Severe accident (SA) codes and their core degradation models have to deal with strongly nonlinear and discontinuous phenomena. In the application of uncertainty quantification to SA simulations, the combination of such phenomena may lead to a strong increase in the uncertainty propagated through the simulation, as well as to the chaotic behavior of the output variables. In this framework, the application of the limit surface search method of the RAVEN tool is proposed for a case where cliff-edge effects of SA phenomena determine a bifurcation of an output figure of merit. The algorithm is based on a predictive method making use of a support vector machine model, and it is applied with the aim of separating those input values that lead to different phenomenologies among the uncertainty calculations. The case study is in regard to the uncertainty analysis of the ASTEC code simulation of the QUENCH6 experimental test conducted in the framework of the International Atomic Energy Agency Coordinated Research Project I31033.

Deterministic integral codes, such as MELCOR and ASTEC, have been developed to predict and characterize severe accident progression in nuclear power plants. Due to the complexity and the mutual interaction of several physical phenomena occurring in severe accident scenarios, the validation of these codes is fundamental. Moreover, considering the limited experimental database in prototypical conditions, sensitivity analyses and quantification of code uncertainties should be carried out.The present paper describes the assessment of a MELCOR v2.2 input deck of the QUENCH test facility, located at Karlsruhe Institute of Technology, and the QUENCH-06 test, which was selected for code validation. This experiment was aimed at evaluating the effect of subcooled water injection on the hydrogen production and degradation of a pre-oxide pressurized water reactor-like rod bundle.Having as reference past QUENCH analyses that are available as public technical literature and the experimental data, the authors developed an input deck exploiting several configurations and code features. The nodalization provides a fine representation of the test bundle active region, as well as a detailed definition of the boundary conditions and of the thermal insulation system.Validation was performed by evaluating the accuracy of the code by comparing, both qualitatively and quantitatively, the MELCOR results for some relevant parameters (such as hydrogen generation, maximum cladding temperature, and oxide scale of the rods) against the experimental data. The results showed that MELCOR can reproduce the experimental data of hydrogen production and cladding oxide thickness in the instrumented bundle positions.In addition, the study included a sensitivity analysis to test the behavior of different Zircaloy-steam oxidation correlations in the temperature range 1100 to 2200 K, assessing their impact on hydrogen production and degradation predictions. Finally, an uncertainty analysis was carried out to evaluate the dispersion of the figures of merit involved in the simulated phenomenology.

The quantification of the uncertainty in the output of the thermal-hydraulic and severe accident codes used for the safety analysis of Nuclear Power Plants (NPPs) typically proceeds by propagating the uncertainty of the input variables and parameters through the codes. The input uncertainty is usually characterized by expert-based probability density functions. Inverse Uncertainty Quantification (IUQ) can be used to inform the characterization of such probability density functions based on experimental data. In this paper, we propose an empirical IUQ method that exploits data from experimental facilities and apply it to a case study of the ATRIUM project of OECD/NEA/CSNI/WGAMA. Specifically, the TRACE best-estimate thermal-hydraulic system code is used to replicate the data of the Sozzi-Sutherland, Super Moby Dick and Marviken experimental facilities with regards to an accident scenario with guillotine break of the pressurizer surge line in a generic three loop PWR-900; the input uncertainties are first characterized and then propagated to the output.

The Management and Uncertainties of Severe Accidents (MUSA) project was funded in HORIZON 2020 and is coordinated by CIEMAT (Spain). The project aims at consolidating a harmonized approach for the analysis of uncertainties and sensitivities associated with Severe Accidents (SAs) analysis, focusing on source term figures of merit. The Application of Uncertainty Quantification (UQ) Methods against Integral Experiments (AUQMIE - Work Package 4 (WP4)), led by ENEA (Italy), was devoted to apply and test UQ methodologies adopting the internationally recognized PHEBUS FPT1 test. FPT1 was chosen to test UQ methodologies because, even though it is a simplified SA scenario, it was representative of the in-vessel phase of a severe accident initiated by a break in the cold leg of a PWR primary circuit. WP4 served as a platform to identify and discuss the issues encountered in the application of UQ methodol-ogies to SA analyses (e.g. discuss the UQ methodology, perform the coupling between the SA codes and the UQ tools, define the results post-processing methods, etc.). The purpose of this paper is to describe the MUSA PHEBUS FPT1 uncertainty application exercise with the related specifications and the methodologies used by the partners to perform the UQ exercise. The main outcomes and lessons learned of the analysis are: scripting was in general needed for the SA code and uncertainty tool coupling and to have more flexibility; particular attention should be devoted to the proper choice of the input uncertain parameters; outlier values of figures of merit should be carefully analyzed; the computational time is a key element to perform UQ in SA; the large number of uncertain input parameters may complicate the interpretation of correlation or sensitivity analysis; there is the need for a statistically solid handling of failed calculations.

Since 2012, many NEA member countries have implemented deterministic safety analyses for operating nuclear power plants under design extension conditions without significant fuel degradation or core melt (DEC-A). However, variations persist among these countries in defining DEC-A scenarios and acceptance criteria, validation and application of computer codes, development and application of deterministic safety analysis methods. Furthermore, there is a dearth of shared international experience and methodologies among various stakeholders, including regulatory authorities, technical safety or support organizations, utilities, engineering and consulting companies. To address these gaps, the OECD/NEA initiated a project in 2021, titled "Good Practices for Analyses of Design Extension Conditions without Significant Fuel Degradation for Operating Nuclear Power Plants" (or "DEC-A"), under the auspices of the Working Group on Accident Management and Analysis (WGAMA) and the Working Group on Fuel Safety (WGFS). The DEC-A project aims to review and summarize the current requirements, knowledge status, and best practices in NEA member countries. This paper outlines the objectives and scope of the OECD/NEA DEC-A project, and presents the findings from the review and discussions for each task.

Small Modular Reactors (SMRs) adopting passive mitigation strategies are currently the most promising technology for the near term deployment of nuclear power generation. Different SMRs designs are currently under development and are, in general, characterized by some common features with the current reactors and by other features typical of their designs. Therefore, though numerous code validation study against natural circulation (NC) have been performed for large scale reactors, further analyses are necessary to characterize the capability of codes against available experimental data representative of SMR phenomenology. Though different scaling methodologies have been developed, considering the complex geometry and phenomena of a NPP, in the design of scaled-down experimental facilities it is not possible to avoid distortions, which should be limited to non-dominant phenomena. Even if dominant phenomena are preserved, due to the missing data at NPP scale, the code accuracy should be tested at different scales. Therefore, in a verification and validation process, the uncertainty related to the code scaling-up capability should be addressed, for example using counter-part tests. Since NC tests at different scales in integral test facilities devoted to SMR are currently not available, a numerical scaling methodology is here proposed. Based on previous activities, having as a reference the NC DOE tests developed in the OSU-MASLWR facility, the USNRC best estimate thermal hydraulic TRACE code has been validated for simulating NC in steady and transient conditions. Since the OSU-MASLWR is volume and height scaled, the target of this paper is to assess the scaling-up capability of the OSU-MASLWR Reactor Pressure Vessel nodalization in the prediction at different scales of NC and other phenomena typical of SMR, having as a base the OSU-MASLWR-002 single phase NC data. This, also, gives some first insights about the TRACE scaling-up capability against single-phase NC in integral type configurations.

In the Best-Estimate Plus Uncertainty (BEPU) framework, the use of best-estimate code requires to go through a Verification, Validation and Uncertainty Quantification process (VVUQ). The relevance of the experimental data in relation to the physical phenomena of interest in the VVUQ process is crucial. Adequacy analysis of selected experimental databases addresses this problem. The outcomes of the analysis can be used to select a subset of relevant experimental data, to encourage designing new experiments or to drop some experiments from a database because of their substantial lack of adequacy. The development of a specific transparent and reproducible approach to analyze the relevance of experimental data for VVUQ still remains open and is the topic of this contribution.In this paper, the concept of adequacy initially introduced in the OECD/NEA SAPIUM (Systematic APproach for model Input Uncertainty quantification Methodology) activity is formalized. It is defined through two key properties, called representativeness and completeness, that allows considering the multifactorial dimension of the adequacy problem. A new systematic approach is then proposed to analyze the adequacy of a set of experimental databases. It relies on the introduction of two sets of criteria to characterize representativeness and completeness and on the use of multi-criteria decision analysis method to perform the analysis. Finally, the approach is applied in the framework of the new OECD/NEA ATRIUM activity which includes a set of practical IUQ exercises in thermal-hydraulics to test the SAPIUM guideline in determining input uncertainties and forward propagating them on an application case. It allows evaluating the adequacy of eight experimental databases coming from the Super Moby-dick, Sozzi-Sutherland and Marviken experiments and identifying the most adequate ones.

Uncertainty estimation to assess figures of merit characterizing evolution of a severe accident transient is a topic of current investigation in development of best-estimate plus uncertainty methodology. The probabilistic method to propagate input uncertainty is one of the methodologies used to develop Uncertainty Analyses (UAs). Using this methodology, UAs are performed by sampling probability distributions that describe the range of possible values that computer simulation model inputs can have. For each sample (or realization) of a set of uncertain input parameters, a computer simulation is performed. From the range of code simulation results obtained for each input realization, a distribution of code results is obtained. In this process, the distribution of input uncertainties is propagated to obtain a distribution of possible code results (i.e., the code output uncertainty). This probabilistic methodology is facilitated using Uncertainty Tools (UTs), which can be coupled with the accident analysis computer code to perform an UA. One of the UTs currently available is DAKOTA, developed by Sandia National Laboratories. DAKOTA is also provided as a SNAP plug-in. SNAP is a graphical user interface designed to support the use of USNRC codes (MELCOR, TRACE, etc). This paper is entirely derived from the NUREG/IA532 issued by USNRC in April 2023 (Mascari et al., 2023) and has as a major target to summarize the main needs of UA in severe accident, the main element of the probabilistic method to propagate input uncertainty, and the workflow within SNAP to assist other interested analysts with their applications given they are members of the USNRC Cooperative Severe Accident Research Program (CSARP).

Sump clogging has been identified as a relevant issue after an accident occurred in the Barseba center dot ck-2 nuclear power plant in Sweden (1992). Following a steam line Loss of Coolant Accident (LOCA) due to the inadvertent opening of a safety relief valve, the jet stripped some insulation material from nearby pipes. The insulation debris were transported to the inlet of the strainers for the drywell spray system, thus clogging the intake. The accident was not serious but showed that the Emergency Core Cooling System (ECCS) could have failed. As a consequence, several actions have been undertaken by international organizations, regulatory bodies and nuclear power plant owners to characterize this issue, and propose solutions and improvements. In the present paper, the Reliability Evaluation of Passive Safety Systems (REPAS) methodology is applied to analyze the sump clogging issue and its effect on the long-term core cooling function. Originally developed to evaluate the reliability of passive systems, REPAS is here applied for the first time to an active system. The application is performed using the TRAC/RELAP Advanced Computational Engine (TRACE) code, developed by the USNRC, to simulate a generic three-loop PWR, with an active decay heat removal system.

The DTT (Divertor Tokamak Test) facility is a new experimental tokamak under development by an Italian consortium in cooperation with several high-standard European laboratories. The ENEA division FSN-SICNUC is involved in the project for carrying out deterministic safety analysis of postulated accidents. In the first year of activity, it has been analyzed an In-Vessel LOCA (IVLOCA) scenario. The IVLOCA scenario selected is caused by a break in the divertor’s cassette cooling tubes with the consequent release of coolant inside the Vacuum Vessel (VV). The best estimate thermal-hydraulic system code TRACE, developed by USNRC, was selected to conduct the preliminary thermal-hydraulic analysis of this accident. DTT is currently under design, so not all the data are frozen. Therefore, based on some engineering assumptions and scaling considerations from similar facilities, the nodalization of DTT VV was developed using the three-dimensional TRACE component “VESSEL”. Then, a sensitivity analysis was carried out to simulate the break and the consequent water injection in the VV. This was done to compare the system behavior and test different nodalization approaches. Subsequently, the data of the DTT divertor cooling system were used to run additional simulations. The results allow to compare different nodalization approaches and to have a preliminary estimate of the pressure peak and temperature behavior in the VV for an IVLOCA. Finally, a first uncertainty analysis was carried out using the DAKOTA toolkit, coupled with TRACE code in SNAP. Two uncertain input parameters were selected: the rupture area of a cooling divertor tube and the temperature of the divertor coolant. The uncertainty analysis allows having a wider spectrum of system behavior and a preliminary insight on the dispersion of the VV pressure, selected as figure of merit. This paper aims to show the results of this preliminary analysis, characterizing the phenomena that occurred during the selected transient.

The Ingress of Coolant Event (ICE) in the plasma chamber is one of the safety issues in fusion nuclear plants. The best estimate thermal-hydraulic system codes adopted to perform deterministic safety analysis should be validated against the phenomena typical of accidental transients in fusion installations. TRACE (TRAC/RELAP Advanced Computational Engine), best estimate thermal-hydraulic system code developed by USNRC, has been adopted to simulate an ICE. The calculated results have been compared to the experimental data obtained in one test performed in the upgraded Integrated ICE facility at JAERI. In this updated configuration the pressure suppression system is connected to the top of the plasma chamber instead of the bottom of the vacuum vessel. The facility nodalization has been developed in the SNAP environment/architecture. To qualify the code and the nodalization, an accuracy evaluation has been performed both from a qualitative and quantitative point of view. Then, considering the presence of some uncertainties in the input-deck development, an uncertainty analysis has been carried out. The probabilistic method to propagate the input uncertainties has been selected and the analysis has been carried out with the DAKOTA toolkit coupled with TRACE code in SNAP. In the uncertainty analysis, some relevant statistical parameters have been considered to characterize the dispersion of the results and the correlation between the uncertain input parameters selected and the PC pressure chosen as figure of merit.

Almost 80 years ago, on December 2nd, 1942, the first nuclear plant (Chicago Pile-1) reached its first criticality in the secret context of the Manhattan Project. After the end of the second World War, the "Atoms for Peace" program supported the exploitation of nuclear energy for civil purposes. Therefore, nuclear power plants (NPP) based on different technologies started to be designed, constructed, and operated. The present chapter follows the history of NPP development from the early prototypes to the current days, considering the historical and socio-economic context and the major nuclear power accomplishments and accidents.

The EU-funded ELSMOR (Towards European Licencing of Small Modular Reactors) project seeks to design methods and tools for stakeholders to assess and verify Light Water SMRs’ safety when installed across Europe. Within the project, an experimental facility has been built at SIET (Piacenza, Italy) to test a passive heat removal system. The passive system is based on natural circulation, with a plate-type Compact Steam Generator (CSG) as heat source and an in-pool condenser as heat sink. An experimental campaign has been conducted to investigate the effect of different parameters on the passive system behavior (e.g. secondary side filling ratio, primary system temperature, pool level, presence of non-condensable gases, etc.). Among the various tests, ELSMOR test 00099_C has been selected to perform a code benchmark and ten parameters were selected for the code comparison. The chosen test explores the effect of the secondary side filling ratio from 60.16% to 24.96%. In the benchmark, the codes from the European reference chains have been applied, Apros by VTT, AC2 by GRS and CATHARE by CEA, and they have been compared with the results obtained with RELAP5 by ENEA and TRACE by PSI. In general, all the codes were able to predict the experimental data both from a qualitative and quantitative point of view. The main discrepancies have been observed in some results for the prediction of the secondary side pressure, secondary side CSG inlet temperature and secondary side flow rate.

Within the Best Estimate Plus Uncertainty framework for the safety analysis of Nuclear Power Plants, the quantification of the uncertainties affecting the Thermal-Hydraulics (T-H) codes used is crucial. For this, Inverse Uncertainty Quantification (IUQ) methodologies are being developed for determining the probability density functions of relevant T-H codes input parameters, based on experimental data from Separate Effect Tests (SETs) experimental facilities. In practice, IUQ is challenged by the large range of variability of the experimental data in terms of Initial and Boundary Conditions (ICs & BCs), because the experimental campaigns are designed to cover the widest possible domain of conditions with the smallest number of experiments, so that same or similar ICs and BCs are seldomly repeated. To address this issue, we propose to use global sensitivity analysis, to tailor the IUQ on specific sub-regions described by segmented ICs & BCs domains. The methodology proposed is exemplified on two SETs, namely Sozzi-Sutherland and Super Moby Dick, whose experimental databases have been made available in the ATRIUM (Application Tests for Realization of Inverse Uncertainty quantification and validation Methodologies in thermal hydraulics) project promoted by the OECD/NEA/CSNI. The results obtained are superior to those of traditional IUQ methodologies for models highly sensitive to ICs & BCs.

Uncertainty estimation to assess figures of merit characterizing evolution of a severe accident transient is a topic of current investigation in development of best-estimate plus uncertainty methodology. The probabilistic method to propagate input uncertainty is one of the methodologies used to develop Uncertainty Analyses (UAs). Using this methodology, UAs are performed by sampling probability distributions that describe the range of possible values that computer simulation model inputs can have. For each sample (or realization) of a set of uncertain input parameters, a computer simulation is performed. From the range of code simulation results obtained for each input realization, a distribution of code results is obtained. In this process, the distribution of input uncertainties is propagated to obtain a distribution of possible code results (i.e., the code output uncertainty). This probabilistic methodology is facilitated using Uncertainty Tools (UTs), which can be coupled with the accident analysis computer code to perform an UA. One of the UTs currently available is DAKOTA, developed by Sandia National Laboratories. DAKOTA is also provided as a SNAP plug-in. SNAP is a graphical user interface designed to support the use of USNRC codes (MELCOR, TRACE, etc). This paper is entirely derived from the NUREG/IA-532 issued by USNRC in April 2023 (Mascari et al., 2023) and has as a major target to summarize the main needs of UA in severe accident, the main element of the probabilistic method to propagate input uncertainty, and the workflow within SNAP to assist other interested analysts with their applications given they are members of the USNRC Cooperative Severe Accident Research Program (CSARP).

MELCOR is an integral code developed by Sandia National Laboratories (SNL) for the US Nuclear Regulatory Commission (USNRC) to perform severe accident analyses of Light Water Reactors (LWR). More recently, MELCOR capabilities are being extended also to analyze non-LWR fission technologies. Within the European MELCOR User Group (EMUG), organized in the framework of USNRC Cooperative Severe Accident Research Program (CSARP), an activity on the evaluation of the applicability of MELCOR 2.2 for fusion safety analyses has been launched and it has been coordinated by ENEA. The aim of the activity was to identify the physical models to be possibly implemented in MELCOR 2.2 necessary for fusion safety analyses, and to check if those models are already available in MELCOR 1.8.6 for fusion version, developed by Idaho National Laboratory (INL). From this activity, a list of modeling needs emerged from the safety analyses of fusion-related installations have been identified and described. Then, the importance of the various needs, intended as the priority for model implementation in the MELCOR 2.2 code, has been evaluated according to the technical expert judgement of the authors. In the present paper, the identified modeling needs are discussed. The ultimate goal would be to propose to have a single integrated MELCOR 2.2 code release capable to cover both fission and fusion applications.

In the last decades, taking into account the operational experience of fission nuclear reactors, the nuclear international technical community started the development of advanced reactor designs in order to satisfy the demand of the people to improve the safety of NPPs and to take into consideration the industry needs to improve the economic efficiency and reduce the capital costs of nuclear power technology. In this framework Small Modular Reactors (SMR) adopting light water as coolant, taking advantage of the experience developed in current larger scale LWR, can bring advantages in terms of increasing “inherent safety” due to the integral type configuration, lower nominal power, and the adoption of passive mitigation strategy. Starting from some of the research activities on code applications developed by the authors along the last decade, and available in the public scientific literature, the target of this paper is to give some insights and recommendations for the future development of new research activities, in national and international frameworks, in relation to thermal hydraulics of SMRs.