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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11

Non-equilibrium simulations of hydraulic permeation: Role of mechanical boundary conditions in dense membranes

Understanding the mechanisms of water transport in reverse osmosis membranes is critical for improving membrane performance and guiding material design. While classical models describe transport as either solution-diffusion (SD)—involving concentration-driven diffusion through a homogeneous medium—or pore-flow (PF)—involving pressure-driven convection through percolated water channels—their applicability to crosslinked polyamide membranes remains debated. Here, using non-equilibrium molecular dynamics simulations, we investigate the impact of mechanical support conditions on pressure-driven water transport in polyamide membranes across varying crosslink densities and pressure differentials (1000–5000 bar). Two support conditions are considered: graphene-restrained, representing experimentally relevant supported membranes, and freeze-restrained, mimicking a self-supported structure. In graphene-restrained systems, water concentration gradients and constant pressure profiles emerge, consistent with SD theory and incompatible with PF assumptions due to the absence of percolated pores and sub-nanometer voids. In contrast, freeze-restrained systems display uniform water concentration and linearly decreasing pressure at 1000 bar, and exhibit compressibility-induced water gradients and partial percolation at 5000 bar, resembling PF-like behavior. However, the underlying assumptions of PF theory—continuous solvent pathways and pressure transmission through water-filled pores—are not met under most conditions. Our results demonstrate that accurate modeling of reverse osmosis membranes must incorporate realistic mechanical boundary conditions to distinguish between transport mechanisms. For dense polyamide membranes supported by porous substrates, graphene-restrained simulations best reflect experimental setups and support the SD model as the dominant mechanism of water permeation.

molecular dynamics↗

Solid State Quantum Refrigeration Superconducting, Absorption and Measurement Based (Final Technical Report)

During this DOE grant, DE-SC0017890, in place for the past six years, all proposed research was carried out and published in peer-reviewed papers, as well as other projects that emerged during the research. In that effort the research team accomplished all proposed research, as well as many closely related research projects discovered and conceived of during the grant. These works included “Efficient Quantum Measurement Engines”, a work published in Physical Review Letters, giving a theory of quantum measurement-based engines, which uses quantum measurement as a resource. These engines are designed to efficiently convert energy from the stochastic quantum measurement process into useful work. Further publications include “Experimental Realization of a Quantum Dot Energy Harvester”, a joint theory and experimental work in collaboration with the group of Charles Smith in Cambridge, UK, as well as long time theoretical collaborators, Rafael Sánchez and Björn Sothmann. This work, featured as an Editor’s Suggestion in Physical Review Letters, realized an earlier theoretical proposal of ours, whereby two resonant tunneling quantum dots are connected to a central electronic cavity that is heated by a hot energy source. We also published “Superconducting Quantum Refrigerator: Breaking and Rejoining Cooper Pairs with Magnetic Field Cycles” a work done in collaboration with experimentalist Francesco Giazotto from ENS Pisa, Italy, which also resulted in a patent. This paper, published in Phys. Rev. Applied, advanced the concept of a cyclic fridge based on the normal/superconducting phase transition together with layered materials separated by tunnel junctions. We also completed the proposed research on a heat transistor, publishing “Thermal transistor and thermometer based on Coulomb-coupled conductors”, carried out as a collaboration between my group and theorists Splettstoesser (Lund U., Sweden), Sothmann (U. Duisburg-Essen, Germany), and Sánchez (U. Autónoma de Madrid, Spain). We carried out an analysis of a quantum coupled to a quantum point contact as a sensitive thermometer and heat transistor. We found the optimal statistical estimator for the temperature and compared it with experiments on the same type of devices. We also investigated autonomous quantum absorption refrigerators using quantum dots to cool by using a very hot thermal reservoir to drive heat between two other reservoirs. In the article “Quantifying the quantum heat contribution from a driven superconducting circuit”, we demonstrated that for a driven superconducting circuit, we showed heat flow provided by a hot source to the qubit can be switched on and off by varying external parameters, the frequency and the intensity of the driving. In the work “Stochastic thermodynamic cycles of a mesoscopic thermoelectric engine”, we reconsidered the autonomous thermoelectric heat engine in terms of underlying cycles. Rather than periodic behavior, the cycles were stochastic in nature. Nevertheless, by undertaking a graph theoretical analysis of the elementary transport processed, great quantitative and qualitative insight could be found. We also considered the quantum measurement process and showed that a quantum version of Maxwell’s demon could be related to the work extraction of a quantum system, closely related to arrow-of-time measures for quantum measurement, as described in our article “Thermodynamics of quantum measurement and Maxwell's demon's arrow of time”. This work was selected in Phys. Rev. A as an Editor’s Suggestion. A recent preprint titled “Cyclic Superconducting Quantum Refrigerators Using Guided Fluxon Propagation” accomplished an important piece of this grant: to propose a new kind of quantum refrigerator using the dynamics of fluxons in a type II superconductor. This invention envisioned a race-track type geometry where fluxons are confined. By applying a gradient of magnetic field together with electric current in a Corbino geometry, the circulating fluxons can actively cool a cold reservoir, realizing a new type of cyclic superconducting refrigerator. We also investigated the possibility of thermal control from different points of view. The application of quantum measurement to the system gives a new kind of control on the system of interest – we have pioneered this approach and shown that measurement can boost the thermal power of quantum engines as described in “Continuous measurement boosted adiabatic quantum thermal machines”. The ability to have heat flows on demand is an outstanding challenge, and we have provided new solutions to this problem in Thermal control across a chain of electronic nanocavities” for a chain of electron cavities using gating voltage control. The control methods using qubit/qubit coupling to create absorption fridges at their most fundamental level have also been developed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A minor respiratory process with major global implications: is atmospheric methane oxidation in tree stems driven by stem respiration rather than microbial methanotrophy?

Tree stem surfaces are widely recognized as sites of carbon dioxide (CO₂) efflux and oxygen (O₂) influx, reflecting the dynamics of aerobic respiration of photosynthate substrates, such as sugars, delivered via the phloem. Stems are also largely considered passive conduits for methane (CH₄) produced in anoxic soils via microbial methanogenesis, where CH₄ is thought to be transported upward through the transpiration stream and/or diffusion and emitted through stem surfaces and the canopy. However, recent observations from dynamic stem chambers suggest that stems may also act as active sinks for atmospheric CH₄. Despite these findings, the extent and drivers of stem CH₄ consumption remain poorly characterized across biomes, species, and environmental gradients, and its quantitative relationship to stem respiration has not been established. Moreover, previous studies captured only snapshot fluxes, leaving diurnal patterns of CH₄ exchange uncharacterized. Here, we address these limitations by combining real-time measurements of stem CH₄ and O₂ uptake under ambient conditions in a California cherry tree, using a dynamic stem gas exchange system with three chambers receiving a continuous flow of ambient air and automated chamber and reference air sampling every 10 min. Our results confirm that stems of upland trees can actively consume both atmospheric CH₄ and O₂, but with decreasing temperature sensitivity as daily temperatures increase. Early mornings were marked by rapid influxes of both gases, followed by declining uptake as temperatures rose further. Methane uptake was tightly coupled with O₂ influx and represented a minor (0.012% ± 0.002%) fraction of stem respiratory activity, as determined by concurrent O₂ uptake. These findings suggest that while atmospheric CH₄ oxidation is a minor respiratory process in stems, it is strongly linked with stem physiological activity. This challenges the current assumption that terrestrial CH₄ uptake is driven solely by microbial methanotrophy and raises the possibility that living stem tissues may contribute to CH₄ oxidation through an as-yet-unidentified plant-based mechanism.

Atmospheric greenhouse gases↗

In-situ L-TEM observations of dynamics of nanometric skyrmions and antiskyrmions

Nanometer-scale magnetic skyrmions and antiskyrmions exhibit unique dynamical behaviors in response to external stimuli, which are critical for their applications in low-power-consumption spintronic devices. This review discusses recent advancements in in-situ Lorentz transmission electron microscopy (L-TEM) observations of skyrmion and antiskyrmion dynamics, and demonstrates the manipulation and evolution of these textures in various magnetic materials under electric, magnetic, and thermal stimuli. Specifically, the motion tracking of single skyrmions and their clusters, and the deformation and transformation of skyrmions has been demonstrated in chiral helimagnets FeGe, Co 9 Zn 9 Mn 2 , and Co 10 Zn 10 with precise application of electric currents. Skyrmions can undergo dynamic transitions in current-driven skyrmion motions, from pinned states to linear flows, and even exhibit deformation into elliptical shapes, underscoring their topological robustness and dynamic flexibility. In addition, the manipulation of single antiskyrmions and antiskyrmion-lattice phases in (Fe 0.63 Ni 0.3 Pd 0.07 ) 3 P with S 4 symmetry is discussed, highlighting their high mobility and unique sliding capabilities along stripe domains at room temperature, facilitated by nanosecond pulsed electric currents. Finally, the temperature gradient-driven motion and topological transformation of elliptical skyrmions and antiskyrmions in this same material are investigated. In conclusion, the comprehensive insights gained from the L-TEM imaging technique are pivotal in advancing the design and functionality of next-generation skyrmion/antiskyrmion-based spintronic devices.

(Anti)skyrmion↗

Flow Boiling Pressure Drop Characteristics of Next-generation Refrigerants in a Micro‑fin Copper Tube

This paper presents experimental frictional pressure-drop data for flow boiling of R-410A, R-134a, and next-generation alternatives R-454C, R-455A, R-1234yf, and R-1234ze(E) in a horizontal micro-fin copper tube. Tests were conducted over a range of mass fluxes and evaporation temperatures to characterize refrigerant-dependent two-phase pressure-drop behavior. The results show that frictional pressure gradient increased with mass flux and vapor quality and generally increased as evaporation temperature decreased, with liquid viscosity strongly affecting the observed trends. Among the evaluated correlations, the Goto et al. (2001) model gave the best overall agreement with the measurements before optimization. Further optimization of the Kuo and Wang (1996) and Goto et al. (2001) models reduced the overall mean absolute deviation to below 15%, with the optimized Goto (2001) model providing the most consistent predictions across all six refrigerants. The results support improved pressure-drop prediction and evaporator design for next-generation refrigerants in micro-fin tubes.

Hu, Yifeng [ORNL] (ORCID:0000000242875185)↗

DEVELOPMENT OF PLASMA SIMULATION TOOL FOR THE ACCEL-ERATING CAVITIES

Plasma processing of superconducting radio frequency (SRF) cavities has shown an improvement in accelerating gradient by reducing the radiation due to field emission and multipacting. Plasma processing is a common tech-nique where the free oxygen produced by the plasma breaks down and removes hydrocarbons from surfaces. This increases the work function and reduces the second-ary emission coefficient. The hydrocarbon fragments of H2, CO, CO2, and H2O are removed from the system with the process gas which is flowing through the system. Here, we present COMSOL for the first time to simulate the plasma processing of an SRF cavity. In this work, we use Jefferson Lab's C75 SRF cavities design as our case study. Using simulation, we predict the condition of plasma ignition inside the SRF cavity. The simulation provides information about the optimal rf coupling to the cavity, mode for plasma ignition, choice of gas concen-tration, power, and pressure.

Senevirathne, I.↗

"Hidden" hydrothermal technical potential & technoeconomics: Revealing permeability & fluids with more data

Historical hydrothermal estimates have largely relied on temperature or heat flow estimates ignoring the need for natural flowing fluids. More accurate hydrothermal estimates require some indication of permeability and fluids that naturally exist in the subsurface. This paper describes a novel approach that includes proxies of permeability and fluids in hydrothermal estimates by leveraging the relatively data-rich Great Basin. Specifically, nameplate capacities (megawatts) of operating geothermal plants, negative (0 megawatt) locations and 48 geophysical and geologic features are used to used in eXtreme Gradient Boosting (XGBoost) regression to make hydrothermal capacity predictions. Additionally, this work inputs the XGBoost-based hydrothermal predictions into the Renewable Energy Potential (reV) model to quantify technical capacity, its uncertainty and techno-economics. Compared to historical hydrothermal estimates, these predictions adhere to the 37 operating geothermal plants and negative locations. We present a method for subsampling the negative sites to bring the labels into balance that uses the geologic domain knowledge to proportionally represent negatives. Overall, the distributions of the hydrothermal technical capacity and the site levelized cost of energy are respectively much tighter, lower and more accurate than the previous estimates for the Great Basin, as they include geological and geophysical surrogates for permeability and fluids. Percentile (50th and 90th, median and high estimate, respectively) models provide bookends for these metrics.

13 HYDRO ENERGY↗

Flows in the space of interacting chiral boson theories

We study interacting theories of N left-moving and N ¯ right-moving Floreanini-Jackiw bosons in two dimensions. A parametrized family of such theories is shown to enjoy (nonmanifest) Lorentz invariance if and only if its Lagrangian obeys a flow equation driven by a function of the energy-momentum tensor. We discuss the canonical quantization of such theories along classical stress tensor flows, focusing on the case of the root- T T ¯ deformation, where we obtain perturbative results for the deformed spectrum in a certain large-momentum limit. In the special case N = N ¯ , we consider the quantum effective action for the root- T T ¯ -deformed theory by expanding around a general classical background, and we find that the one-loop contribution vanishes for backgrounds with constant scalar gradients. Our analysis can also be interpreted via dual U ( 1 ) Chern-Simons theories in three dimensions, which might be used to describe deformations of charged AdS 3 black holes or quantum Hall systems. Published by the American Physical Society 2024

Ebert, Stephen (ORCID:0000000154670155)↗

Decoupling of redox processes from soil saturation in Arctic tundra

Permafrost thaw in warming Arctic landscapes alters hydrology and saturation-driven biogeochemical processes. Models assume that aerobic respiration occurs in drained soils while saturated soils support methanogenesis; however, saturated soils maintain redox gradients that host a range of anaerobic metabolisms. We evaluated how redox potential and redox-active solutes vary with soil moisture in the active layer of permafrost-affected acidic and non-acidic tundra hillslopes. Oxidizing conditions persisted in highly permeable organic horizons of both unsaturated tussock tundra and saturated wet sedge meadows. Redox potential decreased with depth in all soils as increasing soil bulk density restricted groundwater flow and oxygen diffusion. High concentrations of dissolved iron, phosphate, and organic carbon coincided with redox boundaries below the soil surface in acidic tundra, indicating active iron redox cycling and potential release of adsorbed phosphate during iron (oxyhydr)oxide dissolution. In non-acidic tundra, weatherable minerals affected nutrient dynamics more than redox-driven iron cycling, especially in low-lying, saturated areas where thaw reached mineral soils. The role of thaw depth and the ability of saturated soils to maintain oxidizing conditions in organic surface layers highlight the importance of soil physical properties and hydrology in predicting biogeochemical processes and greenhouse gas emissions.

54 ENVIRONMENTAL SCIENCES↗

Effects of hydrogen isotope species on ITG microturbulence in LHD

Abstract The linear and nonlinear effects of hydrogen isotope species on ion temperature gradient (ITG) instability in the Large Helical Device (LHD) stellarator are studied using radially global gyrokinetic simulation. We found that the coupling range of linear toroidal harmonics depends on the ion mass of the hydrogen isotope. The growth rates of ITG mode are almost the same for H, D, and T plasmas, indicating a gyro-Bohm scaling of ion-mass dependence. The nonlinear electrostatic simulations show that the zonal flow breaks the radially elongated eigenmode structures and reduces the size of the turbulence eddies, which suppresses the turbulence and the ion heat transport in the LHD. The turbulence amplitude without the zonal flow is almost the same for H, D, and T plasmas, while it decreases with increasing ion mass of the hydrogen isotope when the zonal flow is present. The reduction of the turbulent transport with larger ion mass is mostly due to the enhancement of zonal flows by larger ion mass. The ion heat conductivity deviates from the gyro-Bohm scaling for both cases with and without the zonal flow.

Physics↗

Estimating scalar turbulent fluxes with slow-response sensors in the stable atmospheric boundary layer

Conventional and recently developed approaches for estimating turbulent scalar fluxes under stable atmospheric conditions are evaluated, with a focus on gases for which fast sensors are not readily available. First, the relaxed eddy accumulation (REA) classical approach and a recently proposed mixing length parameterization, labeled A22, are tested against eddy-covariance computations. Using high-frequency measurements collected from two contrasting sites (the frozen tundra near Utqiaġvik, Alaska, and a sparsely vegetated grassland in Wendell, Idaho, during winter), it is shown that the REA and A22 models outperform the conventional Monin–Obukhov similarity theory (MOST) utilized widely to infer fluxes from mean gradients. Second, scenarios where slow trace gas sensors are the only viable option in field measurements are investigated using digital filtering applied to fast-response sensors to simulate their slow-response counterparts. With a filtered scalar signal, the observed filtered eddy-covariance fluxes are referred to here as large-eddy-covariance (LEC) fluxes. A virtual eddy accumulation (VEA) approach, akin to the REA model but not requiring a mechanical apparatus to separate the gas flows, is also formulated and tested. A22 outperforms VEA and LEC in predicting the observed unfiltered (total) eddy-covariance (EC) fluxes; however, VEA can still capture the LEC fluxes well. This finding motivates the introduction of a sensor response time correction into the VEA formulation to offset the effect of sensor filtering on the underestimated net averaged fluxes. The only needed parameter for this correction is the mean velocity at the instrument height, a surrogate of the advective timescale. The VEA approach is very suitable and simple to use with gas sensors of intermediate speed (∼ 0.5 to 1 Hz) and with conventional open- or closed-path setups.

58 GEOSCIENCES↗

Cross-scale interaction between microturbulence and meso-scale reversed shear Alfvén eigenmodes in DIII-D plasmas

Abstract This paper reports global nonlinear gyrokinetic simulations that couple meso-scale reversed shear Alfvén eigenmodes (RSAEs) driven by energetic particles (EPs) and ion temperature gradient (ITG) microturbulence driven by thermal plasma, using equilibrium and profiles from DIII-D discharge #159243. In simulations focusing only on the ITG, electrostatic ITG drives a huge thermal ion heat transport, which is reduced by a factor of 10 to a level close to the experimental value in electromagnetic simulation due to finite β effect. In the simulations coupling the RSAE and ITG, ITG can scatter the resonant EP nonlinearly trapped by the RSAE and damp the zonal flows generated by the RSAE. The regulation of the RSAE by the ITG greatly reduces the initial saturation amplitude of the RSAE but increases the RSAE amplitude and associated EP transport to experimental levels in the quasi-steady state. The RSAE effects on the ITG, specifically the stronger zonal flows generated by the RSAE and the RSAE frequency modulation of the ITG-induced thermal ion heat transport, in turn, leads to a reduction of the thermal ion heat transport by more than a factor of 2 . For a stronger background ITG, the regulation of the RSAE by the ITG is stronger, while the RSAE effects on the ITG are weaker. This work highlights the importance of cross-scale coupling in the dynamics of the AE turbulence and EP transport.

Physics↗

From Sim to Real: A Pipeline for Training and Deploying Traffic Smoothing Cruise Controllers

Designing and validating controllers for connected and automated vehicles to enhance traffic flow presents significant challenges, from the complexity of replicating real-world stop-and-go traffic dynamics in simulation, to the intricacies involved in transitioning from simulation to actual deployment. In this work, we present a full pipeline from data collection to controller deployment. Specifically, we collect 772 km of driving data from the I-24 in Tennessee, and use it to build a one-lane simulator, placing simulated vehicles behind real-world trajectories. Using policy-gradient methods with an asymmetric critic, we improve fuel efficiency by over 10% when simulating congested scenarios. Our comprehensive approach includes reinforcement learning for controller training, software verification, hardware validation and setup, and navigating various sim-to-real challenges. Furthermore, we analyze the controller's behavior and wave-smoothing properties, and deploy it on four Toyota Rav4’s in a real-world validation experiment on the I-24. Lastly, we release the driving dataset, the simulator and the trained controller, to enable future benchmarking and controller design.

42 ENGINEERING↗

$$\Lambda $$ polarization in very high energy heavy ion collisions as a probe of the quark–gluon plasma formation and properties

Abstract We have studied the spin polarization of $$\Lambda $$ Λ hyperons in heavy ion collisions at center-of-mass energies $$\sqrt{s_\textrm{NN}}= 200$$ s NN = 200 GeV and $$\sqrt{s_\textrm{NN}}= 5.02$$ s NN = 5.02 TeV carried out at RHIC and LHC colliders. We have calculated the mean spin vector at local thermodynamic equilibrium, including all known first-order terms in the gradients of the thermo-hydrodynamic fields, assuming that the hadronization hypersurface has a uniform temperature. We have also included the feed-down contributions to the polarization of $$\Lambda $$ Λ stemming from the decays of polarized $$\Sigma ^*$$ Σ ∗ and $$\Sigma ^0$$ Σ 0 hyperons. The obtained results are in good agreement with the data. In general, the component of the spin vector along the global angular momentum, orthogonal to the reaction plane, shows strong sensitivity to the initial longitudinal flow velocity. Furthermore, the longitudinal component of the spin vector turns out to be very sensitive to the bulk viscosity of the plasma at the highest LHC energy. Therefore, the azimuthal dependence of spin polarization can effectively constrain the initial hydrodynamic conditions and the transport coefficients of the quark gluon plasma.

Physics↗

Multiphase computational fluid dynamics modeling of reacting flows in absorption columns for carbon capture

First-principles derived computational fluid dynamics (CFD) simulations have been proposed as a fundamental tool for investigating solvent-based CO 2 absorption in packed columns due to their ability to accurately represent the underlying nonlinear, multiscale dynamics. Numerous studies have previously utilized such CFD simulations to investigate hydrodynamics of columns with structured and random packings by assessing the key hydrodynamic metrics such as the interfacial and wetted areas. While mapping such metrics for different conditions is essential to the optimization of absorption columns, it is not sufficient, as the CO 2 capture rate depends also on the coupled, nonlinear dynamics from the underlying chemical reaction kinetics, thermodynamics, and heat-transfer rates. In this work, we present detailed CFD simulation results augmented by incorporating the effects of interfacial physical mass transfer of CO 2 , heat release from chemical reaction kinetics, and thermophysical property variations from resulting temperature gradients. We demonstrate the applicability of the proposed approach in numerically assessing the performance of packed columns by evaluating key hydrodynamic quantities, CO 2 absorption rates, and temperature rise in a reference column with packings that are structurally similar to the Sulzer Mellapak™ 250.Y packing, for different solvent inflow velocities and temperatures. Predictions from simulation results are found to be consistent with the trends in experimental observations from the literature, suggesting that the predictive capabilities of the simulation framework can be leveraged to guide the future development of absorber-column designs and optimized process flowsheets.

Absorption columns↗

Characterizing and improving the performance of molten-salt-steam heat exchangers in concentrating solar power plants

Shell-and-tube heat exchangers (HXs) for steam generation from molten salts in concentrating solar power (CSP) plants experience thermal fatigue due to significant temperature gradients and inherent transient operation. Molten salt-steam HX design lifespans exceed actual lifespans, and, as a consequence, designers overpredict plant profitability and operators neglect appropriate prescriptions to optimize these lifetimes. Here, this study refines HX lifespan estimates with data benchmarked against thermal-fluid mechanical modeling of stress and accumulated fatigue. Reduced-order thermal models of the molten salt-steam, shell-and-tube evaporator and superheater predict transient temperature profiles along the two HXs salt-steam flow paths. The modeled evaporator and superheater temperature profiles enable assessment of cyclic stresses within the HX tubesheets, where molten-salt HX failures are most common. Evaporator and superheater performance data from a current 110 MW elec commercial CSP plant provide a basis for validating the reduced-order HX models. HX life predictions derived from stochastic failure distributions serve as inputs for simulating and optimizing existing plant operations. The impact of the updated lifespans on overall plant revenue depends on operating scenarios. This study suggests that typical ramping rates for a CSP plant with a high-temperature Rankine cycle result in an evaporator and superheater life of approximately 10 and 25 years, respectively, compared to the design target of 30 years. Reduced HX lifespans decrease operational plant revenue on average by 4.6-5.1%. Furthermore, there may be as many as four HX replacements over the 30-year lifetime of the plant; and, purchase agreement loss due to failure to meet contractual production requirements can have ramifications that include the risk of bankruptcy.

14 SOLAR ENERGY↗

Criticality analysis of nuclear binding energy neural networks

Machine learning methods, in particular deep learning methods such as artificial neural networks (ANNs) with many layers, have become widespread and useful tools in nuclear physics. However, these ANNs are typically treated as ‘black boxes’, with their architecture (width, depth, and weight/bias initialization) and the training algorithm and parameters chosen empirically by optimizing learning based on limited exploration. We test a non-empirical approach to understanding and optimizing nuclear physics ANNs by adapting a criticality analysis based on renormalization group flows in terms of the hyperparameters for weight/bias initialization, training rates, and the ratio of depth to width. This treatment utilizes the statistical properties of neural network initialization to find a generating functional for network outputs at any layer, allowing for a path integral formulation of the ANN outputs as a Euclidean statistical field theory. We use a prototypical example to test the applicability of this approach: a simple ANN for nuclear binding energies. We find that with training using a stochastic gradient descent optimizer, the predicted criticality behavior is realized, and optimal performance is found with critical tuning. However, the use of an adaptive learning algorithm leads to somewhat superior results without concern for tuning and thus obscures the analysis. Nevertheless, the criticality analysis offers a way to look within the black box of ANNs, which is a first step towards potential improvements in network performance beyond using adaptive optimizers.

artificial neural network↗

Final Report on Predictive Analyses of PRD as Function of Anomalies

This report summarizes the work completed in FY-2024 to analyze the power reactivity decrement (PRD) concepts of the ARC-100 core. The PRD has been traditionally defined by the reactivity change from a hot zero power (HZP) to a particular power. Consequently, the PRD accounts for the core reactivity changes due to increase coolant temperature gradient axially and radially across the core, and increased fuel temperature. The coolant temperature gradient leads to sodium and structure density changes, to radial core expansion from assembly flowering and bowing (due to axial and radial temperature gradients within the assemblies), and to control rod driveline thermal expansion. The fuel temperature increase associated with coolant temperature and power increases leads to Doppler effect and axial thermal expansion. In this work, the normal operating Hot Full Power (HFP) state is the only power level of interest, so analyses focus on the PRD calculated from HZP to HFP. The PRD has been used to assess the reactor safety features asymptotically in unprotected accident scenarios, including the loss of heat sink (LOHS), loss of flow (LOF), and transient overpower (TOP) without scram. The PRD concept relies on the “global” reactivity coefficients A, B, and C that are estimated based on “individual” reactivity effects (Doppler, sodium density, etc.). The objectives of this work are: 1) to improve and verify the methodology used to calculate the ABC coefficients used in the PRD, 2) to assess if the PRD can be used to reliably identify abnormal events. This report fulfills the FY-2024 scope of WBS#1.15.8.3 activity, “ANL0120 – Predictive Analyses of PRD as function of deformation”. The PRD concept is described in Sections 2. Additional effort in refining the methodology for core bowing modeling is performed in Sections 3. Then, two verification exercises are proposed in Section 4 to benchmark these coefficients based on direct neutronic-only calculations and on dynamic core transient simulations. Finally, the PRD approach is assessed for the detection of several unexpected events, such as primary flow perturbation or improper fuel loading, in Section 5.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗