Severe Accident In Nuclear Power Plant Research Articles

Improvement and validation of containment spray removal aerosol models based on single droplet collection particle mechanism

Nuclear safety is the lifeline for the development and application of nuclear energy. In severe nuclear power plant accidents, aerosols are the major carriers of fission products, which may leak into the environment and cause potential radioactive contamination. Containment spray is an important mitigation measure for severe accidents in nuclear power plants. It can effectively reduce containment atmospheric pressure and radioactive aerosol concentration. This paper improves the containment spray removal models so as to address the low accuracy of the original models of the ISAA code. Based on single droplet collection particle mechanism, new inertial impaction and interception models were used to accurately calculate the collection efficiency of large particles. Additionally, a new correlation was used to explain the Brownian diffusion collection mechanism of small particles. Moreover, thermophoresis and diffusiophoresis models were introduced to consider the contribution of steam condensation in the containment to the collection efficiency. A rear capture model was introduced to incorporate the influence of recirculation within the wake of large droplets on the collection efficiency. Furthermore, THAI, TOSQAN and CSE experiments were selected to validate and evaluate the improved ISAA code. According to the calculation results, the improved models can simulate the attenuation trend of suspended aerosols with higher accuracies and significantly improves the calculation accuracy of the spray removal constants. This work contributes to understand of the scavenging mechanism of aerosol particle by containment spray droplets, and provides an analysis method with higher simulation accuracy. At the same time, it points out shortcomings in the simulation of aerosol behavior in the current ISAA code and discusses future improvements to the code.

Influence of Jet on Aerosol Retention by Pool Scrubbing Under Multihole Injector

In severe nuclear power plant accidents, when the containment is in a serious challenging state, the gas mixture in the containment can be injected into the spent fuel pool through the multihole injector by the containment depressurization measure, to reduce the risk of containment overpressure failure and the release of radioactivity to the environment. The pool scrubbing efficiency of aerosol under the jet regime is studied on the small-scale aerosol pool scrubbing facility, focusing on the influence of mass flux, steam fraction, submergence, particle diameter, and pool initial temperature on the aerosol decontamination factor (DF). The results show that under the jet regime, the DF value is significantly greater than that in the bubble regime and the effect of jet flow on the mechanism of steam condensation and aerosol removal of the rising zone is weak under the conditions explored. DF increases with the increase of mass flux owing to the droplet interception and inertial collision aerosol removal mechanisms. Because the high pool temperature weakens the aerosol removal by steam condensation, DF decreases with the increase of initial pool temperature under the conditions explored. Based on the experimental data and the analysis of the removal mechanism under the jet regime, an empirical model of aerosol DF considering mass flux, steam fraction, pool temperature, submergence, and particle size is established and verified by the international experiments. The proposed model can be used to calculate DF in the process of containment overpressure discharge.

ToF-SIMS and XPS characterizations of model fission products (I, Cs) deposits after thermal treatment simulating late phase conditions of a nuclear power plant severe accident

During a Severe Accident (SA) occurring in a nuclear power plant, many Fission Products (FP) are released from the degraded fuel and are transported in the Reactor Coolant System (RCS). Depending on their volatility, FP can be either deposited on the surface of the Reactor Coolant System (RCS) or transported into the containment building from where they may be released into the environment in case of early containment failure. This was the case for the Fukushima Daiichi (FD) accident with important FP releases which were observed following the containment vessel failure which lasted up to several weeks after the accident. If early phase releases were well predicted by SA simulation codes, delayed releases were not correctly predicted [1]. Such discrepancies can be attributed to the revaporization of deposits inside the RCS which were not yet modeled in the SA simulation tools. Previous experiments over the past 20 years evidenced the possible formation and revaporization of CsI [2]. However, up to now, no clear CsI revaporization mechanism has been determined. In order to propose a mechanism, this study (scheduled within the OECD/NEA/ESTER project) aims at determining the speciation of each species remaining on the substrate after revaporization tests under different conditions using XPS and ToF-SIMS (X-ray Photoelectron Spectroscopy and Time of Flight Secondary Ion Mass Spectrometry. These two combined techniques allow the identification of the main species of the residue leading to the proposition of two revaporization reactions.

Severe accident analysis of the dual-functional lithium-lead test blanket module using ISAA-DFLL code

The international thermonuclear experimental reactor (ITER) project aims to build a tokamak fusion test reactor to verify the feasibility of fusion reactors. The test blanket module (TBM) is the key component of the international thermonuclear experimental reactor. The fusion design study team proposed the concept of the dual-functional lithium-lead test blanket module (DFLL-TBM). The integral severe accident analysis (ISAA) is a self-developed ISAA code that models the progression of severe accidents in nuclear power plants. A broad spectrum of severe accident phenomena including fission product release and transport behavior is modeled in ISAA. In this paper, a new version of ISAA, referred to as ISAA-DFLL is introduced for the application of DFLL-TBM test blanket module into the treatment of multi fluids and the modules of the new physical property and heat transfer. The modification is verified by comparing the steady-state temperature distribution of the DFLL-TBM first wall with the design parameters. Then accident analysis of In-vessel loss of helium coolant in first wall and TBM pipe is conducted by using the ISAA-DFLL code. By comparing the calculation results with the general safety requirements for TBM, it is concluded that the design of the DFLL-TBM system and the modifications of the current version are reasonable and accurate.

Investigation on Aerosol Pool Scrubbing Model During Severe Accidents

During a nuclear power plant severe accident, discharging gas mixture into the spent-fuel pool is an alternative containment depressurization measurement through which radioactive aerosols can be scrubbed. However, it is necessary to develop a code for analyzing the decontamination factor of aerosol pool scrubbing. This article has established the analysis model considering key aerosol pool scrubbing mechanisms and introduced the Akita bubble size relationship. In addition, a code for evaluating the decontamination factor of aerosol pool scrubbing was established. The Advanced Containment Experiment and Light Water Reactor Advanced Containment Experiment were simulated with the code considering different bubble sizes of the Akita model and MELCOR default value to verify the suitability of the Akita bubble size model for simulating aerosol pool scrubbing. Furthermore, the simulation results were compared with the results analyzed by MELCOR code and COCOSYS code from literature, and equivalent predictive ability was observed. In addition, a sensitivity analysis on bubble size was conducted, and the contribution of different behaviors and mechanisms has been discussed. Finally, the bubble breakup equation was revised and verified with the conditions of the multi-hole bubbler in the Advanced Containment Experiment and Light Water Reactor Advanced Containment Experiment.

Tellurium transport in the RCS under conditions relevant for severe nuclear accidents

In the case of a severe nuclear power plant accident, tellurium is one of the more problematic and volatile fission products. If released it could become a health issue as it decays to iodine which accumulates in the thyroid gland. Research exists, that indicates tellurium likely interacts with caesium under severe accident conditions, thus it is important to further explore related phenomenon. In this work, tellurium was exposed to high temperature under oxidizing and inert conditions simulating severe accident conditions with and without airborne caesium iodide to determine the effect on the tellurium source term.The effect of caesium iodide was noticeable on tellurium transport behaviour in the gas phase under oxidizing and inert conditions. Under humid oxidizing conditions with caesium iodide, no significant impact on the total aerosol mass transport was noticed. However, less tellurium was transported through the model primary circuit and a potentially new compound was observed on the filter located after this model. Comparing inert dry to humid with caesium iodide showed an increase in the total aerosol mass transport whereas there was a decrease noticed of the tellurium reaching the filter after the model primary circuit. In the latter case, new unidentified compound(s) correlated to caesium, iodine and tellurium were observed on the filter located after the model.In this work, evidence was found that tellurium behaviour will be affected by caesium iodide under the investigated conditions. Moreover, it seems that under inert conditions the formed compounds may be stable at close to ambient temperatures. Unlike under oxidizing conditions, where dissociation likely occurred.

Improved prediction model for H2/CO combustion risk using a calculated non-adiabatic flame temperature model

During severe nuclear power plant (NPP) accidents, a H2/CO mixture can be generated in the reactor pressure vessel by core degradation and in the containment as well by molten corium-concrete interaction. In spite of its importance, a state-of-the-art methodology predicting H2/CO combustion risk relies predominantly on empirical correlations. It is therefore necessary to develop a proper methodology for flammability evaluation of H2/CO mixtures at ex-vessel phases characterized by three factors: CO concentration, high temperature, and diluents. The developed methodology adopted Le Chatelier’s law and a calculated non-adiabatic flame temperature model. The methodology allows the consideration of the individual effect of the heat transfer characteristics of hydrogen and carbon monoxide on low flammability limit prediction. The accuracy of the developed model was verified using experimental data relevant to ex-vessel phase conditions. With the developed model, the prediction accuracy was improved substantially such that the maximum relative prediction error was approximately 25% while the existing methodology showed a 76% error. The developed methodology is expected to be applicable for flammability evaluation in chemical as well as NPP industries.

Tellurium determination by three modes of instrumental neutron activation analysis in aerosol filters and trap solutions for the simulation of a severe nuclear accident

Tellurium belongs to the elements not frequently determined by neutron activation analysis (NAA) or other analytical methods. We present results of a new methodological study using three independent modes of instrumental NAA (INAA) using the 123mTe, 131Te and 131I radionuclides. We compare the results obtained in terms of accuracy, precision and limits of detection (LOD). We utilized the INAA procedures tested for the tellurium determination in aerosol filters and trap solutions in a model experiment aimed at reducing the knowledge gap concerning the behaviour of 132Te, a radiologically significant fission product, which constitutes a considerable health risk towards the public in case of its release in a severe nuclear power plant accident. We found that the nuclear reaction 130Te(n,γ)131Te and gamma-ray spectrometric measurement of 131I, a descendant of 131Te, is the most sensitive way of Te determination by INAA providing as low LOD values as 0.15 µg of Te in the Teflon aerosol filters and 0.22 µg mL-1 in the 0.1 M NaOH trap solutions. The three independent INAA modes allowed employing the self-verification principle of INAA for increasing the trustworthiness of our results. Finally, we also point to the indispensable role of the non-destructive feature of INAA for assay of samples, such as Teflon aerosol filters, that are difficult to be analysed by other analytical methods requiring complete sample destruction without analyte losses.

SOARCA uncertainty analysis of a short-term station blackout accident at the Sequoyah nuclear power plant

The U.S. Nuclear Regulatory Commission initiated the state-of-the-art reactor consequence analyses (SOARCA) project to develop realistic estimates of the offsite radiological health consequences for potential severe reactor accidents. The SOARCA analysis of an ice condenser containment plant was performed because its relatively low design pressure and its reliance on igniters make it potentially susceptible to early containment failure from hydrogen combustion during a severe accident. The focus was on station blackout accident scenarios where all alternating current power is lost. Accident progression calculations used the MELCOR computer code and offsite consequence analyses were performed with MACCS. The analysis included more than 500 MELCOR and MACCS simulations to account for uncertainty in important accident progression and offsite consequence input parameters.Consequences from severe nuclear power plant accidents modeled in SOARCA are smaller than previously calculated. The delayed releases calculated provide more time for emergency response actions. The results show that early containment failure is very unlikely, even without successful use of igniters. The modeled behavior of safety valves is very important to this conclusion, but there is sparse data and a lack of established expert consensus on the failure rates under severe accident conditions. Even for scenarios resulting in early containment failure, the calculated individual latent fatal cancer risks are very small. Early and latent-cancer fatality risks are one focus of this paper. Regression results showing the most influential parameters are also discussed.

Recovery countermeasure features that may preclude MCDA based decisions

Multi Criteria Decision Analysis (MCDA) with stakeholder participation has been suggested as a way to reach mutually acceptable and robust decisions regarding methods and strategies for recovery of inhabited land areas and food production systems severely contaminated by an airborne radioactive plume from a severe nuclear power plant accident. The paper describes a new approach to help ensuring that important issues are not overlooked when decisions are based on MCDA.

Adsorption behavior of methyl iodide on a silver ion-exchanged ZSM-5

Abstract An organic iodide, especially methyl iodide (CH3I), is one of the most safety concerns against a nuclear power plant severe accident because it is highly toxic and easily inhaled. Due to its high volatility, the dry filtration methods are generally employed to capture the gas phase CH3I. Although it is important to accurately assess the performance of dry filter in a postulated severe accident situation, no sufficiently accurate adsorption kinetic behaviors have been reported yet. In this study, we designed the highly accurate experimental set-up, thermogravimetric analysis-gas chromatography coupled system, which overcame the limitations of previous studies, and performed the CH3I adsorption tests on a silver ion-exchanged ZSM-5 (Ag-ZSM-5) zeolite at a wide temperature range (50–150 °C) under the postulated severe accident condition. The fresh and adsorbed Ag-ZSM-5 samples were characterized by powder XRD, elemental analysis, and SEM-EDS, and the further CH3I adsorption behaviors were discussed in depth. From the overall results, we obtained the accurate adsorption rates and activation energies, and an understanding of chemisorption and physisorption behaviors. Our findings provide the useful fundamentals for a model development of dry filter performance assessment.

Two-phase flow pressure loss through packed particle bed for wide void fraction range

The understanding of the two-phase flow phenomena in porous media is a critical issue for debris bed coolability assessment in severe nuclear power plant accidents. Hence, two-phase-flow friction force modeling has been extensively attempted, based on pressure-loss measurement data. However, most previous two-phase flow pressure loss experiments were conducted at a restricted void-fraction range up to approximately 0.6, which is considerably lower than the dryout condition. Therefore, in this research, two-phase flow tests in packed particle beds are conducted to gather two-phase pressure loss data in the high-void-fraction region. The test beds are constructed by packing mm-scale particles, 3–7 mm in diameter. The experimental data are analyzed and compared with the predicted values of the previous two-phase friction models in term of not only the pressure gradient but also the interfacial friction force between the liquid and gas phases. As there was no valid data for the high-void-fraction region during the previous model development processes, an appropriate model for the interfacial friction force at void fractions greater than approximately 0.6 is unavailable. However, the interfacial friction force plays a significant role in the coolability assessment of the ex-vessel debris bed because it determines the water ingression rate under a cocurrent flow condition. The obtained experimental results in this research indicate the necessity to further improve the model in order to decrease the uncertainty in severe accident risk quantification.

Optimizing UAV-based radiation sensor systems for aerial surveys

In this study, we qualitatively and quantitatively analyzed unmanned aerial vehicle (UAV)-based radiation sensor systems suitable for specific survey missions. We examined a variety of UAVs, radiation sensors, and radiological survey missions; after reviewing previous studies that developed and conducted field tests, we categorized them by mission and suggested suitable types of UAVs and radiation sensors for each mission. To quantitatively analyze various system designs previously suggested, we proposed a new figure of merit (FOM) formula that can explain the mutual effects of parameters of both radiation sensors and UAVs on system performance. After targeting a radiological survey mission, we selected UAV and radiation sensor types qualitatively. Then, the quantitative FOM formula can be employed to efficiently assess whether the system achieves the required minimum detectable activity (MDA) without field test, while keeping the error of the MDA values in the order of 100. After defining the constraints including the proposed FOM formula, we replicated a severe nuclear power plant accident scenario. We found that one fixed-wing UAV and multiple rotary-wing UAVs are the minimum number of UAVs, and thus the optimal system for timely achievement of a satisfactory MDA and estimation of the three-dimensional radiation distribution contributed by both ground radiation and an atmospheric radioactive plume.

A sensitivity study on cut frequency of FFTBM for quantitative assessment of thermal-hydraulic modeling by MELCOR code

In this paper, accuracy sensitivity of MELCOR code in prediction of Thermal-Hydraulic (TH) behavior of test facilities of Nuclear Power Plants (NPP) is quantitatively analyzed. MELCOR is a fast-running code with integrated structure, and it is extensively employed for modeling of severe accidents in NPPs. Fast Fourier Transform Based Method (FFTBM) is a tool to determine differences between code predictions and measurements in frequencies. Cut frequency plays an important role in quantitative evaluation of TH calculations by FFTBM. In the current research, a sensitivity study has been carried out by different cut frequencies. Suitable cut frequency removes incorrect influence of higher noise frequencies of investigated signals, while avoiding loss of information in accuracy indices of FFTBM. Determined cut frequencies for both original FFTBM and improved FFTBM by signal mirroring, have a good agreement. Accuracy indices calculated with the determined cut frequency, provide more consistent understanding of calculation accuracy variations during the modeled transients.

Analysis of the radioactive atmospheric dispersion induced by ship nuclear power plant severe accident

For the nuclear powered ship, the radionuclides will be released near the sea surface after a severe nuclear accident. The influence of sea surface on the atmospheric diffusion of radionuclides cannot be ignored. Based on the Lagrangian particle tracking model, the simulation model for atmospheric diffusion of radionuclides above the sea was established. The influences of sea absorption on atmospheric diffusion of radionuclides emitted at different heights were analyzed. It is shown that if emission height is low, the time-integrated concentration of radionuclides in the air will be reduced significantly by the sea absorption. The lower the discharged height is, the more rapidly the concentration of radionuclides in the air near the source decreases. If the emission height is high, the time-integrated concentration of radionuclides in the air will increase firstly and then decrease with the increase of distance. The higher the emission height is, the lower the time-integrated concentration of radionuclides in the air near the sea surface is, and the smaller the amount of radionuclides absorbed by the sea is.

Nuclear reactor vessel water level prediction during severe accidents using deep neural networks

Abstract Acquiring instrumentation signals generated from nuclear power plants (NPPs) is essential to maintain nuclear reactor integrity or to mitigate an abnormal state under normal operating conditions or severe accident circumstances. However, various safety-critical instrumentation signals from NPPs cannot be accurately measured on account of instrument degradation or failure under severe accident circumstances. Reactor vessel (RV) water level, which is an accident monitoring variable directly related to reactor cooling and prevention of core exposure, was predicted by applying a few signals to deep neural networks (DNNs) during severe accidents in NPPs. Signal data were obtained by simulating the postulated loss-of-coolant accidents at hot- and cold-legs, and steam generator tube rupture using modular accident analysis program code as actual NPP accidents rarely happen. To optimize the DNN model for RV water level prediction, a genetic algorithm was used to select the numbers of hidden layers and nodes. The proposed DNN model had a small root mean square error for RV water level prediction, and performed better than the cascaded fuzzy neural network model of the previous study. Consequently, the DNN model is considered to perform well enough to provide supporting information on the RV water level to operators.

GIS-Based Integration of Social Vulnerability and Level 3 Probabilistic Risk Assessment to Advance Emergency Preparedness, Planning, and Response for Severe Nuclear Power Plant Accidents.

In the nuclear power industry, Level 3 probabilistic risk assessment (PRA) is used to estimate damage to public health and the environment if a severe accident leads to large radiological release. Current Level 3 PRA does not have an explicit inclusion of social factors and, therefore, it is not possible to perform importance ranking of social factors for risk-informing emergency preparedness, planning, and response (EPPR). This article offers a methodology for adapting the concept of social vulnerability, commonly used in natural hazard research, in the context of a severe nuclear power plant accident. The methodology has four steps: (1) calculating a hazard-independent social vulnerability index for the local population; (2) developing a location-specific representation of the maximum radiological hazard estimated from current Level 3 PRA, in a geographic information system (GIS) environment; (3) developing a GIS-based socio-technical risk map by combining the social vulnerability index and the location-specific radiological hazard; and (4) conducting a risk importance measure analysis to rank the criticality of social factors based on their contribution to the socio-technical risk. The methodology is applied using results from the 2012 Surry Power Station state-of-the-art reactor consequence analysis. A radiological hazard model is generated from MELCOR accident consequence code system, translated into a GIS environment, and combined with the Center for Disease Control social vulnerability index (SVI). This research creates an opportunity to explicitly consider and rank the criticality of location-specific SVI themes based on their influence on risk, providing input for EPPR.

Effect of honeycomb porous plate on critical heat flux in saturated pool boiling of artificial seawater

During a severe nuclear power plant accident, the integrity of the reactor pressure vessel must be assured. In response to a possible fuel meltdown, operators of the current generation of nuclear power plants are likely to inject water into the reactor pressure vessel cavity to cool down the reactor vessel wall, preserving its integrity and avoiding leakage of radioactive material. This study considers the use of seawater to flood a reactor pressure vessel cavity combined with the attachment of a honeycomb porous plate (HPP) on the vessel outer wall as a way to improve the safety margins for in-vessel retention of fuel. In long-duration experiments, saturated pool boiling of artificial seawater was performed with an upward-facing plain copper heated surface 30 mm in diameter. The resulting value for critical heat flux (CHF) was 1.6 MW/m2 at atmospheric pressure, a value significantly higher than the CHF obtained when the working fluid was distilled water (1.0 MW/m2). It was verified that sea-salt deposits could greatly improve surface wettability and capillarity, enhancing the CHF. The combination of artificial seawater and an HPP attached to the heated surface improved the boiling heat transfer coefficient and increased the CHF up to 110% (2.1 MW/m2) as compared to distilled water on a bare surface. After the artificial seawater experiments, most of the wall micropores of the HPP were clogged due to sea-salt aggregation on the HPP top and bottom surfaces. Thus, the CHF enhancement observed in this case was attributed mainly to the separation of liquid and vapor phases provided by the HPP channel structure and improvement of surface wettability and capillarity by sea-salt deposition.

Mass transfer experiments on the natural convection heat transfer of the oxide pool in a three-layer configuration

We investigated the heat load to the reactor vessel by the natural convection of the core melt in a hypothetical severe nuclear power plant accident condition. It is modeled as the natural convection heat transfer with the volumetric heat source in a chopped hemisphere. To achieve high Ra'H ranging from 1011 to 1013, mass transfer experiments were performed for three-layer configuration of the oxide pool with three different aspect ratios based on the analogy between heat and mass transfer. The local heat transfers to top, side, and bottom were measured, compared with the existing studies, and discussed phenomenologically. Major findings were that the side and bottom heat flux distributions are unaffected by the top plate cooling condition and that the angle dependent heat flux increases with the angle measured from the bottom. Three layer configuration is more conservative as its upward heat ratio was larger than that of two layer configuration. With the decrease of the aspect ratio, the upward heat ratios increased due to the reduced side wall cooling but with very small aspect ratio, multi-cell flow patterns were formed. The heat transfer around the edge of the bottom plate was impaired due to the formation of stagnant flows.

Intelligent Modeling for Nuclear Power Plant Accident Management

This paper explores the viability of using counterfactual reasoning for impact analyses when understanding and responding to “beyond-design-basis” nuclear power plant accidents. Currently, when a severe nuclear power plant accident occurs, plant operators rely on Severe Accident Management Guidelines. However, the current guidelines are limited in scope and depth: for certain types of accidents, plant operators would have to work to mitigate the damage with limited experience and guidance for the particular situation. We aim to fill the need for comprehensive accident support by using a dynamic Bayesian network to aid in the diagnosis of a nuclear reactor's state and to analyze the impact of possible response measures. The dynamic Bayesian network, DBN, offers an expressive representation of the components and relationships that make up a complex causal system. For this reason, and for its tractable reasoning, the DBN supports a functional model for the intricate operations of nuclear power plants. In this domain, it is also pertinent that a Bayesian network can be composed of both probabilistic and knowledge-based components. Though probabilities can be calculated from simulated models, the structure of the network, as well as the value of some parameters, must be assigned by human experts. Since dynamic Bayesian network-based systems are capable of running better-than-real-time situation analyses, they can support both current event and alternate scenario impact analyses.