A dynamic probabilistic risk assessment platform for nuclear power plants under single and concurrent transients
- 6 March 2023
- journal article
- research article
- Published by Taylor & Francis Ltd in Journal of Nuclear Science and Technology
- Vol. 60 (7), 824-838
- https://doi.org/10.1080/00223131.2023.2176377
Abstract
Dynamic probabilistic risk assessment (DPRA) of nuclear power plants (NPPs) has become one of the most critical research areas, especially in the aftermath of the 2011 Fukushima Daiichi nuclear accident. Uncertainty in NPP behavior is key when considering its safety under different operating conditions. Such uncertainty typically results from operation parameters, system conditions, and modeling assumptions. This study integrates the system dynamics (SD) modelling approach with an uncertainty analysis method to quantify the dynamic probabilistic risk in NPPs. To demonstrate the approach’s applicability, the average fuel temperature is used to estimate the probability of reactor core damage under different transients, representing perturbations in reactivity and steam valve coefficient. A Monte Carlo simulation is employed to investigate the effect of uncertainties associated with the different model parameters. A global sensitivity analysis demonstrates that the total delayed neutron fraction, the heat transfer coefficient from fuel to coolant, the coolant temperature coefficient of reactivity, and the fuel temperature coefficient of reactivity are the primary controllers of the plant response variability under the transients considered. In summary, the integration of SD modelling and uncertainty analysis presents an effective DPRA approach that overcomes the limitations of static counterparts while minimizing the computational resources required. Graphical AbstractKeywords
This publication has 32 references indexed in Scilit:
- A survey of dynamic methodologies for probabilistic safety assessment of nuclear power plantsAnnals of Nuclear Energy, 2013
- Overview on Bayesian networks applications for dependability, risk analysis and maintenance areasEngineering Applications of Artificial Intelligence, 2012
- Preliminary Estimation of Release Amounts of131I and137Cs Accidentally Discharged from the Fukushima Daiichi Nuclear Power Plant into the AtmosphereJournal of Nuclear Science and Technology, 2011
- Comparison of Values of Pearson's and Spearman's Correlation Coefficients on the Same Sets of DataQuaestiones Geographicae, 2011
- Survey of sampling-based methods for uncertainty and sensitivity analysisReliability Engineering & System Safety, 2006
- Systems thinking on knowledge and its management: systems methodology for knowledge managementJournal of Knowledge Management, 2002
- Second edition of the EURACHEM Guide Quantifying Uncertainty in Analytical MeasurementAccreditation and Quality Assurance, 2000
- The Event Sequence Diagram framework for dynamic Probabilistic Risk AssessmentReliability Engineering & System Safety, 1999
- The development and application of the accident dynamic simulator for dynamic probabilistic risk assessment of nuclear power plantsReliability Engineering & System Safety, 1996
- Risk assessment for dynamic systems: An overviewReliability Engineering & System Safety, 1994