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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Landmark-embedded Gaussian process with applications for functional data modeling

In practice, we often need to infer the value of a target variable from functional observation data. A challenge in this task is that the relationship between the functional data and the target variable is very complex: the target variable not only influences the shape but also the location of the functional data. In addition, due to the uncertainties in the environment, the relationship is probabilistic, that is, for a given fixed target variable value, we still see variations in the shape and location of the functional data. To address this challenge, we present a landmark-embedded Gaussian process model that describes the relationship between the functional data and the target variable. A unique feature of the model is that landmark information is embedded in the Gaussian process model so that both the shape and location information of the functional data are considered simultaneously in a unified manner. Gibbs-Metropolis-Hasting algorithm is used for model parameters estimation and target variable inference. The performance of the proposed framework is evaluated by extensive numerical studies and a case study of nano-sensor calibration.

42 ENGINEERING↗
DOE OSTI2020

Superallowed 0 + → 0 + nuclear β decays: 2020 critical survey, with implications for V ud and CKM unitarity

A new critical survey of all half-life, decay-energy and branching-ratio measurements related to 23 superallowed 0 + → 0 + β decays is presented. Included are 222 individual measurements of comparable precision obtained from 174 published references. Compared with our last survey in 2015, we have added results from 28 new publications and eliminated an approximately equal number whose results have been superseded by much more precise modern data. We obtain world-average ft values for each of the 21 transitions that have a complete set of data, then apply radiative and isospin-symmetry-breaking corrections to extract “corrected” Ft values. Fifteen of these Ft values now have a precision of 0.3% or better and all take the same value within statistics, as expected from conservation of the vector current. Their average, Ft¯, when combined with the muon lifetime, yields the up-down quark-mixing element of the Cabibbo-Kobayashi-Maskawa matrix, V ud = 0.97373 ± 0.00031. This is lower than our 2015 result by one standard deviation and its uncertainty is increased by 50%. This is a consequence, not of any shifts in the experimental data, but of new calculations for the radiative corrections. The lower V ud value now leads to greater tension in the top-row test of unitarity in the CKM matrix. Updates in experimental data have independently led to a factor-of-two tighter limit being set on the possible existence of a scalar interaction. In conclusion, the new limit on Fierz interference is b F ≤ 0.0033 at the 90% confidence level.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Fiducial-cosmology-dependent systematics for the DESI 2024 full-shape analysis

We assess the impact of the fiducial cosmology choice on cosmological inference from full-shape (FS) fits of the galaxy power spectrum in the DESI 2024 Data Release 1 (DR1). Using a suite of AbacusSummit DR1 mock catalogues based on the Planck 2018 best-fit cosmology, we quantify potential systematic shifts introduced by analysing the data under five secondary cosmologies — featuring variations in matter density, thawing dark energy, higher effective number of neutrino species, reduced clustering amplitude, and the DESI DR1 BAO best-fit w 0 w a CDM cosmology — relative to DESI's baseline Planck 2018 cosmology. We investigate two complementary FS analysis approaches: full-modelling (FM) and ShapeFit (SF), each with distinct sensitivities to the assumed fiducial model. Across all tracers, we find for FM that systematic shifts induced by fiducial cosmology mismatches remain well below the DESI DR1 statistical uncertainties, with maximum deviations of 0.22σ DR1 in ΛCDM scenarios and 0.12σ DR1+SN when including SN Ia mock data in extended w 0 w a CDM fits. For SF, the shifts in the compressed parameters remain below 0.45σ DR1 for all tracers and cosmologies.

dark energy experiments↗
DOE OSTI2025

Machine Learning for Optimized Polarization at Jefferson Lab

Polarized cryo-targets and polarized photon beams are widely used in experiments at Jefferson Lab. Traditional methods for maintaining the optimal polarization involve manual adjustments throughout data taking by human shift takers. This may introduce some level of inconsistency simply due to the wide variety of experience and expertise of the shift takers themselves. Implementing machine learning-based control systems can improve the stability of the polarization without relying on human intervention. The cryo-target polarization is influenced by temperature, microwave energy, the distribution of paramagnetic radicals, as well as operational conditions including the radiation dose. Diamond radiators are used to generate linearly polarized photons from a primary electron beam. The energy spectrum of these photons can drift over time due to changes in the primary electron beam conditions and diamond degradation. As a first step towards automating the continuous optimization and control processes, uncertainty aware surrogate models have been developed to predict the polarization based on historical data. This talk will provide an overview of the use cases and models developed, highlighting the collaboration between data scientists and physicists at Jefferson Lab.

Jeske, Torri [Thomas Jefferson National Accelerato↗
DOE OSTI2022

Regulators of early maize leaf development inferred from transcriptomes of laser capture microdissection (LCM)-isolated embryonic leaf cells

The superior photosynthetic efficiency of C 4 leaves over C 3 leaves is owing to their unique Kranz anatomy, in which the vein is surrounded by one layer of bundle sheath (BS) cells and one layer of mesophyll (M) cells. Kranz anatomy development starts from three contiguous ground meristem (GM) cells, but its regulators and underlying molecular mechanism are largely unknown. To identify the regulators, we obtained the transcriptomes of 11 maize embryonic leaf cell types from five stages of pre-Kranz cells starting from median GM cells and six stages of pre-M cells starting from undifferentiated cells. Principal component and clustering analyses of transcriptomic data revealed rapid pre-Kranz cell differentiation in the first two stages but slow differentiation in the last three stages, suggesting early Kranz cell fate determination. In contrast, pre-M cells exhibit a more prolonged transcriptional differentiation process. Differential gene expression and coexpression analyses identified gene coexpression modules, one of which included 3 auxin transporter and 18 transcription factor (TF) genes, including known regulators of Kranz anatomy and/or vascular development. In situ hybridization of 11 TF genes validated their expression in early Kranz development. We determined the binding motifs of 15 TFs, predicted TF target gene relationships among the 18 TF and 3 auxin transporter genes, and validated 67 predictions by electrophoresis mobility shift assay. From these data, we constructed a gene regulatory network for Kranz development. Our study sheds light on the regulation of early maize leaf development and provides candidate leaf development regulators for future study.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Multi-fidelity information fusion with concatenated neural networks

Recently, computational modeling has shifted towards the use of statistical inference, deep learning, and other data-driven modeling frameworks. Although this shift in modeling holds promise in many applications like design optimization and real-time control by lowering the computational burden, training deep learning models needs a huge amount of data. This big data is not always available for scientific problems and leads to poorly generalizable data-driven models. This gap can be furnished by leveraging information from physics-based models. Exploiting prior knowledge about the problem at hand, this study puts forth a physics-guided machine learning (PGML) approach to build more tailored, effective, and efficient surrogate models. For our analysis, without losing its generalizability and modularity, we focus on the development of predictive models for laminar and turbulent boundary layer flows. In particular, we combine the self-similarity solution and power-law velocity profile (low-fidelity models) with the noisy data obtained either from experiments or computational fluid dynamics simulations (high-fidelity models) through a concatenated neural network. We illustrate how the knowledge from these simplified models results in reducing uncertainties associated with deep learning models applied to boundary layer flow prediction problems. The proposed multi-fidelity information fusion framework produces physically consistent models that attempt to achieve better generalization than data-driven models obtained purely based on data. While we demonstrate our framework for a problem relevant to fluid mechanics, its workflow and principles can be adopted for many scientific problems where empirical, analytical, or simplified models are prevalent. In line with grand demands in novel PGML principles, this work builds a bridge between extensive physics-based theories and data-driven modeling paradigms and paves the way for using hybrid physics and machine learning modeling approaches for next-generation digital twin technologies.

42 ENGINEERING↗
DOE OSTI2021

Downscaled precipitation and mean air temperature datasets; East-Taylor subbasin; 2008-2019; daily temporal resolution; 400 m spatial resolution

This dataset provides gridded meteorological forcing data (specifically, daily precipitation and daily mean air temperature). The dataset has been generated by downscaling the Parameter-elevation Regressions on Independent Slopes Model (PRISM) dataset from a spatial resolution of 800 m to 400 m. The time period is 2008-2019, and the mapped area is East Taylor subbasin in Upper Colorado. The data are in the form of NetCDF files, arranged by year. Compared to the PRISM dataset, the dates of the downscaled dataset are shifted backwards by one (e.g., downscaled data for May 25 corresponds to PRISM data for May 26). This temporal shifting makes the meteorological forcing correspond more closely to the prescribed date. The NetCDF format is a standard raster format that can be read using any Geographic Information System (GIS) software; plenty of modules exist in popular scripting languages (such as Python, R and Matlab) that can also be used to read NetCDF files.East_Taylor_Tavg_PRISM400 corresponds to mean air temperature.East_Taylor_Precip_PRISM400.zip corresponds to precipitation.The proprietary PRISM data (800 m resolution) were purchased with funding from the Watershed Function Scientific Focus Area supported by U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research under award no. DE-AC02-05CH11231.Dataset update on March 9, 2022:Uploaded new data files that are identical to the earlier files but are now in the NetCDF format, arranged by year. Earlier, the files were in the GeoTiff format, arranged by date.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A Data-Driven Voltage Control Strategy for Distribution Grids With Distributed Energy Resources

Traditionally, distribution system control approaches have been model-based. The deployment of advanced metering infrastructure has provided electric utilities with the capability of data-driven control with real-time measurements. The shift from model-based to data-driven control represents a significant advancement in the management of distribution systems, offering a more adaptive approach to system control because of the ability to dynamically adapt to changing conditions without the need for system modeling. Here, in this paper, a behavioral data-driven control method is developed to provide voltage regulation to an actual distribution system by controlling the legacy devices and distributed energy resource (DER) assets. The studied distribution system has a load tap changer and three capacitor banks as the legacy devices and photovoltaic systems as the DERs. The performance of the proposed control algorithm is validated using a laboratory test bed setup considering multiple scenarios. The results show that the proposed control achieved 99% voltage regulation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Validation of time-dependent shift using the pulsed sphere benchmarks

The detailed behavior of neutrons in a rapidly changing time-dependent physical system is a challenging computational physics problem, particularly when using Monte Carlo methods on heterogeneous high-performance computing architectures. A small number of algorithms and code implementations have been shown to be performant for time-independent (fixed source and k-eigenvalue) Monte Carlo, and there are existing simulation tools that successfully solve the time-dependent Monte Carlo problem on smaller computing platforms. To bridge this gap, a time-dependent version of ORNL’s Shift code has been recently developed. Shift’s history-based algorithm on CPUs, and its event-based algorithm on GPUs, have both been observed to scale well to very large numbers of processors, which motivated the extension of this code to solve time-dependent problems. The validation of this new capability requires a comparison with time-dependent neutron experiments. Lawrence Livermore National Laboratory’s (LLNL) pulsed sphere benchmark experiments were simulated in Shift to validate both the time-independent as well as new time-dependent features recently incorporated into Shift. A suite of pulsed-sphere models was simulated using Shift and compared to the available experimental data and simulations with MCNP. Overall results indicate that Shift accurately simulates the pulsed sphere benchmarks, and that the new time-dependent modifications of Shift are working as intended. Validated exascale neutron transport codes are essential for a wide variety of future multiphysics applications.

Palmer, Camille J.↗
DOE OSTI2025

Adoption of AI in the Utility T&D Sector: Use Cases, Consequence, Assessment and Benefits

Digital transformation and utilization of artificial intelligence (AI) in the electric grid are fundamentally changing the industry’s approach to common problems and enabling a broader paradigm shift in grid planning and operations. The change in approach is circularly both enabling and driving modernization, with load growth and reliable management of data center and AI infrastructure shifting away from planning approaches with relatively predictable behaviors and toward a mix of consumer and industrial choices that surpass human cognitive abilities to process. This movement has potential to condition humans to not understand the system on which the AI depends, while requiring it for development of the necessary infrastructure. Approaches which would address most likely grid conditions and events, such as faults, aging of equipment, and weather, now must also account for large loads which shift not based upon weather or time of day, but the computational load. Quantifying computational load is independent of the traditional grid forecasting variables, where a data center’s aggregate load is determined by user and AI system behavior and decoupled from normal grid planning and operations. AI is both the cause and solution for these challenges, with new grid planning tools integrating massive amounts of decisions into frameworks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

The Diurnal Dynamics of Gross Primary Productivity Using Observations From the Advanced Baseline Imager on the Geostationary Operational Environmental Satellite‐R Series at an Oak Savanna Ecosystem

Gross primary productivity (GPP) is the largest flux in the global carbon cycle and satellite-based GPP estimates have long been used to study the trends and interannual variability of GPP. With recent updates to geostationary satellites, we can now explore the diurnal variability of GPP at a comparable spatial resolution to polar-orbiting satellites and at temporal frequencies comparable to eddy covariance (EC) tower sites. We used observations from the Advanced Baseline Imager on the Geostationary Operational Environmental Satellite-R series (GOES-R) to test the ability of subdaily satellite data to capture the shifts in the diurnal course of GPP at an oak savanna EC site in California, USA that is subject to seasonal soil moisture declines. We compared three methods to estimate GPP: (a) a light-use efficiency model, (b) a linear relationship between the product of near-infrared reflectance of vegetation and photosynthetically active radiation (LIN-NIR v P) and EC tower GPP, and (c) a light response curve (LRC-NIR v P) between NIR v P and EC GPP. The LRC-NIR v P achieved the lowest mean absolute error for winter (2 µmol CO 2 m –2 s –1 ), spring (2.51 µmol CO 2 m –2 s –1 ), summer (1.43 µmol CO 2 m –2 s –1 ), and fall (1.35 µmol CO 2 m –2 s –1 ). The ecosystem experienced the largest shift in daily peak GPP in relation to the peak of incoming solar radiation toward the morning hours during the dry summers. The LRC-NIRvP and the light-use efficiency model were in agreement with these patterns of a shift in peak daily GPP toward the morning hours during summer. Our results can help develop diurnal estimates of GPP from geostationary satellites that are sensitive to fluctuating environmental conditions during the day.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A 1-year study on SARS-CoV-2 variant shifts in wastewater using dPCR: comparison with clinical and GISAID data

Wastewater testing can be used to monitor SARS-CoV-2 infections in communities. Data from PCR-based wastewater testing are usually available to public health authorities within 5–7 days after excreta and other body fluids enter the sewer. While PCR-based methods can accurately detect and quantify SARS-CoV-2, sequencing-based methods are usually required to distinguish between variants, delaying the results and adding cost to the process. We developed and assessed a novel, customizable digital PCR (dPCR)-based genotyping method for SARS-CoV-2 variant detection in wastewater, which is more cost-effective, faster, and more accessible than sequencing. This approach was applied to more than 1,400 wastewater samples

Wilton, Rose↗
DOE OSTI2025

Utah FORGE: 16B(78)-32 RFS DSS Strain Change Rate vs. Depth During 16A(78)-32 Stimulation

This dataset contains strain change rate versus depth data acquired using a Rayleigh frequency shift (RFS) distributed strain sensing (DSS) system during hydraulic stimulation of well 16A(78)-32 at the Utah FORGE site in April 2024. The data were collected from an optical fiber installed in the annulus of production well 16B(78)-32, approximately 300 feet from the injection well. The dataset includes tabulated strain data and an explanation of the methodology used to generate the frac log, which integrates strain change rate signals over selected time windows to identify fracture events.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Coulomb phase corrections to the transverse analyzing power AN(t) in high energy forward proton-proton scattering

Study of the polarized proton-proton elastic scattering in the Coulomb Nuclear interference region allows one to measure forward hadronic spin-flip amplitude including the phase. However, in a precision experimental data analysis, a phase shift correction δC due to the long distance Coulomb interaction should be taken into account. For the unpolarized scattering, δC is commonly considered as well established. Here, we evaluate the Coulomb phase shifts for the spin-flip electromagnetic and hadronic amplitudes. The difference between spin-flip and non-flip Coulomb phase shifts was found to be negligible for current experimental accuracy in the high energy transverse spin elastic pp measurements. However, effective alteration of the hadronic spin-flip amplitude by the long distance electromagnetic corrections can be noticeable.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

HDG-1 Fiber Bragg grating data analysis

The main goal of the High dose graphite 1 Advanced test reactor experiment was to study nuclear grade graphite at high fluences. Additional supplementary optical fiber instrumentation was added to this long duration experiment for instrumentation development purposes. The supplementary instrumentation consisted of two pure silica core, fluorine doped cladding optical fibers each etched with 9 fiber Bragg gratings, one fiber being heat treated for 9 hours at 750 C and 16 hours at 750 C, the other being heat treated for 24 hours at 550 C and 48 hours at 650 C. Fiber Bragg gratings are known to have issues of measurement drift when in high temperature and high radiation environments like what is encountered in the Advanced test reactor. At the culmination of this experiment, the optical fibers saw ~1.3E21 n/cm2 total fluence, which is at the highest fluences that fiber Bragg gratings have been studied to date. Reported here is the analysis of this data including radiation induced shift and changes in sensitivity.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2021

Near L-edge Single and Multiple Photoionization of Doubly Charged Iron Ions

Using the photon-ion merged-beams technique at a synchrotron light source, we have measured relative cross sections for single and up to five-fold photoionization of Fe 2+ ions in the energy range of 690-920 eV. This range contains thresholds and resonances associated with ionization and excitation of 2p and 2s electrons. Calculations were performed to simulate the total absorption spectra. The theoretical results show very good agreement with the experimental data, if overall energy shifts of up to 2.5 eV are applied to the calculated resonance positions and assumptions are made about the initial experimental population of the various levels of the Fe 2+ ([Ar]3d 6 ) ground configuration. Furthermore, we performed extensive calculations of the Auger cascades that result when an electron is removed from the 2p subshell of Fe 2+ . These computations lead to a better agreement with the measured product-charge-state distributions as compared to earlier work. We conclude that the L-shell absorption features of low-charged iron ions are useful for identifying gas-phase iron in the interstellar medium and for discriminating against the various forms of condensed-phase iron bound to composite interstellar dust grains.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

CMB distance priors revisited: effects of dark energy dynamics, spatial curvature, primordial power spectrum, and neutrino parameters

As a physical and sufficient compression of the full CMB data, the CMB distance priors, or shift parameters, have been widely used and provide a convenient way to include CMB data when obtaining cosmological constraints. In this paper, we revisit this data vector and examine its stability under different cosmological models. We find that the CMB distance priors are an accurate substitute for the full CMB data when probing dark energy dynamics. This is true when the primordial power spectrum model is directly generalized from the power spectrum of the model used in the derivation of the distance priors from the CMB data. We discover a difference when a non-flat model with the untilted primordial inflation power spectrum is used to measure the distance priors. This power spectrum is a radical change from the more conventional tilted primordial power spectrum and violates fundamental assumptions for the reliability of the CMB shift parameters. We also investigate the performance of CMB distance priors when the sum of neutrino masses Σm ν and the effective number of relativistic species N eff are allowed to vary. Our findings are consistent with earlier results: the neutrino parameters can change the measurement of the sound horizon from CMB data, and thus the CMB distance priors. We find that when the neutrino model is allowed to vary, the cold dark matter density ω c and N eff need to be included in the set of parameters that summarize CMB data, in order to reproduce the constraints from the full CMB data. As a result, we present an updated and expanded set of CMB distance priors which can reproduce constraints from the full CMB data within 1σ, and are applicable to models with massive neutrinos, as well as non-standard cosmologies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Power now, pay later: the evolution of U.S. residential solar financing

Most U.S. residential rooftop solar customers finance their solar purchases through loans or by buying power from third-party owned systems. Prior research demonstrates how third-party ownership (TPO) models such as leases emerged in the early 2010s and accelerated solar adoption by low- and moderate-income households while driving market concentration in the installation industry. Since 2015, loans have emerged as a prevalent financing alternative, but the potential effects of loans on the customer base and industry remain understudied. Here, we fill that research gap by developing a methodology to identify loan-financed and third-party owned systems in a household-level solar adopter data set. The data suggest that loans accounted for increasing solar market shares from 2017 until reaching as high as 70% in 2022, but that the market has since shifted back to TPO. The data show that TPO adopters in our sample earned about 16%–18% less and loan recipients earned 3%–7% less, at the median, than customers who self-financed systems. These results reaffirm prior research showing that TPO has accelerated low- and moderate-income adoption and that loans have likewise expanded the customer base to a lesser extent. The results suggest that loan-financed systems entail around a 16%–26% price premium that is only partly explained by loan fees. Finally, the data suggest that the emergence of loans has likely reduced market concentration in the rooftop solar industry.

financing↗