Nuclear Power Research Articles

Digitalization, Management, and Synthesis of Thermal-Hydraulic Legacy Data Using the Dynamical System Scaling

A unique attribute of the nuclear industry is the extent by which designers, developers, operators, and regulators pay attention to demonstrating the safety case. Nuclear installation resiliency or safety takes overriding priority over function and performance. The preparation of the safety case heavily relies on extensive experimental campaigns that challenge the target design under a spectrum of postulated accident scenarios. For safety reasons, these experiments, typically conducted in subscale test apparatuses intended to reproduce the postulated accident scenarios and event sequences realistically, but subject to proven similarity criteria, are often referred to as scaling analyses. Since the dawn of the nuclear industry, significant resources have been committed to the construction and operation of such test facilities, and a massive amount of data has been generated. Such test data have been and are still used to validate the fundamental assumptions of nuclear power plant phenomena. As we move into the digital world, capturing this multiple decades worth of information in a transparent, easily accessible, and usable manner for the public and industry stakeholders is of paramount importance. Over the last few years, FPoliSolutions has been actively developing an enterprise digital data ontology platform (OGMA) intended to do just that. The goal is to help designers use experimental data to assess their safety case evaluation models. The platform or application programming interface (API) was designed to ontologically organize the experimental data, as well guide the user in the complex analytics associated with the interpretation and use of such test results. The OGMA API supports the user in accessing a library of sophisticated mathematical procedures for performing scaling analyses. For this purpose, the dynamical system scaling (DSS) procedure invented by Dr. Jose’ Reyes was formulated as one of the services in the digital platform. These methods have been demonstrated to provide an excelled mathematical apparatus to identify similarity criteria or quantify distortions between measured data and the target prototypical conditions. Moreover, DSS can provide a level of synthesis across separate effect tests and integral effect tests that has the promise of yielding efficiency in the evaluation code assessment activities, as setting up evaluation models that support the safety case of current and future nuclear power plants is often a daunting and expensive task.

Matching Analysis of Technical Parameters and Safety Standards for Nuclear Replacement of Coal-Fired Units

In the context of the growing share of renewable energy and the impending decommission of a large number of coal-fired units, nuclear energy is the only green energy that can replace coal power for a stable, clean, efficient, and large-scale power supply. This article compares the differences between coal power and nuclear power in terms of thermal system, thermal cycle, turbine parameters, and safety. It discusses the possibility of replacing the boiler of a coal power plant with nuclear power, that is, replacing the boiler of a coal power plant with a nuclear reactor for generation/heating/cogeneration. For coal-fired units with similar capacity that do not use a reheat cycle (at or below high pressure) and nuclear power units (such as a high-temperature gas-cooled reactor), as well as coal-fired units with a reheat cycle (ultra-high pressure and above) and nuclear power units (such as pressurized water reactors), there are great differences in steam parameters. In terms of steam turbines, the size of nuclear power units is relatively larger, requiring additional dehumidification measures. In addition, the safety factors and management methods considered in the site selection, construction, and operation of nuclear power plants are more stringent and complex, and comprehensive analysis and evaluation are needed in aspects such as waste treatment and accident emergency response. Except for the relevant provisions of the American Society of Mechanical Engineers code for pressure vessels, nuclear power units are not compatible with coal-fired units in terms of safety standards. Therefore, considering comprehensively, it is believed that the scheme of nuclear power replacing coal-fired units for power generation/heating/cogeneration program is not feasible at present.

Review on the Application of Living PSA in Nuclear Power

With the increasing standards of safety management in nuclear power plants, Living Probabilistic Safety Assessment (Living PSA) technology has begin to play an increasingly important role in their operation. This paper aims to provide an overview of the application and development of Living Probabilistic Safety Assessment (Living PSA) technology in nuclear power plant safety monitoring and risk assessment, examining the key technologies and future challenges. Initially, we summarize the current safety needs in regard to nuclear power, examine the policy on configuration risk management technology for nuclear power plants, and outline its importance and development process in nuclear power plant safety management. Subsequently, we discuss the basic principle of Living PSAs and the working method of risk monitoring based on Living PSAs, including information monitoring data collection, online identification, real-time model updating, and risk calculation. Within the Living PSA framework, model development is not merely about creating a theoretical or static representation; it is a dynamic and ongoing process that involves a deep understanding and precise simulation of the behavior of nuclear power plant systems and components. This represents the main research efforts in Living PSAs at present. Additionally, this paper identifies the key technologies of Living PSAs in an in-depth manner, such as the reliability-model-updating technology and model building in dynamic reliability analyses, including the fault tree model, multi-layer flow model, GO-FLOW model etc. The paper lists the work of some scholars in this area in recent years, which helps readers and researchers to clearly understand the current progress of Living PSA technologies in terms of model establishment and updating. Finally, the paper summarizes the challenges and future development of Living PSA and emphasizes the possible problems in data quality, human factor engineering, and the development of Living PSA technologies in the future. In the future, Living PSAs will provide more solid support for the realization of safer and more economical methods of operating nuclear power plants.

Theoretical and experimental study on efficient thorium removal from aquatic environment using phosphate-modified graphene oxide polymeric beads

AbstractThorium is an element of immense importance in nuclear industry due to lower environmental impact compared to fossil fuels and conventional nuclear power. In the present study, highly selective adsorption of Th4+ on phosphate modified graphene oxide polymeric beads was investigated. The interaction of –PO4, –OH and –O– functional groups of graphene oxide with thorium ion was thoroughly investigated using Density Functional Theory. The adsorption induced density difference was utilized to investigate the bonding characteristics. The affinity of the Th4+ ions was obtained as –PO4 > –OH > –O– group of the phosphate modified graphene oxide. Phosphate modified Graphene oxide embedded in Calcium alginate matrix was characterized using ATR-FTIR, XRD, SEM and Raman spectroscopy. Highly efficient (> 93%) uptake of thorium at pH 5 with fast rate of sorption (< 5 min) was observed in the batch sorption studies.

Calculation analysis of a severe accident at a nuclear power plant with a sodium-cooled fast reactor

Calculation analysis of a severe accident at a nuclear power plant with a sodium-cooled fast reactor

Effect of forced lateral vibration on flow and heat transfer performance within an annular fuel element

The investigation into the thermo-hydraulic characteristics of fuel elements under forced vibration conditions is of paramount importance in the design and application of offshore nuclear power platforms. This study employs a mathematical model of fluid-solid coupling and applies the theory of multi-field synergy to numerically analyze the flow and heat transfer features in an annular fuel element with internal and external double-sided cooling under forced lateral vibration conditions. The synergistic relationship of each flow field parameter is scrutinized for vibration conditions with frequencies ranging from 0 to 10 Hz and amplitudes from 0.005 to 0.2 m. The results demonstrate that increased amplitude and frequency contribute to enhancing the homogeneity of the temperature and velocity field distributions. Notably, the field synergy angles α, β, ψ, and γ attain minimal values at the gaps (X = 8 mm, X = 25 mm). Furthermore, the variation of vibration frequency and amplitude decreases the mean synergistic angle ψ by 5.14 % and 7.9 % and increases the mean field synergistic angle θ by 23.18 % and 31.21 %, respectively. It indicates that the vibration parameters have the least effect on the synergistic angle ψ and the greatest effect on the synergistic angle θ.

A Comparative Study on Laser Cutting Performance with Varying Speeds at 10 M Underwater

Despite the dismantling structures that are submerged to significant depths of water during the decommissioning of nuclear power plants, there is limited research on deep-water laser cutting processes. A self-designed pressurized chamber was used in this study and successfully conducted the world’s first laser cutting experiment in a simulated 10 m water depth environment. laser cutting was performed in a 10 m underwater environment, and the cutting efficiency was compared to that observed in a 1 m underwater environment. Therefore, A 100 mm thickness of 304 stainless steel was successfully cut underwater, and the highest cutting speed of 100 mm/min was achieved. The result indicates that, as the cutting speed increased during underwater laser cutting, both the heat input and the mass flow rate of the assist gas decreased, resulting in a narrower rear kerf width and an ineffective evacuation of the molten metal.

A numerical study on metallic melt infiltration in porous media and the effect of solidification

The melt infiltration in porous debris is of importance to severe accident prediction and mitigation in nuclear power plants (NPPs), but its mechanism remains elusive. In this study, a computational fluid dynamics (CFD) model is proposed to simulate the evolution of melt infiltration within porous media, incorporating both solidification and melting processes. The CFD model is validated against the experiment (REMCOD facility) and Moving Particle Semi-implicit (MPS) simulation results. Building upon this validated model, the influence of the melt superheat, the initial particle temperature, and its surface wettability on melt infiltration dynamics are mainly analyzed. It is found that increased initial melt superheat enhances melt infiltration length and rate; higher initial particle temperatures promote deeper and faster infiltration, while lower temperatures may result in solidification that blocks further infiltration. Additionally, the wettable particulate bed can enhance melt relocation and heat transfer, but it also accelerates the solidification of the melt, which complicates the infiltration process. Furthermore, phase changes could intensify melt flow instability. This work may expand our understanding of melt infiltration dynamics and pave the way to severe accident modeling in NPPs.

Improved intelligent model predictive controller for the nuclear power reactor system

Abstract Over the last two decades, extensive research has been conducted to enhance the control performance of reactor power. Various methodologies have been suggested and implemented to achieve optimal power control in nuclear reactors. However, due to the diverse characteristics and inherent uncertainties in the models, devising optimal controllers for nuclear systems remains a complex task. To address this, numerous approaches have been adopted to ensure controllability and resilience, aiming for an optimal nuclear power reactor controller. The Model Predictive Control (MPC) algorithm has garnered significant attention as a viable approach to boost operational efficiency and overall system utility. In this research, Particle Swarm Optimization (PSO) method and MPC controller are combined together to form a novel algorithm termed PSO-MPC, aiming to amplify the system’s performance and overcomes the local minima problem that basically happens when using MPC controller. First, MPC controller is applied to the nuclear reactor model, then the suggested technique PSO-MPC also is applied to the system and a comparison of the outcomes using both techniques is done. The results demonstrate enhanced system response using the innovative technique.

Optimizing university-industry collaboration mechanisms for engineering talent development in the nuclear power sector

In the context of the ongoing scientific and technological revolution and industrial transformation, the primary goal of engineering education is to develop innovative and skilled professionals who can address the evolving needs of economic and social development. The success of this endeavor is contingent upon the effectiveness of university-industry collaboration in creating robust talent cultivation models. This study identifies and constructs key elements of a safeguard mechanism for such collaborations, including laws, regulations, management systems, and operational frameworks. A survey was conducted among university and industry leaders engaged in cooperative projects within the nuclear power sector, revealing significant insights into the current state and deficiencies of existing mechanisms. Based on these findings, the study proposes targeted strategies and recommendations for enhancing the effectiveness of these collaboration mechanisms.

Behind the Renewed Interest in Nuclear Power

Electricity demand is outstripping the ability of markets and electric grids to respond quickly to meeting the generation and transmission and distribution system needs for supporting a 21st‐century economy. Electricity demand is increasing faster than it has in decades as manufacturing rebounds, and data centers and cryptocurrency mining operations proliferate across the United States. At the same time, there is mounting pressure on governments globally to reduce greenhouse gas (GHG) emissions in the electricity sector by transitioning buildings and transportation systems away from fossil fuels to electricity.

Research Progress on the Relationship Between Microstructure and Properties of AISI 321 Stainless Steel

AISI 321 stainless steel is widely used in chemical pipelines and nuclear power, prompting research on its high-temperature performance and corrosion resistance. This review focuses on the effects of alloy elements, second-phase particle formation, and heat treatment processes on the microstructure and properties of AISI 321 stainless steel. Fine tuning of alloying elements can affect the mode and effect of dynamic recrystallization, altering the high-temperature flow deformation of AISI 321 stainless steel. In order to achieve phase equilibrium, the relationship between corrosion resistance and high-temperature creep behavior and high-temperature mechanical behavior in the presence of second-phase particles was also analyzed. This review outlines the basic heat treatment procedures for improving material properties, providing a new perspective for solution treatment and improving corrosion resistance. In addition, the latest research progress on other factors affecting the high-temperature performance of AISI 321, such as coatings, was briefly introduced.

Application of iron oxide and its composites containing carbon nanoparticles to the solution of environmental problems

The radioactive materials and the secondary waste after a nuclear power plant accident pose a big environmental problem. The nontoxic iron oxide and iron oxyhydroxide, and their composites with carbon materials were applied to solve the problem. Coal oxide produced by modified Brodie method using coal, NaOH, and γ-Fe2O3 were treated by a hydrothermal process. When the diluted dispersion mixture was treated with SrCl2, the composite particles were attracted to a magnet. On the other hand, the composite without SrCl2 was not attracted. This means only the SrCl2-adsorbed composite can be recovered by a magnet. Hematite doped with various amounts of Nb was synthesized. Its catalytic activities for photo-Fenton reaction were investigated for degradation of methylene blue (MB) in the presence of H2O2 under visible light. Nb-doped hematite calcined at 600 ºC produced smaller particles and showed higher catalytic activity than those calcined at 700 ºC. It was shown that the sample with higher Nb doping showed a better catalytic activity, i.e., the sample with 40 atomic percent of Nb calcined at 600 ºC has the highest catalytic activity. The hematite with 7.4 atomic percent of Nb calcined at 600 ºC showed unique characteristics since it has rapid decomposition rate of MB as well as ferrimagnetic-like characteristics, which makes it separable by a magnet. The polymorphism of iron(III) oxyhydroxide was controlled by adding acetic acid, ethylenediamine, and citric acid. The lepidocrocite obtained by adding the additive of citric acid resulted in the presence of citric acid in the particles and revealed a large specific surface area and negative Zeta potential, which showed an extremely high catalytic activity of MB decomposition for photo-Fenton reaction.

Interaction Parameters of Some Polymers Used in Nuclear Power Plants with Ionizing Radiation, Produced Secondary Radiations and Radiation Damages

AbstractThe primary interactions of polypropylene (PP), poly(vinyl acetate) (PVA), ethylene‐vinyl acetate (EVA), polyvinyl chloride (PVC), polychloroprene (CR) and polyurethane (PUR) polymers preferred in the nuclear industry with gamma and neutron radiations, secondary radiations formed after neutron interactions and damages given to polymers by these ionizing radiations are investigated. The gamma interaction parameters Were determined in the photon energy range of 0.03‐20 MeV using WinXCOM, GEANT4 and FLUKA methods. Also, energy absorption and exposure buildup factors and Kerma parameters are calculated at different photon energies. To investigate the interactions of the studied polymers with neutron, the effective removal cross‐section for fast neutrons with theoretical and the partial neutron rates passing through the studied polymer at 4.5 MeV, 100 eV and 0.025 eV energies are determined with simulation codes. The numbers of secondary gamma‐rays and neutrons Were obtained with GEANT4. The Total Ionizing Dose and Displacements per Atom parameters are studied with the help of FLUKA simulation. It is observed that the interaction of PVC polymer with gamma radiation and PP polymer with neutron particles is higher than the others. The secondary radiation from PVC and CR is less. The PP, PVA, and EVA exhibit superior resistance to radiation damage.

Impact of reactor neutrino uncertainties on coherent scattering's discovery potential

Abstract Nuclear power reactors are the most intense man-made source of antineutrino's and have long been recognized as promising sources for coherent elastic neutrino-nucleus scattering (CE$\nu$NS) studies. Its observation and the spectral shape of the associated recoil spectrum is sensitive to a variety of exotic new physics scenarios and many experimental efforts are underway. Within the context of the reactor antineutrino anomaly, which initially indicated eV-scale sterile neutrino's, the modeling of the reactor antineutrino spectrum has seen a significant evolution in the last decade. Even so, uncertainties remain due to a variety of nuclear structure effects, incomplete information in nuclear databases and fission dynamics complexities. Here, we investigate the effects of these uncertainties on one's ability to accurately distinguish new physics signals. For the scenarios discussed here, we find that reactor spectral uncertainties are similar in magnitude to the projected sensitivities pointing towards a need for $\beta$ spectroscopy measurements below the inverse $\beta$ decay threshold.

Data-Driven Remaining Useful Life Estimation

This paper explores the development and application of data-driven prognostic models for estimating the Remaining Useful Life (RUL) of Nuclear Power Plant (NPP) condensers experiencing tube fouling. Due to the unavailability of run-to-failure industry sensor data, we utilized simulated data generated by the Asherah Nuclear Power Plant Simulator (ANS), initially designed by the International Atomic Energy Agency (IAEA) and programmed in Simulink for cyber security simulations. ANS's adaptability allows it to simulate Pressurized Water Reactor (PWR) behaviors given a time series of operating conditions and to introduce degradation modules to mimic fouling effects. Our study compares two primary approaches applied to data generated by ANS: inference-based and direct prediction methods. The selected inference-based approach estimates the health state of the condenser using a pipeline formed by an Auto Associative Kernel Regressor and a Hidden Markov Model (HMM), which subsequently combines the state estimates with its parameters to predict the RUL. The direct prediction method employs a Gradient Boosting Regressor Decision Tree (GBRDT) to map input variables directly to RUL. Our findings demonstrate the efficacy and limitations of each method through the case study, providing valuable insights for the adoption of data-driven RUL estimation techniques in industrial and energy applications.

Online and Offline Fault Detection and Diagnostics in a Nuclear Power Plant Condenser

Nuclear power plants (NPPs) face significant financial pressures due to operational and maintenance costs. This research investigates Fault Detection and Diagnostics (FDD) techniques to optimize maintenance schedules and reduce expenses. The NPP condenser plays a critical role in converting turbine exhaust steam back into water for reuse. Condenser tube fouling, a prevalent fault mode, impedes heat transfer efficiency and can lead to decreased plant efficiency and safety risks. This study proposes an FDD framework that leverages raw signal analyses from temperature and pressure monitoring to detect and diagnose condenser tube fouling in both online and offline settings. The online approach facilitates close-to-real-time predictions, enabling proactive maintenance strategies. Additionally, the framework explores incorporating a condenser’s maintenance history for enhanced diagnostics. We employ a dataset obtained from a simulated nuclear power plant condenser using the Asherah Nuclear Power Plant Simulator (ANS). ANS replicates the operational dynamics of a pressurized water reactor (PWR) type NPP. The proposed methodology utilizes an encoder-decoder (E-D) structured 1DCNN model to analyze the raw signals. The research demonstrates consistent and accurate fault detection and diagnostics for condenser tube fouling in both online and offline scenarios. A high potential for generalization to unseen conditions was observed. However, online detection using small data windows necessitates caution due to potential false alarms around the transition points. Our findings pave the way for further exploration of robust diagnostics by accommodating a wider spectrum of fouling rates within degradation classes using ANS. This combined online and offline FDD approach offers a promising solution for promoting operational safety, efficiency, and cost-effectiveness in NPP condensers.

A closer look to dose assessment and radiation shielding characteristics of concrete doped magnetite irradiated with 252Cf mixed radiation radionuclide: A Watt Fission approach and Doppler effect

Nuclear radiation emitted by fusion reactors, nuclear power plants, and medical establishments presents potential risks to living organisms personnel, necessitating the implementation of protective measures. To enhance radiation protection for patients workers, various materials can be utilized. Concrete, augmented with various additives, has historically acted as a shielding material. Hence, recent research has predominantly focused on enhancing concrete's ability to attenuate the harmful energy emitted by nuclear sources through modifications to its composition. Accordingly, in the present work, the dose evaluation and radiation shielding characteristics of a range of concrete magnetite (CM) formulations designated as CM-0 (control sample), CM-25, CM-50, CM-75, and CM-100 have been analyzed using MCNPX Monte Carlo (MC) approach and theoretical computations concerning 252Cf mixed radiation radionuclide. In this work, the Watt Fission distribution was employed to derive the neutron spectrum of CM samples, and findings have been thoroughly elucidated in the presence and absence of the specified samples. Then, utilizing the Doppler Effect, the gamma photon spectrum within shielding materials exposed to a spontaneous fission 252Cf source is extracted and characterized. Estimation of Half Value Thickness (HVT) and Mean Free Path (MFP) are provided across a broad spectrum of energy levels. The analysis confirms the successful development of a new type of concrete magnetite (CM) sample that exhibits lower radiation exposure compared to the control sample. This study offers valuable insights into the use of concrete in shielding against mixed radiation radionuclides and opens the door for future research involving similar materials. Specifically, the CM-100 sample demonstrated the lowest half-value thickness (HVT) and provided the most effective reduction of both neutron and gamma radiation. The findings suggest that increasing the concentration of magnetite in concrete greatly enhances its ability to shield against mixed neutron-gamma radiation. This innovation has promising potential for applications in radiation protection, particularly within nuclear reactors and medical facilities. The CM-100 sample showed a notable improvement, achieving an HVT of 0.012 cm and a dose rate reduction of 2.95 × 10−9 Sv.h−1, in contrast to the control sample (CM-0), which had an HVT of 10.358 cm and an equivalent dose rate of 2.84 × 10−9 Sv.h−1. These results underscore the superior shielding properties of the magnetite-doped concrete formulations.

Effective Concrete Failure Area for SC Structures Using Stud and Tie Bar Under Performance Tests

Nuclear power plants, where steel-plate concrete (SC) structures are commonly adopted, require large-scale components to withstand significant loads, such as those caused by sudden explosions. As a result, SC modular members used in nuclear power plants must have thicker walls filled with concrete compared to standard-sized ones. These large walls also require additional components, such as tie bars and H-shaped steel sections, to reinforce adhesion and resist shear stresses. This study focuses on tie bars placed adjacent to studs and evaluates their influence on the tensile strength of wall structures. To investigate this, we conducted experimental tests using full-scale specimens, including various combinations ranging from single stud to combined stud-tie configurations. Based on the results of these performance tests, we propose a design recommendation for estimating the tensile capacity of SC structures, considering the influence of tie bars.

Effects of personal states and personality traits on work performance of commissioning workers in nuclear power plants

Effects of personal states and personality traits on work performance of commissioning workers in nuclear power plants