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DOE OSTI2025

Uncertainty quantification of a physics-informed model based on sparse identification of a Thermal Energy Distribution System

Integrated energy systems (IES)s are crucial for enhancing the economy and efficiency of power generation sources (e.g., nuclear energy) necessary to unleash American energy dominance. These systems can be integrated with thermal energy storage (TES) and intermittent renewable energies to optimize overall energy use, peak-load regulation, and demand-side responses. However, the stabilization of energy generation, transport, and utilization introduces operational complexities that exceed the challenges of managing each sub-component individually. Currently, though IESs rely on human operators for efficiency and stability, reducing human error risk and enhancing performance through automation is highly desirable. Recent advances at Idaho National Laboratory have demonstrated successful control of the Thermal Energy Distributed System (TEDS). However, the automatic control system depends on a deterministic Sparse Identification of Nonlinear Dynamics with Control (SINDyC) model, which are trained based on simulation data from physics-based simulations. Because of uncertainties in physics-based simulation, SINDyC model results in large discrepancies against experimental data and cannot be reliably used in automatic control. In this paper, we present an innovative approach to address these discrepancies by quantifying uncertainties and developing a more robust model. We first generated trajectories by using first-principles physics codes to encapsulate the experiment. Next, we trained thousands of models by randomly sampling these trajectories. We then collapsed all those models into one probabilistic SINDyC by fitting a multivariate Gaussian distribution onto the resulting coefficient’s distribution. Despite its simplicity, our approach successfully produced 95% confidence intervals that captured the experimental trajectories. It even did so with a higher probability and better U-pooling score across six of the seven relevant quantities of interest (QoIs), as compared to other classical approaches. In conclusion, ongoing research is focusing on generating new experimental trajectories to validate this approach, and on employing Bayesian calibration to refine parametric uncertainties and guide future model development efforts.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Doping- and Strain-Dependent Electrolyte-Gate-Induced Perovskite to Brownmillerite Transformation in Epitaxial La 1– x Sr x CoO 3–δ Films

Much recent attention has focused on the voltage-driven reversible topotactic transformation between the ferromagnetic metallic perovskite (P) SrCoO 3-δ and oxygen-vacancy-ordered antiferromagnetic insulating brownmillerite (BM) SrCoO 2.5 . This is emerging as a paradigmatic example of the power of electrochemical gating (using, e.g., ionic liquids/gels), the wide modulation of electronic, magnetic, and optical properties generating clear application potential. SrCoO 3 films are challenging with respect to stability, however, and there has been little exploration of alternate compositions. Here, we present the first study of ion-gel-gating-induced P. BM transformations across almost the entire La 1-x SrxCoO 3 phase diagram (0 ≤ x ≤ 0.70), under both tensile and compressive epitaxial strain. Electronic transport, magnetometry, and operando synchrotron X-ray diffraction establish that voltage-induced P → BM transformations are possible at essentially all x, including x ≤ 0.50, where both P and BM phases are highly stable. Under small compressive strain, the transformation threshold voltage decreases from approximately +2.7 V at x = 0 to negligible at x = 0.70. Both larger compressive strain and tensile strain induce further threshold voltage lowering, particularly at low x. The P → BM threshold voltage is thus tunable, via both composition and strain. At x = 0.50, voltage-controlled ferromagnetism, transport, and optical transmittance are then demonstrated, achieving Curie temperature and resistivity modulations of similar to 220 K and at least 5 orders of magnitude, respectively, and enabling estimation of the voltage-dependent Co valence. The results are analyzed in the context of doping- and strain-dependent oxygen vacancy formation energies and diffusion coefficients, establishing that it is thermodynamic factors, not kinetics, that underpin the decrease in the threshold voltage with x, that is, with increasing formal Co valence. These findings substantially advance the practical and mechanistic understanding of this voltage-driven transformation, with fundamental and technological implications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Integration of a thermoelectric subcooler with an air‑source heat pump to enhance heating capacity and dehumidification

This study presents an innovative configuration of a thermoelectric subcooler (TES) integrated with an air-source heat pump (ASHP). The TES is installed in the liquid line, where it absorbs heat from the refrigerant. On its hot side, it discharges heat to the return air in heating mode or to the supply air in cooling mode, enabling year-round operation. The ASHP–TES system was evaluated under various conditions to reduce supplemental heating needs and improve dehumidification. Experimental heating tests revealed that activating the TES increased the heating capacity by 12%–20%. However, this occurred with a 7.6%–10% reduction in heating coefficient of performance (COP). In cooling mode, TES operation significantly improved moisture removal. The TES reduced the sensible heat ratio (SHR) and enhanced dehumidification, removing 20%–50% more moisture than a conventional system when meeting the same sensible load. The TES can be turned off to use the refrigerant subcooler for reheat supply air or turned on to substantially boost dehumidification. When meeting the same latent load, the ASHP–TES system achieved up to 33% energy savings compared with a conventional ASHP using resistance heating. Relative to a conventional ASHP paired with a whole-house dehumidifier, the ASHP–TES system provided up to 20% energy savings. These findings underscore the potential of TES integration to improve latent load control and enhance overall energy efficiency in hybrid ASHP systems, especially in cold and humid climates.

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

DOE OSTI2023

Investigation of the Effect of Atmospheric Plasma Treatment in Nanofiber and Nanocomposite Membranes for Piezoelectric Applications

In this work, we report the effect of steady-state atmospheric plasma (Corona discharge) in nanofibers and nanocomposite membranes for piezoelectric applications. The investigation was performed in PVDF (Poly vinylidene fluoride) nanofibers, CNT (Carbon Nanotubes)-reinforced PVDF nanocomposites, and PAN (Poly acrylonitrile) nanofiber membranes. Steady-state plasma was generated with a high voltage power source with 1 mA discharge current output and 6 kV discharge voltage, and the gap between tip and the material was maintained to be 1 cm. For the fabrication of nanofibers and nanocomposite membranes, an electrospinning method was used. The electrospinning parameters, such as flow rate and voltage, were optimally tuned for obtaining uniform nanofibers and nanomembranes. Along with the plasma treatment, heat treatment above the glass transition temperature was also conducted on the nanofiber membranes. Using a Scanning Electron Microscope (SEM), the morphology of the nanofibers was observed. X-ray Diffraction (XRD) demonstrated the polycrystallinity of the nanofibers. Fourier Transform Infrared Spectroscopy (FTIR) analysis of the PVDF nanofibers shows a peak at 796 cm−1 representing α-phase (C-H rocking) in the control sample which is absent in the treated samples. Raman spectroscopy of PVDF nanofibers identifies a Raman shift from 873 cm−1 to 877 cm−1 (denoting β-phase) for plasma-treated samples only. Electron Paramagnetic Resonance (EPR) concludes that the intensity of the free radicals increases from 1.37 to 1.46 (a.u.) after plasma treatment. Then, sensors were fabricated from the PVDF nanofibers, MWCNT-reinforced PVDF nanofibers, and PAN nanofibers to characterize their piezoelectric properties. The impact test results showed that the atmospheric plasma and heat-treated samples had 86%, 277%, and 92% increases of the d33 value (piezoelectric coefficient) in the case of PVDF nanofibers, MWCNT-reinforced nanofibers, and PAN nanofibers, respectively. It was also observed that the capacitance of the nanofiber membranes has increased due to the plasma treatment.

Biochemistry & Molecular Biology↗

DOE OSTI2022

Piezoelectric property of PZT nanofibers characterized by resonant piezo-force microscopy

Nano-piezoelectric materials have drawn tremendous research interest. However, characterization of their piezoelectric properties, especially measuring the piezoelectric strain coefficients, remains a challenge. Normally, researchers use an AFM-based method to directly measure nano-materials’ piezoelectric strain coefficients. But, the extremely small piezoelectric deformation, the influence from the parasitic electrostatic force, and the environmental noise make the measurement results questionable. In this paper, a resonant piezo-force microscopy method was used to accurately measure the piezoelectric deformation from 1D piezoelectric nanofibers. During the experiment, the AFM tip was brought into contact with the piezoelectric sample and set to work at close to its first resonant frequency. A lock-in amplifier was used to pick up the sample’s deformation signal at the testing frequency. By using this technique, the piezoelectric strain constant d 33 of the Lead Zirconate Titanate (PZT) nanofiber with a diameter of 76 nm was measured. The result showed that d 33 of this PZT nanofiber was around 387 pm/V. Meanwhile, by tracking the piezoelectric deformation phase image, domain structures inside PZT nanofibers were identified.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Prototype Modeling for a Light-Trapping Planar-Cavity Enclosed Particle Solar Receiver

Concentrating solar thermal (CST) systems present a promising avenue for affordable and reliable energy production. Solar receivers are key components that determine the efficiency and longevity of these systems. Particle-based solar receivers have emerged as a compelling alternative to traditional technologies, offering several advantages that address limitations in current CST systems. This is especially true as next-generation CST technologies target applications including electricity generation, thermochemical processes, and industrial process heat, many of which necessitate higher operating temperatures than current commercial molten salt systems. Molten-salt thermal energy storage (TES) systems, commonly used in CSP, face challenges related to freezing and corrosion. Particle-based TES systems, in contrast, do not experience these issues, as particles are stable at high temperatures, exceeding 1000 degrees Celsius. This capability allows for a wider range of applications, including those requiring higher temperatures for industrial processes and efficient electricity generation. A novel innovation in particle-based solar receiver technology is the light-trapping planar cavity receiver (LTPCR) configuration developed by NREL. The LTPCR design consists of small cavity-like structures using opaque planar surfaces, enabling efficient capture and absorption of solar energy. A high incident flux concentration at the cavity aperture is absorbed on the receiver walls, and subsequently transferred to particles on the inside of cavities. The particles flow through the system, forming a fluidized bed inside of the receiver panels, effectively capturing the absorbed solar heat. Air is used as a fluidizing medium in this process to enhance particle heat transfer and mixing. The effectiveness of this design lies in its ability to manage solar flux conditions and ensure high solar-to-thermal receiver efficiency. A 100-kW prototype is currently being tested at the King Saud University in Saudi Arabia to assess the receiver performance. A range of modeling analyses for the optical, thermal, and mechanical effects were conducted to assess the performance of the receiver under on-sun conditions. The solar flux resulting from the KSU heliostat field was modeled using NREL SolTrace software and produced up to 600 kW/m2 at the receiver aperture. The solar flux absorbed on the receiver walls was then used within a computational fluid dynamics (CFD) model to predict wall temperature distributions along with radiation and convection loss. A two-phase CFD model was developed for the fluidized bed of silica sand inside the receiver panels to predict local wall-to-particle heat transfer coefficients, particle temperature distributions, and outlet temperature of the particles. We have also conducted analyses to understand the thermomechanical behavior of these innovative enclosed light-trapping solar receivers optimized for particle heating. We used finite element analysis (FEA) to predict the receiver's performance using temperature distributions obtained from CFD and based on the resulting stress profiles, evaluated creep-fatigue damage with a goal of achieving a 30-year service life. Analysis showed a significant impact of the particle-to-wall heat transfer coefficients (HTCs) on receiver performance, with higher HTCs resulting in reduced stress and increased lifespan. For instance, when using Inconel 740H, increasing the HTC from 800 W/m2 K to 1400 W/m2 K increased the creep life from 4,000 hours to over 100,000 hours. This highlights the importance of understanding and optimizing heat transfer in the design of high-efficiency receivers.

14 SOLAR ENERGY↗

DOE OSTI2025

Investigating the relationship between simulation parameters and flow variables in simulating atmospheric gravity waves for wind energy applications

Wind farms, particularly offshore clusters, are becoming larger than ever before. Besides influencing the surface wind flow and the inflow for downstream wind farms, large wind farms can trigger atmospheric gravity waves in the inversion layer and the free atmosphere aloft. Wind-farm-induced gravity waves can cause adverse pressure gradients upstream of the wind farm, which contribute to the global blockage effect, and can induce favorable pressure gradients above and downstream of the wind farm that enhance wake recovery. Numerical modeling is a powerful means of studying these wind-farm-induced atmospheric gravity waves, but it comes with the challenge of handling spurious reflections of these waves from domain boundaries. Typically, approaches which employ radiation boundary conditions and forcing zones are used to avoid these reflections. However, the simulation setup of these approaches relies heavily on ad hoc processes. For instance, the widely used Rayleigh damping method requires ad hoc tuning to produce a setup that may only produce satisfactory results for a particular case. To provide more systematic guidance on setting up realistic simulations of atmospheric gravity waves, we conduct a large-eddy simulation (LES) study of flow over a 2D hill and through a wind farm canopy that explores the optimum domain size and damping layer setup depending on the fundamental parameters which determine the flow characteristics. In this work, we only consider linearly stratified conditions (i.e., no inversion layer), thereby focusing on internal gravity waves in the free atmosphere and their reflections from the domain boundaries. This type of flow is governed by a single Froude number, which dictates most of the internal wave properties, such as wavelength, amplitude, and direction. This, in turn, will dictate the optimum domain size and Rayleigh damping layer setup. We find the effective horizontal and vertical wavelengths (the representative wavelengths of the entire wave spectrum) to be the appropriate length scales to size the domain and damping layer thickness, and the optimal Rayleigh damping coefficient scales with the Brunt–Väisälä frequency. Considering Froude numbers seen in wind farm applications, we propose recommendations to limit the reflections to less than 10 % of the total upward-propagating wave energy. Typically, damping is done at the top boundary, but given the non-periodic lateral boundary conditions of practical wind farm simulation domains, we find that damping the inflow–outflow boundaries is of equal importance to damping the top boundary. The Brunt–Väisälä frequency-normalized damping coefficient should be between 1 and 10. The damping layer thickness should be at least one effective vertical wavelength; damping layers exceeding 1.5 times the vertical wavelength are found to be unnecessary. The domain length and height should accommodate at least one effective horizontal and vertical wavelength, respectively. Moreover, Rayleigh damping does not damp the waves completely, and the non-damped energy might accumulate over the simulation time.

17 WIND ENERGY↗

DOE OSTI2022

Reconciliation of asynchronous satellite-based $\mathrm{NO_2}$ and $\mathrm{XCO_2}$ enhancements with mesoscale modeling over two urban landscapes

Fossil fuel carbon dioxide (CO 2ff ), the main driver of global warming and climate change, is often co-emitted with nitrogen oxides (NO x ) and precursors to ground-level ozone from anthropogenic sources like power plants or vehicles. In urban and suburban areas, satellite-based NO 2 can be used as a proxy to track the emissions of CO 2ff . Because of NO 2 ’s shorter lifetime, urban NO 2 plumes are more distinguishable from backgrounds and more sensitive to variations in emissions. However, the combination of these two gases is limited by the asynchrony among NO 2 and CO 2 monitoring satellites. We used CO 2ff simulated by the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) model to reconcile the tropospheric NO 2 vertical column density (VCD) from the Tropospheric Monitoring Instrument (TROPOMI) and column-averaged dry-air mole fractions of carbon dioxide enhancements (ΔXCO 2 ) from Orbiting Carbon Observatory 3 (OCO-3) Snapshot Area Maps (SAMs) over a multicity area, Washington D.C.-Baltimore (DC-Balt), and a basin city, Mexico City. NO 2 /CO 2ff ratios over DC-Balt are smaller than Mexico City, indicative of stricter emission restrictions, a more combustion-efficient vehicle fleet, and higher combustion efficiency due to lower altitude in DC-Balt. For single-track cases, the spatial correlations between NO 2 and ΔXCO 2 over Mexico City are stronger than DC-Balt because the NO 2 and CO 2 are mostly trapped in the valley of Mexico City, while DC-Balt is severely affected by distant sources (i.e., US East Coast cities). Using multi-track averaging, spatial correlation coefficients increase with the number of days used for averaging. The correlations reached a maximum when averaging >12 continuous images for DC-Balt and > 10 continuous images for Mexico City. This finding indicates that multi-track averaging using modeled CO 2ff as a proxy is helpful to filter the noise in single-track images, to cancel the interference from distant sources, and to magnify correlations between NO 2 and CO 2ff . Mexico City showed stronger spatial correlations but weaker temporal correlations than DC-Balt due to biomass burning hot spots and large transport errors caused by the trapping effects of the surrounding mountains. Tracking the 20-day moving average of CO 2ff emissions using TROPOMI NO 2 seems technically feasible, considering the relationship between correlation coefficients and the number of available satellite images.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Map-level baryonification: unified treatment of weak lensing two-point and higher-order statistics

Precision cosmology benefits from extracting maximal information from cosmic structures, motivating the use of higher-order statistics (HOS) at small spatial scales. However, predicting how baryonic processes modify matter statistics at these scales has been challenging. The baryonic correction model (BCM) addresses this by modifying dark-matter-only simulations to mimic baryonic effects, providing a flexible, simulation-based framework for predicting both two-point and HOS. We show that a 3-parameter version of the BCM can jointly fit weak lensing maps' two-point statistics, wavelet phase harmonics coefficients, scattering coefficients, and the third and fourth moments to within 2% accuracy across all scales ℓ < 2000 and tomographic bins for a DES-Y3-like redshift distribution ( z ≲ 2), using the FLAMINGO simulations. These results demonstrate the viability of BCM-assisted, simulation-based weak lensing inference of two-point and HOS, paving the way for robust cosmological constraints that fully exploit non-Gaussian information on small spatial scales.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Krylov subspace recycling for evolving structures

Krylov subspace recycling is a powerful tool when solving a long series of large, sparse linear systems that change only slowly over time. In PDE constrained shape optimization, these series appear naturally, as typically hundreds or thousands of optimization steps are needed with only small changes in the geometry. In this setting, however, applying Krylov subspace recycling can be a difficult task. As the geometry evolves, in general, so does the finite element mesh defined on or representing this geometry, including the numbers of nodes and elements and element connectivity. This is especially the case if re-meshing techniques are used. As a result, the number of algebraic degrees of freedom in the system changes, and in general the linear system matrices resulting from the finite element discretization change size from one optimization step to the next. Changes in the mesh connectivity also lead to structural changes in the matrices. In the case of re-meshing, even if the geometry changes only a little, the corresponding mesh might differ substantially from the previous one. Obviously, this prevents any straightforward mapping of the approximate invariant subspace of the linear system matrix (the focus of recycling in this work) from one optimization step to the next; similar problems arise for other selected subspaces. In this paper, we present an algorithm to map an approximate invariant subspace of the linear system matrix for the previous optimization step to an approximate invariant subspace of the linear system matrix for the current optimization step, for general meshes. This is achieved by exploiting the map from coefficient vectors to finite element functions on the mesh, combined with interpolation or approximation of functions on the finite element mesh. We demonstrate the effectiveness of our approach numerically with several proof of concept studies for a specific meshing technique.

42 ENGINEERING↗

DOE OSTI2020

Development and Validation of Passive Yaw in the Open-Source WEC-Sim Code

A passive yaw implementation is developed, validated, and explored for the WEC-Sim, an open-source wave energy converter modeling tool that works within MATLAB/Simulink. The Reference Model 5 (RM5) is selected for this investigation, and a WEC-Sim model of the device is modified to allow yaw motion. A boundary element method (BEM) code was used to calculate the excitation force coefficients for a range of wave headings. An algorithm was implemented in WEC-Sim to determine the equivalent wave heading from a body’s instantaneous yaw angle and interpolate the appropriate excitation coefficients to ensure the correct time-domain excitation force. This approach is able to determine excitation force for a body undergoing large yaw displacement. For the mathematically simple case of regular wave excitation, the dynamic equation was integrated numerically and found to closely approximate the results from this implementation in WEC-Sim. A case study is presented for the same device in irregular waves. In this case, computation time is increased by 32x when this interpolation is performed at every time step. To reduce this expense, a threshold yaw displacement can be set to reduce the number of interpolations performed. A threshold of 0.01° was found to increase computation time by only 22x without significantly affecting time domain results. Similar amplitude spectra for yaw force and displacements are observed for all threshold values less than 1°, for which computation time is only increased by 2.2x.

50 EE - Wind and Water Power Program - Water (EE-4↗

DOE OSTI2025

A resolution independent neural operator

The Deep operator network (DeepONet) is a powerful yet simple neural operator architecture that utilizes two deep neural networks to learn mappings between infinite-dimensional function spaces. This architecture is highly flexible, allowing the evaluation of the solution field at any location within the desired domain. However, it imposes a strict constraint on the input space, requiring all input functions to be discretized at the same locations; this limits its practical applications. Here, in this work, we introduce a general framework for operator learning from input–output data with arbitrary number and locations of sensors. This begins by introducing a resolution-independent DeepONet (RI-DeepONet), enabling it to handle input functions that are arbitrarily, but sufficiently finely, discretized. To this end, we propose two dictionary learning algorithms to adaptively learn a set of appropriate continuous basis functions, parameterized as implicit neural representations (INRs), from correlated signals defined on arbitrary point cloud data. These basis functions are then used to project arbitrary input function data as a point cloud onto an embedding space (i.e., a vector space of finite dimensions) with dimensionality equal to the dictionary size, which can be directly used by DeepONet without any architectural changes. In particular, we utilize sinusoidal representation networks (SIRENs) as trainable INR basis functions. The introduced dictionary learning algorithms are then used in a similar way to learn an appropriate dictionary of basis functions for the output function data, which defines a new neural operator architecture referred to as the R esolution I ndependent N eural O perator (RINO). In the RINO, the operator learning task simplifies to learning a mapping from the coefficients of input basis functions to the coefficients of output basis functions. We demonstrate the robustness and applicability of RINO in handling arbitrarily (but sufficiently richly) sampled input and output functions during both training and inference through several numerical examples.

Deep operator network (DeepONet)↗

DOE OSTI2020

Development and Validation of Passive Yaw in the Open-Source WEC-Sim Code: Preprint

A passive yaw implementation is developed, validated, and explored for the Wave Energy Converter Simulator (WEC-Sim), an open-source wave energy converter modeling tool that works within MATLAB/Simulink. The Reference Model 5 (RM5) is selected for this investigation, and a WEC-Sim model of the device is modified to allow yaw motion. A boundary element method (BEM) code was used to calculate the excitation force coefficients for a range of wave headings. An algorithm was implemented in WEC-Sim to determine the equivalent wave heading from a body’s instantaneous yaw angle and interpolate the appropriate excitation coefficients to ensure the correct time-domain excitation force. This approach is able to determine excitation force for a body undergoing large yaw displacement. For the mathematically simple case of regular wave excitation, the dynamic equation was integrated numerically and found to closely approximate the results from this implementation in WEC-Sim. A case study is presented for the same device in irregular waves. In this case, computation time is increased by 32x when this interpolation is performed at every time step. To reduce this expense, a threshold yaw displacement can be set to reduce the number of interpolations performed. A threshold of 0.01 was found to increase computation time by only 22x without significantly affecting time domain results. Similar amplitude spectra for yaw force and displacements are observed for all threshold values less than or equal to 1, for which computation time is only increased by 2.2x.

50 EE - Wind and Water Power Program - Water (EE-4↗

DOE OSTI2020

A buoyancy–shear–drag-based turbulence model for Rayleigh–Taylor, reshocked Richtmyer–Meshkov, and Kelvin–Helmholtz mixing

A phenomenological turbulence model for Rayleigh–Taylor, reshocked Richtmyer–Meshkov, and Kelvin–Helmholtz instability-induced mixing is developed using a general buoyancy–shear–drag model. Analytic solutions to the simplified model equations corresponding to each instability are derived separately, which are then used to calibrate the model coefficients to predict specific values of the mixing layer growth parameters and exponents. The buoyancy-shear–drag equations for the bubble and spike mixing layer widths are then solved numerically, and a turbulent diffusivity (or viscosity) is constructed dimensionally as the product of the mixing layer width, h, and its time-derivative, dh/dt. Surrogate turbulent fields are then constructed by multiplying a presumed, approximate self-similar spatial profile by appropriate functions of h and dh/dt. Using several simplifying approximations, the turbulent diffusion equations satisfied by the mean mass fraction and mean shear velocity are solved analytically in a reference frame moving with the mean advection velocity, and it is shown that the mean fields evolve in space and time as expected. The explicit modeling and solution of turbulent transport equations (e.g., for the turbulent kinetic energy and its dissipation rate or a lengthscale) are not required. By using separate equations for the bubble and spike evolution, the model naturally captures the asymmetry induced by an increasing density contrast between the heavy and light fluids. The model also includes molecular dissipation and diffusion, and therefore, can describe transition to fully-developed turbulence if the initial turbulent diffusivity/viscosity is much smaller than the molecular diffusivity/viscosity. This model is applied to constant-acceleration Rayleigh–Taylor, impulsively reshocked Richtmyer–Meshkov, and variable-density Kelvin–Helmholtz mixing layers to demonstrate its utility. It is shown that the numerical solutions of the model calibrated using specific values of the instability growth parameters and exponents: (1) produces mixing layer widths in agreement with the expected self-similar growth power laws; (2) gives spatiotemporal profiles of turbulent fields that are expected and consistent with previous results; (3) predicts the expected power-law growths and decays of the spatially-integrated turbulent fields, and; (4) gives spatiotemporal profiles of the mean fields that are expected and consistent with previous results. This relatively simple model can be implemented numerically, and is expected to be useful for fundamental as well as astrophysical and inertial confinement fusion applications.

42 ENGINEERING↗

DOE OSTI2025

Heating performance of an air source heat pump with a portable thermoelectric subcooler

This study investigates the heating performance of an integrated air-source heat pump (ASHP) with a thermoelectric subcooler (TES) module, revealing significant performance enhancements, particularly in colder temperatures. Results show that adding the portable TES boosts the ASHP's heating capacity, making it feasible for residential applications. The coefficient of performance (COP) for the TE system, which is influenced by condensing temperatures and ambient conditions, ranges from 1.51 to 2.07. If condensing temperatures are consistently maintained above 35 °C, a TE COP of approximately 2.07 is achievable, supporting system downsizing and reducing supplemental heating. When coupled with an oversized indoor coil, the TES-ASHP system delivers comparable heating to a baseline unit while achieving a 10 % higher COP. Capacity increases by 8.7 %–24 % with TES in colder conditions, though COP declines by 9 %–18 %, diminishing as temperatures drop. Compared to systems with supplemental heating, this setup achieves a COP 10 %–17 % higher. Future work will involve extended field testing in various climates, exploration of advanced materials for thermal efficiency, and assessment of alternative refrigerants to improve performance and sustainability. This integrated ASHP-TES system holds promise for increased efficiency and reduced environmental impact in cold climates.

Air source heat pump↗

DOE OSTI2026

Evaluation of a high-resolution regional climate simulation for surface and hub-height wind climatology over North America

Assessing the availability of key wind resources requires augmenting observations to support the implementation of wind energy infrastructure. However, observations are limited, necessitating the development of high-resolution, long-term gridded datasets. This study presents a robust, dynamically downscaled climatological dataset, offering 20 years of hourly wind data at a 4 km spatial resolution across North America, and evaluates its performance against observations, including meteorological towers and automated surface-observing system (ASOS) stations, as well as coarse-resolution reanalysis data (the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis version 5 (ERA5)). Results demonstrate that the downscaled high-resolution wind data outperform ERA5 in regions of complex terrain and coastal areas, with improved overlap coefficients for wind data distributions and reduced root mean square errors (RMSEs) for hub-height and near-surface diurnal wind patterns. The downscaled simulation also captures the synoptic drivers of seasonal wind direction patterns reasonably well, indicated by high wind rose similarity indices. This study also provides an analysis of interannual variability, utilizing the dataset's full 20-year period, and model uncertainty, generated by varying model initial conditions and physics parameterizations across 1-year ensemble members, which are key considerations for wind resource assessment in wind farm development.

17 WIND ENERGY↗

DOE OSTI2021

Isotropic nanocrystalline Sm(Fe,Co) 11.3 Ti 0.7 magnets modified with B and Zr

Rare-earth-lean Sm(Fe,Co,Ti) 12 alloys with the ThMn 12 crystal structure and less than one Ti atom per formula unit have the potential of exceptionally powerful permanent magnets, but all prior attempts to develop high coercivity in bulk alloys, especially coercivity combined with crystallographic texture, have fallen short of the expectations. This study was aimed at improvement of the currently best Sm(Fe,Co,Ti) 12 magnets prepared through melt-spinning which are inherently isotropic. Modifications of the alloys with B and Zr, already demonstrated in earlier studies to be effective separately, have been implemented simultaneously. Here, a systematic study of Sm 1.1-x (Fe,Co) 11.3-y Ti 0.7 B y alloys melt-spun at a tangential speed of 50 m/s and annealed at 600–950 °C allowed for monitoring the continuous evolution of the two consecutive crystal structures, those of the TbCu 7 and ThMn 12 types. Zirconium was found to facilitate the formation of the 1:12 structure at the expense of the 1:7, whereas boron has the opposite effect, at certain concentrations completely suppressing the 1:12. When the two alloying elements are introduced simultaneously, they inhibit growth of the 1:12 crystallites at annealing temperatures higher than 800 °C, thus allowing for the development of a higher coercivity. Because of instrumental limitations, bulk magnets were prepared through a two-step process – compaction of the melt-spun ribbons at 650 °C and additional treatment at a higher temperature – and they were characterized by a reduced, 90–93%, density. Nevertheless, an isotropic Sm 0.9 Zr 0.2 (Fe,Co) 10.8 Ti 0.7 B 0.5 magnet exhibited fair values of the remanence (7.4 kG), maximum energy product (8.5 MGOe) and coercivity (5.4 kOe), as well as high Curie temperature of 525 °C and remarkably small temperature coefficient of the coercivity, -0.25%/°C.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Turbulence simulations of drift-Alfvén wave effects on edge-localized modes and divertor target heat flux width

A series of BOUT++ turbulence simulations are performed for two Pre-Fusion Power Operation (PFPO-1,2) phases of the ITER Research plan proclaimed in 2019. Linear simulation results show that PFPO-1 is unstable to Peeling-ballooning modes (PB), while the PFPO-2 is unstable to the coupling of PB and Drift-Alfvén wave (DAW) instabilities. The linear results are qualitatively consistent with the dispersion relation of DAW. To study the influence of the DAW on the edge-localized mode (ELM) crash, the PFPO-2 is adopted in this section. Different from the grassy ELM in [Li et al 2022 Nucl. Fusion 62, 096030], nonlinear simulations show that the ELM size of PFPO-2 is almost one-third of the grassy ELM, representing a distinct small ELM. However, simulations then show that if the PB instability is removed, the fluctuation amplitude drops by an order of magnitude and the ELM crash disappears, which is in accord with the theory in [Xu et al 2010 Physical Review Letters, Vol. 105, 175005] and the results in [Li et al 2022 Nucl. Fusion 62, 096030], confirming that the PB instability is a necessary condition for an ELM crash. Furthermore, removing the DAW drive also suppresses ELM crashes, implying that PB instability is necessary but insufficient for PFPO-2 ELM and that DAW could amplify PB-driven turbulence. In addition, by integrating results of both PFPO phases by BOUT++ turbulence analysis with heat flux width (λ q ) and electron thermal diffusivity (χ e ), these simulations establish a predictive framework for heat flux width and its dominant mechanisms, thereby providing a comprehensive scheme for the prediction of the heat flux width. Moreover, simulations indicate that DAW driving can increase the transport coefficient by enhancing the turbulent transport, leading to a broadened heat flux width once the transport coefficient exceeds

Drift-Alfvén wave↗