Phenomena Identification And Ranking Table Research Articles

Time-Series Forecasting of a Typical PWR Undergoing Large Break LOCA

In this work, a machine learning (ML) metamodel is developed for the time-series forecasting of a typical nuclear power plant response undergoing a loss of coolant accident (LOCA). The plant model of choice is based on the APR1400 nuclear reactor. The key systems and components of APR1400 relevant to the investigated scenario are modelled using the thermal-hydraulic code, RELAP5/MOD3.4, following the description published in the design control document. The model is tested under a spectrum of initial and boundary conditions via propagation of key uncertain parameters (UPs) which are derived from the phenomena identification and ranking table (PIRT). This is achieved by loosely coupling RELAP5/MOD3.4 with the statistical tool, Dakota. The most probable nuclear power plant (NPP) response was calculated using the best estimate plus uncertainty (BEPU) approach. Next, the database generated from the NPP system response was used as an input for the ML model. The NPP system response was represented by peak cladding temperature (PCT), safety injection system (SIT), mass flow rate, reactor power, and primary system pressure. In this research, two regression models were tested with reasonably good performance, namely, the gated recurrent unit (GRU) and the long short-term memory (LSTM).

Phenomena Identification and Ranking Table for Thermal-Hydraulic Safety of China Fusion Engineering Test Reactor

The China Fusion Engineering Test Reactor (CFETR) is presently in the engineering design phase, and it is crucial to establish a thermal-hydraulic safety analysis method. First of all, the identification of phenomena in selected accident scenarios affecting reactor safety performance metrics should be focused on with the phenomenon identification and ranking table (PIRT), in which phenomena related to the thermal-hydraulic safety of the vacuum vessel and related systems are screened, including both design-basis accidents and beyond-design-basis accidents. The development of this PIRT exercise for CFETR thermal-hydraulic safety is addressed in this study; specifically, the importance ranking and stage of knowledge (SoK) of phenomena in the selected accidents are evaluated by the PIRT panel. The results of the PIRT analysis revealed that there exist certain safety-critical phenomena for which SoK is relatively low despite their perceived significance in safety performance metrics, which include the phase change of coolant, the migration of the multicomponent gas mixture, the migration of radionuclides within confinement, and the dispersion of gaseous radionuclides in the atmosphere. Ongoing research works and follow-up plans to improve the SoK of phenomena are presented.

Experiment and new analysis model simulating in-place cooling of a degraded core in severe accidents of sodium-cooled fast reactors

In severe accidents of SFRs, the cooling of the residual core materials, which is called “in-place cooling”, is one of the important factors for In-Vessel Retention (IVR). For the evaluation, behavior of the in-place cooling was analyzed by the SIMMER-III code. In order to understand the in-place cooling, method of Phenomena Identification and Ranking Table (PIRT) was applied. Based on the result, an out-of-pile experiment which focused on the extracted factors was conducted. In the experiment, continuous oscillation of sodium level was observed by sodium vaporization and condensation. Analysis for the out-of-pile experiment was conducted by SIMMER-III, but the results were different between the experiment and the analysis. By investigation of the analysis result, it was revealed that the difference was due to occupation of non-condensable gas. Therefore, an analysis model of inter-cell gas mixing was newly developed, and the agreement was significantly improved by the new model.

Phenomena identification Ranking Table (PIRT) study for suppression containment of small modular reactor using new methodology

The Phenomena Identification and Ranking Table (PIRT) is a significant method for analyzing the safety of nuclear reactors. It helps researchers identify important phenomena within the reactor, enabling a focused and appropriate simplification of accident scenarios during the study. However, traditional PIRT methods often rely on experts' subjective opinions to rank phenomena’ importance and knowledge level, potentially distorting the PIRT results. This paper proposes a new PIRT method inspired by literature evaluation techniques used in the medical and healthcare field, which can be more objective. This new method utilizes a literature evaluation framework instead of relying solely on expert judgments, resulting in a more objective assessment of the phenomena’ importance and knowledge level. This study applies the new method to a simplified small modular reactor with a suppression containment system. Following a Loss of Coolant Accident (LOCA), the suppression containment can effectively suppress temperature and pressure increases, ensuring containment integrity. Relevant PIRT tables and a knowledge-level structure are obtained using the new method.

OECD/NEA R&D priorities for loss-of-cooling and loss-of-coolant accidents in Spent-Fuel-Pools

Motivated by the 2011 accident at the Fukushima Daiichi Nuclear Power Station, the Nuclear Energy Agency (NEA) Committee on the Safety of Nuclear Installations (CSNI) of the Organisation for Economic Cooperation and Development (OECD) launched several activities with the aim to support the post-Fukushima accident decision making process. One of these activities, discussed in the present paper, consisted in the production of a Phenomena Identification and Ranking Table (PIRT) in order to systematically highlight Spent-Fuel-Pool (SFP) accident-related phenomena that are of both high importance and high uncertainty, and thus of primary interest for further experimental or modeling activities. For that purpose, an international panel of experts identified and ranked more than a hundred physical phenomena with regard to their safety importance and current level of knowledge. Altogether eighteen unique phenomena were identified as having priority research needs. About half of these phenomena are related to thermal-hydraulics and heat transfer in the SFP, and they are judged to be important to the coolability of the spent fuel in loss-of-cooling and/or loss-of-coolant accidents. The other half comprises fuel-related phenomena such as fuel volatilization, cladding oxidation in mixed steam–air environment and nitrogen-assisted oxide breakaway at moderate temperature, judged as important and poorly modeled in the scope of SFP accidents. The final part of the paper discusses the research programmes performed on Spent Fuel Pool loss-of-cooling and loss-of-coolant accidents since the publication of the PIRT report in 2018 and the remaining R&D needs.

Developing PCC and DCC integral effects test experiments at the High Temperature Test Facility

Among the Next-Generation Nuclear Plant (NGNP) designs, the High-Temperature Gas-Cooled Reactors (HTGRs) are very attractive, due to their inherent safety features, high power conversion efficiency, and potential of providing high-temperature process heat. To perform a thorough safety study and to license these types of reactors, sufficient information needs to be provided about the phenomena that occur during accident scenarios. While several experimental research efforts have been dedicated in the past to investigate accident scenarios, knowledge gaps still exist in the phenomena characteristic of pressurized and depressurized conduction cooldown (PCC/DCC) transients as well as for normal operation scenarios. This paper summarizes the Oregon State University High Temperature Test Facility (HTTF) test matrix, experimental campaign, and selected tests results. High Temperature Test Facility is a scaled Integral Test Facility (IET) that is capable of mimicking scaled dimensions and operational conditions of the Modular High-Temperature Gas Cooled Reactor (MHTGR). The goal of the High Temperature Test Facility is to provide experimental data on the DCC, PCC and normal operating scenarios of the reference Modular High-Temperature Gas Cooled Reactor design. The DCC, PCC, mixing, heat up and cooldown tests described in this paper were performed at prototypical Modular High-Temperature Gas Cooled Reactor temperatures, scaled initial pressure conditions (∼200 kPa), and thermal power input of less than 70 kW. Presented test data show temperature distributions in the High Temperature Test Facility core, upper plenum, cross duct, or lower plenum. Based on these temperature profiles attempts to investigate stratified flow, natural convection flow, heat up, cooldown and mixing phenomena are made. Furthermore, this paper evaluates the performed test campaign in the light of the Very High Temperature Gas-cooled Reactor Phenomena Identification and Ranking Table (PIRT) and proposes experiments to complement the existing PCC/DCC testing database for the validation of the thermal-hydraulic codes.

Uncertainty and Sensitivity Analysis of Hydrogen Source Term under Severe Accident of Marine Reactor

In order to explore the hydrogen source term characteristics under severe accidents of marine pressurized water reactors (PWR) and effectively assess the hydrogen risk, the best estimation program SCDAP/RELAP5/MOD3.2 is used to establish the marine reactor severe accident analysis model. Based on the Latin Hypercube sampling (LHS) method and the Wilks sampling theory, a set of methods for the uncertainty analysis of severe accidents is developed. This method can be applied to the uncertainty and sensitivity analysis of different target parameters. The phenomenon identification and ranking table (PIRT) under the severe accident induced by the break are established, and 14 uncertain parameters are selected as input variables. The established PIRT fills the gap in the uncertainty and sensitivity analysis of severe accidents of marine reactors and provides a reference for subsequent research. The quantitative uncertainty analysis of the calculation results is carried out, and the uncertainty range of hydrogen production is defined. The Spearman correlation coefficient is used to evaluate the sensitivity of input parameters, and the sensitivity of each parameter to hydrogen production is obtained. The results show that under the severe accident caused by the medium equivalent diameter break, the uncertainty range of hydrogen production in the zirconium–water reaction in the pressure vessel is 20.14 kg~22.19 kg with 95% confidence, and the fuel cladding thickness has a significant positive correlation on the hydrogen production.

Coupled simulations for prismatic gas-cooled reactor

The development and deployment of gas-cooled reactors (GCRs) require flexible modelling and simulation tools for a detailed understanding of the system behavior in normal operation and accidental scenarios. Amongst the identified safety-relevant scenarios for the gas-cooled reactors, outlet plenum flow distribution during normal operations was ranked to be of high importance with a low knowledge level in the phenomenon identification and ranking table (PIRT). The present paper contributes to the development of accurate simulation models using stand-alone and coupled codes for the GCR lower plenum region, which are needed to address nuclear reactor safety issues early enough so that delays in licensing and facility construction can be minimized. For the first time in this paper, an assessment of the predictive capabilities of coupled system-thermalhydraulics and CFD codes against heat transfer measurements in the lower plenum of a prismatic block GCR is reported. The lower plenum mixing experiments of the integral high temperature test facility at the Oregon State University (OSU HTTF) were simulated in the stand-alone and coupled mode to predict the lower plenum mixing. The coupled-code analysis used a 3D CFD code STAR-CCM + and a 1D thermalhydraulics code RELAP5-3D to account for system-level feedback on the flow and heat transfer for lower plenum mixing occurring during the normal operation at the reduced power and/or mass flow rate. For one of the simulated OSU test conditions, the existing models in STAR-CCM + and RELAP5-3D predicted the measured core temperatures reasonably well at two different elevations, suggesting that the available models are adequate for such an analysis. Through this study, a better understanding of the suitability of the models in the CFD and system thermalhydraulics (TH) codes is gained for more accurate prediction of flow and heat transfer in GCRs in anticipation of the eventual need to perform safety and licensing analyses.

Mapping thermal energy storage technologies with advanced nuclear reactors

Advanced nuclear power plants (NPPs) will potentially need to operate in environments where power generation flexibility is more highly valued than the stability or baseload generation capability for conventional demand curves. Thermal energy storage (TES) systems would enable NPPs to respond nimbly to market variability and could also position advanced NPPs to participate differently in restructured markets, thus further enhancing their economic competitiveness. TES systems could also benefit the electric grid by eliminating the need for peaking plants, as well as by improving the economic performance of baseload NPPs. While TES technologies afford a unique opportunity to address many of these challenges, the applicability of these systems is also complicated by the fact that various advanced NPPs are designed differently, each with its own temperature range, size, operating fluids, and operating conditions. Hence, TES systems face significant barriers to investment, as more information on their compatibility and performance metrics is needed to quantify the advantages provided by each, as well as the challenges these technologies might face if coupled with a particular type of advanced NPP. This study explores the possibility of integrating a wide variety of TES technologies with various categories of advanced NPPs, based on their operating characteristics. To help decision makers, users and developers decide which TES technology is best suited to a particular category of advanced NPPs, this research present a Phenomena Identification and Ranking Table (PIRT) analysis of 10 TES systems that could potentially be coupled with advanced NPPs, which themselves are divided into nine categories based on their operating conditions. Each advanced NPP category is evaluated for compatibility with the 10 TES systems by assembling and discussing a database of information concerning 10 engineering questions, defined herein in as figures of merit (FOMs), such as: technology readiness level (TRL), temperature compatibility, energy density, size, cycle frequency, ramp time, realignment frequency, geographic needs, environmental impact, and interventions. By assembling a database of information concerning the TES technologies’ compatibility with various advanced NPP systems, this study can help developers acquaint themselves with a particular TES technology before choosing to build a new integrated installation.

International case survey and literature review of maintenance strategy for decommissioning nuclear power plant during transition period

The Chinshan nuclear power plant in Taiwan has currently shutdown when the operating license expired in 2018. However, because the operation license of the independent spent nuclear fuel dry storage facility has not been approved yet, and the fuel storage racks of Spent Fuel Pool (SFP) has almost saturated, there is not enough space to accommodate all irradiated fuels from the reactor core during the transition period. Therefore, part of the mechanical systems, plant structures and electrical equipment of the plant still have to meet the functional requirements for maintaining the safety under the pre-decommissioning activities.In this article, we introduce the international cases of permanent shutdown but the fuel still in the reactor core, and also describe the actions of the Taiwan Power Company in response to this situation. For the providing regulatory advice, we have also proposed a framework of the maintenance strategy associated with important issues for the transition period since 2018, including a revised Aging Management Program (AMP) for keeping the safety of spent nuclear fuel. From the knowledge level and important issues related to the topic, the Phenomena Identification and Ranking Table (PIRT) is quoted to complete the understanding level of requirements during the transition period.

Aerosol pool scrubbing phenomena during the containment depressurization venting. Part I: Scaling analysis

For the Chinese Advanced Passive Pressurized Water Reactor, one of the possible containment depressurization measures is to discharge to the Spent Fuel Pool (SFP) during severe accidents. During containment depressurization venting process, carrier gas with aerosol is injected into the SFP from the containment through a discharge sparger. To obtain the aerosol retention effect during this process, a scaled-down test facility have been designed and built. In this paper, the Phenomena Identification and Ranking Tables (PIRT) in the discharge pipe and the SFP is developed. Then, based on the Hierarchical Two-tiered Scaling analysis (H2TS) method, the scaling analysis of SFP scrubbing phenomena is completed. A jet flow model and a particle retention model are developed to analyze these important phenomenon, and a series of similarity criteria are obtained. Based on these similarity criteria, the CASSI test facility is designed, and the scaling rationality is evaluated.

Using Machine Learning to Predict the Fuel Peak Cladding Temperature for a Large Break Loss of Coolant Accident

In this paper the use of machine learning (ML) is explored as an efficient tool for uncertainty quantification. A machine learning algorithm is developed to predict the peak cladding temperature (PCT) under the conditions of a large break loss of coolant accident given the various underlying uncertainties. The best estimate approach is used to simulate the thermal-hydraulic system of APR1400 large break loss of coolant accident (LBLOCA) scenario using the multidimensional reactor safety analysis code (MARS-KS) lumped parameter system code developed by Korea Atomic Energy Research Institute (KAERI). To generate the database necessary to train the ML model, a set of uncertainty parameters derived from the phenomena identification and ranking table (PIRT) is propagated through the thermal hydraulic model using the Dakota-MARS uncertainty quantification framework. The developed ML model uses the database created by the uncertainty quantification framework along with Keras library and Talos optimization to construct the artificial neural network (ANN). After learning and validation, the ML model can predict the peak cladding temperature (PCT) reasonably well with a mean squared error (MSE) of ∼0.002 and R2 of ∼0.9 with 9 to 11 key uncertain parameters. As a bounding accident scenario analysis of the LBLOCA case paves the way to using machine learning as a decision making tool for design extension conditions as well as severe accidents.

Phenomenon Identification and Ranking Table Development for Future Application Figure-of-Merit Studies on Thermal Energy Storage Integrations with Light Water Reactors

There are no standard prioritization criteria for evaluating thermal energy storage (TES) options for use in integrated energy systems. A framework for proposing, analyzing, and presenting energy storage integration with power producers and users is presented along with a specific figure-of-merit (FOM) study based in this framework. This basis for evaluating storage technologies can provide a structure for the energy industry to analyze and prioritize energy storage in different applications and environments. The phenomena identification and ranking table (PIRT) presents a series of design questions specific to energy storage applications. The FOM study, built in this PIRT framework based on a nuclear-renewable hybrid energy system using TES to produce power and provide process energy for a secondary user, successfully identified specific technologies to use based on the project requirements. Expanding the library of projects using this framework will expand the deployable options for energy storage and increase its potential for energy security.

Liquid spray modeling under sodium fire accidents

The Sodium-Cooled Fast Reactor (SFR) system, which features a fast-spectrum, sodium-cooled reactor and a closed fuel cycle for efficient management of actinides and conversion of fertile uranium, is rather prominent in the nuclear reactor design in Generation IV (Gen IV), and likely to be widespreadly used and well-constructed all over the world. However, molten sodium may be sprayed into the ambient or secondary side of steam generator, induced by the pressure drop, in case of an inevitable break in the primary system. This kind of leakage can result in sodium spray fire accident, as a result of the chemical activity of sodium, significantly damaging the equipment and working staffs nearby. Sodium spray fire, which occurs not only in the nuclear industry, but also in solar industry, is a complex process consisting of several specific phenomena, such as the spray dynamics (e.g. droplet particle size/velocity distribution, particle collision and agglomeration), droplets evaporation, sodium aerosol diffusion, thus being drawn many experts’ attention. Based on International Atomic Energy Agency (IAEA)’s effort on phenomena identification and ranking table (PIRT) for sodium spray fire, prediction of droplet size distribution and the mean diameter in particular, are supposed to be in the very first place at level 2, due to the lack of available experimental data for both of model development and validation, and code inadequacy, as well. In this paper, sodium droplet size distribution model is theoretically derived, regarding both of mass and momentum equations as constraints, based on the maximum entropy principle, which can quantitatively describe the effects of two main influencing factors, including initial injection velocity and thermophysical properties of molten sodium. This analytical model is implemented in three typical conditions, including two sodium droplets size distribution experiments and one water droplet experiment. Validations against both of the available test data and predictions by an empirical model, named of Nukiyama-Tanasawa correlation, are conducted with the relative error of median diameter ranging from 17.3% to 18.2%, which ensures the reliability and feasibility of the new model. Moreover, sensitivity analyses are carried out, in terms of typical test conditions of sodium spray fire, which demonstrates that the median diameter of droplets’ size decreases with both of the increase of initial injection velocity and sodium temperature, thus probable triggering positive effect on the propagation of the accident, due to rapid interaction of violent chemical reaction and sodium spray. Besides, the present work can provide a reliable analytical model for the development of safety analysis codes for SFRs.

Challenges and opportunities in verification and validation of low temperature plasma simulations and experiments

This paper describes the verification and validation (V&V) framework developed for the stochastic Particle-in-Cell, Direct Simulation Monte Carlo code Aleph. An ideal framework for V&V from the viewpoint of the authors is described where a physics problem is defined, and relevant physics models and parameters to the defined problem are assessed and captured in a Phenomena Identification and Ranking Table (PIRT). Numerous V&V examples guided by the PIRT for a simple gas discharge are shown to demonstrate the V&V process applied to a real-world simulation tool with the overall goal to demonstrably increase the confidence in the results for the simulation tool and its predictive capability. Although many examples are provided here to demonstrate elements of the framework, the primary goal of this work is to introduce this framework and not to provide a fully complete implementation, which would be a much longer document. Comparisons and contrasts are made to more usual approaches to V&V, and techniques new to the low-temperature plasma community are introduced. Specific challenges relating to the sufficiency of available data (e.g., cross sections), the limits of ad hoc validation approaches, the additional difficulty of utilizing a stochastic simulation tool, and the extreme cost of formal validation are discussed.

Phenomena identification and ranking table of station blackout accidents for China sodium cooled fast reactor

In order to satisfy analysis of safety requirements for China pool type sodium-cooled fast reactor, a phenomena identification and ranking table (PIRT) is developed for station blackout (SBO) accidents by 15 experts. The SBO accidents could be divided into two phases, i.e. phase 1: force circulation and phase 2: natural circulation, and the most important phenomena but maximum disagreements among experts are the gap conductance model between fuel and clad, the inter wrapper flow, the heat transfer between coolant and inter wrapper. Those phenomena should be carefully assessed and done more theorical and experiment analysis to develop more accurate and realistic model, to reduce uncertainty of safety analysis. The PIRT could be also used for developing verification and validation matrix for thermal hydraulic safety code, guiding researchers and designers to conduct experiments to close technological gap and giving related researcher and designer a comprehensive understanding for pool-type sodium-cooled fast reactor.

Assessment of the Predictive Capability of VERA—CS for CASL Challenge Problems

Abstract This paper describes the process for assessing the predictive capability of the Consortium for the advanced simulation of light-water reactors (CASL) virtual environment for reactor applications code suite (VERA—CS) for different challenge problems. The assessment process is guided by the two qualitative frameworks, i.e., phenomena identification and ranking table (PIRT) and predictive capability maturity model (PCMM). The capability and credibility of VERA codes (individual and coupled simulation codes) are evaluated. Capability refers to evidence of required functionality for capturing phenomena of interest while credibility refers to the evidence that provides confidence in the calculated results. For this assessment, each challenge problem defines a set of phenomenological requirements (based on PIRT) against which the VERA software is evaluated. This approach, in turn, enables the focused assessment of only those capabilities that are relevant to the challenge problem. The credibility assessment using PCMM is based on different decision attributes that encompass verification, validation, and uncertainty quantification (VVUQ) of the CASL codes. For each attribute, a maturity score from zero to three is assigned to ascertain the acquired maturity level of the VERA codes with respect to the challenge problem. Credibility in the assessment is established by mapping relevant evidence obtained from VVUQ of codes to the corresponding PCMM attribute. The illustration of the proposed approach is presented using one of the CASL challenge problems called chalk river unidentified deposit (CRUD) induced power shift (CIPS). The assessment framework described in this paper can be considered applicable to other M & S code development efforts.

Development of phenomena identification and ranking table for Westinghouse lead fast reactor's safety

The Westinghouse Lead-cooled Fast Reactor (LFR) is a medium-size, passively safe, economic, Gen-IV nuclear reactor. An important effort within the Westinghouse LFR program is the development of the safety analysis methodology, which comprises computer code development, model development, and experimental testing. A key initial task associated with the development of the safety analysis methodology is the identification of processes and phenomena that affect the plant's capability to meet selected safety performance indicators. This is accomplished through the development of a Phenomena Identification and Ranking Table (PIRT) for selected accident scenarios which, for this specific PIRT effort, included selected postulated design basis accidents and hypothetical beyond design basis accidents in LFRs.This paper describes the role of PIRT in the development of the Westinghouse LFR safety analysis methodology and the process used in the PIRT development. Specifically, the Westinghouse LFR PIRT assessed importance of pertinent phenomena and identified gaps in their knowledge-base by evaluating current modeling capabilities and data available for validation. The ultimate goal was to provide guidance on computer code development and validation efforts and to prioritize testing to support LFR design and licensing. The key phenomena and processes that are deemed highly important for the safety performance indicators, but for which the state of knowledge is low, are presented. The testing program and analyses development are planned to address significant phenomena in the PIRT.

Study on dominant aspects of unprotected loss-of-flow to be evaluated in the initiating phase for a sodium-cooled fast reactor

ABSTRACT SAS4A is presently the worldwide standard computer code for simulation of the initiating phase of the Core Disruptive Accident (CDA) in MOX-fueled Sodium-cooled Fast Reactors (SFR). In order to improve the capability of the computational code, SAS4A, to be applied to the safety assessment for SFRs, detailed investigations of physical phenomena under unprotected loss-of-flow (ULOF) conditions were conducted, and physical models to be developed and improved were identified using the Phenomena Identification and Ranking Table (PIRT) method. A fuel stub motion, in which the residual fuel pellets would move to the core central region after fuel pin disruption, was selected as one of the key phenomena to be simulated properly and a key concept of the fuel stub motion model was presented.

Adequacy evaluation of smoothed particle hydrodynamics methods for simulating the external-flooding scenario

In modern nuclear risk analysis for external-flooding scenarios, Computational Fluid Dynamics (CFD) tools are used to simulate the generation, propagation, and interactions of Nuclear Power Plants (NPPs) with the nuclear Systems, Structures, and Components (SSCs). Smoothed Particle Hydrodynamics (SPH), as a Lagrangian and mesh-free method, is one of the particle-based CFD methods. Since SPH methods can effectively handling large-scale fluid simulations with complex interfacial structures, SPH-based software has been used to simulate the impacts of external flood onto nuclear facilities, and the simulation results have been used to support nuclear safety analysis. However, previous risk analysis assumes that SPH methods and the corresponding simulation packages are applicable to the external-hazards risk analysis, and their simulation uncertainties do not affect the confidence of safety decision. Considering the high consequences to nuclear safety induced by simulation errors, a systematic and complete validation process is needed to evaluate the adequacy of SPH simulations in informing related safety decisions.In this study, a scoping-stage assessment is performed for SPH’s adequacy in simulating the real-scale external flooding scenarios, especially in predicting the surface-wave impacts on SSCs at NPP sites. To ensure the completeness and consistency, validation frameworks, Code Scalability Applicability and Uncertainty (CSAU), and its regulatory guide, Evaluation Model Development and Assessment Process (EMDAP) are followed to guide validation activities and to make final code adequacy assessment. First, an external-flooding scenario is designed, and SPH simulations are performed with an SPH-based software named Neutrino. A Phenomenon Identification and Ranking Table (PIRT) is created, and the surface-wave impacts are identified as one of the high-rank phenomena. At the same time, a performance measurement standard is created for measuring the code adequacy in informing safety decisions consistently and transparently. Next, numerical benchmarks are designed for assessing the code adequacy of SPH methods and corresponding software implementations on Neutrino. Next, code accuracy is evaluated by comparing simulation results from Neutrino against experimental measurements in each benchmark. Meanwhile, a scaling analysis is performed to determine a group of dimensionless number for characterizing important physics and to assess the applicability of validation database collected in reduced-scale facility to the prototypic scenario. Finally, results from all activities are brought together to make an adequacy decision. It is found that, based on the current evidence, SPH methods and associated Neutrino software can predict the unbroken surface-wave peak pressure onto stationary rigid with reasonable accuracy if the suggested sizes of particles are used. However, it is suggested by independent reviews that the validity of major assumptions in target applications need to be evaluated with large-scale experiments, and the relevancy of other phenomena like turbulence and air pockets need to be identified with more benchmarks. As for the SPH’s adequacy in predicting the impact forces on dynamic rigid, the available evidence is not sufficient to support the decisions.