Nuclear Plant Research Articles

Microstructure and Mechanical Properties of GH3535 Superalloy Joints Using Electron Beam Welding

To achieve low‐stress and small‐deformation welding of thin‐walled structures for the fourth‐generation nuclear power plants, GH3535 superalloy is welded to itself using electron beam welding (EBW). The microstructure and mechanical properties of the GH3535 superalloy joints are characterized by scanning electron microscopy (SEM), energy dispersive spectrometer (EDS), hardness, and tensile tests. A macro‐defect‐free GH3535 superalloy joint could be obtained using 22 mA welding beam current under 65 kV welding voltage with 300 mm min−1 welding speed. Different sub‐grain solidification morphologies are observed at the weld zone because of the influence of composition undercooling on the solidification process of the weld pool. The M6C type carbides formed in the weld zone and heat‐affected zone (HAZ) take place eutectic transformation under the action of thermal cycles. The eutectic transformation of M6C has no significant effect on the strength of HAZ, whereas this phenomenon is beneficial to hinder the dislocation movement in the weld zone, thereby promoting the tensile strength of the joint. The Vickers hardness of weld zone and HAZ are 250.6 and 252 HV0.5, remarkably lower than that of the base metal (261.2 HV0.5), due to the grain coarsening in those zones. The tensile strength of the GH3535 superalloy joint reached 791 MPa, ≈93.5% that of the base metal, with the fracture occurred in the weld zone.

Study and characterization of zeolites for the removal of artificial radionuclides in wastewater samples from nuclear power plants

4A, 13X, phillipsite and chabazite zeolites have been characterized regarding their capacity to remove Cs+ and Co2+ ions from aqueous solutions. The aim is to simulate the decontamination process of radioactive wastewater, originating from the former Garigliano nuclear plant in Italy, which is contaminated with 137Cs and 60Co. The four zeolites, in powder state, have been tested with solutions containing cesium nitrate and cobalt nitrate hexahydrate, in both individual and combined configurations, at different solid/liquid ratios. The Cs+ and Co2+ concentrations have been monitored over time by inductively coupled plasma (ICP) spectrometry. The results demonstrate the high efficacy of 13X zeolite providing almost 100 % of removal of both elements in a relatively short time (20–30 min). These findings are the basis for the kinetic characterization of the zeolite using radioactive solutions and, hence, for the setup of an in-situ pre-pilot plant to carry out tests with contaminated wastewater at the Garigliano facility. 13X zeolite presents a promising alternative for decommissioning radioactive wastewater.

Magnetic Indicator for Evaluating Cu Clustering and Hardening Effect in RPV Model Alloy

The reactor pressure vessel (RPV) is a critical barrier in nuclear power plants, but its embrittlement during service poses a significant safety challenge. This study investigated the effects of Cu-enriched clusters on the mechanical and magnetic properties of Fe-0.9 wt.%Cu model alloys through thermal aging. Using Vickers hardness tests, Magnetic Barkhausen Noise (MBN) detection, and Atom Probe Tomography (APT), the study aimed to establish a quantitative correlation between MBN signals, Vickers hardness, and Cu-enriched clusters, facilitating the non-destructive testing of RPV embrittlement. Experimental results showed that the hardness and MBN parameters (RMS and Vpp values) changed significantly with aging time. The hardness increased rapidly in the early stage (under-aged), followed by a plateau and then a decreasing trend (over-aged). In contrast, MBN parameters decreased initially and then increased. APT analysis revealed that Cu-enriched clusters increase in size to 4.60 nm and coalesced during aging, with their number density peaking to 3.76 × 1023 m−3 before declining. An inverse linear correlation was found between MBN signals and the combined factor Nd2Rg (product of the number density squared and the mean radius of Cu-enriched clusters). This correlation was consistent across both under-aged and over-aged states, suggesting that MBN signals can serve as applicable indicators for the non-destructive evaluation of RPV steel embrittlement.

Concurrent fault diagnosis of small pressurized water reactors based on long-short term memory networks

The control systems of small pressurized water reactors (SPWR) with complex structures, compact layouts, and variable operating environment may be involved in various types of signal and concurrent faults. Concurrent faults can be taken as two or more single faults occurring simultaneously, which usually cause much larger damage to the system and are more difficult to be diagnosed than single faults. However, their fault diagnosis methods are rarely studied because of the numerous fault types and tremendous diagnostic difficulty. This paper explores the concurrent fault diagnosis method for sensors and actuators in SPWR control systems. An intelligent current fault diagnosis model is developed using long short-term memory network with the training and test datasets generated based on a fault simulation platform of the target SPWR. The test results show that both single and concurrent faults of the SPWR can be diagnosed rapidly in an average of 1.06 s after their occurrence with the classification and diagnosis accuracies reaching up to 96.61% and 97.27%, respectively. Moreover, by injecting different noise signals on the faulty dataset for training and validation, it is shown that the proposed LSTM network has strong noise immunity. This demonstrate the excellent diagnosis accuracy and efficiency of the model under both single and concurrent fault conditions. This study provides valuable guidance for the accuracy diagnosis of complex concurrent faults of nuclear power plants.

A Reduced-Order Model of a Nuclear Power Plant with Thermal Power Dispatch

This paper presents reduced-order modeling of thermal power dispatch (TPD) from a pressurized water reactor (PWR) for providing heat to nearby heat consuming industrial processes that seek to take advantage of nuclear heat to reduce carbon emissions. The reactor model includes the neutronics of the reactor core, thermal–hydraulics of the primary coolant cycle, and a three-lump model of the steam generator (SG). The secondary coolant cycle is represented with quasi-steady state mass and energy balance equations. The secondary cycle consists of a steam extraction system, high-pressure and low-pressure turbines, moisture separator and reheater, high-pressure and low-pressure feedwater heaters, deaerator, feedwater and condensate pumps, and a condenser. The steam produced by the SG is distributed between the turbines and the extraction steam line (XSL) that delivers steam to nearby industrial processes, such as production of clean hydrogen. The reduced-order simulator is verified by comparing predictions with results from separate validated steady-state and transient full-scope PWR simulators for TPD levels between 0% and 70% of the rated reactor power. All simulators indicate that the flow rate of steam in the main steam line and turbine systems decrease with increasing TPD, which causes a reduction in PWR electric power generation. The results are analyzed to assess the impact of TPD on system efficiency and feedwater flow control. Due to the simplicity of the proposed reduced-order model, it can be scaled to represent a PWR of any size with a few parametric changes. In the future, the proposed reduced-order model will be integrated into a power system model in a digital real-time simulator (DRTS) and physical hardware-in-the-loop simulations.

Mini-Reactor Proliferation-Resistant Fuel with Burnable Gadolinia in Once-Through Operation Cycle Performance Verification

A miniature nuclear reactor is desirable for deployment as a localized nuclear power station in support of a carbon-free power supply. Coupling aspects of proliferation-resistant fuel with natural burnable absorber loading are evaluated for once-through operation cycle performance to minimize the need for refueling and fuel shuffling operations. The incorporation of 0.075 wt.% 237Np provides favorable plutonium isotopic vectors throughout an operational lifetime of 5.5 years. providing 35 MWe. Core performance was assessed using a verification-by-comparison approach for core designs with or without 237Np and/or gadolinia burnable absorber. Burnup Monte Carlo calculations were performed via MCOS coupling of MCNP and ORIGEN to an achievable burnup of ~62.5 GWd/t. The results demonstrate a minimal penalty to reactor performance due to the addition of these materials as compared against the reference design. Coupling of a proliferation-resistant fuel concept with a uniform loading of natural gadolinia burnable absorber for LEU+ fuel (7.5 wt.% 235U/U UO2) provides favorable excess reactivity considerations with minimized concerns for additional residual waste and more uniform distribution of un-depleted 235U in discharged fuel assemblies.

Recommendations for Protective Actions Based on Projected Public Health Risks Following a Postulated Nuclear Power Plant Accident

This study conducted a regional assessment of the environmental and health consequences due to the release of radionuclides, including the most harmful, such as Cs-137 and I-131, from a hypothetical reactor accident at the first Nuclear Power Plant (NPP), Akkuyu Nuclear Power Plant, in Turkiye under different meteorological conditions. Simulations of the atmospheric flow were done using a Gaussian-based probabilistic model. Based on the estimated air and land contamination, radiation doses and cancer risks to the population were calculated. The assessment results were then compared with the criteria for protective actions in the event of a radioactive release and were subsequently used to assess the sufficiency of the Precautionary Action Zone (PAZ) and Urgent Protective Zone (UPZ) provided by regulations. The assessment indicated that evacuation outside the UPZ would likely be required during the early phase of the emergency, while sheltering indoors might be necessary up to 80 km. Protective actions such as restrictions on being outdoors or iodine prophylaxis are needed far beyond the radius of the UPZ. These results provide important insights into safe protective measures to reduce the risk of radiation-related cancer when considering a hypothetical severe nuclear accident. In addition, the results of this study aim to improve the current nuclear emergency response program and support nuclear decision-making.

A jövőbeli erőművi portfólió elemzés költség- és kibocsátás minimum optimalizálás szempontjából

The article examines the expected composition of the power plant portfolio in Hungary by 2030. The indicators considered are the life-cycle unit costs (LCOE) and the life-cycle specific carbon dioxide emissions (LCA(CO2)) of the power plant types. The minimum of these two indicators, as objective functions, is determined by a linear programming method for the power plant portfolio. The results show that the LCOE minimum for the power plant portfolios in 2030 is worse in absolute terms and better in specific terms than in 2021. In both absolute and specific terms, the LCA(CO2) minimum is more favourable in 2021. These results are met under the thirty and twenty-five percent electricity import scenarios. With twenty percent imports, the absolute values are worse and the specific values are better for both indicators. On the other hand, the results of the calculations for 2030 fall short of the 2030 Agenda of the Institute for a Green Transition. This is due to the delay in commissioning a new nuclear power plant and the transformation of industry with increasing electricity demand. For the portfolios under review, a minimum of thirty percent of domestic generation from renewable sources is met. This contributes significantly to the European Union's ambition for the sector to be net greenhouse gas-free by 2050.

Accuracy and scalability of incompressible inductionless MHD codes applied to fusion technologies

Abstract It is well-known that magnetohydrodynamics (MHD) dominates the dynamic of the liquid metal flows inside the breeding blankets (BB) of future nuclear fusion plants by magnetic confinement. MHD is a multiphysics phenomenon involving both electromagnetism and incompressible fluid mechanics. From the computational point of view, the simulation of MHD flows in fusion relevant conditions entails a significant challenge. Indeed, due to the shape of the induced electrical currents inside the bulk of the fluid, high spatial resolutions are needed to capture the large gradients found in boundary layers and 3D effects. Besides, solving the equations accurately typically requires very small time steps for the transient algorithms. Over the past few decades, some parallel MHD codes have been developed with success to simulate complex flows in increasingly realistic geometries. Among them, the MHD tools of commercial CFD platforms have attracted attention due to their relatively soft learning curve. Most of these codes are based on the so called ϕ-formulation which, by applying the divergence free condition of the current density to the Ohms law, reduces the electromagnetic part of the problem to a single Poisson equation. As a downside, the approach segregates the fluid and electromagnetic problem. In practice, this establishes important limits to the mesh element size, to the mesh quality and to the time-step needed to obtain accurate and stable solutions that maintains charge conservation at a discrete level. In this work, these limits are explored for the commercial platform ANSYS-Fluent using a test geometry under different conditions. As an alternative, a new code based on Finite Element Methods (FEM) is introduced as well. This open-source code, called GridapMHD (https://github.com/gridapapps/GridapMHD.jl), aims at solving the full set of MHD equations using a monolithic approach. GridapMHD is still in early stages of development but it has already shown promising results.

Impacts of vertical variations in soil properties on H*(10) simulations for 137Cs deposition

Photon transport simulations based on the Monte Carlo method have played a crucial role in assessing and estimating the ambient dose equivalent rates H*(10), resulting from the deposition of 137Cs in soil following the nuclear power plant accident in Fukushima. However, a comprehensive examination of the effect of vertical variations in soil properties on the simulation outcomes has not yet been performed. Disregarding the vertical distribution of soil properties not only leads to potential inaccuracies in the shielding responses of soil layers but also in the determination of the radioactive source inventory, particularly when using the concentration data in Bq/kg. These oversights diminish the reliability of the simulation results. This study addresses several soil property factors that could potentially influence the simulation results, including variations in chemical composition induced by water content, bulk density profile, and estimated inventory profile, all evaluated through an examined simulation model. The results show that inappropriate assignment of the soil density profile can cause considerable errors in the H*(10) simulation outcomes. Furthermore, the sensitivity of H*(10) to variations in soil vertical density is analyzed, with the results indicating that H*(10) can be highly sensitive to changes in the bulk density of the top 0–5 cm soil layers. These results should facilitate the establishment of appropriate simulation strategies and support the reassessment of past simulation results.

An estimation method for bias error of measurements by utilizing process data, an incidence matrix and a reference instrument for data validation and reconciliation: Part 2 Extension to the energy balance relation

Abstract Ensuring data reliability is becoming increasingly important for further applications of AI, IoT, and digital twins. One promising technology for ensuring data reliability is data validation and reconciliation (DVR), which minimizes the uncertainty of measurements based on statistics. DVR has been widely used for the operation and maintenance of nuclear power plants in Europe and the United States in recent years. The most important input for DVR analysis is measurement uncertainty. The catalog value provided by sensor manufacturers includes the measurement uncertainty, but in reality, the actual measurement uncertainty is often smaller. Previous studies have proposed several methods for evaluating the actual measurement uncertainty based on process data, which have been confirmed to be effective for evaluating random errors. It is important to note that bias errors also contribute significantly to the measurement uncertainty. In our previous paper, we proposed a method for estimating bias error using process data, an incidence matrix, and a reference instrument. The proposed method was limited to a mass balance relation, i.e., flow rate measurements. In this paper, we extend the method to include an energy balance relation by considering energy conservation in addition to mass conservation. This extension enables the evaluation of measurement uncertainty for flow rate and temperature. The proposed method was validated with two benchmark problems. It was found to be applicable to various flow conditions, including physically fluctuating flow, such as that observed in the feedwater flow in nuclear power plants.

Fixed-time fractional-order sliding mode controller with disturbance observer for U-tube steam generator

Water level control of a U-tube steam generator plays a critical and challenging role in ensuring safe and reliable operation for a pressurized-water reactor-type nuclear power plant, as both excessively high and low water level in the U-tube steam generator would affect the normal operation of the nuclear power plant and even lead to unplanned shutdown events. This work presents a fixed-time fractional-order sliding mode water level controller coupled with a fixed-time disturbance observer, aiming to further improve the water level control performance under full operating conditions, considering uncertainties and actuator saturation. The proposed scheme is formulatedbased on the popular Irving water level model with uncertainties and the pre-existing actual water level control framework, while at the same time incorporating the benefits of the state-of-the-art anti-windup techniques, disturbance observer-based feedforward compensation techniques, fractional-order calculus, sliding mode control techniques, and fixed-time stability theorem, such that the transient water level response and steady-state control accuracy can be further enhanced even in the presence of uncertainties and actuator saturation phenomenon. It is theoretically proved that under the proposed scheme, both the estimation error of the uncertainties and the water level control error can be driven to zero within a fixed time regardless of their initial values by Lyapunov’s theorem. Meanwhile, simulation studies, involving the comparisons with a real-world adopted water level controller and a pre-existing integer-order sliding mode water level controller coupled with an uncertainty estimator, reveal the feasibility and superiority of the proposed approach.

Martensite-austenite transformation during dual-stage tempering and work-hardening characteristics of Mn–Ni–Mo steel

The reactor pressure vessel (RPV) in nuclear power plants is mainly made from Mn–Ni–Mo steel. After quenching, this steel's microstructure features martensite-austenite (M-A) islands. Tempering above 600 °C poses a challenge, as these islands can transform into harmful rod-like Fe3C precipitates, adversely affecting the RPV's tensile properties and structural integrity. This study explores the effects of M-A transformation during dual-stage tempering on the tensile properties of Mn–Ni–Mo steel, focusing on two austenite grain sizes (5 μm and 47 μm). The dual-stage tempering included a 2-h pre-tempering phase at temperatures between 200 °C and 500 °C, followed by a 3-h final tempering stage at 650 °C. Results showed that M-A transformation is temperature-dependent. At 200 °C, partial transformation led to rod-like Fe3C precipitates during final tempering, similar to direct tempering at 650 °C, reducing the critical stress for micro-crack nucleation and compromising tensile properties. Pre-tempering at 350 °C produced fine, aggregated precipitates that improved tensile strength by inhibiting dislocation movement. Conversely, pre-tempering at 500 °C resulted in coarser, more dispersed spherical precipitates. The Kocks-Mecking plot indicated that the 350 °C pre-tempered sample had the highest strain hardening capacity, with the strain hardening rate curve farthest from the origin and the shallowest slope during stage IV hardening. However, the 500 °C pre-tempered samples showed the best combination of elongation and strength.

Knowledge representation to support EMDAP implementation in advanced reactor licensing applications

The Data, Information, Knowledge, and Wisdom (DIKW) pyramid depicts the general principle of a decision-making process. Various levels of abstraction are required to formalize the available data/information/knowledge with respect to the decision being supported. The Evaluation Model Development and Assessment Process (EMDAP) was developed by the United States Nuclear Regulatory Commission (US NRC) to guide the development and assessment of Evaluation Models (EMs) for transient and accident analysis of nuclear power plants under design basis accidents. It concerns the decision of adequacy of an EM with respect to the purpose of analysis (NPP application). However, lack of data, scaling issues, modeling limitations, computation, and experimental overhead are some of the key factors that challenge the EM adequacy decision in EMDAP. Phenomena Identification and Ranking Table (PIRT) which is used for complexity resolution can also introduce noise due to bias and variance in expert opinion and judgment. The uncertainty in the decision due to these issues and challenges can be minimized by enhancing the EMDAP from the DIKW perspective. In this work, we formulate a systematic scheme for knowledge representation, and classification and characterization of evidence to enhance clarity and transparency in the EMDAP implementation. The proposed scheme is governed by the concept of the value of information, where we contextualize, classify, characterize, and evaluate the evidence (relevant data/knowledge/information related to EM development, verification, validation, and uncertainty quantification) with respect to the relevant decision attributes or elements of EMDAP. We make use of the Predictive Capability Maturity Model (PCMM), Argumentation technique, and process quality assurance for knowledge representation to support EMDAP implementation in advanced reactor licensing applications. The main objective of the proposed scheme is to support decision-making by making it more transparent, traceable, and accountable. The illustration of the proposed scheme is provided using a system simulation code (SAS4A/SASSYS-1) as the primary EM and a generic sodium fast reactor under loss of flow accident as the target reactor application.EMDAP involves different elements that require expert input and insights. However, the process of expert elicitation may require significant resources and time. To address these issues, we identify generative artificial intelligence models as potential tool which (after systematic testing and capabilities analysis) can be used for domain specific expert elicitation and information extraction for efficient implementation of EMDAP.

Impact of the Great East Japan Earthquake followed by the nuclear power plant accident on the nursing students’ academic progress in Soma, Fukushima, Japan: a retrospective cohort study with questionnaire survey

BackgroundThe Great East Japan Earthquake and the subsequent Fukushima nuclear power plant accident in 2011 posed significant challenges to the educational sector, particularly affecting nursing students in the disaster area. However, to the best of our knowledge, there are no reports on the effects of the natural disaster coupled with the nuclear accident on the nursing students. Therefore, this study aimed to determine the impact of the Fukushima disasters on rate of academic failure events in nursing education.MethodsA retrospective cohort approach was conducted, focusing on 677 students from Soma Nursing School admitted between 2001 and 2017. Four failure events—failure to pass the national examination, student retention, suspension, and withdrawal from school—were compared between three time periods: pre-disaster, early peri-disaster, and later peri-disaster. This analysis was followed by a questionnaire survey among the students and an interview with faculty members to gain further insights.ResultsOf the student cohort, 17% had at least one failure event. Students in the later peri-disaster phase faced an elevated failure rate at 29%. Variables such as being male, admission during later peri-disaster period, and local pre-admission residence played a significant role in these failure events in multivariate logistic regression analysis (adjusted odds ratio [95% confidence interval, p value]; 2.63 [1.49–4.64, < 0.001], 3.207 [2.00–5.15, < 0.001], and 1.84 [1.12–3.02, 0.02], respectively).ConclusionsThis study highlights the impact of the Great East Japan Earthquake and the following nuclear accident on nursing education. The elevated failure rates in the later peri-disaster period emphasize the challenges posed by continuing disaster phases. Thus, there is a need for intensified and tailored strategies in nursing education in disaster-affected regions.

Risk and consequence analysis of ammonia storage units in a nuclear fuel cycle facility

AbstractIndustrial disasters, such as unintended toxic gas releases resulting in fires, explosion, and fatalities, are damaging both the global ecology and the social acceptance of the related technology. Risk and consequence analysis is the key feature of process safety measures for the protection of environment and human life. In this work, the risk and consequence analysis of unintended release of anhydrous liquid ammonia for one of the storage tanks, located inside the nuclear fuel cycle facility, was analyzed for leakages leading to exposure of surrounding human population and fire with allied thermal radiation risk. The risk assessment was performed using four methods: Fault tree, E&amp;FI methodology, Probit, and ALOHA, It was observed that while the predicted hazard severities from fault‐tree analysis, Probit analysis, and ALOHA nearly converged, the conventional F&amp;EI, the safety workhorse of the chemical industry estimated low numeric values of the respective hazard. A methodology was proposed to load this general F&amp;EI value for the case of chemical plant being located inside a nuclear facility. Overloaded F&amp;EI procedure estimated hazard value for envisaged unintended ammonia release in good agreement, with results from FTA, Probit, and ALOHA analyses.

Application of methods for the chemical and radiometric monitoring of liquid radioactive waste processing

ABSTRACT The processing and control of liquid radioactive waste (LRW) in nuclear power plants (NPP) are critical aspects of nuclear energy management. This study details the principles of the methods and the measuring instruments used for control, and highlights the features and advantages of chemical and radiometric control in radioactive waste processing. The purpose is to systematize and analyze the results and methods used for chemical and radiometric monitoring, treatment technologies, and adherence to regulatory standards. The paper presents findings from an operating NPP with water–water energy reactor power units, showcasing the novelty of systematizing monitoring methods at each stage of LRW processing and ensuring compliance with regulatory standards. Moreover, the chemical and radiometric indicators in the LRW were analysed, which provides insight into the dynamics of waste processing and classification. In addition, the application of Pearson correlation analysis allowed us to identify the relationships between chemical and radiometric indicators in the LRW, which provides valuable information for waste management practices. The selection of appropriate chemical and radiometric methods is crucial given the complexity of LRW characteristics, making this study relevant for enhancing LRW monitoring and management practices.

Seismic Fragility Assessment of Equipment in Nuclear Power Plant Structures Considering Nonlinear Hysteretic Behavior of Squat Walls

Accurate seismic risk assessment of structures necessitates precise fragility analysis. This study focuses on the seismic fragility assessment of equipment in nuclear power plant structures, particularly emphasizing the influence of nonlinear hysteretic behavior exhibited by squat walls. By developing and comparing linear and nonlinear models of reactor containment and auxiliary buildings within a nuclear power plant, this research elucidates the significant impact of nonlinear behaviors on the seismic response and subsequent fragility curves of associated equipment and systems. Utilizing a lumped-mass stick model, the study efficiently captures the characteristics of squat shear walls, facilitating the calculation of floor response spectra and fragility for nuclear facility structures. The impacts of pinching and degradation, inherent characteristics of a squat wall’s hysteresis under cyclic loading, were identified as significant. These include the shift and change in amplitude of the floor response’s peak, along with amplification in high-frequency domains. Fragility assessments, informed by seismic response analysis, indicate significant variations in fragility curve parameters based on equipment location and frequency. The findings question the effectiveness of traditional response factor methods and general regression techniques in accurately addressing the complex probabilistic seismic demands of equipment, thus highlighting the importance of using direct analysis for calculating fragility in situations with significant nonlinearity.

Online inventory modeling of a CANDU-6 reactor for nuclear forensic applications

To develop the expected isotopic signatures of online nuclear power plants, a CANDU-6 quarter-core reactor was modeled using Serpent, a Monte Carlo and Burnup code. The reactor model was simulated using nominal operating parameters, steady power levels and standard refueling procedures, to set the baseline for online operations. The model was burned for 500 refuelings totaling 1400 effective full power days. The core was divided into 1140 spatially-discrete fuel bundles with each tracking the density of 237 isotopes. Instantaneous core inventory snapshots were recorded at the time of each refueling to create a continuous inventory database. These snapshots provide the expected isotopic densities and ratios for virtually any fuel bundle position or burnup under nominal operating parameters. These values are useful in the event of accidents, short-cycles, or nuclear proliferation. The time-dependent and spatially dependent results for xenon effluent are used to develop an analytical method for calculating the expected International Monitoring System xenon ratio measurements based on fuel bundle leak rates. A possible false-positive nuclear proliferation scenario for a CANDU-6 operating under nominal parameters is also identified.

System design and analysis of thermal power dispatch systems for boiling water reactors

Nuclear power plants are crucial to meeting net zero emission goals and achieving energy sustainability. Integrating these plants with clean energy technologies such as high-temperature steam electrolysis (HTSE) may improve the efficiency and economic competitiveness of these plants. The current study investigates the design and operation of a thermal power dispatch (TPD) system for coupling boiling water reactors (BWRs) to HTSE plants. The TPD system extracts a portion of the steam from the reactor’s main steam line and transfers its thermal energy to an HTSE plant through a power transport loop. A TPD system for 5 % steam extraction has been designed and the system performance during steady and transient operations has been analyzed. The TPD system dispatched a total of 197 MW thermal energy to the HTSE plant under nominal design conditions. Saturated steam at 7.17 MPa from the BWR plant was condensed and subcooled to a temperature of 168 °C, while a mass flow rate of 91.1 kg/s of superheated steam was dispatched to the HTSE plant. Furthermore, the system performance during transient operation showed a continuous transition from the initial hot standby mode to the nominal power dispatch level. The transient simulation results emphasized the importance of investigating component level performance for the TPD system design. The current results will guide future works on the development of integrated energy systems for hydrogen production or process heat applications.