Future Reactors Research Articles

Enhancing methane production from corn straw via illumination-assisted Fe3O4/g-C3N4 nanocomposite in anaerobic digestion

This study proposes a novel anaerobic digestion (AD) strategy combining recyclable photoactivated nanomaterials with illumination to enhance electronic transfer for anaerobic microorganisms. Results showed that 7000 Lux illumination increased methane production yield and rate. Incorporating Fe3O4 into graphite carbon nitride (g-C3N4) created a recyclable Fe3O4/g-C3N4 (FG) nanocomposite with improved light absorption, conductivity, redox properties, and methane promotion. The highest methane yield from corn straw was achieved with 7000 Lux and 1.5 g/L FG nanocomposite, 22.6% higher than the dark control. The AD system exhibited increased adenosine triphosphate content, improved redox performance, reduced electron transfer resistance, and higher photocurrent intensity. These improvements bolstered the microorganisms and key genes involved in hydrolysis and acidification, which in turn optimized the acetoclastic pathway. Furthermore, this strategy promoted microorganisms associated with direct interspecies electron transfer, fostering a favorable environment for methanogenic activities, paving the way for future anaerobic reactor developments.

Comparison of Monte Carlo Tools for Displacement Calculations for Protons and Heavy Ions Irradiation on Iron and EUROFER97

Abstract Ion irradiation of structural materials for the current and future generation nuclear reactors is a widespread technique used to simulate neutron irradiation in the context of material science research. During the designing phase of irradiation experiments Monte Carlo transport codes are often employed to quantify the radiation exposure, by estimating the displacements per atom (dpa) quantity. From the available displacement calculation codes, four popular choices were selected: cern-fluka, mcnp, phits, and srim. These codes will be used to simulate the irradiation effects of proton and Fe ions on pure iron (G379) and EUROFER97 alloy (a common material in fusion applications) targets. Results coming from the different software are presented in the form of damage profiles and of number of displacements as a function of the primary beam energy. This study identifies discrepancies between the codes' outputs and provides optimized simulation setup parameters.

Depth-resolved deuterium retention analysis in displacement-damaged tungsten using laser-induced breakdown spectroscopy

Fuel retention in plasma-facing components (PFCs) is a critical issue in future nuclear fusion reactors operating with Deuterium-Tritium (DT) regarding nuclear safety and fulfillment of the T cycle. However, during DT plasma operation, highly energetic neutrons will induce damage in the lattice of W PFCs causing enhanced fuel retention in defects or traps. Laser-Induced Breakdown Spectroscopy (LIBS) is a potential tool to monitor the T-content in situ in PFCs of future nuclear fusion devices. This article presents an ex situ study on pre-damaged W material after D plasma exposure to qualify the method and mimic conditions expected in a reactor. ITER grade W samples were displacement-damaged by 10.8 MeV W ions to a damage dose of 0.23 dpa and exposed to low temperature deuterium plasma at low energy in PlaQ. The resulting deuterium concentration was analyzed by using 3He Nuclear Reaction Analysis (depth resolution of ≈150 nm) as a well-established method, and LIBS (picosecond laser pulses, depth resolution of 15 nm). The sample with the highest deuterium concentration showed a deuterium-rich zone up to a depth of 1.13 μm using both techniques. This is close to the expected W ion-induced damage depth of ≈1 μm. The results imply that LIBS as an in situ technique for tritium monitoring could be a viable option for a reactor.

Thermomechanical Processing for Improved Mechanical Properties of HT9 Steels.

Thermomechanical processing (TMP) of ferritic-martensitic (FM) steels, such as HT9 (Fe-12Cr-1MoWV) steels, involves normalizing, quenching, and tempering to create a microstructure of fine ferritic/martensitic laths with carbide precipitates. HT9 steels are used in fast reactor core components due to their high-temperature strength and resistance to irradiation damage. However, traditional TMP methods for these steels often result in performance limitations under irradiation, including embrittlement at low temperatures (<~430 °C), insufficient strength and toughness at higher temperatures (>500 °C), and void swelling after high-dose irradiation (>200 dpa). This research aimed to enhance both fracture toughness and strength at high temperatures by creating a quenched and tempered martensitic structure with ultrafine laths and precipitates through rapid quenching and unconventional tempering. Mechanical testing revealed significant variations in strength and fracture toughness depending on the processing route, particularly the tempering conditions. Tailored TMP approaches, combining rapid quenching with limited tempering, elevated strength to levels comparable to nano-oxide strengthened ferritic alloys while preserving fracture toughness. For optimal properties in high-Cr steels for future reactor applications, this study recommends a modified tempering treatment, i.e., post-quench annealing at 500 °C or 600 °C for 1 h, possibly followed by a brief tempering at a slightly higher temperature.

A RELAP5-3D Model of the Lobo Lead Loop

The goal of our research is to build upon the capability of RELAP5-3D to model molten lead systems. Molten lead has several potential uses in future advanced reactors, like the lead fast reactor or fusion reactors that utilize dual-coolant lead lithium blankets. This potential for use in future generations of reactors highlights the necessity of developing molten lead models to ensure that they can accurately predict thermohydraulic behavior. We have developed a RELAP5-3D model of the Lobo Lead Loop facility located at the University of New Mexico to verify the accuracy of RELAP5-3D via comparison to existing computational fluid dynamics results and analytical calculations. It was found that RELAP5-3D accurately calculated radiative heat transfer (within <1%) when compared to theoretical calculations. In addition, pressure drop calculations done in RELAP5-3D demonstrated reasonable agreement within 20 kPa, mostly within ~7% to 15%, when compared to the computational fluid dynamics model of the facility developed by the University of New Mexico, and captured the dependence of pressure drop on flow velocity accurately. Finally, a hypothetical loss-of-flow transient was imposed on the RELAP5-3D model to determine the feasibility of performing a similar experiment with the Lobo Lead Loop. It was found that such an experiment could be possible, as the RELAP5-3D model indicated that the temperatures of the fluid would not exceed the limiting temperatures of the structure (1658 K) nor the maximum temperature of the electromagnetic pump inlet (823 K). Although there are no experimental data to begin validation, the model will be readily available for future validation studies when the experimental data are generated, especially as the model continues to evolve over time. The results so far demonstrate a promising first step in the verification/validation of the RELAP5-3D model of the Lobo Lead Loop. The highlights from our research are as follows: 1. The Lobo Lead Loop facility at the University of New Mexico is a good candidate for molten lead system code validation. 2. The Lobo Lead Loop currently has extensive pressure drop results from a high-fidelity computational fluid dynamics model, which offers the opportunity for code-to-code verification of pressure drop in RELAP5-3D. 3. A RELAP5-3D model of the Lobo Lead Loop has been developed to begin verification studies and to prepare for potential validation studies. 4. Development of the model will continue throughout the future to prepare for potential validation studies.

High-beta disruption prediction study on HL-2A with instance-based transfer learning

Unmitigated disruptions pose a much more serious threat when large-scale tokamaks are operating in the high performance regime. Machine learning based disruption predictors can exhibit impressive performance. However, their effectiveness is based on a substantial amount of training data. In future reactors, obtaining a substantial amount of disruption data in high performance regimes without risking damage to the machine is highly improbable. Using machine learning to develop disruption predictors on data from the low performance regime and transfer them to the high performance regime is an effective solution for a large reactor-sized tokamak like ITER and beyond. In this study, a number of models are trained using different subsets of data from the HL-2A tokamak experiment. A SHapley Additive exPlanations (SHAP) analysis is executed on the models, revealing that there are different, even contradicting, patterns between different performance regimes. Thus, simply mixing data among different performance regimes will not yield optimal results. Based on this analysis, we propose an instance-based transfer learning technique which trains the model using a dataset generated with an optimized strategy. The strategy involves instance and feature selection based on the physics behind differences in high- and low-performance discharges, as revealed by SHAP model analysis. The TrAdaBoost technique significantly improved the model performance from 0.78 BA (balanced accuracy) to 0.86 BA with a few high-performance operation data.

Induced-aggregates in photocatalysis: An unexplored approach to reduce the noble metal co-catalyst content

Photocatalysis has emerged as a promising and environmentally sustainable solution to produce high-purity hydrogen through ethanol photoreforming. It is commonly accepted that adding co-catalysts, especially noble metals, significantly enhances the catalytic activity of semiconductors. However, the high cost of noble metals such as Pt may limit the real application of this emerging technology. Here we evaluate the possibility of reducing the noble metal loading by creating the appropriate interface between pre-formed semiconductor nanoparticles. Commercial titania (P25) was selected as the semiconductor due to its commercial availability, facilitating the straightforward validation and corroboration of our results. Pt was selected as co-catalyst because one of the most efficient photocatalysts for the ethanol photo-reforming is still based on the use of P25 in combination with Pt. We report that the creation of induced aggregates dramatically improves the total hydrogen produced when very low loadings (≤0.05 wt%) of Pt are used. We have developed a pioneering reactor designed for conducting photoluminescence studies under authentic operational conditions of nanoparticle suspensions in the liquid phase. This approach allows us to obtain the average photoluminescence emission from the P25 agglomerates what it would be impossible to obtain by using standard solid samples holders. Thanks to this equipment, we can conclude that this remarkable improvement of the activity is mainly due to creation of an interface that favors the charge transfer between the particles of the aggregates. According to this, the titania nanoparticles of the agglomerates act as an antenna to collect the photons of the sun-light and produce the photo-excited electrons that will be transferred to the platinum nanoparticles located in the same agglomeration. In contrast, raw P25 with low loadings of Pt would have a high number of titania nanoparticles without platinum, and therefore, inactive. This result would be especially relevant in the case of immobilized photocatalytic systems for real future photocatalytic reactors because the immobilization of the semiconductors would generate similar interactions to the one created by our method. Consequently, the initial semiconductor immobilization followed by the subsequent photo-deposition of the co-catalyst emerges as a promising approach for a substantial reduction of the co-catalyst content.

Experimental confirmation of the linear relation between plasma current and external vertical magnetic field in EXL-50 spherical torus energetic electron plasmas

A three-fluid equilibrium plasma with bulk plasma and energetic electrons has been observed on the Xuanlong-50 (EXL-50) spherical torus, where the energetic electrons play a crucial role in sustaining the plasma current and pressure. In this study, the equilibrium of a multi-fluid plasma was investigated by analyzing the relationship between the external vertical magnetic field (B V), plasma current (I p), the poloidal ratio (β p) and the Shafranov formula. Remarkably, our research demonstrates some validity of the Shafranov formula in the presence of multi-fluid plasma in EXL-50 spherical torus. This finding holds significant importance for future reactors as it allows for differentiation between alpha particles and background plasma. The study of multi-fluid plasma provides a significant reference value for the equilibrium reconstruction of burning plasma involving alpha particles.

Bayesian parameter estimation and evaluation of the K-ω shear stress transport model for plane impinging jets

Numerical simulations with semi-empirical turbulence models are commonly used to model impinging jets, often used for cooling solid surfaces. In this work, the constants in the k-ω shear stress transport model in ANSYS FLUENT are calibrated to experimental velocity and heat transfer data for a plane turbulent impinging air jet to determine if Kennedy-O’Hagan calibration (Kennedy and O’Hagan 2001 J. R. Stat. Soc. B 63 425–64) can improve predictions of near-surface velocities and surface Nusselt numbers for similar flows. Impinging jets have been proposed to cool the target plates of the divertor in future magnetic fusion energy reactors, where simulations are used to estimate divertor performance. The flat-plate divertor (Wang et al 2009 Fusion Sci. Technol. 56 1023–7) uses a plane jet of helium issuing from a B = 0.5 mm slot to cool a surface with radius of curvature of 44B at a distance 4B from the slot. Predictions from the calibrated numerical model are compared with independent experimental data at different flow conditions, as well as surface temperature data for a flat plate divertor test section. The contribution of this work is evaluation of the accuracy of a calibrated turbulence model for modest extrapolations in flow geometry and flow conditions for a plane impinging jet.

Observation of alpha-particles in recent D–T experiments on JET

The fusion reaction between deuterium and tritium, D(T,n)4 He is the main source of energy in future thermonuclear reactors. Alpha-particles (4 He-ions) born with an average energy of 3.5 MeV transferring energy to the thermal plasma during their slowing down, should provide the self-sustained D–T plasma burn. The adequate confinement of α-particles is essential to provide efficient heating of the bulk plasma and steady burning of a reactor plasma. That is why the fusion-born α-particle studies have been a priority task in the second D–T experiments (DTE2) on the Joint European Torus (JET) to understand the main mechanisms of their slowing down, redistribution and losses and to develop optimal plasma scenarios. JET with Be-wall and W-divertor, enhanced auxiliary heating systems and improved energetic-particle diagnostic capabilities, producing significant population of α-particles, provided the possibility for comprehensive studying of the α-particle behaviour. Selected results of the confined and lost α-particle measurements, evidence of α-particle self-heating and assessments of the fusion performance are presented in this paper giving an opportunity for further modelling and extrapolation to the International Thermonuclear Experimental Reactor and burning plasma reactors.

Identification of TRISO pebbles at arbitrary orientation using pairs of X-ray radiographs

TRISO (tri-structural isotropic) fuel is anticipated to be one of the fuel types for future small modular reactors. A TRISO-fuelled pebble in a pebble bed reactor (PBR) consists of thousands of TRISO fuel particles embedded inside a graphite sphere. The diameter of each of the fuel particles is approximately 1 mm. A PBR can contain hundreds of thousands of pebbles, each with a diameter of approximately 6 cm. Unlike in traditional reactor designs, which have a relatively small number of discrete fuel assemblies, the large number of pebbles inside a PBR makes the tracking of individual fuel pebbles difficult. The distribution of TRISO particles within the pebble provides a unique fingerprint that identifies a pebble and can be used to track it. This fingerprint can be determined using a standard X-ray radiograph or a more time-consuming X-ray computed tomography scan. When an individual radiograph is used, the pebble image is compared to a library of reference images of the pebbles. To obtain a good match, the orientation of the pebble must be close to the orientation used for the reference image. As a pebble exits the reactor in a random orientation, the pebble must be reorientated before its identification can take place. This paper discusses the addition of a reference particle in the non-fuelled region of the pebble, as well as the simultaneous acquisition of pairs of radiographs at 90° with respect to each other, to aid pebble reorientation and the development of an identification framework. The framework follows a hybrid approach in which the pebble is first reorientated using machine learning techniques before being identified using traditional computer vision techniques. Other effects such as the impact of transmutation of the elements inside the fuel and the radioactivity of irradiated pebbles are also discussed.

The optimization of the MgO/MgCO3 decarbonation process and machine learning-based improved reactor design approach

MgO/MgCO3 reaction system is considered as a promising candidate of thermochemical heat storage. Most relevant studies focus on the improving the material chemical reaction performance. The reaction process inside the reactor has been less studied. In this study, a comprehensive multi-physics model is developed to analyze the decarbonization process of the MgO/MgCO3 reaction system. Impacts of various factors on the reaction process, including the injected energy flux density, reactor height and configuration of the thermal conductive plate (represented by thermal conductive area ratio) were analyzed. The heat transfer process is identified as the primary hindrance. By increasing the thermal conductive area ratio from 0.085 to 1.16, overall reaction time is decreased by 77 % and temperature difference from the top to bottom is decreased by 86 K. Additionally, a prediction model is developed using machine learning method and the prediction error is less than 5 %. Based on the predictive model, a design guideline was further developed so that various critical factors in reactor design could be explored and optimal choices could be obtained without consuming excessive computational resources. The identified influence laws of key factors and the proposed machine learning-based reactor design guideline may provide valuable insights for future thermochemical reactor designs.

Particle physics using reactor antineutrinos

Nuclear reactors are uniquely powerful, abundant, and flavor-pure sources of antineutrinos that have played a central role in the discovery of the neutrinos and in elucidation of their properties. This continues through a broad range of experiments investigating topics including Standard Model and short-baseline oscillations, beyond-the-Standard-Model physics searches, and reactor flux and spectrum modelling. This Report will survey the state of the reactor antineutrino physics field and summarize the ways in which current and future reactor antineutrino experiments can play a critical role in advancing the field of particle physics in the next decade.

Discovering tungsten-based composites as plasma facing materials for future high-duty cycle nuclear fusion reactors

Despite of excellent thermal properties and high sputtering resistance, pure tungsten cannot fully satisfy the requirements for plasma facing materials in future high-duty cycle nuclear fusion reactions due to the coupled extreme environments, including the high thermal loads, plasma exposure, and radiation damage. Here, we demonstrated that tungsten-based composite materials fabricated using spark-plasma sintering (SPS) present promising solutions to these challenges. Through the examination of two model systems, i.e., tungsten-zirconium composite for producing porous tungsten near the surface and dispersoid-strengthened tungsten, we discussed both the strengths and limitations of the SPS-fabricated materials. Our findings point towards the need for future studies aimed at optimizing the SPS process to achieve desired microstructures and effective control of oxygen impurities in the tungsten-based composite materials.

Modelling and experiment to stabilize disruptive tearing modes in the ITER baseline scenario in DIII-D

The achievement of high gain, stationary conditions in a tokamak scenario aimed at producing fusion energy in the ITER Project is crucial to the demonstration that this form of energy can be used in future reactors to provide cheap and clean energy globally. Disruptions are a challenge for the fusion energy field, in particular for the ‘ITER Baseline Scenario’ (IBS), as reproduced in the DIII-D tokamak. This work shows that a solution has been found for the m= 2/n = 1 tearing modes that have consistently caused disruptions in the IBS: stable operation down to zero input torque was achieved by modifying the current density profile at the beginning of the pressure flattop and the ELM character later in the discharges, guided by previous results showing that the most likely cause of these instabilities is the current density profile. The coupling between sawteeth, n>2 modes and the 2/1 TMs is shown to not be statistically significant, nor the leading origin for the evolution towards instability. Ideal and resistive MHD modeling provide positive verification that a steeper ‘well’ in the region of the q = 2 rational surface leads to worse ideal stability, higher tearing index Δ’ and lower threshold Δ’c for resistive instabilities, consistent with the experimental results. This provides confidence that the methods used in this work can be extrapolated to other devices and applied to avoid disruptions in ITER and pulsed fusion devices worldwide.

Temperature Effects of Nuclear and Electronic Stopping Power on Si and C Radiation Damage in 3C-SiC.

Silicon carbide has been considered a material for use in the construction of advanced high-temperature nuclear reactors. However, one of the most important design issues for future reactors is the development of structural defects in SiC under a strong irradiation field at high temperatures. To understand how high temperatures affect radiation damage, SiC single crystals were irradiated at room temperature and after being heated to 800 °C with carbon and silicon ions of energies ranging between 0.5 and 21 MeV. The number of displaced atoms and the disorder parameters have been estimated by using the channeling Rutherford backscattering spectrometry. The experimentally determined depth profiles of induced defects at room temperature agree very well with theoretical calculations assuming its proportionality to the electronic and nuclear-stopping power values. On the other hand, a significant reduction in the number of crystal defects was observed for irradiations performed at high temperatures or for samples annealed after irradiation. Additionally, indications of saturation of the crystal defect concentration were observed for higher fluences and the irradiation of previously defected samples.

Wall heating by subcritical energetic electrons generated by the runaway electron avalanche source *

Subcritical energetic electrons (SEEs) produced by the runaway electron (RE) avalanche source at energies below the runaway threshold are found to be the primary contributor to surface heating of plasma-facing components (PFCs) during final loss events. This finding is supported by theoretical analysis, computational modeling with the Kinetic Orbit Runaway electrons Code (KORC), and qualitative agreement with DIII-D experimental observations. The avalanche source generates significantly more secondary electrons below the runaway threshold, which thermalize rapidly when well-confined. However, during a final loss event, the RE beam impacts the first wall, and SEEs are deconfined before they can thermalize. Additionally, because the energy deposition length decreases faster than energy, the deposited energy density, and thus the maximum PFC surface temperature change, is larger for SEEs than REs. KORC simulations employ an analytic first wall to model particle deconfinement onto a non-axisymmetric wall composed of individual tiles. PFC surface heating is calculated using a 1D model extended to include an energy-dependent deposition length scale. Simulations of DIII-D qualitatively agree with infrared (IR) imaging only when SEEs from the avalanche source are included. These results demonstrate that SEEs are the dominant contributor to PFC surface heating and indicate that the avalanche source plays a critical role in the PFC damage caused during final loss events. The prominence of SEEs also has important implications for interpreting IR imaging, one of the primary diagnostics for RE-wall interaction diagnosis, despite REs dominating the energy and current density. This result improves predictions of wall damage due to post-disruption REs to estimate material lifetime and design RE mitigation systems for ITER and future reactors.

COMPASS Upgrade: a high-field tokamak for ITER- and DEMO-relevant research

To achieve their goals, future thermonuclear reactors such as ITER and DEMO are expected to operate plasmas with a high magnetic field, triangularity and confinement. To address the corresponding challenges, the concept of the high-field ( BT⩽ 5 T), high-current ( IP⩽ 2 MA) COMPASS Upgrade tokamak was established, and the device is currently being constructed in Prague, Czech Republic. This contribution provides an overview of the priority physics topics for the future physics programme of COMPASS Upgrade, namely: (i) characterisation of alternative confinement modes, (ii) a power exhaust including liquid metals, (iii) operation with a hot first wall and (iv) the influence of plasma shape on pedestal stability and confinement. The main scenarios are presented, as predicted by METIS and FIESTA codes. Pedestal pressure and density are estimated using EPED, multi-machine semi-empirical scaling and a neutral penetration model. Access to detachment is estimated using a detachment qualifier.

Probing nuclear properties and neutrino physics with current and future CEνNS experiments

The recent observation of coherent elastic neutrino-nucleus scattering (CEνNS) with neutrinos from pion decay at rest (π-DAR) sources by the COHERENT Collaboration has raised interest in this process in the search for new physics. Unfortunately, current uncertainties in the determination of nuclear parameters relevant to those processes can hide new physics effects. This is not the case for processes involving lower-energy neutrino sources such as nuclear reactors. Note, however, that a CEνNS measurement with reactor neutrinos depends largely on a (still-missing) precise determination of the quenching factor at very low energies, making its observation more challenging. In the upcoming years, once this signal is confirmed, a combined analysis of π-DAR and reactor CEνNS experiments will be very useful to probe particle and nuclear physics, with a reduced dependence on nuclear uncertainties. In this work, we explore this idea by simultaneously testing the sensitivity of current and future CEνNS experiments to neutrino nonstandard interactions (NSIs) and the neutron root mean square (rms) radius, considering different neutrino sources as well as several detection materials. We show how the interplay between future reactor and accelerator CEνNS experiments can help to get robust constraints on the neutron rms and to break degeneracies between the NSI parameters. Our forecast could be used as a guide to optimize the experimental sensitivity to the parameters under study. Published by the American Physical Society 2024

Critical role of transport phenomena in the performance of a catalytic fixed bed reactor for the CO2 hydrogenation to CH4 evaluated by modeling and simulation

CO2 hydrogenation with renewable hydrogen enables the production of CH4 to be used as energy carrier (CO2 + 4H2 ⇆ CH4 + 2H2O). Steady state 1D pseudo-homogeneous and heterogeneous models, in the absence or presence of mass and energy transport in the axial direction of the reactor and inside the solid phase, are considered to simulate a non-isothermal fix bed reactor. Numerical strategies for solving these models in Matlab R2022b are discussed. The pseudo-homogeneous plug-flow model is not able to describe the experimental results irrespective of the global heat transfer coefficient considered. The inclusion of mass and energy transport in the reactor axial direction is crucial for describing the experimental data. The inclusion of mass and heat transport inside the solid phase by the heterogeneous model enables the best fitting. This work provides a valuable modeling tool for future industrial-scale reactor design.