Accident Scenarios Research Articles

Gas phase interactions between tellurium and organic material in severe nuclear accident scenarios

One of the volatile fission products potentially released during a severe nuclear accident is tellurium. Recently, tellurium has been shown to form volatile organic tellurides from paint solvents in aqueous solutions which could further increase the release. However, not much is known about the possible interactions between tellurium and organic material in gas phase. In this study, tellurium was exposed to conditions simulating the containment atmosphere during an accident. Moreover, volatile organic compounds were introduced to the gas phase representing the presence of organic material in the containment during the accident. The results suggest that tellurium aerosols and organic material interact in the gas phase which was observed as an increase in the gaseous fraction and a change in the XPS spectra. Although no exact species were identified, the results raise questions about the behavior of tellurium in severe accident conditions, especially, regarding the reactions involving organic material.

Realistic performance assessment of FeCrAl-UN/U3Si2 accident tolerant fuel under loss-of-coolant accident scenario

The rigorous safety requirements in the nuclear industry have necessitated the development of accident tolerant fuels, with FeCrAl-UN/U3Si2 being one of the latest innovations in this field. To comprehensively evaluate the performance of this fuel type under accident scenarios, the best estimate plus uncertainty method is employed to conduct a realistic safety assessment of a large break loss-of-coolant accident in the HPR-1000 nuclear power plant using FeCrAl-UN/U3Si2 fuel. The peak cladding temperature and peak pellet temperature are selected as figures of merit, while the uncertainties of key performance models for the FeCrAl cladding and UN/U3Si2 pellet are quantified. The upper tolerance limits of the two figures of merit are determined through uncertainty propagation calculations, and the key influencing parameters are also identified based on the sensitivity analysis. Results demonstrate that the FeCrAl-UN/U3Si2 fuel type owns larger safety margin than the conventional Zr-UO2 fuel type and effectively reduces the cladding temperature while significantly reducing oxidation and hydrogen production during the accident.

Public perception of autonomous vehicle capability determines judgment of blame and trust in road traffic accidents

Road accidents involving autonomous vehicles (AVs) will not only introduce legal challenges over liability distribution but also generally diminish the public trust that may make itself manifested in slowing the initial adoption of the technology and call into question the continued adoption of the technology. Understanding the public’s reactions to such incidents, especially the way they differentiate from conventional vehicles, is vital for future policy-making and legislation, which will in turn shape the landscape of the autonomous vehicle industry. In this paper, intuitive judgments of blame and trust were investigated in simulated scenarios of road-traffic accidents involving either autonomous vehicles or human-driven vehicles. In an initial study, five of six scenarios showed more blame and less trust attributed to autonomous vehicles, despite the scenarios being identical in antecedents and consequences to those with a human driver. In one scenario this asymmetry was sharply reversed; an anomaly shown in a follow-up experiment to be dependent on the extent to which the incident was more likely to be foreseeable by the human driver. More generally these studies show—rather than being the result of a universal higher performance standard against autonomous vehicles—that blame and trust are shaped by stereotypical conceptions of the capabilities of machines versus humans applied in a context-specific way, which may or may not align with objectively derived state of affairs. These findings point to the necessity of regularly calibrating the public’s knowledge and expectation of autonomous vehicles through educational campaigns and legislative measures mandating user training and timely disclosure from car manufacturers/developers regarding their product capabilities.

A machine learning diagnosis of the severe accident progression

A Machine Learning (ML) platform is proposed to assist the operator in diagnosing the severe accident progression, where some of the signal is corrupted, and/or estimation of key parameters for accident management is needed. To predict the key parameters for accident management such as lost signals for the pressure and core water level, the amount of hydrogen generation, and the mass of nuclear aerosols, a Machine Learning (ML) platform with long short term memory (LSTM) network is proposed, where multiple accident scenarios can be accumulated and used for training. Training and test data were produced by MELCOR simulations of the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident at unit 3. The MELCOR simulation data is presented as time series at equal intervals. Feature variables were selected among many plant parameters, where the importance ranking was determined by a recursive feature elimination technique using RandomForestRegressor. We performed a sensitivity study of the different choices of training and test scenarios, the number of feature variables, the number of neurons, and target variables on the prediction accuracy of the ML platform. Among eight MELCOR simulation results, different combinations of training and test data are selected in terms of similarity between them. It is found that when the number of feature variables is more than five, the proposed ML platform was able to predict not only similar test data but also unseen test data with reasonable accuracy. It is also found that the proposed ML platform consistently predicts any of the lost signals and key parameters for accident management with reasonable accuracy. Pre-trained ML model predicted the target variable within several minutes on a desktop computer.

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.

Iodine source term assessment under DBA SGTR accident scenario

In the framework of the European project denominated Reduction of Radiological Consequences of design basis and design extension Accidents (R2CA), application of Best Estimate advanced codes for evaluating the radiological release under Design Basis Accident and Design Extended Conditions was considered. The aim is to assess the current modelling capabilities and to propose new calculation methodologies in order to produce more realistic evaluations of radioactive releases resulting from such accidents.In this paper, the studies are conducted for a reference Design Basis Accident Steam Generator Tube Rupture scenario in a 3-loop PWR-1000 reactor in terms of key thermal–hydraulic and radiological variables that condition and characterize the fission product release to the environment. The assessment includes a comparative study of the results performed by three organisations using three different computational tools and approaches. The outcomes highlighted issues considered for the design basis evaluation, modelling differences as well as some challenges and limitations in carrying out such analysis.

Strategic analysis on sizing of flooding valve for successful accident management of small modular reactor

In contrast to all-time flooded small modular reactor (SMR) systems, an in-kind flooding safety system (FSS) has been proposed as a passive safety system applicable to small modular reactors (SMRs) that adopt a metal containment vessel (MCV). Under transient conditions, the FSS can provide emergency cooling to dry reactor cavities and sustain long-term coolability using re-acquired evaporated steam in the reactor building on demand. When designing an FSS, the effect of the flooding flow area is vital as it affects the overall accident sequence and safety. Therefore, in this study, a MELCOR model of a reference SMR is developed and numerical analysis is performed under postulated accident scenarios. Without flooding, the MCV pressure of the reactor module exceeds the design pressure before core damage. To prevent core damage, an emergency flooding strategy is devised using various flow path parameters and requirements to ensure an adequate emergency coolant supply before the core damage is investigated. The results indicate that a flow area exceeding 0.02 m2 is required in the FSS to prevent MCV overpressure and core damage. This study is the first to report a strategic analysis for appropriately sizing an FSS flooding valve applicable to innovative SMRs.

Screening of accident scenarios of hydrogen refueling stations based on HyRAM+ and Latin hypercube sampling

Due to the boom in hydrogen energy, risk assessment for hydrogen refueling station (HRS), which is as an infrastructure to supply hydrogen energy, is increasingly important. It is also crucial to screen out accident scenarios with low probabilities and low harms. This study theoretically focuses on an accident scenarios screening method for HRS based on Hydrogen Plus Other Alternative Fuels Risk Assessment Models (HyRAM+) and Latin hypercube sampling (LHS). According to the unit division of process flow in HRS, accident scenarios were preliminarily screened by accident consequence frequencies and maximum leakages. By comparing credible factor C and Potential Loss of Life (PLL), accident scenarios were screened secondly to obtain maximum credible accident scenario (MAS). The uncertainties of hydrogen leak, leak isolation, ignition possibilities, and the occupant positions were considered using LHS method for accident consequence frequencies and PLL. The assessment results for one HRS indicate that consequence frequencies of jet fire and explosion may be underestimated by HyRAM+. Moreover, MASs of jet fire and explosion were determined by complete rupture of the pipeline of the hydrogen compressor unit and explosion has a more significant impact on property loss than jet fire.

A high-fidelity biomechanical modeling framework for injury prediction during frontal car crash

Injuries arising from car crashes are ubiquitous across the globe and account for over 1.3 million fatalities annually. 93% of mortalities are observed in middle- and low-income countries owing to the lack of infrastructure in the safety assessment of car designs. It is therefore imperative to predict the extent of injuries to the occupants during car crashes, which would lead to safer vehicle design. To date, conventional computational testing methods use Hybrid III dummies, which fail to reproduce fracture and tear injuries. In this work, a full-frontal collision of a vehicle against a rigid wall with a highly biofidelic human body model of an occupant was simulated for the first time to investigate fractures and tears using a novel fracture modeling technique. Fractures were observed in ribs (5–7), which occurred at stresses of 120 MPa at the left lateral vertebrosternal region. In the lower extremity, tears in the ligaments at 70.80 MPa, and fractures in the tibia and femur at 236 MPa were quantified. Stresses in the skull were limited to 11 MPa, indicating a possibility of concussion rather than fractures. The developed computational model would be indispensable for car manufacturers to test the crash impact on the human body at all possible accident scenarios accurately, which will help design better solutions for automotive injury mitigation.

Risk Assessment of Domestic Wastewater Treatment System Based on Constructed Wetlands

Risk assessment methods vary and have been applied to areas such as environmental, technological, and occupational safety, adapting to the complexities of the subjects under study. The objective of this work is to conduct a risk analysis of a domestic wastewater treatment system based on constructed wetlands (CW) and to evaluate actions to reduce the operational risk of the studied installation. The approach used is the three-dimensional risk matrix, which is a simplified version of the probabilistic risk evaluation method, making it more accessible and allowing for broader application. To apply the risk matrix method to a wastewater system based on CW, it was necessary to modify a risk model. This modification involved creating a process map and identifying accidental scenarios or sequences within each stage, including their initiating events, defenses, and consequences. The results enabled the identification of the most critical initiating events and defenses. Notably, human factors emerged as the primary contributors to the risk associated with wetland operation. The findings from this study can be used to enhance wetland security, including the prioritization of controls for the most critical defenses identified in this research.

Reactivity-initiated accidents in two pressurized water reactor high burnup core designs

This paper presents a safety analysis of two proposed core loadings for 24-month Pressurized Water Reactor (PWR) fuel cycles. This analysis focuses on reactivity-initiated accidents (RIAs) and evaluates core safety performance impacts of rod-averaged burnup limits up to 75 GWD/MTU and less than 7 % enriched UO2. The capabilities of Polaris, PARCS, and RELAP5-3D are leveraged to evaluate the core neutronic and thermal–hydraulic behavior for normal-operation, uncontrolled control rod withdrawal (CRW) transients, and control rod ejection (CRE) accidents. The two core designs are compared to identify features of realistic high burnup/extended enrichment core design approaches which have significant safety impact, identify experimental data needs for high-fidelity predictive modeling, and provide recommendations for future high burnup core designs. The first core design evaluated in this study was developed by Southern Nuclear Company and used an ZrB2 Integral Fuel Burnable Absorber (IFBA) and B4C Wet-Annular Burnable Absorber (WABA)-based burnable poison strategy. The second core design assessed in this work used a Gd2O3-doped UO2 burnable poison, similar to that used in boiling water reactors or French PWRs. Results indicate that fuel thermal limits are maintained for limiting CRW and hot full power (HFP) CRE transients. Cladding failure is predicted for the highest energy deposition rods in each core during limiting hot zero power (HZP) CRE accidents (where maximum radially averaged enthalpy exceeds 120 cal/g), though licensing may be permissible with a limited number of failed rods. While concerns exist regarding high critical boron concentration during steady state for the IFBA core and large plenum pressures for the gadolinia core design, the analysis demonstrates adequate safety performance during limiting RIA accident scenarios for two representative high burnup core designs. Design changes limiting plenum pressures and implementation of accident tolerant fuel (ATF) cladding features which minimize hydriding and susceptibility to pellet-cladding mechanical interaction (PCMI) are recommended for future high burnup fuel concepts. To support the technical basis for burnup limit increases, high-fidelity fuel performance models are needed to address physical effects not considered in this analysis, and high burnup irradiated fuel tests are required to extend applicability of the fuel failure limits and validate existing and future models.

A Whole-Core Transient Thermal Hydraulic Model for Fluoride Salt-Cooled Reactors

Abstract A thermal hydraulic model is developed for a solid pin-fueled fluoride-salt-cooled small modular advanced high temperature reactor (SmAHTR). This preconceptual SmAHTR was developed by the Oak Ridge National Laboratory (ORNL). For the fuel assembly configuration investigated in this study, the fuel and non-fuel pins are arranged in a hexagonal layout. The molten FLiBe salt coolant flows parallel to the bank of pins. A finite volume model is developed and used to compute temperatures in the solid regions (fuel and non-fuel pins, and the graphite reflectors) in the core. The temperature, flow, and pressure profiles for the coolant flowing through the pin bundles in the core are calculated using the conventional subchannel methodology. Pertinent closure relations are used to compute the hydraulic losses, momentum, and energy exchange between adjacent subchannels, and heat transfer between the solid and fluid regions. The resulting model can perform both steady-state and transient computations across the entire core. This fully implicit model also includes an adaptive time-stepping algorithm for automatic time-step adjustment. A preliminary code-to-code comparison demonstrates good agreement between the present subchannel-based model and a computational fluid dynamics (CFD)-based model for a transient case in which the core inlet flowrate varies with time. Following the code-to-code comparison, the thermal hydraulic model is used to analyze the protected loss of heat sink (P-LOHS) accident scenario. Key results such as the transient evolution of peak fuel, non-fuel, and coolant temperatures, and 3-D core temperature distribution are presented and discussed.

Preliminary design of the suppressive containment system based on HPR1000

The current HPR1000 has a high construction cost and weak economic competitiveness due to its complex system and large containment. This study proposes a conceptual design of an advanced containment system based on HPR1000, which aims at reducing the construction cost of nuclear power plants without reducing their safety. In the design, the In-containment Refueling Water Storage Tank (IRWST) and spray system were discarded, and the space of the double containment vessel was used to create an annular cavity pool (ACP). The transient pressurization in the containment caused in the early stages of the accident can be quickly suppressed by ACP instead of the traditional large-volume suppression concept. And due to the significant condensation of steam within the ACP water, the transportation of air into the ACP results in a reduction in the air mass fraction in the vicinity of the passive containment heat removal system (PCHR) located within the containment structure. This phenomenon subsequently leads to an enhancement in heat transfer performance. In addition, ACP also serves as the water source for the safety injection system, the reactor cavity water injection system, and the core replacement system. Compared with HPR1000, the system of the preliminary design has been greatly simplified, and the size of the containment vessel has been reduced by nearly 47%. The simulation of the large-break loss-of-coolant accident (LBLOCA) scenario has been conducted to examine the response of the containment system, specifically focusing on the performance of the safety injection system and suppression system. The results show that the integrity of the containment and core was ensured throughout the accident, and there was a safety margin.

Multiscale analysis of the boron dilution sequence in the NuScale reactor using TRACE and SUBCHANFLOW

In the ‘High-Performance Advanced Methods and Experimental Investigations for the Safety Evaluation of Generic Small Modular Reactors’ McSAFER H2020 European project the main aim pursued is to advance the research in safety analysis methods for water cooled Small Modular Reactors (SMRs). Hence, several light-water-cooled SMR concepts were selected along with the corresponding accident scenarios to be modelled to evaluate the potential application of advanced modeling tools based on the coupling of different codes and their benefits and drawbacks. In this study, the simulation of the postulated boron dilution scenario caused by the malfunction of the Chemical and Volume Control System (CVCS) in the NuScale reactor is performed using different modeling tools and approaches. More in particular, a TRACE-1D, a TRACE-3D and a TRACE-3D/SUBCHANFLOW (SCF) models have been developed to perform this analysis. Two cases have been carried out in this work: the first case is based on the calculation of the boron concentration evolution within the Reactor Coolant System (RCS) of NuScale to compute the time to loss of shutdown margin (SDM), and secondly, a best estimate calculation is performed to evaluate the plant response considering the reactivity feedbacks and the performance of the safeguards and safety systems of NuScale according to the public literature. These investigations have demonstrated that the applied modeling approaches and tools can capture the physics of the problem providing less conservative results than those obtained using the analytical methods presented in the DCA report of NuScale. In addition, it has been demonstrated that the NuScale design is robust against the consequences of the boron dilution transient and that no relevant asymmetrical effects appears due to the singular arrangement of the Helically Coiled Steam Generators (HCSGs) surrounding the riser.

Performance Evaluation of Routing Protocols for Vehicle Re-Routing in ITS-based Vehicular Networks

This study aims to assess the performance of routing protocols in Intelligent Transportation System (ITS)-based vehicular networks, specifically in accident and highway scenarios. The effective management of traffic flow in these situations is crucial for ensuring the safety and smooth operation of vehicular networks. Therefore, it is imperative to evaluate routing protocols to identify the most suitable one for these scenarios. The evaluation considers various commonly used routing protocols in vehicular networks, including Ad hoc On-Demand Distance Vector (AODV), Ad hoc On-Demand Multipath Distance Vector (AOMDV), and Destination-Sequenced Distance Vector (DSDV). The evaluation is based on several performance metrics, such as packet delivery ratio, end-to-end delay, network throughput, normalized routing load, and routing overhead. These metrics provide insights into the effectiveness and efficiency of the routing protocols in handling re-routing in accident and highway scenarios. The research is divided into two modules, Module I and Module II, to evaluate the effectiveness of routing protocols in these distinct scenarios using the NS2 simulation tool. The simulation results are analyzed and compared to determine the performance of the routing protocols in each module. The findings indicate that AODV consistently achieves the highest throughput, packet delivery ratio, and lowest end-to-end delay, routing overhead, and normalized routing load, followed by AOMDV and then DSDV. The findings of this study contribute to the understanding of the strengths and weaknesses of different routing protocols in accident and highway scenarios. This knowledge can assist in the development of more efficient and reliable routing protocols for vehicular networks.

Quantitative safety assessment for reactor size variation on high pressure methanol production

This work studied carbon capture utilization (CCU) to methanol synthesis, which analyses reactor size's impact on high-pressure methanol production. As high pressure poses a high probability of process vessel leakage, assessment on its potential hazardous chemical impact such as toxicity, fire, and explosion must be conducted. This study examines how reactor size affects high-pressure methanol plant accident scenarios due to different leakage sizes of reactors and at various day and night conditions. HYSYS was used in this investigation to identify significant chemical components at high pressures. The analysis only limited to four hazardous chemical components namely methanol, carbon dioxide, carbon monoxide, and hydrogen. Then, ALOHA specifies the principal chemical component for the worst-case accident scenario. MARPLOT was used to quantify the methanol plant's safety by utilising distance and area plot threat analysis for reactor size variation. The volume of the reactor used is 42, 20, and 5 m3, with pressure conditions of 76, 184, and 331 bar, as the 10 mm, 75 mm, and 160 mm leakage size of the reactor has been simulated. The simulation in ALOHA was done by considering day and night conditions with one dominant wind direction according to the plant's location. The results show that the highest people affected incident was due to the toxic release of methanol from a 160 mm leak size during the night in Modified Plant 2. This scenario resulted in a percentage people affected for night conditions of 56.53%. This study is useful to predict worst-case people affected with variation for reactor size on high-pressure conditions.

Optimum power determination and comparison of multi-pass and OTTO fuel management schemes of HTGR-based PeLUIt reactor

A co-generation reactor based on pebble-bed High-Temperature Gas-Cooled Reactor (HTGR) has been designed. This study focuses on designing a modular nuclear reactor based on pebble bed high-temperature reactor (Electric Power and Industrial Hot Steam Plant/Pembangkit Listrik dan Uap Panas Industri, abbreviated as PeLUIt), an upgrade from Indonesia’s 10 MW Experimental Power Reactor (Reaktor Daya Eksperimen, RDE). PeLUIt is proposed as a solution for electricity and co-generation application. The 5-pass and Once-Through-Then-Out (OTTO) refueling scheme for the PeLUIt has been analyzed. PEBBED was used for equilibrium core calculations, whereas COMBINE7 was used for spectrum calculations utilizing ENDF/B-VII.0 as nuclear data. Based on the results, it can be inferred that the PeLUIt co-generation reactor analysis with an optimal power of 40 MWt is produced by increasing fuel intake into the core while retaining core geometry and fuel design. In this study, burn-up levels for each refueling scheme are also analyzed, and the value for OTTO is lower than 5-pass refueling schemes. In addition, the Depressurized Loss of Forced Cooling (DLOFC) accident scenario for both types of refueling schemes was also analyzed. The result showed that the OTTO refueling scheme has a higher safety level than the 5-pass refueling scheme.

Modeling of hydrogen dispersion and explosion of a fuel cell vehicle in an underground parking garage

Numerical simulations were conducted to investigate the hydrogen dispersion and deflagration in an underground garage, considering potential leaks from hydrogen fuel cell vehicles. This study constructed a geometric model based on vehicles equipped with 70 MPa hydrogen tanks and considered various accident scenarios by adjusting the orifice diameter and ignition time. The results indicated that the peak overpressure was influenced by the equivalence ratio, hydrogen distribution and ignition time. Specifically, increasing orifice diameter led to greater overpressure when ignition occurred 0.1 s after release, while the opposite trend was observed for ignition at 1 s or 10 s. Temperature and overpressure were measured to evaluate the hazard distances, revealing inconsistencies between distances determined by pressure and temperature, with the latter yielding larger results. This research contributes to determining affected areas and safety distances in hydrogen accidents, provides references for the design of parking intervals and the development of emergency plans.

Improved pool fire-initiated domino effect assessment in atmospheric tank farms using structural response

Domino effects are severe accident scenarios affecting storage tanks and are often initiated by pool fires. Flame engulfment and heat radiation are the two major sources triggering domino effect. Threshold-based and probit-based methods are widely used to assess the possibility and probability of a secondary accident. These methods are also a part of advanced methods devoted to examining synergic or coupling effects. The current work examines (i) how effective the threshold-based methods are and (ii) how accurate the current time to failure (TTF) estimation models are, which are the basis of probit-based methods. The results suggest that threshold-based methods are not pertinent for the quantitative assessment of domino effect and that significant improvement can be made in the existing TTF prediction models using site-specific structural response data. A new set of equations for TTF estimation using data analytics is proposed. Application to 4,080 pool fire scenarios demonstrates that the newly developed model can improve the TTF prediction performance compared to the existing models (around 22% in terms of R2). In addition, a method has been proposed and validated to correlate time with the failure probability for time-dependent domino effect assessment, which is a limitation of probit-based methods.

A Database Extension for a Safety Evaluation of a Hydrogen Refueling Station with a Barrier Using a CFD Analysis and a Machine Learning Method

A methodology is proposed to extend datasets in a database suitable for use as a reference tool to support an evaluation of damage mitigation by a barrier wall in a hydrogen refueling station (HRS) during a vapor cloud explosion (VCE) accident. This is realized with a computational fluid dynamic (CFD) analysis and machine learning (ML) technology because measured data from hydrogen explosion tests with various installed barrier models usually require considerable amounts of time, a secured space, and precise measurements. A CFD sensitivity calculation was conducted using the radXiFoam v1.0 code and the established analysis methodology with an error range of approximately ±30% while changing the barrier height from that was used in an experiment conducted by the Stanford Research Institute (SRI) to investigate the effect of the barrier height on the reduction in peak overpressures from an explosion site to far fields in an open space. The radXiFoam code was developed based on the open-source CFD software OpenFOAM-v2112 to simulate a VCE accident in a humid air environment at a compressed gaseous or liquefied HRS. We attempted to extend the number of datasets in the VCE database through the use of the ML method on the basis of pressure data predicted by a CFD sensitivity calculation, also uncovering the possibility of utilizing the ML method to extend the VCE database. The data produced by the CFD sensitivity calculation and the ML method will be examined to confirm their validity and applicability to hypothetical VCE accident simulations if the related test data can be produced during experimental research. The database constructed using core data from the experiment and extended data from the CFD analysis and the ML method will be used to increase the credibility of radXiFoam analysis results for VCE accident scenarios at HRSs, ultimately contributing to safety assurances of HRSs in Republic of Korea.