Expert judgement-based risk factor identification and analysis for an effective nuclear decommissioning risk assessment modeling

Awodi, Ngbede Junior; Liu, Yong-kuo; Ayodeji, Abiodun; Adibeli, Justina Onyinyechukwu

doi:10.1016/j.pnucene.2021.103733

Cited by 13 publications

(17 citation statements)

References 17 publications

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“…Factors using belief structures synthesize individual belief structures into group trust structures and rank expected risk results using the minimax regret approach (MRA). Risk analysis in energy is a popular topic and is of great importance, especially when it comes to the security of supply and safety through the use of nuclear, thermal, or renewable sources [57][58][59].…”

Section: Implementing the Mcdm And Other Methods To Rpnmentioning

confidence: 99%

Risk Evaluation: Brief Review and Innovation Model Based on Fuzzy Logic and MCDM

et al. 2022

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The risk assessment of engineering systems represents an important part of the quality of service and dependability. The existing methods for risk evaluation use crisp sets for rating partial indicators’ proposition and their cumulative products as an overall indicator. In this paper, existing FMEA and FMECA methods have been improved using the fuzzy expert system for calculating the risk priority number. The application of fuzzy logic allows the use of linguistic descriptions for risk analysis. In this way, the state of the system in terms of risks and consequences is better described. The settings of the fuzzy systems are based on the application of two multi-criteria decision-making methods. The AHP method was used to define the mutual relationship of the impact of partial indicators (occurrence, severity, and detectability) on risk. In this way, subjectivity in risk assessment is reduced. In the composition of the fuzzy model, the TOPSIS method is introduced to reduce the dissipation of results, which contributes to the accuracy of the outcome. This contributes to the accuracy of the results. The results were verified through a case study of a complex engineering system—bucket-wheel excavators. The risk was observed from the aspect of the danger of damage and the danger of downtime. The initial information for weak points of ES is defined according to historical damage events and statistics of downtime. Expert knowledge was used for weak points grading in the model. Additional model verification was performed using similar methods, using the same input data. The innovative model, presented in the paper, shows that it is possible to correct different weights of risk indicators. The obtained results show less dispersion compared with other existing methods. Weak points with increased risk have been located, and an algorithm has been proposed for risk-based maintenance application and implementation.

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Section: Implementing the Mcdm And Other Methods To Rpnmentioning

confidence: 99%

Risk Evaluation: Brief Review and Innovation Model Based on Fuzzy Logic and MCDM

et al. 2022

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“…The higher the resultant damage, the higher the level of consequences will be. Both values are often provided as ranking or leveling and obtained from the experiences, expert judgments, or spesific references [27]. For TRIGA 2000 research reactor, we recommend the use of level of probability, level of radiological and non-radiological consequences, and risk matrix, as shown in Tables 2-5.…”

Section: Hazard Analysismentioning

confidence: 99%

Risk Assessment on the Decommissioning Stage of Indonesian Triga 2000 Research Reactor

Tyas

Deswandri²,

Intaningrum³

et al. 2022

Tri Dasa Mega

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Decommissioning is the final stage of a nuclear reactor. In preparing the decommissioning plan, one of the important elements that need to be considered is safety assessment. During decommissioning, there are many complex tasks to be done where the radiological and non-radiological hazards arise and can significantly affect not only the workers but also the general public and the environment. Indonesia has no experience with nuclear reactor decommissioning, so it is necessary to study various experiences of decommissioning activities in the world. This study proposes a framework to implement the safety assessment on the decommissioning of the TRIGA 2000 research reactor. The framework was developed on desk-based research and analysis. The proposed framework involves the facility and decommissioning activities, hazard identification, hazard analysis, hazard evaluation, hazard or risk control, and independent review.

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“…These risks are specifically identified for each environment. Awodi et al, as well as Treshchevsky, pointed out in their research the diversity of risks in specific environments and the importance of their specification based on the experience of experts [43,45]. Project risks do not affect the process of its individual phases of the project life cycle in isolation.…”

Section: Project Risk Managementmentioning

confidence: 99%

“…When identifying, it is important to assess the reliability of the information sources used, the need to obtain additional information, the suitability of the selection of persons involved in the identification, the completeness of the list of identified sources of risk, etc. [43][44][45].…”

Section: Introductionmentioning

confidence: 99%

Sustainability of Business through Project Risk Identification with Use of Expert Estimates

et al. 2021

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Projects are a tool that enables enterprises to implement innovation and development activities and achieve the goals in the set time, costs and required quality but they also bring risks that need to be adequately identified, analyzed and assessed. Important tools that can be used in project management in the process of risk identification are expert estimates. However, little attention is paid to determining the accuracy of expert estimates. To verify the accuracy of expert estimates, an analysis of all completed projects for a certain period of enterprise that implemented them was performed. The purpose of the study was to determine the accuracy of expert estimates in the enterprise implementing projects. This was ascertained by analyzing all available completed projects and by Barnard’s test at the significance level of α = 0.05. The Phi coefficient of association was used to determine its extent. In the paper, we pointed out how inappropriate expert estimates affect the completion of the project within the specified period.

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Expert judgement-based risk factor identification and analysis for an effective nuclear decommissioning risk assessment modeling

Cited by 13 publications

References 17 publications

Risk Evaluation: Brief Review and Innovation Model Based on Fuzzy Logic and MCDM

Risk Evaluation: Brief Review and Innovation Model Based on Fuzzy Logic and MCDM

Risk Assessment on the Decommissioning Stage of Indonesian Triga 2000 Research Reactor

Sustainability of Business through Project Risk Identification with Use of Expert Estimates

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