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Development of a steady-state model is the first step in nuclear safety analysis. The developed model should be qualitatively analyzed first, then a sensitivity analysis is required on the number of nodes for models of different systems to ensure the reliability of the obtained results. This contribution aims to show through sensitivity analysis, the independence of modeling results to the number of nodes in a qualified MELCOR model for a Westinghouse type pressurized power plant. For this purpose, and to minimize user error, the nuclear analysis software, SNAP, is employed. Different sensitivity cases were developed by modification of the existing model and refinement of the nodes for the simulated systems including steam generators, reactor coolant system and also reactor core and its connecting flow paths. By comparing the obtained results to those of the original model no significant difference is observed which is indicative of the model independence to the finer nodes.

This paper deals with simulation, sensitivity and uncertainty analysis of LP-FP-2 experiment of LOFT test facility. The test facility simulates the major components and system response of a pressurized water reactor during a LOCA. MELCOR code is used for predicting the fission product release from the core fuel elements in LOFT LP-FP-2 experiment. Moreover, sensitivity and uncertainty analysis is performed for different CORSOR models simulating release of fission products in severe accident calculations for nuclear power plants. The calculated values for the fission product release are compared under different modeling options to the experimental data available from the experiment. In conclusion, the performance of 8 CORSOR modeling options is assessed for available modeling alternatives in the code structure.

This paper deals with determination of the minimum number and identification of the best configurations of passive autocatalytic recombiners (PAR) for the effective design of the containment in a pressurized water reactor (PWR). It considers the current design of PAR in the containment of a PWR and for that tries to identify, through a large number of sensitivity analyses, the minimum required number of PARs in different compartments. In this regard, a qualified nodalization has been developed for best estimate modeling by MELCOR integrated code. The developed model includes primary and secondary systems, containment, and related safety systems. A large number of simulations including the plant specific probabilistic safety assessment and success criteria analysis are used to identify the accident scenario with the highest amount of hydrogen production and risk. We first screened postulated accidents based on the PSA results and then based on the deterministic severe accident computations. It is found that the large break loss of coolant accident (LB-LOCA) without emergency core cooling system (ECCS) actuation is the bounding case from the hydrogen hazard point of view. To find the optimal configuration with minimum number of PARs in the containment, 40 different configurations are analyzed for the selected accident for a Westinghouse type PWR. The main finding of this work is identification of the minimum required number of PARs and their best distribution among the associated compartments. The obtained configuration is equally effective for the hydrogen risk mitigation with 36% reduction in the number of PARs in comparison to the base case design. The methodology of the analysis can be used for other plants.

The Level-2 probabilistic safety assessment (PSA) of pressurized water reactors studies the possibility of creep rupture for major reactor coolant system components during the course of high pressure severe accident sequences. The present paper covers this technical issue and tries to quantify its associated phenomenological uncertainties for the development of Level-2 PSA. A framework is proposed for the formal quantification of uncertainties in the Level-2 PSA model of a PWR type nuclear power plant using an integrated deterministic and PSA approach. This is demonstrated for estimation of creep rupture failure probability in station blackout severe accident of a 2-loop PWR, which is the representative case for high pressure sequences. MELCOR 1.8.6 code is employed here as the deterministic tool for the assessment of physical phenomena in the course of accident. In addition, a MATLAB code is developed for quantification of the probabilistic part by treating the uncertainties through separation of aleatory and epistemic sources of uncertainty. The probability for steam generator tube creep rupture is estimated at 0.17.

Safety-related structures are designed to provide a safe environment for the occupants and equipment during and after earthquakes. This is due to the fact that any damage imposed to the systems might lead to catastrophic consequences. Seismic probabilistic risk assessment (SPRA) is a systematic approach for the quantification of the seismic risk. One of the crucial steps in this assessment is to determine the seismic capacity of the structures by fragility method. After a review of available methodologies, this article analyzes the seismic fragility for a typical power plant containment considering the effects of soil-structure interaction (SSI). The structure and underneath soil profile are analyzed as a unified model by the subtraction method. Two steps are considered for the assessment of seismic response: In the first step, a fixed-base hypothesis framework is implemented to the computational problem. The second step covers computations taking into account the SSI effects. Using the results of seismic response analysis and safety factor method, seismic fragility of the structure is computed and related fragility curves are developed. Finally, by comparing the fragility curves, the effects of SSI are quantified on the overall seismic risk.

This paper describes a systematic framework for quantifying the degree of contribution of each parameter to the uncertainty of the output in severe accident assessment. This research is an extension of the recent work of the authors on uncertainty assessment of severe accident calculations where the main sources of uncertainty are identified through the so-called modified PIRT approach. The proposed methodology here utilizes uncertainty importance measures for the quantification of the effect of each input parameter on the output uncertainty. A response surface fitting approach is proposed for estimating the associated uncertainties with less calculation cost. The quantitative results are used to plan in reducing epistemic uncertainty in the input variable(s). The application of the proposed methodology is demonstrated for the ACRR MP-2 severe accident test facility.