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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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Radar - 449MHz - Forks, WA (FKS) - Raw Data

**Winds.** A radar wind profiler measures the Doppler shift of electromagnetic energy scattered back from atmospheric turbulence and hydrometeors along 3-5 vertical and off-vertical point beam directions. Back-scattered signal strength and radial-component velocities are remotely sensed along all beam directions and are combined to derive the horizontal wind field over the radar. These data typically are sampled and averaged hourly and usually have 6-m and/or 100-m vertical resolutions up to 4 km for the 915 MHz and 8 km for the 449 MHz systems. **Temperature.** To measure atmospheric temperature, a radio acoustic sounding system (RASS) is used in conjunction with the wind profile. These data typically are sampled and averaged for five minutes each hour and have a 60-m vertical resolution up to 1.5 km for the 915 MHz and 60 m up to 3.5 km for the 449 MHz. **Moments and Spectra.** The raw spectra and moments data are available for all dwells along each beam and are stored in daily files. For each day, there are files labeled "header" and "data." These files are generated by the radar data acquisition system (LAP-XM) and are encoded in a proprietary binary format. Values of spectral density at each Doppler velocity (FFT point), as well as the radial velocity, signal-to-noise ratio, and spectra width for the selected signal peak are included in these files. Attached zip files, *449mhz-spectra-data-extraction.zip* and *449mhz-moment-data-extraction.zip*, include executables to unpack the spectra, (GetSpectra32.exe) and moments (GetMomSp32.exe), respectively. Documentation on usage and output file formats also are included in the zip files.

17 WIND ENERGY↗
DOE OSTI2025

Electric Utility Communications Standards Landscape 2025 Edition

Historically, challenges to managing electric utility data exchange have been addressed through dedicated communication solutions, enabling the transmission of data with both speed and security. Protocols have been deployed in a relatively uniform fashion; for example, field communications for Supervisory Control and Data Acquisition (SCADA) are commonly implemented using IEEE 1815 (DNP3).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

The case for data science in experimental chemistry: examples and recommendations

The physical sciences community is increasingly taking advantage of the possibilities offered by modern data science to solve problems in experimental chemistry and potentially to change the way we design, conduct and understand results from experiments. Successfully exploiting these opportunities involves considerable challenges. In this Expert Recommendation, we focus on experimental co-design and its importance to experimental chemistry. We provide examples of how data science is changing the way we conduct experiments, and we outline opportunities for further integration of data science and experimental chemistry to advance these fields. Our recommendations include establishing stronger links between chemists and data scientists; developing chemistry-specific data science methods; integrating algorithms, software and hardware to ‘co-design’ chemistry experiments from inception; and combining diverse and disparate data sources into a data network for chemistry research.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Forming a database to study reversed magnetic shear from the National Spherical Torus eXperiment using machine learning

Achieving a long-lived reversed magnetic shear (RMS) target plasma in the National Spherical Torus eXperiment Upgrade will require developing various sustainment scenarios. To help with the ongoing plasma control efforts, the development of a new analysis for the motional Stark effect (MSE) diagnostic using a machine learning algorithm, namely, MSE-ML, is described. MSE-ML will be used to identify patterns during RMS discharges, some of which suffer magnetohydrodynamic (MHD) events resulting in current redistribution and monotonic q-profiles. A database consisting of q and magnetic shear profiles is being constructed primarily based on the existing National Spherical Torus eXperiment data with equilibrium reconstructions constrained by the magnetic field pitch angle profile measured using the multi-channel MSE diagnostic. An unsupervised k-means clustering of the data is developed to study the RMS formation as a function of time. The initial clustering from the q-profiles shows significant differences in both amplitude and the duration of the RMS period. As a goal, the clustering results that detect and distinguish shots with substantial and sustained RMS are to be used as a preprocessing step in a supervised algorithm to identify the underlying conditions that lead to long-lasting improved confinement with RMS. Another aim of the MSE-ML study is to identify precursors of RMS-destroying MHD events in either derived data such as the q-profile or directly measured data such as the magnetic field pitch angle profile.

Uzun-Kaymak, I. U. (ORCID:0000000276251493)↗
DOE OSTI2023

Software for Heliospheric Science

This software is being developed to support data analysis, modeling, and simulation for the growing field of heliosphere physics. In particular, this software will implement data analysis, modeling, inference, and simulation of physical mechanisms describing how energetic neutral atoms behave within the Earth’s heliosphere and in the interstellar medium beyond.

VanDervort, Lauren↗
DOE OSTI2021

Quality Control of and Analysis Enabling Use of MARCUS and MICRE data for Scientific Applications

The primary objective of this project was to provide a preliminary investigation of data collected during the MARCUS/MICRE field experiments and to produce products and analysis for the scientific community that will enable future scientific investigations and hypothesis testing. Further, the goal was to assist those in the scientific community to understand the strengths and caveats of the MARCUS/MICRE data so that members of the scientific community could use the data in their publications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Metadata Standards for the NSE: Extended Field Standards

This standard presents a set of optional metadata fields for managed digital objects within the Nuclear Security Enterprise (NSE) and provides a deeper look at data representation in metadata by looking at the representation of 1) Records Management required metadata, and 2) common representations of technical/scientific data. Metadata standardization is a critical enabler for effectively sharing data, documents, and other digital objects between NSE sites, and for tracing the digital thread at the object level. Standardization is necessary for both schemas and vocabularies, meaning that both field standards and value standards must be specified. This document serves as a complementary field standard, recommending an optional set of fields that should be uniformly built for all managed digital objects within the NSE. This document specifically focuses on extending the shared discovery layer defined in the first white paper by introducing additional descriptive and data representation fields that improve cross-site search and interpretation.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2026

SPT-3G D1: Quadratic-Estimator CMB Lensing Reconstruction and Cosmology

We present a map of the cosmic microwave background (CMB) lensing potential reconstructed from observations taken during the 2019 and 2020 seasons with the third-generation camera on the South Pole Telescope (SPT), covering the $1500\,{\rm deg}^{2}$ SPT-3G Main field, referred to as the SPT-3G D1 dataset. From the multi-frequency temperature and polarization data, we reconstruct the CMB lensing field using a quadratic estimator that jointly accounts for the $T$, $E$, and $B$ fields and their covariance. The resulting lensing map is dominated by polarization information for $L \lesssim 600$ and provides the highest signal-to-noise measurement per mode reported to date. With nuisance parameters fixed to their best-fit values, we measure a lensing amplitude consistent with unity at $2\%$ precision relative to the $Λ$CDM model that best fits the combined Planck, ACT DR6, and SPT-3G D1 $TT/TE/EE$ likelihoods (${\rm CMB}_{\rm SPA}$). We further measure the structure-growth parameter $σ_{8}Ω_{\rm m}^{0.25}$ to be $0.6046\pm0.0096$ from the SPT-3G D1 lensing spectrum alone and $0.6020\pm0.0084$ when combined with ACT DR6 and Planck PR4 CMB lensing. By further combining this with ${\rm CMB}_{\rm SPA}$ and the latest DESI DR2 BAO data, we obtain $\sum m_ν < 0.072\,\mathrm{eV}$ (95% C.L.) when allowing the neutrino mass to vary within $Λ$CDM. Compared with previous work, the better agreement of our measurement with DESI DR2 BAO yields both this relaxed upper bound and reduced ($\mathord{\sim}2σ$) preferences for nonzero spatial curvature and for deviations of $(w_0,w_a)$ from the $Λ$CDM expectation. When we combine CMB lensing with the DES Y3 3$\times$2pt analysis, we obtain $S_{8}=0.811\pm0.011$, corresponding to a $1.4\%$ constraint on the late-time clustering amplitude. This precision is competitive with that obtained from the primary CMB within $Λ$CDM.

Omori, Y. [Chicago U., Astron. Astrophys. Ctr.; Ch↗
DOE OSTI2025

SITCOMTN-162: Testing the implementation of Metadetection and Cell-Based Coadds on Abell 360 LSSTComCam data

The purpose of this technote is to test the technical quality of LSSTComCam commissioning data, specifically the Rubin_SV_38_7 field, by utilizing cell-based coadds and Metadetection by measuring the tangential and cross weak lensing shear profiles of the massive cluster Abell 360 (called A360 throughout the technote). The process entails generating the cell-based coadds for Metadetection to run on, identifying and removing cluster member galaxies, applying quality cuts, calibrating the shear measurements, and validation. Cell-based coadds and Metadetection are both currently in the process of being implemented within the LSST Science Pipelines at the time of this technote. There is substantial technical value in attempting a difficult measurement prior to full implementation. Measuring the tangential shear around A360 will showcase the current abilities of these algorithms, as well as highlight where work is still needed. As seen from the resulting shear profile of A360, the cell-based coadds and Metadetection are able to work in tandem to produce a shear catalog and resulting reduced shear profile. This technote is one part of a series studying A360 in order to both stress test the commissioning camera and demonstrate the technical capabilities of the Vera Rubin Observatory. We study the quality of the PSF modeling and impact it can have on cluster WL in [Combet et al., 2025], implementation of cell-based coadds and subsequent use for Metadetect [Sheldon et al., 2023] in this technote, photometric calibration in (in prep), source selection and photometric redshifts in [Adari et al., 2025], use of Anacal [Li et al., 2024] to produce a cluster shear profile in [Li et al., 2025], and background subtraction in this field and Fornax in [Zhou et al., 2025].

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Landsat-based Irrigation Dataset (LANID): 30 m resolution maps of irrigation distribution, frequency, and change for the US, 1997–2017

Abstract. Data on irrigation patterns and trends at field-level detail across broad extents are vital for assessing and managing limited water resources. Until recently, there has been a scarcity of comprehensive, consistent, and frequent irrigation maps for the US. Here we present the new Landsat-based Irrigation Dataset (LANID), which is comprised of 30 m resolution annual irrigation maps covering the conterminous US (CONUS) for the period of 1997–2017. The main dataset identifies the annual extent of irrigated croplands, pastureland, and hay for each year in the study period. Derivative maps include layers on maximum irrigated extent, irrigation frequency and trends, and identification of formerly irrigated areas and intermittently irrigated lands. Temporal analysis reveals that 38.5×106 ha of croplands and pasture–hay has been irrigated, among which the yearly active area ranged from ∼22.6 to 24.7×106 ha. The LANID products provide several improvements over other irrigation data including field-level details on irrigation change and frequency, an annual time step, and a collection of ∼10 000 visually interpreted ground reference locations for the eastern US where such data have been lacking. Our maps demonstrated overall accuracy above 90 % across all years and regions, including in the more humid and challenging-to-map eastern US, marking a significant advancement over other products, whose accuracies ranged from 50 % to 80 %. In terms of change detection, our maps yield per-pixel transition accuracy of 81 % and show good agreement with US Department of Agriculture reports at both county and state levels. The described annual maps, derivative layers, and ground reference data provide users with unique opportunities to study local to nationwide trends, driving forces, and consequences of irrigation and encourage the further development and assessment of new approaches for improved mapping of irrigation, especially in challenging areas like the eastern US. The annual LANID maps, derivative products, and ground reference data are available through https://doi.org/10.5281/zenodo.5548555 (Xie and Lark, 2021a).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Machine learning on FPGA for event selection

Real-time data processing is a frontier field in experimental particle physics. The application of FPGAs at the trigger level is used by many current and planned experiments (CMS, LHCb, Belle2, PANDA). Usually they use conventional processing algorithms. LHCb has implemented Machine Learning (ML) elements for real-time data processing with a triggered readout system that runs most of the ML algorithms on a computer farm. The work described in this article aims to test the ML-FPGA algorithms for streaming data acquisition. Herein, there are many experiments working in this area and they have a lot in common, but there are many specific solutions for detector and accelerator parameters that are worth exploring further. This report describes the purpose of the work and progress in evaluating the ML-FPGA application.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Relativistic mean-field theories for neutron-star physics based on chiral effective field theory

We describe and implement a procedure for determining the couplings of a relativistic mean-field theory (RMFT) that is optimized for application to neutron star phenomenology. In the standard RMFT approach, the couplings are constrained by comparing the theory's predictions for symmetric matter at saturation density with measured nuclear properties. The theory is then applied to neutron stars which consist of neutron-rich matter at densities ranging up to several times saturation density, which allows for additional astrophysical constraints. In our approach, rather than using the RMFT to extrapolate from symmetric to neutron-rich matter and from finite-sized nuclei to uniform matter, we fit the RMFT to properties of uniform pure neutron matter obtained from chiral effective field theory. Chiral effective field theory incorporates the experimental data for nuclei in the framework of a controlled expansion for nuclear forces valid at nuclear densities and enables us to account for theoretical uncertainties when fitting the RMFT. We construct four simple RMFTs that span the uncertainties provided by chiral effective field theory for neutron matter, and are consistent with current astrophysical constraints on the equation of state. Lastly, our RMFTs can be used to model the properties of neutron-rich matter across the vast range of densities and temperatures encountered in neutron stars and their mergers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Machine learning in materials science: From explainable predictions to autonomous design

The advent of big data and algorithmic developments in the field of machine learning (and artificial intelligence, in general) have greatly impacted the entire spectrum of physical sciences, including materials science. Materials data, measured or computed, combined with various techniques of machine learning have been employed to address a myriad of challenging problems, such as, development of efficient and predictive surrogate models for a range of materials properties, screening and down-selection of novel candidate materials for targeted applications, new methodologies to improve and further expedite molecular and atomistic simulations, with likely many more important developments to come in the foreseeable future. While the applications thus far have provided a glimpse of the true potential data-enabled routes have to offer, it has also become clear that further progress in this direction hinges on our ability to understand, explain and rationalize findings of a machine learning model in light of the domain-knowledge. This focused review provides an overview of the main areas where machine learning has been widely and successfully used in materials science. Subsequently, a brief discussion of several techniques that have been helpful in extracting physically-meaningful insights, causal relationships and design-centric knowledge from materials data is provided. Finally, we identify some of the imminent opportunities and challenges that materials community faces in this exciting and rapidly growing field.

36 MATERIALS SCIENCE↗
DOE OSTI2022

AmeriFlux FLUXNET-1F US-CS1 Central Sands Irrigated Agricultural Field

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-CS1 Central Sands Irrigated Agricultural Field. This is the FLUXNET version of the carbon flux data for the site US-CS1 Central Sands Irrigated Agricultural Field produced by applying the standard ONEFlux (1F) software. Site Description - Heartland Farms Center-Pivot Irrigated Potato Field

Desai, Ankur↗
DOE OSTI2022

AmeriFlux FLUXNET-1F US-CS3 Central Sands Irrigated Agricultural Field

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-CS3 Central Sands Irrigated Agricultural Field. This is the FLUXNET version of the carbon flux data for the site US-CS3 Central Sands Irrigated Agricultural Field produced by applying the standard ONEFlux (1F) software. Site Description - Heartland Farms Center-Pivot Irrigated Potato Field

Desai, Ankur↗
DOE OSTI2022

AmeriFlux FLUXNET-1F US-CS4 Central Sands Irrigated Agricultural Field

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-CS4 Central Sands Irrigated Agricultural Field. This is the FLUXNET version of the carbon flux data for the site US-CS4 Central Sands Irrigated Agricultural Field produced by applying the standard ONEFlux (1F) software. Site Description - Heartland Farms Center-Pivot Irrigated Potato Field

Desai, Ankur↗
DOE OSTI2024

AmeriFlux FLUXNET-1F US-CS5 Central Sands Irrigated Agricultural Field

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-CS5 Central Sands Irrigated Agricultural Field. This is the FLUXNET version of the carbon flux data for the site US-CS5 Central Sands Irrigated Agricultural Field produced by applying the standard ONEFlux (1F) software. Site Description - Heartland Farms Center-Pivot Irrigated Potato Field

Desai, Ankur↗
DOE OSTI2024

AmeriFlux FLUXNET-1F US-CS6 Central Sands Irrigated Agricultural Field

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-CS6 Central Sands Irrigated Agricultural Field. This is the FLUXNET version of the carbon flux data for the site US-CS6 Central Sands Irrigated Agricultural Field produced by applying the standard ONEFlux (1F) software. Site Description - Worzella Farms Center-Pivot Irrigated Potato Field

Desai, Ankur↗