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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Generalized symmetries of nonsupersymmetric orbifolds

We determine generalized symmetries for 4D theories engineered via type II strings on nonsupersymmetric orbifold backgrounds ℝ 3,1 × ℝ 6 /Γ. Probe branes detect generalized symmetries via the adjacency matrix for fermionic degrees of freedom in an associated quiver gauge theory. In situations where the tachyons are sequestered away from the boundary 𝑆 5 /Γ, this exactly matches the result extracted from singular homology. In situations with an unsequestered tachyon which stretches out to the boundary, the presence of tachyonic pulses partitions up the space into several distinct sectors, and the net contribution again matches with the answer expected via quiver methods. For IIA backgrounds, the presence of a localized closed string tachyon leads to transitions in the spectrum of states, generalized symmetries, higher-group symmetries, as well as the level matrix of the associated symmetry topological field theory (SymTFT). For IIB backgrounds with a stack of spacetime filling probe D3-branes, the onset of a radiatively generated potential leads to similar considerations involving scale dependent transitions in the symmetries of the theory, including structures such as duality defects/interfaces.

compactification↗
DOE OSTI2025

Operator origin of anomalous dimensions in de Sitter space

The late-time limit of the power spectrum for heavy (principal series) fields in de Sitter (dS) space yields a series of polynomial terms with complex scaling dimensions. Such scaling behavior is expected to result from an associated operator with a complex dimension. In a free theory, these complex dimensions are known to match the constraints imposed by unitarity on the space of states. Yet, perturbative corrections to the scaling behavior of operators are naively inconsistent with unitary evolution of the quantum fields in dS space. This paper demonstrates how to compute one-loop corrections to the scaling dimensions that appear in the two-point function from the field theory description in terms of local operators. We first show how to evaluate these anomalous dimensions using Mellin space, which has the feature that it naturally accommodates a scaleless regulator. We then explore the consequences for the soft de Sitter effective theory (SdSET) description that emerges in the long wavelength limit. Carefully matching between the UV and SdSET descriptions requires the introduction of novel nondynamical “operators” in the effective theory. This is not only necessary to reproduce results extracted from the Källén-Lehmann representation (that use the space of unitary states directly), but it is also required by general arguments that invoke positivity. Published by the American Physical Society 2025

Cohen, Timothy↗
DOE OSTI2025

Universal energy-speed-accuracy trade-offs in driven nonequilibrium systems

The connection between measure theoretic optimal transport and dissipative nonequilibrium dynamics provides a language for quantifying nonequilibrium control costs, leading to a collection of thermodynamic speed limits, which rely on the assumption that the target probability distribution is perfectly realized. This is almost never the case in experiments or numerical simulations, so here we address the situation in which the external controller is imperfect. We obtain a lower bound for the dissipated work in generic nonequilibrium control problems that (1) is asymptotically tight and (2) matches the thermodynamic speed limit in the case of optimal driving. Along with analytically solvable examples, we refine this imperfect driving notion to systems in which the controlled degrees of freedom are slow relative to the nonequilibrium relaxation rate, and identify independent energy contributions from fast and slow degrees of freedom. Furthermore, we develop a strategy for optimizing minimally dissipative protocols based on optimal transport flow matching, a generative machine learning technique. Furthermore, this latter approach ensures the scalability of both the theoretical and computational framework we put forth. Crucially, we demonstrate that we can compute the terms in our bound numerically using efficient algorithms from the computational optimal transport literature and that the protocols we learn saturate the bound.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Determination of the Collins-Soper Kernel from Lattice QCD

This Letter presents a determination of the quark Collins-Soper kernel, which relates transverse-momentum-dependent parton distributions (TMDs) at different rapidity scales, using lattice quantum chromodynamics (QCD). This is the first such determination with systematic control of quark mass, operator mixing, and discretization effects. Next-to-next-to-leading logarithmic matching is used to match lattice-calculable distributions to the corresponding TMDs. The continuum-extrapolated lattice QCD results are consistent with several recent phenomenological parametrizations of the Collins-Soper kernel and are precise enough to disfavor other parametrizations. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Imaging coherent phonons and precursor dynamics in LaFeAsO with 4D ultrafast electron microscopy

In this work, we used 4D ultrafast electron microscopy (UEM) to directly image femtosecond photoinduced structural dynamics in single-crystal LaFeAsO at initial temperatures of 300 and 100 K, above and below the known structural and magnetic phase-transition temperatures, respectively. With nanometer-picosecond resolution, we resolved an initial (precursor) sigmoidlike response arising from photothermal expansion and lattice reorientation that precedes the onset of propagating coherent acoustic phonons (CAPs). In the specific regions probed, the precursor response at 100 K is shorter than at 300 K ($t$ 0.5;100 K = 11.3ps vs $t$ 0.5;300 K = 17.8ps), and the CAP oscillation frequency is lowered with cooling (ƒ CAP;100 K = 12 GHz vs ƒ CAP;300 K = 21 GHz), correlated to known lattice softening due to the structural phase change. The transient CAP behaviors at 300 K are dispersive, displaying an exponentially decaying phase velocity over the first nanosecond. Further, the CAP symmetry at 300 K matches a first-order antisymmetric shear mode (A 1 ), while at 100 K it is best matched by a mostly nondispersive zero-order symmetric mode (S 0 ). These findings illustrate the sensitivity of UEM imaging to spatially heterogeneous dynamics in the Fe-pnictide materials and more broadly in other quantum materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Direct Measurement of Diffusion Coefficients: Evidence for Diffusive Stochastic Heating in Collisionless Plasmas

Open questions in collisionless plasma dissipation can be addressed using space-based observations in different astrophysical environments, with implications for both astrophysical and laboratory plasma systems. We study a low-𝛽, highly imbalanced, sub-Alfvénic stream observed by Parker Solar Probe (PSP) to identify and distinguish between signatures of stochastic heating (SH) and resonant heating (RH) by parallel ion cyclotron waves (∥-ICWs). Prior work studying this stream [Trevor A. Bowen et al., Stochastic heating in the sub-Alfvénic solar wind, Phys. Rev. Lett. 135, 255201 (2025)] showed that the SH rate, accounting for intermittency, matched the amplitude of the local energy transfer (LET) rate, while the RH rate did not. This comparison relied on a number of assumptions regarding the nature of the diffusive process and the calculation of the LET rate. We introduce a novel technique of inverting the proton guiding center equation to empirically measure velocity-space diffusion coefficients using three-dimensional proton velocity distribution functions, from the ion electrostatic analyzer (the Solar Probe Analyzer for Ions) on PSP. Measured diffusion coefficients are used to determine phase-space heating rates, leading to a calculation of a fully kinetic heating rate independent of assumptions made in prior work. We show that scale-dependent analytic expressions for SH via noncoherent fluctuations match the empirical measurements from PSP data, provided that we account for intermittency in the heating calculation. In contrast, the derived heating rates for SH that accounts for the effects of the helicity barrier and heating rates for RH via ∥-ICWs do not peak in the same region of velocity space as the empirical measurements, nor do they reach the required magnitude. Our approach provides novel methodology to uniquely identify and constrain heating processes in collisionless plasmas and shows evidence of a Fokker-Planck-like diffusive process in the near-Sun solar wind.

Plasma kinetic theory↗
DOE OSTI2026

Moments of parton distribution functions of the pion from lattice QCD using gradient flow

We present a nonperturbative determination of the pion valence parton distribution function (PDF) moment ratios ⟨𝑥 𝑛−1 ⟩/⟨𝑥⟩ up to 𝑛 = 6, using the gradient flow in lattice quantum chromodynamics (QCD). As a testing ground, we employ SU(3) isosymmetric gauge configurations generated by the OpenLat initiative with a pseudoscalar mass of 𝑚 𝜋 ≃ 411 MeV. Our analysis uses four lattice spacings and a nonperturbatively improved action, enabling full control over the continuum extrapolation, and the limit of vanishing flow time, 𝑡 →0. The flowed ratios exhibit O(𝑎 2 ) scaling across the ensembles, and the continuum-extrapolated results, matched to the $\overline{MS}$ scheme at 𝜇 = 2 GeV using next-to-next-to-leading order matching coefficients, show only mild residual flow-time dependence. The resulting ratios, computed with a relatively small number of configurations, are consistent with phenomenological expectations for the pion’s valence distribution, with statistical uncertainties that are competitive with modern global fits. These findings demonstrate that the gradient flow provides an efficient and systematically improvable method to access partonic quantities from first principles. Future extensions of this work will target lighter pion masses toward the physical point, and applications to nucleon structure such as the proton PDFs and the gluon and sea-quark distributions.

lattice QCD↗
DOE OSTI2025

Search for an Anomalous Production of Charged-Current 𝜈 𝑒 Interactions without Visible Pions across Multiple Kinematic Observables in MicroBooNE

This Letter presents an investigation of low-energy electron-neutrino interactions in the Fermilab Booster Neutrino Beam by the MicroBooNE experiment, motivated by the excess of electron-neutrino-like events observed by the MiniBooNE experiment. This is the first measurement to use data from all five years of operation of the MicroBooNE experiment, corresponding to an exposure of 1.11 × 10 21 protons on target, a 70% increase on past results. Two samples of electron neutrino interactions without visible pions are used, one with visible protons and one without any visible protons. The MicroBooNE data show reasonable agreement with the nominal prediction, with 𝑝 values ≥26.7% when the two 𝜈 𝑒 samples are combined, though the prediction exceeds the data in limited regions of phase space. The data are further compared to two empirical models that modify the predicted rate of electron-neutrino interactions in different variables in the simulation to match the unfolded MiniBooNE low energy excess. In the first model, this unfolding is performed as a function of electron neutrino energy, while the second model aims to match the observed shower energy and angle distributions of the MiniBooNE excess. This measurement excludes an electronlike interpretation of the MiniBooNE excess based on these models at >99% CLs in all kinematic variables.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Quantifying dispersity in size and shape of nanoparticles from small-angle scattering data using machine learning based CREASE

Here, we use machine learning (ML) enhanced computational reverse engineering analysis of scattering experiments (CREASE) to interpret small-angle X-ray scattering (SAXS) data obtained from a system of nanoparticles without a priori knowledge of their exact shapes (e.g. spheres or ellipsoids), sizes (0.5–50 nm) and distributions. The SAXS measurements yielded three categories of scattering profiles exhibiting 'strong', 'weak' and 'no' features. Diminishing features (e.g. broadening or disappearing peaks) in scattering profiles have always been attributed to the presence of significant dispersity in the system. Such featureless SAXS data are not suitable for traditional analysis using analytical models. If one were to fit a relevant analytical model (e.g. the lmfit analytical model for polydisperse spheres) to these 'weak' and 'no' SAXS profiles from our nanoparticle systems, one would obtain non-unique interpretations of the data. Relying on electron microscopy to identify the distributions of nanoparticle shapes and sizes is also unfeasible, especially in high-throughput synthesis and characterization loops. In such situations, to identify the distributions of particle sizes and shapes that could be present in the sample, one must rely on methods like ML-CREASE to interpret the data quickly and output all relevant interpretations about the structure present in the system. The ML-CREASE optimization loop takes the experimental scattering profile as input and outputs multiple candidate solutions whose computed scattering profiles match the SAXS profile input. The ML-CREASE method outputs distributions of relevant structural features, such as the volume fraction of the nanoparticles in the system and the mean and standard deviation of the particle size and aspect ratio, assuming a type of distribution (e.g. normal, log-normal) for size and aspect ratio. We find that, for the SAXS profiles analyzed here, accounting for the shape dispersity along with size dispersity of the nanoparticles using ML-CREASE improved the match between the computed scattering profiles and input experimental profiles.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Electron image contrast analysis of mosaicity in rutile nanocrystals using direct electron detection

Direct electron detection provides high detective quantum efficiency, significantly improved point spread function and fast read-out which have revolutionized the field of cryogenic electron microscopy. However, these benefits for high-resolution electron microscopy (HREM) are much less exploited, especially for in situ study where major impacts on crystallographic structural studies could be made. By using direct detection in electron counting mode, rutile nanocrystals have been imaged at high temperature inside an environmental transmission electron microscope. The improvements in image contrast are quantified by comparison with a charge-coupled device (CCD) camera and by image matching with simulations using an automated approach based on template matching. Together, these approaches enable a direct measurement of 3D shape and mosaicity (~1°) of a vacuum-reduced TiO 2 nanocrystal about 50 nm in size. Thus, this work demonstrates the possibility of quantitative HREM image analysis based on direct electron detection.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Dynamic Model Reduction for Large-Scale Power Systems Using Wide-Area Measurements

To perform faster than the real-time dynamic simulation of large-scale power systems, it is necessary to reduce the simulated system size by using equivalents for surrounding areas of the study area, and existing dynamic model reduction approach could provide the needed structure of the reduced area. However, further parameter optimization is required to achieve the desired accuracy. In this paper, a particle swarm optimization (PSO) based approach is used to solve the above problem. Parameters for the individual dynamic elements in the reduced system are calibrated repeatedly until the wide-area measurements of the reduced model and the original model are very similar to each other with satisfactory accuracy. Results indicate that after optimization, the dynamic response of the reduced model matches better with that of the original one than using existing methods. Under both the generator-trip event and the bus-fault event, the reduced model has a higher frequency match and less power mismatch.

42 ENGINEERING↗
DOE OSTI2024

Comprehensive Comparative Analysis: VSI-based vs. CSI-based Motor Drive Systems with Sinusoidal Output Voltage

The emergence of wide-bandgap (WBG) power devices opens opportunities for current source inverters (CSIs) to provide a promising alternative drive configuration for motor drive applications. The sinusoidal output voltage of CSI offers significant advantages for numerous motor drive applications, including reducing the risks associated with motor terminal overvoltages and bearing discharge currents. This paper compares the performance of CSIs and voltage source inverters (VSIs) with the same performance capabilities. More specifically, sine filters are added to the VSI output terminals to match the CSI performance, and a front-end boost converter is added to the VSI to match the CSI’s voltage-boost capability. The results show that the CSI active components require 48% less volume than the VSI, combined with other performance advantages that make it an appealing candidate for some future motor drive applications.

current source inverter, motor drive system, passi↗
DOE OSTI2024

Online Learning of Effective Turbine Wind Speed in Wind Farms

To develop better wind farm controllers that can meet more complex objectives, methods of modeling the wind turbine wakes at low computational expense are needed. Gaussian process (GP) regression offers a computationally inexpensive framework for learning complex functions from noisy measurements with very few datapoints. In this work, an online learning approach is presented to learn the rotor-averaged wind velocity at downstream wind turbines with GPs, using the available datastream of wind field measurements and wind turbine control set-points. This framework can readily be integrated into model-based controls methods because the model a) is updated online at low computational expense, b) assumes a mathematically favorable Gaussian form, and c) explicitly quantifies the stochastic nature of the wake field so that the trade-off between exploration and exploitation, and the uncertainty in the prediction, can be utilized. We show that a GP-learned model can match true values with errors within 0.5% on average, with as few as 5 training data points.

Gaussian process↗
DOE OSTI2025

Spatiotemporal Automatic Calibration of Infrastructure Lidar, Radar, and Camera with a Global Navigation Satellite System

Robust and accurate perception is important for modern intelligent transportation systems (ITS), which use sensors of various modalities for data fusion to create a digital twin of an intersection. Sensor calibration is an important process that creates a unified coordinate frame for the sensor output data so that it can be used for data fusion. Classical approaches for sensor calibration are time-consuming, require an overlapping field of view for feature matching, and are not feasible for ITS application as they cause disruptions in the flow of traffic. In this paper, we present a spatiotemporal automatic calibration approach to calibrate multiple infrastructure lidar, radar, and cameras installed at a traffic intersection. The approach uses global navigation satellite system (GNSS) positioning information shared by connected vehicles, and when the vehicle is detected by the sensor, we match the sensor detections with the GNSS coordinates. The proposed algorithm is evaluated with a real-world dataset utilizing detections from two radars, cameras, and lidars with a test vehicle instrumented with a post-processing kinematic (PPK)-corrected GNSS driving past the sensors installed at a four-way traffic intersection. The experimental results show that the proposed automatic calibration approach can achieve the transformation with a root mean squared error of less than 0.5 for radar and lidar and less than 2 for camera detections. The ability to rapidly calibrate sensors not only benefits initial installations, but can also be used for system health monitoring, while utilizing available connected vehicle data to test the real-time sensor fidelity and operational status.

ADVANCED PROPULSION SYSTEMS,ENERGY CONSERVATION, C↗
DOE OSTI2021

Light Propagation Considerations For Internally Clad Sapphire Optical Fiber Using the 6Li(n,)3H Reaction

Optical frequency domain reflectometry measurements in internally clad single crystal sapphire fiber have received attention in recent years due to their high temperature distributed sensing potential. As work with these fibers has proceeded, there have been some inconsistencies in the results. Deeper investigation and testing has identified two critical considerations for the proper functioning of these fibers. First, users must address the propagation of multimode light along the outer surface of the fiber. Here, by observing the far-field image of an internally clad sapphire fiber when adding index matching fluid to the outer fiber surface, we demonstrate the effects of removing the higher order modes from these fibers. The addition of index matching fluid resulted in nearly single mode performance where multimode performance was previously observed. Second, users must address the effect that coupling the fiber to the interrogator via silica based fiber has on the internally clad sapphire fibers performance. Direct fusion splicing of silica to sapphire, as has been used in the recent work with these fibers, has a mode filtering effect which can be beneficial towards the modal behavior of the fibers. However, in this paper we demonstrate that the splicing can cause a sensing failure due to little or no low order mode light, that is useful for sensing, returning to the detector. The positive results from recent years have demonstrated that optical frequency domain reflectometry sensing performance will be successful in clad sapphire fiber; but only when the considerations described herein are addressed properly.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Cost Reduction of School Bus Fleet Electrification With Optimized Charging and Distributed Energy Resources: Preprint

Considerations for electrifying school buses are presented with an analysis of battery sizing to match bus driving requirements. The charging and vehicle-to-building dispatch of the electric school buses were optimized to evaluate the potential to reduce the impact of the bus charging on the school's electric utility bill. Distributed energy resources (DER) and flexible building loads were also considered with the school bus electrification to evaluate the further reduction in energy costs with enhanced system integration and optimized dispatch. The effect of degradation on the school bus batteries was analyzed to determine if the smart charging and vehicle-to-building battery operation decreases the life of the battery. The results show that there is an opportunity to mitigate the increase of electric utility bills with improved charging controls and bi-directionally operating the school bus batteries to reduce building demand charges. The battery degradation analysis using dispatch with optimized charging and discharging shows acceptable battery life.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Effects of Reactive Power on Photovoltaic Inverter Reliability and Lifetime

This paper performs research on predicting Photovoltaic (PV) inverters reliability and lifetime based on thermal cycling. Thermal cycling is considered the most important stressors in an inverter system. In order to achieve this, a detailed electro-thermal model of the PV inverter will be developed along with their controllers capable of providing voltage support through reactive power. An in-house inverter was built, and a PV inverter model was developed to match the physical inverter. The PV inverter electrothermal model was validated for different ambient temperatures to match the in-house inverter hardware. The in-house inverter was placed inside a thermal chamber to emulate different ambient temperatures and their losses and temperature rises within the system were measured. After the validation of the model, a reduced order model of the inverter will be implemented to translate the mission profile of ambient temperature and solar irradiance into load profile of junction temperatures of the switches. The junction temperature data will be used to identify the reliability indices and hence predict the useful lifetime of the inverter system. Along with the model to predict useful lifetime of the system, the impact of reactive power on the overall reliability of the system will be studied. The key observation in this paper shows that lifetime of the inverter decreases as the operating power factor moves away from unity.

14 SOLAR ENERGY↗
DOE OSTI2021

Using Spectral Measurements to Characterize Solar Reference Cells on a Two-Axis Tracker

A study is commencing relating the spectral responsivity of reference cells in the field to changing spectral distribution during the day. Initial results indicate that measurements of the incident spectral distribution can be used to match results of reference cell measurements on a two-axis tracker with a standard deviation of ±0.25% under clear-sky conditions. Initial results are provided. As more data are obtained covering a variety of field conditions and locations, the robustness of these results will be tested. The website https://midcdmz.nrel.gov/apps/sitehome.pl?site=PVRES contains the data generated by this project.

41 EE - Solar Energy Technologies Office (EE-4S)↗