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At least 721 records · Page 40

Adaptive Data-Driven Model Predictive Control for Heat Pipe Microreactors

To establish a technical basis for self-regulating microreactors, a model predictive control (MPC) system is investigated to proactively respond to anomalies and disturbances in anticipation of potential deviations from operating setpoints. Due to the difficulty of developing a physics-based surrogate model that can accurately match plant data in various operating conditions, machine learning algorithms are used in MPC, which allow for learning from both simulation and operation data, thus efficiently describing the targeted transient with arbitrary accuracy. However, one of the biggest concerns in applying ML algorithms like artificial neural networks (ANNs) is that the predictive capabilities of ANN are limited by training data. If there are gaps between the training and target domain, the accuracy of an ANN can degrade significantly when it is used to predict unseen data. To improve the predictive capability of ANN and enable a confident use of data-driven MPCs outside the training data, this study proposes an adaptive data-driven MPC framework. The system will monitor the discrepancy between plant responses and surrogate predictions, fine-tune the ANN-based surrogate when a large discrepancy is detected, and continue MPC operation with updated surrogates. The framework is demonstrated on a point kinetic model for microreactors. The hyperparameters of the update strategy, including layers to update, error thresholds, learning rate discount, and number of data points used for fine-tuning, are optimized so the simulated microreactor is able to follow changes in setpoint with the smallest of deviations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Adaptable Data Driven Model Predictive Control for Heat Pipe Microreactors

To establish a technical basis for self-regulating microreactors, a model predictive control (MPC) system is investigated to proactively respond to anomalies and disturbances in anticipation of potential deviations from operating setpoints. Due to the difficulty of developing a physics-based surrogate model that can accurately match plant data in various operating conditions, machine learning algorithms are used in MPC, which allow for learning from both simulation and operation data, thus efficiently describing the targeted transient with arbitrary accuracy. However, one of the biggest concerns in applying ML algorithms like artificial neural networks (ANNs) is that the predictive capabilities of ANN are limited by training data. If there are gaps between the training and target domain, the accuracy of an ANN can degrade significantly when it is used to predict unseen data. To improve the predictive capability of ANN and enable a confident use of data-driven MPCs outside the training data, this study proposes an adaptive data-driven MPC framework. The system will monitor the discrepancy between plant responses and surrogate predictions, fine-tune the ANN-based surrogate when a large discrepancy is detected, and continue MPC operation with updated surrogates. The framework is demonstrated on a point kinetic model for microreactors. The hyperparameters of the update strategy, including layers to update, error thresholds, learning rate discount, and number of data points used for fine-tuning, are optimized so the simulated microreactor is able to follow changes in setpoint with the smallest of deviations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Kinetic study of Ni-M/CNT catalyst in methane decomposition under microwave irradiation

Methane catalytic decomposition has been studied with catalysts that can attenuate the energy of electromagnetic waves to heat and drive the reaction. Herein, we report, for the first time, a comprehensive kinetic study of Ni-M (M=Pd, Cu, or Fe)-CNT catalysts under microwave irradiation. These binary metal alloy nanoparticles have been synthesized on multiwalled carbon nanotube support with solvothermal process. These catalysts showed incredible performance for both absorbing microwave energy and catalyzing the reaction to form carbon nanotubes and hydrogen. Ni-M-CNT has a reaction order of 0.74. 10Ni-1 Pd-CNT, 10Ni-1Cu-CNT, and 10Ni-1Fe-CNT have activation energies at 87, 75, and 69 kJ/mol. The investigation was carried out in a differential reactor. The results indicated that 10Ni-1Fe-CNT had the lowest activation energy due to the increase in microwave susceptibility. Here, this work pioneered the microwave catalytic methane decomposition field as well as paving the way for future electrification of CO x -free hydrogen production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optimizing Ammonia Separation via Reactive Absorption for Sustainable Ammonia Synthesis

Metal halide salts such as magnesium chloride have been shown to be promising candidates for ammonia storage materials for energy storage and agriculture applications due to their ability to incorporate several moles of ammonia per mole of salt. Ammonia exiting a synthesis reactor can be separated from nitrogen and hydrogen by absorption into magnesium chloride. Such an absorption can be more complete and hotter than separation via ammonia condensation, the current standard in the Haber–Bosch process. Here, we discuss the optimal conditions for the cyclic uptake and release of ammonia from the supported magnesium chloride absorbents. An automated system was designed for measuring the nonequilibrium working capacity of the absorbent, as well as the impact of important operating conditions such as absorption and desorption temperature, pressure, and desorption time. Measurements of absorption and desorption kinetics provide insight into the mechanisms involved. The temperatures and pressures during absorption and desorption were designed to use minimal energy input to maximize the uptake and release of ammonia within a reasonable amount of time. In a laboratory-scale bed, absorption has a small unused bed length, so it is largely independent of mass transfer; it is dominated by how fast ammonia is fed to the bed. Yet, desorption is restricted both by the speed of heating the bed and by diffusion out of the absorbent. These measurements provide guidelines for ammonia separations and cycling sorbent materials on a larger scale.

10 SYNTHETIC FUELS↗

Radiation induced athermal diffusivity in uranium mononitride

Uranium mononitride (UN) is one of the ceramic nuclear fuel alternatives to oxide fuel considered for light water reactors and advanced reactor designs. Properties like self- and fission gas diffusivity need to be better understood, given that they influence key fuel performance phenomena such as fission gas swelling and release. In particular, the radiation induced athermal (D 3 ) diffusivity remains challenging to accurately predict and has only been sparsely characterized in UN, despite its importance as it likely governs diffusion at the low temperatures this high-thermal-conductivity fuel form may operate. Molecular Dynamics simulations are used to estimate the mean square displacement induced by a primary knock-on atom (PKA) with a given kinetic energy. These results are combined with the PKA energy distributions obtained from binary collision approximation calculations to obtain the displacement due to a particular fission fragment. Finally, this is combined with experimental fission fragment yields to determine the displacement due to an average fission event and, thus, express the athermal diffusivity as a function of the fission rate density. These results are in excellent agreement with available experimental data. In conclusion, a particular importance is given to the understanding and the quantification of the variability of these results.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Critical and Subcritical Californium Source Driven Noise Analysis Experiments with Fresh PWR Fuels Pins

These experiments were performed in 1983 between August 1 and September 16 and used 35 operational days of critical facility time at the Babcock & Wilcox critical facility in Lynchburg, Va. These measurements were to assess the capability of the Cf source driven noise analysis method to measure the subcriticality of light water reactor fresh fuel configurations. This report documents the experiments of 1983 that were not reported at that time. These measurement with 2.459 wt. % 235 U enriched uranium oxide fresh fuel pins started at the delayed critical configuration of the fully assembled pressurized water reactor (PWR) core configuration with 1511 parts per million (ppm) natural boron (19.8 wt. % 10 B) in the water. This was a cylindrical configuration of 4961 fuel pins. After the initial measurements at delayed criticality, subcritical measurements by the Cf source driven noise analysis method were performed in which the number of detectors and Cf source locations were varied. Additional boron was added to the water moderator and reflector to reduce the neutron multiplication factor, with resulting boron concentrations of 1561, 1613, 1765, 1880, 2104, 2384, 2975, 3606, and 4303 ppm. After the completion of these measurements the increased, the boron concentration was returned to that at delayed critical (1511 ppm) and the reactivity was decreased by reducing the number of fuel pins in steps to 3713, 2553, 1281, 749, and 333 fuel pins and then to that (289) of a s ingle square 17 x 17 pin array, corresponding to a single PW fuel element. For all measurement that started at delayed criticality and then reduced the neutron multiplication factor to various subcritical states, inverse kinetics rod drop measurements at the higher reactivities were also performed but not reported here. At all subcritical states the break frequency noise analysis data was fitted to obtain the prompt neutron decay constant. Some data presented in this report are from notes not in the logbook. The purpose of this report is to document the experimental information for the measurements performed so that a later date someone could perform the required uncertainty and calculational analyses and documentation to use these data for an International Nuclear Criticality Safety Benchmark Program (INCSBEP) or Nuclear Energy Agency (NEA) benchmark. The data from these measurements is available from the Laboratory Records Department of Oak Ridge National Laboratory and the logbook is available from INCSBEP at Idaho National Laboratory.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Runaway electron seed formation at reactor-relevant temperature

Systematic variation of the pre-disruption core electron temperature (T e ) from 1 to 12 keV using an internal transport barrier scenario reveals a dramatic increase in the production of ‘seed’ runaway electrons (REs), ultimately accessing near-complete conversion of the pre-disruption current into sub-MeV RE current. Injected Ar pellets are observed to ablate more intensely and promptly as T e rises. At high T e , the observed ablation exceeds predictions from published thermal ablation models. Simultaneously, the thermal quench (TQ) is observed to significantly shorten with increasing T e —a surprising result. While the reason for the shorter TQ is not yet understood, candidate mechanisms include: insufficiently accurate thermal ablation models, enhanced ablation driven by the seed RE population, or significant parallel heat transport along stochastic fields. Kinetic modeling that self-consistently treats the plasma cooling via radiation, the induced electric field, and the formation of the seed RE is performed. Including the combined effect of the inherent dependence of hot-tail RE seeding on T e together with the shortened TQ, modeling recovers the progression towards near-complete conversion of the pre-disruption current to RE current as T e rises. Measurement of the HXR spectrum during the early current quench (CQ) reveals a trend of decreasing energy with pre-disruption T e . At the very highest T e (≈ 12 keV), ≈ 100% conversion of the thermal current to runaway current is found. The energy of this peculiar RE beam is inferred to be sub-MeV as it emits vanishingly few MeV hard x-rays (HXRs). These measurements demonstrate novel TQ dynamics as Te is varied and illustrate the limitations of treating the RE seed formation problem without considering the inter-related dependencies of the pellet ablation, radiative energy loss, and resultant variations of the TQ duration. Finally, if the observed shortening of the TQ with increasing T e extends to fusion-grade plasmas, than their propensity to form large quantities of RE seeds at high T e may be far worse than previously thought. Positively, the high T e scenario in DIII-D produces REs so prodigiously that it can serve as a meaningful new platform for demonstrating RE avoidance techniques.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Particle Size Optimization of Thermochemical Salt Hydrates for High Energy Density Thermal Storage

Thermal energy storage (TES) solutions offer opportunities to reduce energy consumption, greenhouse gas emissions, and cost. Specifically, they can help reduce the peak load and address the intermittency of renewable energy sources by time shifting the load, which are critical toward zero energy buildings. Thermochemical materials (TCMs) as a class of TES undergo a solid–gas reversible chemical reaction with water vapor to store and release energy with high storage capacities (600 kWh m −3 ) and negligible self‐discharge that makes them uniquely suited as compact, stand‐alone units for daily or seasonal storage. However, TCMs suffer from instabilities at the material (salt particles) and reactor level (packed beds of salt), resulting in poor multi‐cycle efficiency and high‐levelized cost of storage. In this study, a model is developed to predict the pulverization limit or R crit of various salt hydrates during thermal cycling. This is critical as it provides design rules to make mechanically stable TCM composites as well as enables the use of more energy‐efficient manufacturing process (solid‐state mixing) to make the composites. The model is experimentally validated on multiple TCM salt hydrates with different water content, and effect of R crit on hydration and dehydration kinetics is also investigated.

25 ENERGY STORAGE↗

Probing O 2 -dependence of cyclopentyl reactions via isomer-resolved speciation

Modeling chemical kinetics relevant to low-temperature combustion requires complete description of reactions involving critical species such as hydroperoxyalkyl radicals, Q̇OOH, which undergo competing unimolecular reactions and bimolecular reactions with O 2 . The balance of flux across the two pathways affects rates of chain-branching and depends on temperature, pressure, and oxygen concentration. Accordingly, the influence of [O 2 ] on product formation from alkyl + O 2 reactions and the subsequent fate of Q̇OOH and related products is central to the development of an accurate chemical kinetics mechanism. Furthermore, chemical reactions consuming Q̇OOH-mediated species are often simplified to such a degree that mechanism truncation error (uncertainty derived from incomplete reaction networks) becomes significant.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Study of vacuum ultraviolet emission in helium and helium/nitrogen mixtures

Helium is frequently used as a working medium for the generation of plasmas and is capable of energetic photon emissions. These energetic photon emissions are often attributed to the formation of helium excimer and subsequent photon emission. When the plasma device is exposed to another gas, such as nitrogen, this energetic photon emission can cause photoionization and further ionization wave penetration into the additional gas. Often ignored are the helium resonance emissions that are assumed to be radiation trapped and therefore not pertinent to photoionization. Here, experimental evidence for the presence of helium atomic emission in a pulsed discharge at ten’s of Torr is shown. Simulations of a discharge in similar conditions agree with the experimental measurements. In this context, the role of atomic and molecular helium light emission on photoionization of molecular nitrogen in an ionization wave is studied using a kinetic modeling approach that accounts for radiation dynamics in a developing low-temperature plasma. Three different mixtures of helium at a total pressure of 250 Torr are studied in simulation. Photoionization of the nitrogen molecule by vacuum ultraviolet helium emission is used as the only seed source ahead of the ionization front. It is found that even though radiation trapped, the atomic helium emission lines are the significant source of photoionization of nitrogen. The significant effect of radiation trapped photon emission on ionization wave dynamics demonstrates the need to consider these radiation dynamics in plasma reactors where self-absorbed radiation is ignored.

42 ENGINEERING↗

Integrated simulation of U-10Mo monolithic fuel swelling behavior

Here, a separate computational branch has been implemented within the DART (Dispersion Analysis Research Tool) computational code to simulate the swelling behavior of U-10Mo monolithic fuel under the operating conditions of high-power research and test reactors (RTRs). The monolithic branch of the DART code implements a mechanistic rate-theory-based fission-gas-behavior model for the calculation of fission gas swelling, as well as a suite of thermal, physical, and mechanical models to take into account various processes occurring in RTR fuels during irradiation. In order to accurately simulate and eventually predict U-10Mo monolithic fuel irradiation behavior, the code uses materials properties calculated with lower length-scale computational methods, such as gas atom diffusivity and U-Mo surface energy from atomic simulations and grain-morphology-specific recrystallization kinetics (recrystallized fuel volume fractions vs. fission density) predicted using the phase-field method. The remainder of fission gas behavior parameters used in the model were calibrated with measured intergranular bubble size distributions. With this integrated simulation approach, the swelling behavior of U-10Mo monolithic fuel was simulated for various initial grain sizes at different operating conditions and compared with measured data. Furthermore, because limited experimental data exist for parameter calibration detailed sensitivity studies for the important parameters used in the fission gas behavior model were performed in order to examine their impact on both intergranular gas bubble morphology at low fission density, and on total porosity at high fission density.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Supercritical Water Oxidation: Testing of Ersatz Wastewater

Supercritical Water Oxidation (SCWO) technology is under consideration by NASA for treatment of wastewater and other wet waste streams. The dramatic changes in water's thermophysical properties near its critical point (374◦C and 22 MPa) result in nearly complete solubility of organics and gases. The absence of inter–phase transport processes and phase separation results in dramatically reduced reaction timescales and the elimination of complications of two–phase transport and processing in reduced gravity. Other advantages are that the product streams are microbially inert,benign, amenable to resource recovery and organic waste. This paper first described the design and construction of tubular SCWO reactor built at NASA Glenn. It consists of separate wastewater and oxidizer inlets, which are independently heated and pressurized to conditions approaching the critical point of water. These flows enter a reactor chamber having a volume of 62 ml. The reactor section is heated to the desired temperature in the range of 450 ◦C – 650 ◦C. A pressure regulator maintains the operating pressure nominally between 27.6 MPa and 28.3 MPa. The reacted fluid is captured downstream of the pressure regulator during an experiment run. A separate vent line may also be used for collection of the effluent. Next, the results of SCWO experiments using both a representative organic (ethanol) as well as a wastewater simulant provided by NASA Ames are presented. Raman analysis of the pre–reacted and post–reacted solutions are presented. Finally, initial efforts on supplementary chemical kinetics modeling of ethanol oxidation with and without inclusion of a nitrogenous compounds (ammonia) are presented.

Michael C Hicks↗

Automated Control for Nuclear Thermal Propulsion Start-Up using MOOSE-based Applications

This report presents a Griffin/Bison/RELAP-7 numerical model of a prototypical NTP system that features fuel assemblies arranged in rings, and which was designed to simulate rapid startup transients. The physics modeled include full-core neutronics, assembly-wise heat conduction, and conjugate heat transfer, with the balance of plant mainly imposed through boundary conditions. In addition, various forms of automated reactivity control were deployed by using the MOOSE to autonomously drive the model and simulate the reactor transitioning from assumed initial conditions to nominal power in a fraction of a minute. To generate the cross-sections of the neutronics model, and in an effort to simultaneously account for the tremendous axial temperature gradients in the reactor and to limit the number of state points required for cross-section generation, the average component temperatures and hydrogen densities in the cooling channels were correlated to the average fuel and moderator temperatures, and fixed axial profiles were derived for nominal conditions and then used during the transient. With this approximation, a tractable cross-section library tabulated with fuel/moderator temperatures and CD angles was generated using Serpent. The full-core SPH correction procedure and the CD decusping technology in Griffin, respectively, ensure preservation of the multiplication factor and reaction rates at state points, along with a reasonably accurate reactivity worth between tabulated CD angles, despite using a coarse mesh. Feedback from other physics was calculated by modeling one representative fuel assembly per ring, along with the corresponding fuel and moderator cooling channels. To limit power overshoots during startup, another layer of multiphysics coupling was added to the model in order to automatically control the drums. Two different technologies presented herein showed outstanding performance in this regard: (1) a novel hybrid PID controller based on both power and reactivity signals, and (2) a PGC that relies on kinetics parameters and reactivity coefficients to predict future behavior and adjust the desired signal accordingly. A challenging benchmark was devised, featuring a power demand curve that exponentially increases by a factor of 500 within 30 seconds, then levels out after that. Both control approaches create a simulated power curve that closely follows the power demand curve and limits power overshoots to 1% or less. While the former approach requires more tuning of the internal parameters, the latter requires additional knowledge of the reactivity feedback coefficients and rates of change of the corresponding variables, including fuel and moderator temperature, which could be difficult to dynamically measure for a real NTP system. Fortunately, some inaccuracy in these quantities will not drastically degrade the PGC performance. Subsequently, a more realistic startup sequence was considered, in which the mass flow rate and outlet pressures are ramped up to model bootstrap and thrust build-up phases prior to reaching steady-state conditions, demonstrating the ability of the hybrid PID and PGCs to handle such transients, with both types of controllers exhibiting very similar behavior. Nevertheless, a significant chamber temperature overshoot was observed, caused by the demanded power signal and assumed mass flow rate. This issue could be mitigated by deploying a reactor controller that follows the chamber temperature signal and actuates both the control valves and drums (rather than using a power signal based solely on the drums to control reactivity). Enhancement of the hydrogen fluid properties available in MOOSE, as well as a better understanding of prototypical initial conditions, are also needed to further enhance this startup model. Finally, a study was performed to model decay heat post-shutdown, and to prepare for extending this model to predict shutdown behavior and post-shutdown pulsed cooling requirements.

33 ADVANCED PROPULSION SYSTEMS↗

Plasma-Catalytic Ammonia Synthesis beyond the Equilibrium Limit

In this work, we explore the consequences of nonthermal plasma-activation on product yields in catalytic ammonia synthesis, a reaction that is equilibrium-limited at elevated temperatures. We employ a minimal microkinetic model that incorporates the influence of plasma-activation on N 2 dissociation rates to predict NH 3 yields into and across the equilibrium-limited regime. NH 3 yields are predicted to exceed bulk thermodynamic equilibrium limits on materials that are thermal-rate-limited by N 2 dissociation. In all cases, yields revert to bulk equilibrium at temperatures at which thermal reaction rates exceed plasma-activated ones. Beyond-equilibrium NH 3 yields are observed in a packed bed dielectric barrier discharge reactor and exhibit sensitivity to catalytic material choice in a way consistent with model predictions. The approach and results highlight the opportunity to exploit synergies between nonthermal plasmas and catalysts to affect transformations at conditions inaccessible through thermal routes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Influence of ozone addition on the low-temperature oxidation of dimethyl ether in a jet-stirred reactor

The influence of ozone addition on the low-temperature oxidation of dimethyl ether (DME) was investigated experimentally in an atmospheric-pressure jet-stirred reactor, over the temperature range of 400–800 K. Detailed speciation information was obtained by employing synchrotron vacuum ultraviolet photoionization mass spectrometry. Experimental results revealed that the ozone addition had a positive influence on the production of the highly reactive intermediates. Moreover, the low-temperature reactivity of DME was significantly enhanced, which resulted in the broadening of the temperature window of fuel consumption and intermediates formation at lower temperatures. Therefore, novel experimental data of the low temperature regime (400–500 K) could be obtained. The data set of this special temperature regime yielded insights into the DME low-temperature kinetics, which were further supported with modeling analysis based on two existing DME models (Metcalfe et al., 2013; Wang et al., 2015) combined with an ozone sub-mechanism (Zhao et al., 2016). The analysis showed that temperature-sensitive reactions such as the second oxygen channel could be nearly “frozen” at this low temperature (T < 440 K). Furthermore, the production of some intermediates was found to be strongly governed by reaction pairs, such as CH 3 OCH 2 + O 2 = CH 3 OCH 2 O 2 and CH 3 OCH 2 + O 2 = 2 CH 2 O + OH for the CH 2 O formation. This finding could be useful for examining branching ratios in both models, and the analysis suggested the further modification of the branching ratios for the oxygen addition to CH 3 OCH 2 O 2 pathways and the CH 3 OCH 2 O 2 self-reactions were required. Finally, the influences of the O 3 addition in the sensitive reactions of the fuel initial low-temperature oxidation were investigated in this work. It was interesting to note that O 3 addition could change the dominating reactions in the initial low-temperature oxidation, by the addition of some O 3 -related pathways with relatively high sensitivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Influence of aluminum source and Ni/Al ratio in a batch stirred tank reactor on the structure, morphology, and electrochemical performance of Ni-rich NMA cathodes

Here, the structural, morphological, and electrochemical performance of Ni-rich LiNi 0.9 Mn 0.05 Al 0.05 O 2 (955NMA) and LiNi 0.85 Mn 0.05 Al 0.1 O 2 (85,510) cathodes strongly depends on the properties of their hydroxide precursors. Ni-Mn-Al hydroxide precursors were synthesized through controlled co-precipitation in a batch stirred tank reactor, where pH, reaction time, metal-ion feed rate, aluminum source, and aluminum concentration were systematically varied to tailor particle morphology, phase composition, and dopant distribution. Two aluminum sources, aluminum nitrate and sodium aluminate produced two distinct hydroxide precursors NMA(OH) 2 -1 and NMA(OH) 2 -2, which were lithiated to form LiNMA1 (Li 0.992 [Ni 0.905 Mn 0.049 Al 0.046 ]O 2 ) and LiNMA2 (Li 0.990 [Ni 0.850 Mn 0.047 Al 0.103 ]O 2 ). Structural and compositional analyses revealed that aluminum incorporation and phase formation in Ni–Mn–Al hydroxides are governed by local supersaturation and interfacial growth kinetics. Rapid dilute aluminum addition produced aluminum-free β-phase hydroxides, intermediate conditions generated mixed α/β phases, whereas slow concentrated dosing enabled uniform aluminum incorporation and stabilization of the β-phase structure. LiNMA1 delivers a high initial discharge capacity of 223 mAhg −1 but significant capacity fading with 67% retention after 100 cycles, associated with structural instability. In contrast, LiNMA2 delivers a lower initial capacity 172 mAhg −1 yet excellent cycling stability 91% retention, attributed to improved TM–O framework stability and reduced cation disorder.

Capacity↗

Assessing the impact of alpha particles on thermal confinement in JET D-T plasmas through global GENE-Tango simulations

The capability of the global, electromagnetic gyrokinetic GENE code interfaced with the transport Tango solver is exploited to address the impact of fusion alpha particles (in their dual role of fast particles and heating source) on plasma profiles and performance at JET in the discharges with the highest quasi-stationary peak fusion power during the DTE2 experimental campaigns. Employing radially global nonlinear electromagnetic GENE-Tango simulations, we compare results with/without alpha particles and alpha heating. Our findings reveal that alpha particles have a negligible impact on turbulent transport, with GENE-Tango converging to similar plasma profiles regardless of their inclusion as a kinetic species in GENE. On the other hand, alpha heating is found to contribute to the peaking of the electron temperature profiles, leading to a 1 keV drop on the on-axis electron temperature when alpha heating is neglected in Tango. The minimal impact of alpha particles on turbulent transport in this JET discharge–despite this being the shot with the highest fusion output–is attributed to the low content of fusion alpha in this discharge. To assess the potential impact of alpha particles on turbulent transport in regimes with higher alpha particle density, as expected in ITER and fusion reactors, we artificially increased the alpha particle concentration to levels expected for ITER. By performing global nonlinear GENE standalone simulations, we found that increasing the alpha particle density beyond five times the nominal value lead to significant overall turbulence destabilization. These results demonstrate that an increased alpha particle concentration can significantly impact transport properties under simulated JET experimental conditions. However, these findings cannot be directly extrapolated to ITER due to the substantial differences in parameters such as plasma size, magnetic field, plasma current, and thermal pressure.

energetic particles↗

Optimizing chemistry for designing oxidation resistant FeCrAl alloys

Abstract Traditionally, FeCrAl alloys played an important role in high-temperature applications due to their ability to form a passive Al oxide film at temperatures above ~ 800 °C. Recently, FeCrAl alloys became of interest for the application of accident tolerant nuclear fuel cladding. This study covers work done at GE Research for better understanding the role of Al, Cr, and Mo in oxidation kinetics and thermodynamics. Several models and commercial prototype alloys have been tested in hydrothermal corrosion autoclave loops, at low temperature steam exposure (~ 400 °C), high temperature steam exposure (~ 1000 °C or higher), and high temperature air exposures. The results provide insights on how chromium and aluminum play a significant role in both high temperature and low temperature oxidation of FeCrAl. Additionally, machine learning tools are used to gain further insights on both predicting future optimized chemistries for balancing the properties of hydrothermal corrosion, low and high temperature steam oxidation, and thermal aging (which is exacerbated due to radiation in a nuclear reactor environment). GE plans to use this framework to further optimize the FeCrAl alloy system for use in nuclear reactor environments. Graphical abstract

Roy, Indranil (ORCID:0000000336124323)↗