. The main scope is to suggest a simple, but suitable model for ranking risks in a company, to reach the maximum effectiveness of prevention and protection strategies. The TERPN method is an integration of the popular Failure Mode Effect and Criticality Analysis (FMECA) with other important factors in risk assessment.
Scientia Iranica
Nowadays, because of the advancement of technology and subsequently unpredictable events, it is important for addressing risk management as an important part of projects and business. In this paper, a novel approach based on Monte Carlo simulation has been proposed for risk assessment, which considers the co-occurrence of risks. In this method, the output of extended and classic Monte Carlo simulation is applied for co-occurrence-based risk assessment (CORA) and prioritization. Also, the magnitude in each source of uncertainty has been determined by a new approach. The proposed model investigates risk's relationship and determines the type of effect as resonance or reduction in addition to identifying and analyzing the risks. Also, a system dynamic model is applied to illustrate the relationships of risks. Finally, this method is applied to a petrochemical project. Five risks as temperature, rain, labor, cost, and inflation are considered in this project. Based on the numerical results, the most important risk is inflation. Also, there is a significant different between the result of the proposed model in comparison with model that ignore the co-occurrence of risks. CORA helps the manager to consider all aspect of risks and help them to have a better decision.
Probabilistic risk assessment method development and applications (PRAMEA)
2017
Simultaneously research has been carried out in the national nuclear waste management programmes (KYT2018 runs in parallel with SAFIR2018). SAFIR2018 consist of four main research areas: (1) Plant safety and systems engineering; (2) Reactor safety; (3) Structural safety and materials; and (4) Research infrastructure. Research has been carried out annually in 28 projects that are guided by six reference groups. The research results of the projects are published in scientific journals, conference papers and research reports. The programme management structure consists of the Management Board, three Steering Groups managing the research areas, six Reference Groups, and programme administration. SAFIR2018 Management Board consists of representatives of the Radiation and Nuclear Safety Authority (STUK), Ministry of Economic Affairs and Employment (MEAE), Fennovoima Oy, Fortum, Teollisuuden Voima Oyj (TVO),
A new approach for quantitative risk analysis
Annals of Operations Research, 2014
Project risk management aims to provide insight into the risk profile of a project as to facilitate decision makers to mitigate the impact of risks on project objectives such as budget and time. A popular approach to determine where to focus mitigation efforts, is the use of so-called ranking indices (e.g. the criticality index, the significance index etc.). Ranking indices allow the ranking of project activities (or risks) based on the impact they have on project objectives. A distinction needs to be made between activity-based ranking indices (those that rank activities) and risk-driven ranking indices (those that rank risks). Because different ranking indices result in different rankings of activities and risks, one might wonder which ranking index is best? In this article, we provide an answer to this question. Our contribution is threefold: (1) we set up a large computational experiment to assess the efficiency of ranking indices in the mitigation of risks; (2) we develop two new ranking indices that outperform existing ranking indices and (3) we show that a risk-driven approach is more efficient than an activity-based approach.