A new subassembly-type passive reactor shutdown device has been proposed to expand the versatility and robustness of core disruptive accident prevention measures for sodium-cooled fast reactors (SFRs). This device can passively provide a large negative reactivity to the core by rapidly transferring the device fuel, which liquefies as the core temperature rises during an accident, to the lower plenum region of the device pins using only simple physical phenomena such as gravity falls. The fuel used in this device is assumed to be a metal alloy or chloride with the characteristics of fast reactor fuel and a relatively low melting point. In this study, the transient response analysis of the initiating phase during a typical unprotected loss of flow (ULOF) event was performed for a device loaded core of 750 MWe-class MOX fuel SFR, and the effect of different device fuel materials on the event termination was investigated. The results indicate that, no matter what device fuel material is used, it is expected to be possible to terminate the ULOF event without coolant sodium boiling in the core during the initiating phase of the event by replacing about 30 of the 286 fuel subassemblies in the core with device fuel subassemblies.

In recent years, intelligent control in the field of nuclear power has been received attention. The application of deep learning methods in the field of nuclear power control is promoted. The nuclear power system is a complex structure system, the complexity of the structure lead to the more complexity of the system data. As a result, ordinary prediction methods cannot effectively reflect the relationship between time series data and equipment operating states. To solve the problem that the operating state of nuclear power equipment is difficult to accurately predict, this paper proposes a method for predicting the operating state of heat pipe cooled reactor based on long short-term memory (LSTM) neural network. Heat pipe reactor electric power, nuclear power and other parameters are predicted by LSTM, RNN, CNN. Comparing the predicted parameters obtained by the three methods, the results show that compared with RNN and CNN, the fitting performance and prediction performance of LSTM are better. The applicability of the deep learning method based on the LSTM model in the field of nuclear power plant operation safety assurance has been verified. The method based on LSTM lays the foundation for the subsequent establishment of the operator manual control intelligent auxiliary system to realize the change trend prediction of the controlled quantity.

Nuclear power generation is a stable basic power source that does not emit CO2 on the premise of ensuring safety, and has recently been re-evaluated as an attractive option from the viewpoint of energy security and environmental protection.

Factors such as the recent sluggish power demand, power grid capacity limits, and initial investment limits to avoid risks do not favor large-scale plant output. In order to globalize nuclear power generation to mitigate the greenhouse effect, the authors introduced a new SMR, which is the simplified BWR with a small modular reactor (SMR) with load follow function, that can be easily adopted in any country and can be modularized and manufactured in factories with short construction periods.

The concept of the reactor introduced as a simplified BWR (LSBWR) configuration with a low output, long operating cycle, and comprehensive safety features, which was presented in 1999 at the annual meeting of the JSME and ICONE11 by Narabayashi et, al.

To be economically competitive, the LSBWR design includes system and structural simplifications, modularity for short construction times, and increased availability. Comprehensive safety features are not intended to be evacuated by reliable equipment or systems such as lower core layout, IVR features, and hybrid ECCS including passive features.

The concept proposed here is to provide flexibility for different site conditions and power demands, reduce investment risk and promote public acceptance. Finally, the author also introduces a new SMR named LLBWR, which uses a reactor internal recirculation pump (RIP) for the purpose of load follow with fluctuating renewable energy and enhance facilitates for stable grid control.

The Mark 1 pebble bed fluoride-salt-cooled high-temperature reactor (Mk1 PB-FHR) is a promising kind of molten salt reactor (MSR) design that is cooled with molten salt, fueled with TRISO-based fuel, and equipped with the advanced direct reactor auxiliary cooling system (DRACS) for decay heat removal. The use of molten salt endows the reactor can be operated at low pressure while at very high temperatures. Additionally, the excellent natural circulation capability of the molten salt makes the FHR features passive safety, which can remove the decay heat without an external power supply. However, the freezing point of molten salt is much higher than the ambient, which arises a new risk of coolant solidification accidents. The hot molten salt was cooled by the cold water in the DRACS which is highly susceptible to the coolant solidification accidents. The failure time of the DRACS after the reactor shut down is critical for the safety of the reactor system. In this study, a transient solidification model was employed and coupled with the ASYST code to investigate the complete failure time of the DRACS. Besides the conventional design of DRACS, two different optimal designs were applied to investigate the solidification behavior of the molten salt. On the premise of satisfying the limited temperature of the reactor system, the optimal design was obtained according to the principle of as long as possible the failure time.

To improve the social acceptance of a nuclear power plant, the effective Minor Actinide (MA) transmutation by fast reactors with inherent safety has been studied in Japan. However, the design range of the fast reactor with inherent safety has not been clarified well. The negative void reactivity coefficient is the one of recommended requirements of inherent safety. Therefore, in this study, the feasible range of design parameters is clarified for the fast reactor with MA under the constraint of negative void reactivity. Furthermore, the maximum amount of MA transmutation and the design parameters are clarified.

First, various core designs are considered by changing four design parameters: core volume, MA mass fraction in fuel, the volume fraction of fuel containing MA, and the arrangement of these fuels. Second, the void reactivity is used for screening these core designs. The fast reactor has two fuel regions: the first one is the fuel region with MA, and the second one is without MA. The MA composition is referred from the discharge fuel of the light water reactor. The ratio of the radius to the height of the reference core is fixed at 3/4. As a result, the feasible range of parameters for the fast reactor with inherent safety is clarified in terms of “the core volume”, “the mass fraction of MA in the fuel”, “volume fraction of the MA containing fuel region”, and “the arrangement of these fuels”.

Heat pipe cooled reactor uses high temperature heat pipes to export heat from the core, which has obvious advantages in terms of safety performance compared to conventional pressurized water reactor. Analysis of the operational characteristics of the heat pipe core is an essential element of reactor design. However, further analytical demonstration is lacking for the transient three-dimensional heat transfer situation and the final steady state of the failed heat pipe near the fuel rod. In this paper, a core transient thermal analysis program for a heat pipe cooled reactor is constructed, which includes neutron physics program and heat transfer analysis program. The results of the program were validated using reference data, and the transients of the thermal parameters of the core under a single heat pipe failure accident were analyzed. The results show that the maximum fuel temperature during the accident transient was 1037.7 K, and the maximum metal monolith temperature was 1015.5 K, which did not exceed the temperature limits. The fuel assembly maintained stable operation after the accident, and the reactor's safety was not affected.

The modular high temperature gas-cooled reactor (MHTGR) has inherent nuclear safety feature, which is playing an important role in the development of the nuclear energy. The 600MW multi-module high-temperature gas-cooled reactor nuclear power plant HTR-PM600 is a newly developed nuclear power plant (NPP), which contains six MHTGR-based nuclear steam supply system (NSSS) modules to drive a single thermal load system. This multi-modular NPP design combines safety and economic features, but its control strategies are quite different from the classical single modular NPPs. The main difference of the HTR-PM600 control can be summarized as "multiple reactors drive one load" and "one operator controls multiple reactors". The multi-module coupling effect makes it more difficult for the operator to operate during the steam converging and withdrawing process. Therefore, it is necessary to improve the automation level of the control system to assist the operator in start-up and shutdown process. In order to meet the above requirements, an automatic control strategy is designed to ensure that the pressure and flow rate of each node and branch during the start-up process remain stable. A fluid flow network (FFN) model considering flow capacity characteristics of the secondary-loop equipment is developed. Numerical and hardware-in-loop simulations are carried out to verify the control strategy under typical operating conditions. The simulations results prove that the control strategy can meet the requirements of the start-up process of the reactor nuclear power plant.

Micro heat pipe reactors are potential in remote areas, space, marine and other special environments. The heterogeneity and characteristic sensitivity in the geometry of microreactor designs challenge current tools in reactor physic analysis. A Monte Carlo (MC) global homogenization method is proposed in this paper. The calculation scheme uses the continuous-energy MC method to generate multi-group cross-sections (MGXS) for all regions needed in a 3D heterogeneous whole-core model. The superhomogenization (SPH) algorithm is implemented to correct the MGXS datasets. The MGXS generated by the method is verified in a micro heat pipe benchmark with the Monte Carlo multi-group (MCMG) transport solver. The locally heterogeneous structures such as control drums are retained. The Results showed that the core reactivity and power distribution can be accurately predicted by the MCMG simulation with MGXS generated in 3D whole core and SPH correction. The locally heterogeneous model exhibits good performance in modeling heterogeneous structures. MCMG calculation can save significant computation time compared to the continuous-energy MC method.

Due to the surface covered by the capillary wick in the high temperature heat pipe, the classical evaporation and condensation model may be difficult to characterize the evaporation process well in the high temperature heat pipe under different working conditions. Therefore, this paper carried out an experimental study on the heat transfer characteristics of the evaporation process of high temperature heat pipe with capillary wick. By measuring the axial and radial temperature distribution in the high temperature heat pipe under different working conditions, the phase interface evaporation thermal resistance and evaporation coefficient (Hertz-Knudsen equation) at different temperatures in the high temperature heat pipe were calculated, and the variation law of evaporation coefficient under different working conditions was analyzed. The results show that the magnitude of the evaporation thermal resistance is between 0 and 10-3, which means the evaporation heat transfer coefficient is very high. In general, with the increase of temperature(pressure), the logarithm of evaporation coefficient has a good negative linear correlation with pressure. In addition, it is found that if the adiabatic section temperature commonly used in engineering calculation is taken as the saturation temperature, the value of evaporation coefficient obtained is relatively small, as well as the data dispersion, which is due to axial thermal resistance is introduced. Furthermore, by fitting the experimental data, a correlation for the evaporation of high temperature heat pipe with capillary wick is proposed.

Feasibility of a concept of innovative subassembly-type passive-reactor-shutdown device has been studied, targeting to strengthen safety-"diversity" and -"robustness" of measures to prevent core damage accidents in sodium-cooled fast reactors. We have investigated target measures to achieve inherent safety capability under unscrammed (Anticipated Transient without Scram; ATWS) events in a 750MWe class mixed oxide-fuel fast reactors. As the countermeasure to prevent occurrence of core disruptive accidents (CDAs), we have built a basic proposal of this passive device designs, taking into accounts for engineering restrictions to be required in some design phase. Two types of the devise subassembly are discussed in this work; one device utilizes metal-fuel-alloys and another device salt compound to meet required passive capability.

In this study we have determined the basic specifications of device fuel materials for alloy-type Pu-U-Fe alloy and salt-type (U-Pu) Cl₃, respectively. Ternary Pu-U-Zr alloy is selected for the candidate fuel materials used in the pre-heating pins placed within this device subassembly. Through the studies, it has been suggested that the effectiveness and applicability of U-Pu-Fe alloys and low-enriched U (LEU) -Fe alloys as device fuels span a wide range of fast reactors to enhance safety tolerances against CDAs.

The Passive Residual Heat Removal System (PRHRS) of Fluoride-Salt-cooled high-Temperature Advanced Reactor (FuSTAR) has already been designed, and the transient safety analysis code FUSY was developed to perform the design benchmark accidents. However, the real transient thermal-hydraulic response of PRHRS still needs to be validated by the integral effect test facility. Considering the corrosion and high-temperature difficulties caused by the fluoride-salt of PRHRS, in this study, the heat transfer oil is used as the fluid of the test facility. Firstly, based on the Reynold transport theorem, the complete form of partial differential equations (PDEs) is derived without introducing additional assumptions. Subsequently, to understand the corresponding mechanism, the Hierarchical Two-Tiered Scaling (H2TS) method is adopted to scale the PDEs variables, which reflects the transient natural cycle process in accidents. According to the dimensionless parameters, the heat exchangers and pipelines are designed and arranged to satisfy the steady-state modeling. Finally, one dimension analysis was performed to verify the rationality and distortion of the modeling method. The results show that with the H2TS method, the steady-state effect of the natural cycle with the conjugate heat transfer process can be effectively modeled. In addition, the complete forms of governing equations of the natural cycle are independent of the type and regime of fluids, and there is no need to introduce any additional assumptions. This study provides a reference for the dynamic modeling of natural cycle loops and provides data for future experimental testing.

The liquid lead-bismuth eutectic（LBE）used in the reactor has the characteristics of high density and ultra-low Prandtl number(Pr) which is different from the conventional coolants. Numerical simulation study on the flow characteristics of vertical downward flow in a rectangular channel of 500mm×2.8mm×60mm is carried out in order to explore the flow mechanism of LBE in the narrow rectangular channel of plate-type fuel and determine the computational models of frictional resistance coefficient which is suitable for different working conditions. In the condition of cold state, with the conditions of channel inlet temperature of 180℃ and mass flow rate range of 0.176 kg/s ~25.392kg/s, the calculated results of frictional resistance coefficient is compared with the calculated results of current empirical correlations. In addition, the sufficient turbulence of LBE flow processes in rectangular channel is discussed. The thickness of velocity boundary layer is determined by SST k−ω model in steady and transient state. The results of flow filed distribution which calculated by SST k−ωmodel and RNG k−ε model is discussed. The results show that, the critical Reynolds number of laminar to turbulent flow of the LBE in the narrow rectangular is 181422.95, and the thickness of velocity boundary layer is about 0.42857mm. In addition the vorticity attenuation is happened in viscous sublayer by the calculated results compared by different turbulent models.

The lead-bismuth eutectic alloy (LBE) is a candidate coolant for the generation IV liquid metal reactors, and the plate-type fuel assemblies are widely used in the small or research reactors. However, the turbulent heat transfer behaviors of low Prandtl number LBE are quite different from that of ordinary fluids due to its violation in Reynolds analogy, and its flow and heat transfer process in narrow rectangular channels need to be studied with new methods. For this purpose, the authors conduct numerical simulation and analysis of turbulent flow of the LBE in narrow rectangular channel and compare the numerical simulation results with correlation proposed for liquid metal, moreover, the applicability of different near wall treatment methods, turbulence models and turbulent Prandtl number (Prt) models is compared. The focus of the analysis is on the impacts of the collocation of various models on the Nusselt number, the flow redistribution phenomena, as well as the difference in flow and heat transfer capacity in channels. According to the results, the suggested turbulence model and Prt model for different Peclet (Pe) numbers are recommended, besides the flow redistribution phenomenon in the three channels fuel assembly can be ignored, only slightly affects the flow and heat transfer in the narrow rectangular inlet region.

The small Na-K reactor used in this paper adjusts and controls the power by moving the reflector, which will not only have a great impact on the reactor core structure, but also greatly affect the neutron flux monitoring system. In this paper, the MCNP program is used to calculate the change of neutron fluence rate or equivalent thermal neutron fluence rate of some detector points around the reactor when the reflector moves under the condition of constant power.According to the calculation results,the influence of reflector movement on detector arrangement is analyzed, and the appropriate detector arrangement area is selected to reduce the influence of reflector on detector and the complexity of subsequent circuit.Due to the small size of small Na-K reactors, the size and number of neutron detectors are limited.Furthermore the temperature of the environment where the neutron detector is located is greater than 500 degrees Celsius, and the gamma dose rate is greater than 104Gy /h, so we use the high temperature wide range fission chamber to measure the neutron fluence rate of the reactor from complete shutdown to 150%FP operation.Finally, a reasonable and reliable neutron flux monitoring system is designed according to the neutron flux range at the fission chamber.

Supercritical carbon dioxide (S-CO₂) Brayton cycle power generation technology is developing rapidly worldwide. Compared with traditional thermal power generation technology, S-CO₂ Brayton cycle has great advantages in terms of cycle efficiency and equipment size. In the Brayton cycle, the main equipment compressor plays a vital role in the whole cycle. In this paper, the design model and loss model of S-CO₂ centrifugal compressor are studied, and the performance prediction results of the proposed model are compared with the experimental data based on Sandia Laboratories. At the same time, the loss model of each part of the compressor is given in detail and analyzed.

In order to reduce Minor Actinides (MA), the transmutation of MA in fast reactor has been studied in Japan. However, the design range of the fast reactor, which has inherent safety and can be operated using MA mixed fuel, has not been clarified completely. Therefore, in this study, proposal of a design plan of the plant system which can remove the decay heat in the transient condition is aimed. Here, the transient condition means all control rods are inserted, the pumps are shut down and only the natural convection is the driving force. As decay heat map of the core, the results of simulations using the design parameter range of the fast reactor with MA under the constraint of negative void reactivity for the inherent safety is applied. The heat removal efficiency is aimed to be modeled dividedly into some components, a reactor vessel, piping systems, intermediate heat exchangers (IHX), a pump, and so on by the detailed CFD simulation. As the first step of this study, in this report, the verification of the occurrence condition of the natural convection in the reactor vessel due to the decay heat after shifting to the transient situation is confirmed. After that, the heat transfer efficiency is evaluated against each Ra number condition on core walls, and temperature and flow rate at the core exit is estimated. These results will be developed into the estimation of flow rate of natural convection in the entire primary system and the proposal of the optimal capability of the air cooler in the secondary sodium system and the hydraulic head of components for passive safety.

The modular small pressurized water reactor ACP100 (hereinafter referred to as the small reactor) is a small pressurized water reactor independently developed in China. Compared with traditional large pressurized water reactors, small pressurized water reactors have many differences in design.[1] Due to the huge difference in design, the characteristics of small pressurized water reactor have changed greatly. Therefore, it is necessary to use the transfer function model to analyze its dynamic characteristics.[2]

In this paper, the differential equation of the system is derived according to the physical laws or rules followed by the system, and then the transfer function is obtained through linearization and Laplace transform. Using the results of the small modular reactor model in RELAP5 program and the method of system identification, the calculation formula of the model reactivity feedback in the transfer function is obtained, which can accurately describe the dynamic characteristics of the reactor. Based on the above model, the time domain analysis of small PWR can be carried out, which is helpful for the above dynamic characteristics analysis provides a basis for the design of control system and the later control strategy. For the model of transfer function obtained, after introducing reactivity change disturbance, The comparison with the results of other models shows that the established model is accurate and the response of model parameters to disturbances is consistent.

Achieving carbon neutrality is a big ambition, especially for China. The annual carbon emission reduction rate will have to reach an average of 8-10%. Nuclear power technology, especially advanced reactors, took an important role in green energy transition. Relying on innovation, China’s nuclear reactor technology has made the leap from the second generation to the third generation -- 51 nuclear power units in operation helped reducing 300 million tons of carbon dioxide, and is advancing on various fronts of the 4th generation reactor technologies. Among the six 4th generation reactors recommended by Generation IV International Forum, most of them are the fast reactors. For now, the sodium cooled reactor is the main route of choice in China. The closed fuel cycle can reprocess the spent fuel generated by the nuclear power plant and recycle the reprocessed product. It improves the utilization rate of uranium resources, as well as the safety management conditions of spent fuel and make nuclear development more environmentally friendly. In the meantime, China is also carrying out research on other types of advanced reactors such as high-temperature gas cooled reactors and small modular reactors. There will be enhanced investment and policy support in nuclear energy to facilitate more advanced technologies.

In the present work, one of the studies performed by the Universidad Politécnica de Madrid research group within McSAFER H2020 European project is presented. This project is pursuing the aim of improving the research in the safety simulations by means of the application of conventional and advanced modeling tools to several SMRs designs. In particular, this study is focused on the modeling of the boron dilution sequence in the NuScale SMR caused by the malfunction of the Chemical and Volume Control System (CVCS) with an asymmetrical injection of the FeedWater (FW) system. By doing so, it is possible to assess the impact on the main plant parameters and on the transient evolution of asymmetrical effects which are forced to take place in the RCS.

The modeling of the NuScale Power Module is performed using the system code TRACE following two lines of work based on the application of 1D and 3D components for the modeling of the primary side, respectively. Finally, the comparison between the results of the simulations obtained applying both modeling approaches is made showing that the 3D effects are almost completely absorbed by the performance of the Helically Coiled Steam Generators (HCSG) and that TRACE is able to capture the physics involved in the boron dilution sequence in NuScale.

Previous work has shown in-core printed circuit heat exchange can provide substantial benefits for molten salt fueled reactors. Reductions in overall salt volume and corrosion/deposition cycles due to loop temperature gradients can be achieved. Excore delayed neutron losses are drastically reduced or eliminated, power density is substantially increased, and hot leg/cold leg corrosion is eliminated along with gaining a nearly flat axial temperature profile across the core. In this analysis, a gas cooled, molten salt fueled core is directly coupled to a Brayton cycle and peak core temperature is tracked over the course of a pump failure transient to determine if safe temperature levels are maintained. An NTU-effectiveness calculation is coupled with a point kinetics model as well as feedback to coolant flow rate and heat exchange to model the overall behavior of the system over time. These feedbacks are used to estimate the power and temperature response for a molten salt reactor at steady state and during a primary flow loss transient. Peak temperature conditions are of particular interest in the transient case to determine if the temperature feedback response is sufficient to prevent the system from achieving high temperatures that are incompatible with standard structural materials such as SS-316H or nickel/molybdenum alloys such as Hastelloy-N. While the strongly negative temperature reactivity coefficients inherent to molten salt fuels aid in preventing high temperatures, the passive nature of the coolant flow through the power cycle allows for excellent safety performance in the event of loss of off-site power accidents or pump failures. Safe temperatures can be maintained in an accident scenario, and as much as a third of nameplate electrical power can continue to be produced during a primary pump failure or loss of offsite power accident. The concept promises not only to be “walk-away-safe” but to be a resilient source of power production in the face of accident conditions. This may offer advantages in terms of grid stability in unforeseen circumstances.

The Ukraine-Russia war rekindled the attention and concern for the threats caused by the external man-induced events. Particularly, great concerns arise for the integrity of the nuclear facilities, safety and security systems, power supply, etc. The missile impact on NPP aged may determine an extensive damage and, in the worst case, the partial or total collapse of buildings.

The aim of this study is to determine numerically the ballistic resistance of reinforced concrete/armor materials to penetration by defining a scabbing threshold.

A 3D finite element (FE) model of the nuclear building where the spent fuel pool is located, was implemented considering different types of models for wall perforation and velocity perforation and assuming cylindrical shape for the projectile. Plasticity-based material damage was also assumed.

Results show that at the instant of the impact, an intense shock wave is initiated in the projectile and target causing the fracture or flow of materials.

The residual debris expands as a “bubble” behind the impacted wall and some fragments are seen in front of the surface. For thin wall as the impact velocity increases, damage modes progress for simple dimple formation to spallation, and perforation. Thermal degradation determines a further reduction of the structural integrity.

The operation process of the management of abnormal events in nuclear power plant operates in a closed loop that includes the detection and screening of abnormal events, the cause analysis of events, the formulation and implementation of corrective actions, the closure of actions, and the effectiveness validation of actions, etc. Corrective actions that correspond to Nuclear power plant events are corrective measures taken to prevent incident recurrence and improve nuclear safety management level. Nuclear power plants should establish a standardized tracking and evaluation mechanism for corrective actions, and carry out corrective action evaluation to ensure the effectiveness of corrective actions for events, so as to improve the standardization and timeliness of nuclear safety management. This paper provides a nuclear power plant corrective action evaluation mechanism to evaluate the effectiveness of corrective action for events, including evaluation object, evaluation personnel, evaluation method, evaluation process, evaluation criteria, evaluation results and application of evaluation results, etc. By using of this mechanism, engineers can grasp and analyze the implementation and development trend of multi-plant corrective actions, monitoring the effect of corrective actions, and detect the deviation between the effect of corrective actions and expectations. In this case, the closed loop and timeliness of corrective actions will be assured, the recurrence of events will be prevented and the occurrence frequency of events will be reduced. Finally, nuclear safety performance of nuclear power plants will be improved. The practical methods and case in this paper will provide references for the effectiveness evaluation of corrective actions for nuclear power plant events, and are helpful for the on-site implementation of nuclear safety management concepts and measures.

The spent fuel reprocessing plant is the core link to realize the closed cycle of nuclear energy and plays a pivotal role in the whole nuclear industry system. However, the current safety management system of spent fuel or high radioactive waste liquid is not perfect, there are potential threats in the spent fuel reprocessing plant in the aspects of facilities, transportation and safe storage of radioactive sources. In order to take the most appropriate preventive measures to improve the overall safety of the reprocessing plant, it is urgent to carry out the analysis of the nuclear security incidents and the importance of the construction of the spent fuel reprocessing plant. In this paper, the importance of nuclear security incidents is analyzed by fault tree method. Eight types of nuclear security incidents with high probability in spent fuel reprocessing plant are determined through investigation and the probability of basic events is obtained by using expert scoring and probability-mathematical statistics processing method. In order to improve the reliability of statistical data, the evaluation results of each expert are given corresponding weights by the assignment method because of their different qualifications and work experiences. Secondly, the importance of the buildings is analyzed by the method of fuzzy decision method. This paper mainly studies the main process area and the three-waste area of the reprocessing plant, which is further subdivided into seven units, the expert scoring results are used as the judgment matrix. The results of comprehensive decision-making are processed by mathematical statistics. Therefore, seven units can be obtained. The importance of the main process area and the three-waste area are calculated by the method of summation and average. The results show that the highest importance of computer nuclear security incidents is 0.193 and the lowest importance of theft incidents is 0.018. Therefore, more protection efforts should be put into the computerized nuclear security incidents. The maximum importance of the transformation plant unit at the tail end is 0.561, which has a significant impact on the overall safety of the spent fuel reprocessing plant. The importance of the main process area (0.153) is higher than that of the three-waste area (0.135), indicating that more safety protection forces need to be invested in the main process area. This study can provide theoretical support for the design of nuclear security action plan and the safe operation of spent fuel reprocessing plants.

The Lagrangian Particle Dispersion Model is widely utilized in predicting the transport trajectory of air pollutants and reproducing concentration fields to assess pollution levels. Except for the traditional particle concentration calculation method (the Box counting), several alternative particle concentration calculation methods (the Gaussian kernel, the Uniform kernel and the Parabolic kernel) have been investigated. However, the effectiveness of these methods under radionuclide dispersion scenarios has not been sufficiently uniformly evaluated, so evaluating the capabilities of these methods under radionuclide dispersion scenarios is essential for their future applications in nuclear emergency decision-making and nuclear accident assessment. This paper aims to evaluate the capacity of three different particle concentration calculation methods via the Belgian field experiment by coupling the California Meteorological Model and the Lagrangian Particle Dispersion Model. In comparison with the observed values, the simulated results of three methods successfully reproduced parts of the peak values. The results of Gaussian kernel show an overall slight underestimation, while the Uniform kernel and Parabolic kernel display an overall slight overestimation. Furthermore, all three methods basically meet the statistical acceptance criteria. The numerical distributions of Parabolic kernel exhibit the best degree of matching with observations, while these of Uniform are the weakest.

The transport containers are important guarantees for the safety of radioactive materials transportation activities, which can resist vibration, shock, fire and other impacts. Radioactive materials transport packages have the characteristics of complex structure, difficult processing and high cost, especially spent fuel and high-level waste transport packages. Therefore, the economy should be fully considered during the service life. The transport container usually retains a large safety margin in the design stage, so that the service life of it can be appropriately extended through the regular safety performance evaluation, maintenance and repair, as well as the service performance evaluation. At present, some research institutions have carried out material aging research on container components and conducted performance tests on aging containers so as to quantitatively explore the influence of determined aging factors. On this basis, some users have also developed aging management and maintenance procedures for containers to delay the aging process. So that the purpose of prolonging the life of transport packages can be realized. In the work of extending the life of radioactive material transport packages, the research on material aging and aging management are the key points worth exploring and summarizing.

Although the prediction of system behavior plays a crucial role in accident management, there is very limited research on this subject in the nuclear industry. Accident process prediction methods are usually implemented as data-based methods due to the fast inference speed. However, the existing methods used for reactor accidents often ignore the predictive capability of the forecasting models over long-term patterns, or do not analyze the confidence of the prediction.

In this paper, we have proposed a method for accident process prediction based on a Temporal Fusion Transformer (TFT) model. On the one hand, the method leverages multiple types of covariates as auxiliary, such as static labels of accidents and other monitoring data, to improve the prediction accuracy; on the other hand, it carries out uncertainty assessment of the predicted sequences.

The method proposed in this paper is applied to MBLOCA post-accident prediction of HPR1000. Extensive results show that the method significantly outperforms the NiHiTS, Nbeats, Transformer, LSTM, GRU and RNN etc. models in terms of prediction accuracy on the test dataset. Furthermore, the uncertainty analysis of the prediction results allows the method to be applied to production scenarios of nuclear reactors, which is of high safety demands.

The release rate of airborne contaminants is a crucial element to assess the consequences. The inverse modeling technique has been developed to provide such a release rate of emissions, which minimizes the discrepancies between the atmospheric dispersion simulations and the environmental observations. Because of the transport nature and the sparse network of measurement in space and time, the coverage of the observations is typically spatiotemporal insufficient, especially the temporal absence. The existing objective approach of inverse modeling poorly handles this trouble of insufficient observations and present oscillations or release missing in the corresponding periods. The total variation regularization introduces a piecewise constant prior with a balance of the constant and peak releases, enabling the inverse modeling automatically retrieve the boundaries of potential release windows and adaptively recover the missing releases. We have investigated the impacts of the number and duration of missing periods on this method using three designed datasets based on hourly air concentration observations following the Fukushima accident, as well as the influence of poor 6-hour temporal resolution. The method recovers the missing releases with constant releases and enhances piecewise-constant features to the estimate, and it also outperforms the Tikhonov method in these cases both qualitatively and quantitatively.

The transport of radionuclides in the marine has been a hot issue of social concern since the Fukushima accident, especially the Japanese government announced to discharge the wastewater from Fukushima Daiichi Nuclear Power Plant (FDNPP) into Pacific Ocean in 2021, which can directly affect the environment and human health. Regarding inland nuclear power plants, freshwater habitats such as reservoirs and rivers could also be polluted by the radioactive effluents. An adequate model is expected to be instrumental in assessing radioactive pollution in various water environments. Scientists have proposed various models to simulate the advection and diffusion of radionuclides released by the Fukushima nuclear accident in the marine in different marine environmental conditions. In this study, the behaviors of radionuclides in water bodies are introduced, including advection, turbulent mixing, decay, and interaction with sedimentss and biota. The processes of Lagrangian models, which are commonly used to simulate the transport of radionuclides in the marine, are explained in detail. The research progress and application examples of radionuclide transport models in rivers and marines in recent years are systematically summarized. Current research can provide suggestions for the development of numerical models for describing the transport behavior of radionuclides in the marine environment.

In the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident, a large volume of 137Cs was discharged and broadly transported by the atmosphere, which left long-term ground radioactivity deposition in Japan. The wet deposition process substantially affected the spatiotemporal distribution of both atmospheric and deposited 137Cs concentrations in the FDNPP accident. Numerous efforts have been devoted to understanding the wet deposition following the FDNPP accident and to improving the modelling. However, accurately modelling the wet deposition remains a challenge because of the nonuniformities and uncertainties in the meteorological fields, source terms, modeling, and parameterization. Furthermore, the rough resolution of the meteorological fields might limit a detailed investigation of model behavior at the local scale. In this paper, a meteorology input with a 1 km resolution is applied to study the model sensitivity. The in-cloud (Roselle) and below-cloud (Baklanov) schemes, which both perform well in the 3 km model intercomparison study, were integrated into the WRF-Chem model. A detailed evaluation is performed based on the cumulus deposition and concentration during several plume events to provide a clearer insight into different model performances under various resolutions of the meteorological fields.

As a kind of clean energy, the efficient and sustainable development of nuclear energy can reduce carbon emissions and greatly reduce the burden on the environment. However, due to the particularity of fuel type, once a nuclear accident occurs, it will cause serious consequence, especially the three major accidents in the history of nuclear power, which have increased the public’s concern about nuclear safety. How to timely and effectively judge the occurrence of nuclear accidents has become an important part of nuclear power plants (NPPs) safety analysis.

This paper proposes a method for NPP accident diagnosis by establishing a Bayesian inference model. During the operation of a NPP, a large amount of monitoring data will be generated. The operator can determine the occurrence of an accident based on experience through abnormal changes in monitoring signals. However, relying solely on human judgment cannot more systematically maximize the use of all available monitoring information. In this study, according to the results of NPP’s safety analysis, the key variables that change when the accident occurs are extracted to establish a Bayesian network model, and the quantitative causal relationship between each node is represented by the conditional probability table (CPT), so as to achieve both qualitative and quantitative accident reasoning. This method can be applied to the emergency decision support system of NPPs, and the detection signals are imported into the established Bayesian network model as evidence information to give the possibility of a specific type of accident. Taking two typical accidents of HTR-10 unit as an example, this paper expounds modeling process of the Bayesian network and verification results, which shows that the Bayesian inference model can better infer the occurrence of an accident. It not only makes full use of the existing knowledge of safety analysis, but also combines the current operating state of the NPP.

In a nuclear accident consequence evaluation, the complex terrain is one of the key factors that affect the simulation result. Increasing the grid resolution of the dispersion model can reproduce more plume details in a scenario with complex terrain, but it will inevitably lead to higher computing costs. Therefore, it is necessary to arrange the grid resolution reasonably according to different regions, so that it can balance the calculation cost and the calculation accuracy.

In this paper, the accuracy of the variable grid and the fixed grid is tested and verified by two experiments, one is a complex terrain simulation experiment and the other is the Kincaid field experiment with flat terrain. The simulation results of the variable grid are evaluated by comparing plume images and statistical results against the fixed grid simulation data and the measurement data. The comparison results show that the variable grid resolution scheme has more plume details in complex terrain scenes than the fixed grid resolution scenario. However, the variable grid resolution scheme does not improve the simulation effect in flat terrain scenario.

The objective of this study is to modify the three-step design method proposed by Bruhl. et al. to support the design of steel plate reinforced concrete (SC) slabs against perforation under missile impact. To determine a more reasonable initial concrete slab thickness described in the first step of the design method, the effects of type, weight and impact velocity of missile on the ratio of perforation limit of SC slabs, es, to the perforation limit of reinforced concrete (RC) slab, er, will be investigated. In the first part of this study, experimental data available in literature and referring to large-scale impact tests of rigid and soft missile on SC and RC slabs were selected for benchmarking. To the aim of the study numerical impact simulations were performed using an explicit dynamic Finite element (FE) code for predicting the behavior and load bearing capacity of impacted wall. Suitable finite element models of SC slabs, RC slabs and missiles developed, the implemented numerical algorithms, constitutive models and adopted parameters were also verified by comparing the numerical results with the experimental data. Then in the next part of this study, validated numerical simulation methods will be applied to the parametric study to determine the relationships between the missile weight and impact velocity and both RC and SC perforation limit, for rigid and soft missile impact. An explicit formula will be proposed to predict the ratio es/er, which is helpful for engineers to reasonably select an initial concrete thickness for designing SC structures used in the nuclear facilities.

Graphite and carbon components are important materials for the core and reflector of a high temperature gas-cooled reactor-pebble bed module (HTR-PM). Expansion to the critical point will cause the components to rupture and fall off, which will pose a huge threat to the structural safety of the HTR-PM and its safe and stable operation. Therefore, before the reactor is built, the defect detection of graphite and carbon components is particularly important, which is not only the basic guarantee for the long-term safe operation of the nuclear reactor but also an important support for predicting the fatigue state of irradiated materials based on the pre-service data of the reactor to evaluate the life of the reactor. Considering the large volume of reactor components, long production cycle, and small internal defect volume, the defect detection accuracy and efficiency are required to be high, and traditional non-destructive testing methods such as ultrasound, eddy current, and X-ray are no longer applicable. Multi-slice spiral CT technology has the advantages of high detection accuracy and fast detection speed and is suitable for 3D digital imaging of graphite and carbon components. However, the amount of reconstructed data from spiral CT images is huge, and the manual image review based on visual inspection has shortcomings such as false detection and missed detection. Therefore, it is particularly important to intelligently detect defects. In this paper, the detection images of graphite and carbon component samples by multi-slice spiral CT system are used as the dataset, artificial defect annotation is carried out, and the deep learning algorithm based on YOLOX is used to realize the intelligent detection of defects of large-size graphite and carbon components in HTR-PM. The results show that the YOLOX algorithm achieves good performance in defect detection of graphite and carbon components, and can achieve 96.4% accuracy and 64.85 fps value, with high detection accuracy and detection efficiency.

Carbon/graphite bricks are used as the supporting structure and neutron moderator for high-temperature gas-cooled reactors (HTGR) because of their excellent mechanical properties and neutron moderation ability. These bricks require computed tomography (CT) non-destructive detection before they are put into service. The number and size of defects inside them must be below the limits to ensure the reactor’s operation. However, the CT non-destructive detection system cannot find part of the defects due to the image artifacts caused by scattered photons. This study thus proposes a Monte Carlo scatter correction method, which uses simulation software based on photon transportation to simulate the physical process of CT scanning. CT image quality can be improved by calculating and deducting the share of scattered photons in the data received by the detector. Results prove that the Monte Carlo scatter correction method is effective. The influence of the ray source energy on the scatter correction is also discussed to assist the design of the detection system. We believe our research would help to improve the defects inspection performance of the detection system and is of great significance to ensure the safety of the reactors.

In order to study the characteristics of single rod flow-induced vibration in axial flow, the vibration response of single rod flow-induced vibration in axial flow with different constraints at both ends and different flow velocity was measured with a Laser Doppler Vibrometer. Based on spectral analysis and statistical analysis, the transient vibration response was analyzed in depth. The results show that the vibration amplitude increases with the increase of the flow velocity, and the two ends of the constraints have a significant influence on the flow-induced vibration response. The root means square amplitude value of the simply-supported single rod is 35% larger than that of the fixed one at 3 m/s. Spectrum analysis shows that with the increase of flow velocity, the dominant frequency decreases from 17.5 Hz at 1.5 m/s to 13.8 Hz at 3.0 m/s under simply-supported constraints, while the dominant frequency basically fluctuates around 13.0 Hz under fixed support constraints. The vibration frequency of simply-supported constraints are distributed between 6 Hz and 28 Hz, while those of fixed constraints are mainly distributed between 12 Hz and 16 Hz. The statistical results show that in the X direction of the simply-supported constraints, the geometric center point of the rod is shifted, which indicates that the rod is buckling.

In recent years, cases of unknown leakage of radioactive materials have aroused more public concern and promoted the need for rapid leakage source reconstruction methods applied to estimate the source location and the release rate. In our work, we propose a source reconstruction method based on backward atmospheric dispersion simulation that is validated against the first European tracer experiment (ETEX-I). First, the source receptor sensitivity (SRS) matrix is calculated by the backward mode of the FLEXible PARTicle (FLEXPART) model, whose running times are equal to the number of measurements. Then our method reconstructs the source location and the release rate separately based on the SRS matrix, providing a way that can avoid the “overfitting” effect in the ill-posed minimization problem. The results demonstrate that our method can accurately reconstruct the source location at a low error level and retrieve the temporal profile of the release rate with the total release amount estimated within a 10% error level. In addition, we make a comparison between our method and a cost function method. The results indicate that our method has a great advantage in reconstruction efficiency since it does not need to traverse the entire computational domain. Finally, the sensitivity to the ratio threshold of SRS higher than 0 is also investigated. For the sake of the reconstruction accuracy and efficiency, the presented source reconstruction method here is potentially a practical tool for further integration into nuclear emergency response systems.

The experimental analyses of the U–Pu–Zr fuel pin behavior during transient overpower (TOP) tests were performed using CANIS, and the residual cladding wall thickness, molten region of the fuel alloy after the tests, and the reactivity inserted by molten fuel extrusion before the fuel pin failure were compared with experimental results. On the basis of the obtained analysis results, detailed calculation models were developed to make it possible to reflect changes in the local properties of the fuel alloys due to the redistribution of fuel constituents during steady-state irradiation and in cladding thinning rate depending on the fuel–cladding interface temperature. With such calculation models implemented, CANIS properly predicted fuel behavior and resulting reactivity changes before fuel pin failure in TOP events.

The dryout behavior of debris bed is an important safety issue in the postulated Core Disruptive Accidents (CDAs) of a sodium-cooled fast reactor. In this paper, the coolability of debris beds is studied experimentally and quantitatively assessed by the dryout heat flux (DHF). Dryout phenomenon of three cases with different particle diameter of 1mm, 2mm and 3mm and two cases of axial stratified beds are investigated. And the dryout location is monitored by the sudden rise in temperature and observed by visualization. The mechanism of the dryout behavior of axial stratified beds is discussed. Results show that the dryout location of homogeneous bed occurs at the bottom of the debris bed, while the dryout location of the axial stratified debris bed with different stratified mass ratio is found at the interface and then expands downward. The DHF of axial stratified bed is about 10% of that of the homogeneous debris bed packed with small particles of the same size at the upper layer of axial stratified bed, because of the low permeability at the interface.

Enhancement of the ability to manage abnormal situations is important for improvement of the safety of nuclear power plants. It is needed to investigate potential risks thoroughly in advance, and to prepare countermeasures against the identified risks. In addition, in case of occurrence of an abnormal situation, plant operators are required to recognize the plant situation promptly and select a suitable countermeasure. However, the human ability to perform it is limited because the number of such abnormal situations in actual nuclear power plants is indefinite. Due to the advent of AI, it becomes possible to compensate for such limitation, by learning abnormal situations and assessing the effectiveness of prepared countermeasures virtually. The present study aims to develop such AI-based system to support plant operators to deal with abnormal situations steadily. Although many previous studies about detection of anomalies have been conducted, few studies consider countermeasures, especially against unexperienced abnormal situations. In this study, a novel plant operator support system that can estimate anomalies in a plant and propose countermeasures adaptively is proposed by using several AI technologies such as deep neural network and reinforcement learning. A plant simulator is used to prepare training data for AI. The combination of the proposed AI-based system and the plant simulator makes it possible to identify abnormal situations unknown to operators and propose countermeasures. The design and performance of the proposed system is illustrated using High Temperature engineering Test Reactor (HTTR) in Japan Atomic Energy Agency as an example.

The recent trend of nuclear reactor miniaturization may require reconsideration of the existing framework of safety. This study conceptually explores the safety goals for transportable microreactors (TMRs), by focusing on the differences between large light-water reactors (LLWRs) which contain large amounts of hazardous fission products and TMRs. For LLWRs, the safety goals and surrogate goals representing the integrity of the reactor have played a significant role in reducing negative health effects of radiation exposure in cases of nuclear disasters. Practitioners, notably the operator, have typically been classified as the main users of these goals. However, the innovative feature of TMRs will lead to the reconsideration of the contents and users of safety goals. The size of radiological consequences of TMR accidents may highlight the need to capture broader consequences other than direct health effects when formulating the top-level goals. Correspondingly, additional surrogates for representing the interplay between the reactor and surrounding areas may be required. Effectively meeting these new goals only by the efforts of licensees may be a challenge; this indicates a need for the local actors wherein the TMRs are deployed become the extended users of safety goals.

Equipment reliability data is an important basis for nuclear power plants to carry out probabilistic safety analysis (PSA), maintenance rules (MR) reliability related work. This paper introduces the practical experience of PSA equipment reliability data acquisition in China. In view of the importance of equipment reliability data of nuclear power plant, take a pressurized water reactor nuclear power plant in China as an example to preliminarily count the PSA equipment reliability data collected by each unit of the nuclear power plant from 2019 to 2021. Through secondary analysis of PSA failure data, operation data and I0 data of safety important system equipment, we can find out whether there is abnormal adverse trend in the reliability data of nuclear power plant equipment, and propose improvement suggestions to continuously improve the safety level of nuclear power plants and the efficiency of nuclear safety supervision.

The rapid search for missing radiation source can reduce the harm to the human body and the generation of panic, which is of great significance to the people's life, work and social stability. This paper is based on solving the problem of searching for radiation source in a complex environment closer to reality, construct obstacle scenarios, and consider the situation of limited communication. Use the consensus-based distributed source parameter estimation algorithm to process the detection values and the posterior information, which is obtained by itself and its neighbors, and the location and activity of the missing radiation source are gradually estimated. Then the variable step length distributed free energy strategy is used to guide the robot to the next position to continue detection. The two processes run iteratively until the missing radiation source search task is completed. The sharing of neighbor information within the communication range will increase the particle diversity of the local particle filter algorithm, improve the estimation accuracy, and also achieve the consistency of source parameter estimation and source search result. Experimental results show that the algorithm in this paper has a higher search success rate and shorter search time in complex environment.

Working at nuclear facilities subjects workers to a number of industrial health and safety risks. During their normal duties, workers are potentially exposed to hazardous processes and materials (e.g., hot steam, harsh chemicals, electricity, and pressurized fluids) the facilities may contain and other hazards (including slips, trips and falls). Nonetheless, even though workers are trained to stay away from potential dangers, there are still many types of risks that can occur within only a few minutes of carelessness. Occupational safety and health (OSH) monitoring at nuclear facilities requires observing and identifying a variety of specific unsafe behaviors with feedback to on-site workers. However, this mostly relies on manual observation and recording, which is time-consuming and costly. To this end, this paper presents an automated identification approach to enhance OSH management in nuclear facilities. First, a visual information extraction module integrating the state-of-the-art deep learningbased models is proposed to obtain hybrid visual information. Subsequently, on-site occupational hazards are identified by automatically analyzing relationships of detected entities. The experimental results demonstrate that with high-performance extraction and analysis of hybrid visual information, occupational hazards can be effectively and automatically identified for intelligent OSH management.

Metal product corrosion is a concern for various products as the appearance of metal products is compromised when red rust or other corrosion occurs, resulting in a decline in product value. In addition, embrittlement, depletion, and destruction of metal materials can result in a loss of strength, causing social effects. In some cases, this can result in serious accidents involving human lives, attracting significant social attention. Protective coatings, such as the widely used zinc plating, are frequently applied to metal products to protect the metal base. When inspecting the corrosion of such metal products, it is desirable to be able to measure not only the areas containing red rust but also those with white rust while monitoring the progress of corrosion simultaneously. However, most corrosion inspections are performed visually and subject to the inspector’s experience. In this study, we propose an unsupervised rust image segmentation method. Inspired by invariant information clustering, we optimize the parameters of a multi-layer convolutional neural network to maximize the mutual information content and achieve rust area segmentation without using annotation data. We investigated the appropriate number of clusters through corrosion experiments on zinc-coated metal plates and realized the image segmentation of red and white rust.

The control rods moved into and out of the reactor core by means of Control Rod Drive Mechanisms (CRDMs). During reactor trips, the loss of power to the CRDMs will drop all control rods into the core quickly, thereby shutting down the nuclear reaction. The Rod Drive Motor-Generator Sets provide 260V three-phase power to the CRDMs through the reactor trip switchgear. There are two MG sets with flywheels. During normal operating conditions, both MG sets operate in parallel and equally share the total load demand. Each MG set is capable of supplying the entire load requirements when the other set is out of service. However, it is not uncommon the simultaneous failure of two MG sets resulted in loss of power to the CRDMs.

Normally, the nuclear power plant sets the shutdown protection signal with a Power Range High Negative Neutron Flux Rate. Therefore, if the control rods moved into reactor core quickly, the signal will be generated to trigger the shutdown signal, and then the turbine trip signal will be sent. However, because the passive nuclear power plants are equipped with a Rapid Power Reduction System, it is impossible to set a Power Range High Negative Neutron Flux Rate signal, which can trigger the shutdown signal. If both MG sets fail unexpectedly in passive nuclear power plant, CRDMs will lose power supply, and the control rods will fall into the reactor core under the action of gravity , and the reactor automatically shuts down. However, no trip signal will be generated during this process, which cannot trigger the turbine trip. The safeguards actuation caused by the low steamline pressure unexpectedly in a short time.

For the above problems, the following two solutions are proposed. Solution 1: some undervoltage relays are set on the outlet power supply cable of the MG sets to monitor the status. During the power operation, if both MG sets fail at the same time, the reactor trip signal will be triggered according to the low voltage signal, and triggers the turbine trip signal will also be triggered after a delay of 5 seconds. Solution 2: referring to other conventional nuclear power plants, reactor trip protection with power range high negative neutron flux rate could also be adopted in passive nuclear power plants. Of course, necessary optimization is indispensable.

Small modular reactor adopts integrated reactor, passive safety and other advanced design concepts, with high inherent safety and engineering safety design characteristics. The accident of loss heat sink is a typical design extended conditions accident of PWR. The heat sink function of SMR can be divided into primary heat sink and secondary heat sink. The accident of loss heat sink of SMR refers to the loss of both types of heat sink. If the heat sink is lost, the residual heat cannot be removed in time, which risks the safety of the reactor. In this paper, the best estimation method based on realistic assumptions is used to conduct accident analysis, and the process of accident consequence after the loss heat sink of SMR is studied. According to the safety system design of SMR, the accident operation strategy of loss heat sink is given. After analysis and calculation verification, this strategy can effectively alleviate the core state after loss heat sink, establish a stable residual heat removal way, and ensure the safety of SMR after the accident of loss heat sink.

Accidental fires in nuclear fuel fabrication and reprocessing plants can cause the rupture of the glove box (GB) containment with a risk of dispersion of plutonium dioxide (PuO2) within the facility. Fire safety analyses need an assessment of the resulting radiological consequences to strengthen the appropriate prevention and protection measures in these plants. To this end, the French institute for radiological protection and nuclear safety (IRSN), in partnership with the Japanese nuclear regulation authority (NRA), has carried out since 2019 a research project that aims at assessing the airborne release fraction (ARF) of PuO2 involved in GB fires. This project, named FIGARO (Fires Involving Glove boxes with Aerosol Release Occurrences) follows a phased approach, starting with small and medium-scale analytical tests to study separately the various mechanisms involved in the GB fires and the PuO2 airborne release and ending with large-scale GB fire tests to transpose and validate the analytical works for realistic assessments of the ARF of PuO2 in confined conditions. This project also includes the development of a GB fire model in the IRSN SYLVIA and CALIF3S-ISIS softwares and its validation. In addition to presenting the FIGARO project, this paper provides its first outcomes.

Risk informed Safety Margin Characteristic Analysis (RISMC) combines the advantages of two existing safety analysis techniques, using discrete dynamic event tree (DDET) and Monte Carlo (MC) methods to quantify safety margin and risk response to optimize the design of power plant critical safety systems. The existing RISMC method needs to simulate a large number of accident scenes and power plant state, which has high time and economic cost. Due to the limited sample size of the best estimation program relying on high fidelity, the reliability of the prediction results of safety parameters such as core damage frequency (CDF) is poor. In this paper, the safety analysis of SBO accidents of CPR1000 unit is carried out by RISMC method, and support vector machine (SVM) is used to reduce the order of the original core failure frequency prediction model under typical sequence. By comparing with the simulation results of the original optimal estimation program, it is found that the accuracy of the reduced order model to predict the core damage frequency is more than 90% under the two types of SBO accident conditions. It is proved that the study in this paper can replace the best estimation program and predict the core damage of different power plant conditions faster under the typical SBO accident sequence. It can effectively improve the reliability of core failure frequency prediction and save a lot of time cost and calculation requirements.

The research investigates novel techniques to enhance supply chain security via addition of configuration management controls to protect Instrumentation and Control (I&C) systems of a Nuclear Power Plant (NPP). A secure element (SE) is integrated into a proof-of-concept testbed by means of a commercially available smart card, which provides tamper resistant key storage and a cryptographic coprocessor. The secure element simplifies setup and establishment of a secure communications channel between the configuration manager and verification system and the I&C system (running OpenPLC). This secure channel can be used to provide copies of commands and configuration changes of the I&C system for analysis.

The Information Harm Triangle (IHT) is an approach that seeks to simplify the defense-in-depth design of digital instrumentation and control (I&C) systems. The IHT provides a novel framework for understanding how cyber-attacks targeting digital I&C systems can harm the physical process. The utility of the IHT arises from the decomposition of cybersecurity analysis into two orthogonal vectors: data harm and physical information harm. Cyber-attacks on I&C systems can only directly cause data harm. Data harm is then transformed into physical information harm by unsafe control actions (UCAs) identified using Systems-Theoretic Process Analysis (STPA). Because data harm and physical information harm are orthogonal, defense-in-depth can be achieved by identifying control measures that independently limit data harm and physical information harm.

This paper furthers the development of the IHT by investigating the defense-in-depth design of cybersecurity measures for sequences of UCAs. The effects of the order and timing of UCAs are examined for several case studies to determine how to represent these sequences using the IHT. These considerations are important for the identification of data harm and physical information harm security measures, and they influence the selection of efficient measures to achieve defense-in-depth. This research enables the benefits of the IHT’s simple approach to be realized for increasingly complex cyber-attack scenarios.