Advanced Reactor Research Articles

In-Situ synchrotron investigation of elastic and tensile properties of oxide dispersion strengthened EUROFER97 steel for advanced fusion reactors

The augmentation of mechanical properties of reduced activation ferritic martensitic steels through the introduction of creep resistant nano-oxide particles produces a class of oxide dispersion strengthened steels, which have attracted significant interest as candidates for first wall supporting structural materials in future nuclear fusion reactors. In the present work, the effect of temperature on the elastic properties and micro-mechanics of 0.3 wt% Y2O3 oxide dispersion strengthened steel EUROFER97 is investigated using synchrotron high energy X-ray diffraction in-situ tensile testing at elevated temperatures, alongside the non-oxide strengthened base steel as a point of comparison. The single crystal elastic constants of both steels are experimentally determined through analysis of the diffraction peaks corresponding to specific grain families in the polycrystalline samples investigated. The effect of temperature on the evolving dislocation density and character in both materials is interrogated, providing insight into deformation mechanisms. Finally, a constitutive flow stress model is used to evaluate the factors affecting yield strength, allowing the strengthening contribution of the oxide particles to be assessed, and correlation between the thermally driven microstructural behaviour and macroscopic mechanical response to be determined.

First-principles study of behaviors of point defects in Mo-14 Re alloy

Molybdenum alloys with rhenium additions of 14 % (Mo-14 Re) are regarded as structural materials for advanced nuclear reactors. The performance of Mo-14 Re alloy under irradiation is crucial for its application. Irradiation performance is related to the behaviors of point defects produced by irradiation. The behaviors of point defects in Mo-14 Re alloy were investigated using first-principles methods in this work. Compared with the results in pure Mo alloy, the formation energy and the migration energy of vacancy in Mo-14 Re were both reduced, and the migration energy of interstitial dumbbell increased while the formation energy decreased in Mo-14 Re. In Mo-14 Re, vacancy preferred to form and diffuse faster in Re-enriched environment. Knowing the number of Re atoms in the 1NN (first nearest neighbor) shell of the vacancy and saddle point, the vacancy formation energy and migration energy can be estimated. Since the interstitial atom has a certain orientation, the distribution of the atoms around it is anisotropic. To estimate the interstitial formation energy, it was necessary to count the number of Re atoms at the tensile and compressive sites at the 1NN shell around the interstitial. The interstitial motion was three-dimensional (3D) in Mo-14 Re. At 1200 K, the diffusion coefficient of Re atom was a little higher than that of Mo atom, which could lead to the segregation of Re atoms at defect sinks and the formation of Re-enriched phase. It is possible to investigate the longer-term evolution of microstructure using cluster dynamics (CD) or kinetic monte carlo (KMC) techniques based on these results.

An integrated assessment method of real-time source term for high temperature gas-cooled reactor

To address high temperature gas-cooled reactor (HTR) nuclear power plant (NPP) safety analysis and emergency response, this paper proposes an integrated source term assessment (ISTA) method, guided by the principles of reality, rapidity and rationality. The fundamental concept of ISTA is to establish a connection between the theoretical model of source term (ST) calculation and actual conditions of HTR NPPs. According to the ISTA method, STs can be evaluated by mapping key parameters through monitoring variables during any abnormal operational conditions or accident conditions, resulting in a more realistic representation. Furthermore, the output of STs in various typical spaces within an HTR NPP further expands the application scope beyond the development of nuclear emergency protection strategies. In addition, a corresponding tool (ISTAT) for engineering application is developed and the case is given to verify the feasibility. This research highlights the technological advancement affecting radiological release scenarios and avoiding unnecessary conservatism, which also can give reference for other advanced reactor NPPs.

Microstructure and mechanical properties of oxide dispersion strengthened FeNiMnCr high-entropy alloy fabricated by spark plasma sintering

High-entropy alloys (HEAs) strengthened by dispersed oxide nanoparticles are considered potential structural materials used in advanced nuclear reactors. Herein, a novel Y-Si-O nanoparticle-strengthened near-equiatomic FeNiMnCr HEA was prepared via the powder metallurgy method. Microstructural characterizations revealed that the oxide dispersion-strengthened (ODS) FeNiMnCr HEA consisted of the face-centered cubic (FCC) matrix and high-density Y-Si-O nanoparticles (Y2SiO5 and Y2Si2O7). The average diameter and volume fraction of the nanoparticles were counted to be 21.3 nm and 1.02%, respectively. The grain size was reduced from 10.13 μm of the FeNiMnCr HEA to 0.79 μm of the ODS FeNiMnCr HEA. The ODS FeNiMnCr HEA showed a yield strength of 1125 MPa, an ultimate tensile strength of 1137 MPa, and a moderate elongation of 8.3% at room temperature. At 500°C, the ODS FeNiMnCr HEA also had a high yield strength of 662 MPa. Theoretical calculation showed that the high strength of the ODS FeNiMnCr HEA was mainly due to the grain boundary strengthening, dislocation strengthening, and precipitation strengthening.

REACTOR SECTION PRESSURE CONTROL AT DIESEL HYDROTREATING UNIT

Diesel Hydrotreating Units (DHUs) are essential components within petroleum refineries, playing a critical role in the production of clean and high-quality diesel fuel. This abstract provides a comprehensive overview of the mechanisms, necessity, and operational significance of DHUs in the refining process. Firstly, the abstract discusses the fundamental principles underlying the operation of DHUs. The catalytic hydrotreating process is elucidated, highlighting the role of hydrogenation reactions in the removal of sulfur, nitrogen, and aromatic compounds from diesel feedstocks. The synergy between catalysts and hydrogen gas in promoting desulfurization, denitrification, and hydrodenitrogenation reactions is examined, emphasizing the pivotal role of DHUs in enhancing the environmental and performance attributes of diesel fuel. Furthermore, the abstract addresses the imperative need for Diesel Hydrotreating Units. The detrimental impacts of sulfur-containing compounds, such as sulfur oxides (SOx), on air quality and human health are discussed, underscoring the regulatory mandates aimed at reducing sulfur emissions from diesel fuel. DHUs emerge as indispensable tools for compliance with stringent environmental regulations, ensuring the production of low-sulfur diesel fuel that meets or exceeds regulatory standards. Moreover, the abstract emphasizes the operational significance of DHUs within petroleum refineries. Through the integration of advanced reactor designs, catalyst technologies, and process optimization strategies, DHUs enable refineries to achieve efficient desulfurization and meet production targets while minimizing energy consumption and operational costs. The adaptability of DHUs to varying feedstock compositions and processing conditions further underscores their versatility and importance in the refining industry. In conclusion, this abstract provides a comprehensive overview of Diesel Hydrotreating Units, elucidating their mechanisms, necessity, and operational significance in the production of clean and high-quality diesel fuel. By facilitating the removal of sulfur and other impurities from diesel feedstocks. Keywords: Diesel Hydrotreatment Unit, Control Systems, Petrochemical Industry, Efficiency, Safety.

Equilibrium core modeling of a pebble bed reactor similar to the Xe-100 with SCALE

As the nuclear industry moves towards licensing and constructing advanced reactors, new attention has been focused on the advanced reactor designs that have past operational experience, such as pebble-bed high-temperature gas-cooled reactors (PB-HTGRs). Pebble-bed reactor designs have many advantages, such as their higher operating temperatures and online refueling capabilities. However, high-fidelity computational modeling of pebble-bed reactor designs, from reactor startup to operation at equilibrium, is more challenging compared to conventionally fueled reactors due to the continuous movement of the fuel pebbles through the reactor during operation. In previous work at Oak Ridge National Laboratory (ORNL), the SCALE Leap-In method for Cores at Equilibrium (SLICE) was developed around tools within the SCALE code system. This iterative method can effectively generate pebble-bed reactor zone-wise fuel inventories at equilibrium core operation within a reasonable computational time. The objective of this work was to further verify the ORNL SLICE method and to investigate the impact of considering temperature profiles during the application of the method. The SLICE method was applied to a modular high-temperature gas-cooled reactor design based upon publicly available design specifications of the Xe-100 pebble-bed reactor. Upon comparing the results from the SLICE method to published literature, the differences in the eigenvalue keffective were on the order of several hundred pcm (percent millirho). To investigate one possible cause of these differences, a study looking at the sensitivity of the full-core equilibrium keffective and discharge nuclide inventory to temperature was performed by developing equilibrium cores of two additional temperature profiles. From this temperature study, differences on the order of hundreds of pcm for the full-core equilibrium keffective, and up to 15% difference for the discharge inventories were found. These results indicated the strong dependence on temperature that needs to be considered for future work in equilibrium modeling of PB-HTGRs.

An intelligent fault detection and diagnosis monitoring system for reactor operational resilience: Unknown fault detection

Multiple advanced reactor designs envision deployment scenarios that feature reactor operations with significantly reduced operating staff compared to present reactors, or even feature fully autonomous operations. Since many of these new reactor designs, like small modular reactors (SMRs) and microreactors, also include extended fuel cycles which limit inspection intervals, load-following capabilities, and reduced access to critical components, safe and reliable semi- or fully autonomous operations must be enabled through an on-line monitoring (OLM) system that effectively detects and diagnoses any faults in the reactor. This paper presents the development of the Fault Detection Module of the previously proposed intelligent OLM system: the Fault Detection and Diagnosis Monitoring System (FDDMS). The Fault Detection Module monitors various plant parameters from 86 sensors throughout the nuclear power plant and accurately defines operations as nominal or abnormal. The methodology leverages the advantages of unsupervised learning and semi-supervised optimization data-driven techniques to successfully detect any fault in the system in real-time without fault information a priori. This allows the Fault Detection Module to identify any unknown fault that may affect the system. When integrated with the rest of the FDDMS architecture, the Fault Detection Module provides power transient dependent fault detection by using a separate model for steady state, ramping up in power, and ramping down in power operations. This makes the FDDMS especially applicable for load-following reactor systems. The Fault Detection Module architecture features a dimensionality reduction algorithm followed by an anomaly detection method. Three dimensionality reduction techniques: 1) Principal Component Analysis (PCA), 2) Deep Neural Network Autoencoder (DNNAE), and 3) Convolutional Neural Network Autoencoder (CNNAE); and three anomaly detection methods: 1) One-Class Support Vector Machine (OC-SVM), 2) Clustering (DBSCAN), and 3) Reconstruction Error (RecErr) thresholding were compared to find the best model for each power transient dataset. Precision rates, recall rates, F1-scores, and accuracies were used to compare model performance. The best models produced total accuracies of 94.50%, 93.63%, and 91.76% for the steady state, ramp up, and ramp down datasets, respectively, or 99.19%, 98.97%, and 97.09% when omitting 1%-severe fault cases. Specifically, the best performing models for the steady state, ramp up, and ramp down cases were the CNNAE-RecErr, DNNAE-DBSCAN, and CNNAE-RecErr, respectively. Recall rates were calculated for various fault types at multiple severity levels. The results show that the Fault Detection Module can identify any type of fault in the system with a delay of a few seconds on average. Additionally, robustness against noisy sensor data was tested, with models maintaining 100% accuracy at various levels of noise, and an illustrative real-time application of the methodology is provided.

3.0 - MOOSE: Enabling massively parallel multiphysics simulations

The development of MOOSE has kept accelerating since the last release, with over 2,100 pull requests merged over the last 30 months that involved nearly fifty contributors across close to a dozen institutions internationally. The growth in MOOSE's capabilities and downstream applications is reflected in the growth of the community. User support provided on the GitHub discussions forum has steadily increased to nearly 50 daily interactions. New simulation projects, notably to model advanced nuclear reactor and fusion devices, are driving a significant expansion of the capabilities. This paper reports on these developments, with several major released features, new physics modules, and key improvements to the user experience and simulation workflow.

Mobile Robot for Security Applications in Remotely Operated Advanced Reactors

This review paper addresses the escalating operation and maintenance costs of nuclear power plants, primarily attributed to rising labor costs and intensified competition from renewable energy sources. The paper proposes a paradigm shift towards a technology-centric approach, leveraging mobile and automated robots for physical security, aiming to replace labor-intensive methods. Focusing on the human–robot interaction principle, the review conducts a state-of-the-art analysis of dog robots’ potential in infrastructure security and remote inspection within human–robot shared environments. Additionally, this paper surveys research on the capabilities of mobile robots, exploring their applications in various industries, including disaster response, exploration, surveillance, and environmental conservation. This study emphasizes the crucial role of autonomous mobility and manipulation in robots for diverse tasks, and discusses the formalization of problems, performance assessment criteria, and operational capabilities. It provides a comprehensive comparison of three prominent robotic platforms (SPOT, Ghost Robotics, and ANYmal Robotics) across various parameters, shedding light on their suitability for different applications. This review culminates in a research roadmap, delineating experiments and parameters for assessing dog robots’ performance in safeguarding nuclear power plants, offering a structured approach for future research endeavors.

Improved Collision Probability Analysis of the Double-Heterogeneity Problem Based on Matrix Chord Length Correction

Dispersion fuel exhibits excellent safety performance and effectively reduces the risk of radioactive leakage, making it widely applied in high-temperature gas-cooled reactors (HTGRs) and other advanced nuclear reactors. The presence of stochastic media in dispersion fuel leads to the challenging double-heterogeneity problem in neutron transport calculations. Hébert proposed a collision probability analysis model for treating stochastic media, which has been implemented in the DRAGON5 code. As one important basis of derivation, it is assumed in the Hébert model that the neutron transmission probability is identical to the neutron escaping probability in matrix material. In this paper, it is figured out that the assumption is not rigorous for realistic stochastic media. Then, an improved approach based on the Hébert model is proposed to take into account the realistic chord length distribution as well as to ensure the conservation and reciprocity of collision probabilities. The proposed methodology has been implemented in the HTGR lattice physics code XPZ. By numerical analysis against Monte Carlo reference solutions, it is demonstrated that the improved Hébert model with chord length correction gives good accuracy for addressing realistic double-heterogeneity problems.

Performance analysis of integrated Nuclear-Solar Energy system sharing same molten salt thermal energy storage

Advanced nuclear reactors may be deployed with integrated thermal energy storage to improve flexibility and maximize revenue. This presents opportunities for thermal integration with concentrating solar power (CSP) to generate component synergies and/or improve performance. In this study, a computational model is developed for an integrated nuclear and CSP system that both share the same molten salt thermal energy storage (TES). Optimized dispatch schedules are developed subject to various market conditions, and the ratio of the nuclear to CSP thermal output is also varied. Performance of the combined system is compared to separate nuclear and solar plants, to determine if there is an overall benefit that can be derived from sharing the TES. Given sufficient volatility in electricity prices (e.g., under CAISO market conditions), synergies of up to 8% in net revenue are observed as a result of sharing the same TES, primarily due to improved revenue from enabling operation of the turbine closer to its design point, as well as being able to better take advantage of higher electricity prices. The synergy benefits are largest when the nuclear and solar plants have similar thermal output. However, when prices are less volatile the opposite behavior can be observed and it can be preferable to operate the nuclear plant as a baseload generator.

Numerical simulation of cavitation-vortex interaction mechanism in an advanced rotational hydrodynamic cavitation reactor

Hydrodynamic cavitation (HC), a promising technology for enhancing processes, has shown distinct effectiveness and versatility in various chemical and environmental applications. The recently developed advanced rotational hydrodynamic cavitation reactors (ARHCRs), employing cavitation generation units (CGUs) to induce cavitation, have demonstrated greater suitability for industrial-scale applications than conventional devices. However, the intricate interplay between vortex and cavitation, along with its spatial-temporal evolution in the complex flow field of ARHCRs, remains inadequately elucidated. This study investigated the interaction mechanism between cavitation and vortex in a representative interaction-type ARHCR for the first time using the “simplified flow field strategy” and the Q-criterion. The findings reveal that the flow instability caused by CGUs leads to intricate helical and vortex flows, subsequently giving rise to both sheet and vortex cavitation. Subsequently, utilizing the Q-criterion, the vortex structures are identified to be concentrated inside and at CGU edges with evolution process of mergence and separation. These vortex structures directly influence the shape and dimensions of cavities, establishing a complex interaction with cavitation. Lastly, the vorticity transport equation analysis uncovered that the stretching and dilatation terms dominate the vorticity transport process. Simultaneously, the baroclinic term focuses on the vapor-liquid interface, characterized by significant alterations in density and pressure gradients. These findings contribute to a better comprehension of the cavitation-vortex interaction in ARHCRs.

A Consequence-Informed Licensing Path Selection for the Design of Physical Protection Systems at Commercial Nuclear Power Facilities

The survivability of the domestic nuclear power industry depends on the cost-competitiveness of safe and secure nuclear power generation. Advanced reactor design concepts aim to have increased safety margins over traditional large light water reactors (LWRs). With increased safety margins comes the potential for a corresponding decrease in off-site risk to the general public from a hypothetical release of radioactivity due to sabotage or theft. Without sacrificing safety or security, advanced reactor designers may be able to achieve operational cost improvements over current LWRs in part by designing less burdensome physical protection systems (PPSs) and by replacing on-site response forces with off-site response forces. To accommodate these developments, the U.S. Nuclear Regulatory Commission is drafting new rulemakings for physical security when licensing through the current frameworks in 10 CFR 50 or 10 CFR 52 along with drafting an entirely new licensing framework: 10 CFR 53. A novel technology-inclusive consequence-informed methodology for the selection of the optimal licensing path for the design of PPSs at advanced fixed-site commercial nuclear power facilities is presented herein. This methodology proposes integrating security considerations at the beginning of a reactor facility design effort to streamline the licensing process. Off-site total effective dose equivalents at the exclusion area and low population zone boundaries were identified as the key metrics when determining a design’s most appropriate licensing path that in turn affects the design requirements placed upon the PPS. Given these metrics, source-term generation of potential adversary-induced physics-based sabotage actions utilizing severe accident modeling software and off-site plume dispersal modeling were identified as appropriate for determining siting constraints, potential target sets for hypothetical sabotage events, and their subsequent off-site dose consequences. The methodology proposes using the consequence results from the sabotage modeling, in combination with desired cost-saving PPS characteristics, to help inform the licensing path selection. Once a licensing path is chosen, the methodology utilizes the Design and Evaluation Process Outline to evaluate an effective PPS following the licensing requirements placed on the facility. This paper also presents examples of hypothetical commercial nuclear power facilities with varying consequence levels and demonstrations of how to select the optimal licensing pathways for each.

Experimental investigation and prediction of CHF in wire-wrapped rod bundles

The wire-wrapped tight lattice fuel assembly is one of the options for small modular reactors. To clarify the characteristics of critical heat transfer for departure from nucleate boiling, experiments were conducted to investigate the critical heat flux in a wire-wrapped 19-rod bundle. The critical heat flux coincident with associated thermal–hydraulic parameters was obtained under typical pressurized water reactor conditions. Validation of data accuracy was performed to provide confidence in the experiment results. It was found that the critical heat flux in the wire-wrapped rod bundle is sensitive to the change in steam quality at some steam quality regions. Besides, the critical heat flux in wire-wrapped rod bundles has a similar reflection under the effects of local pressure, local mass flux, and steam quality. However, the current correlations tend to overestimate the critical heat flux for a wire-wrapped rod bundle. Hence, further development of KfK-3 correlations was proposed for better prediction of the critical heat flux in wire-wrapped bundles. This work is helpful for rod bundle designs of advanced pressurized water reactors.

Characterization of fluidized bed chemical vapor deposition ZrC coatings on PyC/YSZ kernels deposited under differing conditions

Coated fuel particle architectures with ZrC coatings are candidate fuels for advanced power reactors and space nuclear propulsion (SNP) concepts. Owing to its relevance to SNP, the composition, microstructure, and mechanical properties of eight ZrC coatings prepared by fluidized bed chemical vapor deposition were evaluated. Evaluation by SEM and EBSD showed that all grains were columnar. Across the various examined samples, minor axis diameters varied between 0.3 and 1.1 μm, and major axis diameters varied between 0.4 and 2.3 μm. Major and minor diameters increased with thickness particularly at higher deposition temperatures in which the major grain axis (from an ellipse fit to the grain shape) increased by 2.5 μm over the entire coating. Coatings with higher reactive gas flows and Zr/C concentrations closer to 1 were observed to contain nanocrystalline graphite deposits. Reactive gas flow doubling led to increases in coating thickness from around 10–15 μm to around 22–27 μm.

Data-driven model order reduction for sensor positioning and indirect reconstruction with noisy data: Application to a Circulating Fuel Reactor

Sensor positioning and real-time estimation of non-observable fields is an open question in the nuclear sector, especially for advanced nuclear reactors. In Circulating Fuel Reactors (CFR), liquid fuel and coolant are homogeneously mixed, and thus these reactors will not have internal structures, making sensor positioning in the primary circuit, including the core, an unresolved problem, making most of the core blind to sensors. Thus, the possibility of estimating the system state in the whole domain using a few local measurements has important implications for safety, monitoring, and control both in nominal and accidental conditions. In this context, the integrated Model Order Reduction and Data Assimilation framework offers intriguing opportunities to reliably combine experimental data and background knowledge from a reduced mathematical model. This work discusses and applies innovative methods within this framework, based on the Generalized Empirical Interpolation and the Indirect Reconstruction algorithms, to a proposed concept of CFR. This work aims to identify the optimal sensor positioning within the core and assess the feasibility of reconstructing the quantities of interest starting only from transient sparse data on fuel temperature, possibly noisy, and testing the predictive capabilities of the discussed methods.

Evaluation of neutronic characteristics of accident tolerant fuel concepts in SMART reactor fuel assemblies using DRAGON

The selection of perfect accident-tolerant nuclear reactor fuels necessitates a neutronic study of the various fuels for Small Modular Reactors (SMRs). This study demonstrates a neutronic assessment of 17 × 17 fuel assemblies of Korean SMART (System-Integrated Modular Advanced ReacTor) integral type SMR using three types of Accident Tolerant Fuel (ATF) by the deterministic code DRAGON. These reactors are less expensive to build, have a shorter construction period, are safer, and have a higher power density. Uranium Nitride (UN), Uranium Di-Silicide (U3Si2), and Composite material (70 % UN- 30 % U3Si2) are considered the most potential ATF candidates. The effective multiplication factor (keff), different fissionable materials, neutron poisons, neutron-induced power, decay power, and fuel burnup are investigated as well as presented on graphs and compared from the conventional fuel UO2. Throughout the entire duration of the operation, all four models maintain a critical state while maintaining consistent dimensions. However, due to enrichment and chemical composition differences, it is found that the UN has the highest keff value. UN displayed lower concentration variation for different isotopes, whereas UO2 showed the highest power analysis study among the models. The different approaches to Accident Tolerant Fuel are not quite significant. However, opting for Uranium Nitride (UN) could offer a slight advantage in terms of effectiveness because of the higher power-up rates and burnup as well as increased cycle length when compared to the other three options.

Multiphysics Analysis of PLOFC and DLOFC Accidents in the HTGR-TR

High-temperature, gas-cooled reactors (HTGRs) are promising advanced reactor designs. Leveraging passive safety features, higher core outlet temperatures, previous commercial operational experience, and potential coupling with nonelectrical systems, HTGRs present many advantages over traditional light water reactors and other advanced reactor designs. The High-Temperature, Gas-Cooled Test Reactor (HTGR-TR) is a point design developed by Idaho National Laboratory as a response to the need for the expansion of U.S. test reactor capabilities. The HTGR-TR was designed to serve as a test reactor for Generation-IV small modular prismatic block HTGRs and to provide irradiation data, two crucial contributions to the development of advanced reactors. As in any reactor design, it is necessary to understand the behavior of the reactor during accident scenarios to determine the overall safety of the design. Pressurized loss of forced cooling (PLOFC) and depressurized loss of forced cooling (DLOFC) are two accidents that can occur in HTGRs and that present challenges to decay heat removal. In order to understand the behavior of the fuel during these accidents, the resulting mechanical behavior and fission product migration in the fuel are evaluated. Using the HTGR-TR design, which utilizes tristructural isotropic (TRISO) fuel, a multiphysics analysis during the PLOFC and DLOFC transients was performed. This study utilizes neutronics, thermal hydraulics, and fuel performance modeling to analyze the behavior of TRISO particles during steady-state operation and the described transients. This analysis aims to characterize the hoop stress and strain during the transients, as well as predict fission product migration and radiological release. Due to the startup conditions of the HTGR-TR, the silicon carbide (SiC) layer for both of the transients and steady-state conditions are initially in compression for both the hoop stress and strain. The DLOFC transient at the beginning of cycle was the most challenging overall to the fuel, having the closest to tensile behavior and the closest to tensile strain. Because the integrity of the SiC layer was not challenged during any of the transients, the release of 90Sr and 137Cs was found to be negligible. The PLOFC transient at the end of cycle resulted in the largest 110mAg release and subsequent radioactivity increase. However, the increase in radioactivity was minor when compared to typical operating conditions due to the relatively large diffusivity of 110mAg though SiC at normal operating temperatures. Highlights include Neutronics and thermal-hydraulic modeling generating steady-state and transient conditions for use in fuel performance analysis.2. Detailed BISON analysis demonstrating the excellent performance of TRISO fuel during PLOFC and DLOFC transients.3. Fuel behavior showing negligible fission product release.

Combined advanced oxidation dye-wastewater treatment plant: design and development with data-driven predictive performance modeling

The recalcitrant nature of the industrial dyes poses a significant challenge to existing treatment technologies due to the stringent environmental regulations. This combined with the inefficiency of a single treatment method has led to the implementation of the combination of primary, secondary, and tertiary treatment processes, which fails during complex secondary aeration processes due to variable pH loads of industrial effluent wastewater. This article presents a modified design methodology of a pilot-scale micro-pre-treatment unit using a solar-triggered advanced oxidation process reactor that both effectively controls the influent variability at the source and mitigates textile effluents for making the discharge reusable for different industrial purposes. The proposed modified combination technique of controlled serial processes inclusive of primary, secondary, and tertiary treatment steps with ZnO/ZnO-GO NanoMat-based advanced oxidation process demonstrates complete remediation of industrial grade effluent with effective reuse of the discharge. Further, a reliable prediction model for estimating water quality parameter using machine learning models are proposed. Multi-linear regression and Artificial Neural network modeling provide simple, accurate, and robust prediction capabilities, which are evaluated for the efficiency of the processes. The generated prediction models capture the output parameters within an acceptable level of accuracy (Radj2>0.90)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$({{\\boldsymbol{R}}}_{{adj}}^{{\\bf{2}}}\\, >\\, 0.90)$$\\end{document} and allow compliance with the discharge Inland Water Discharge Standards (IWDS).

Fabrication Aspects and Performance Characterization of α-Al2O3/AlPO4 Based Sandwich Configuration Flow Channel Inserts and Coatings for High Temperature Liquid Metal Applications

Abstract Liquid metals (LMs) exhibit several key characteristics justifying their utilization as coolants and breeders for nuclear fusion reactors and advanced fission reactors. In fusion reactors, the LMs confront an exorbitantly high flow retarding force, due to the magneto-hydro-dynamics (MHD) effect, imposing significant demands on the pumping power and designs of ancillary coolant systems. Corrosion of structural materials leading to activated corrosion products and coolant chemistry control are some of the vital issues common to both fusion and fission reactors employing liquid lead (Pb) and its alloys. To address these concerns, different technological solutions such as flow channel inserts (FCIs) and high temperature compatible corrosion resistant coatings are being investigated to provide a chemical and/or electrical isolation between the LM and structural material for advanced reactors. In this study, three different prototype geometries (circular, square, and 90 deg bend) of steel-insulator-steel sandwich FCIs are fabricated for fusion reactor applications and an extensive characterization of the electrical insulation is performed over an operating temperature range of 100 °C–600 °C. Welding trials and pneumatic pressure tests up to 10 kg/cm2 (g) are performed on the assemblies to validate the electrical and mechanical integrity over typical fusion reactor operational regime. This paper presents detailed fabrication aspects along with quantitative estimations of insulation filling density, electrical insulation performance and, for the first time, a detailed systematic study of insulation degradation resulting from the combined effects of tungsten inert gas (TIG) welding, exposure to pressure and machining operations on these FCIs. The paper also provides critical details derived from the metallurgical examinations and visual observations from the destructive tests executed on the prototypes. Further, from an implementation perspective toward Lead-cooled Fast Reactors (LFRs), a preliminary feasibility assessment of the α-Al2O3/AlPO4 coating is performed through thin film deposition trials on planar and non-planar substrates followed by mechanical characterizations, such as coating thickness, surface roughness, adhesion strength and microhardness. Metallurgical analyses are presented and discussed to assess Pb ingress after 700 h of continuous exposure to molten Pb alloy at 300 °C–400 °C.