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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 253 records · Page 14

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DOE OSTI2026

Slow Wake Recovery and Low Turbulence Behind Wind Farms Parameterized in Mesoscale Simulations

Numerical weather prediction (NWP) and climate models equipped with wind-farm parameterizations (WFPs) can simulate cluster wake effects affecting downstream wind farms in both onshore and offshore environments. This study evaluates wake recovery behind a wind farm represented by the NWP-WFP approach in the Weather Research and Forecasting (WRF) model using either the Fitch et al. (2012) or Ma et al. (2022a, b) WFPs. Results are benchmarked against large-eddy simulations (LES) of an idealized offshore wind farm with aligned and staggered layouts under neutral atmospheric stability. Near-farm wake recovery is underestimated in NWP-WFP simulations due to its representation on a coarse mesoscale grid. This limitation leads to slow wake recovery through two interconnected mechanisms: (i) spatial gradients in the wind velocity field are weaker compared to LES and (ii) turbulence kinetic energy (TKE) remains low not because of excessive dissipation but due to insufficient shear production caused by these weakened gradients. For the scenario considered here, a wind-speed bias develops in the near-farm wake and persists into the far wake. Differences between the NWP-WFP simulations and LES emerge within a short distance downstream of the farm exit, where the mesoscale simulations recover too slowly. This reduced recovery contributes approximately 0.15-0.50 m s-1 to the near-farm wind-speed bias. The bias established in this region is not subsequently compensated for downstream but instead propagates into the far wake, where wind-speed differences of approximately 0.4-0.6 m s-1 remain up to 50 km downstream. Higher-resolution mesoscale simulations partially reduce this bias. Increasing turbine-added TKE or including subgrid wake effects provides additional improvement, but neither fully addresses the underlying cause. The slow wake recovery is not caused by limitations of the WFPs themselves, as it also occurs outside their region of influence, and adding subgrid wake effects does not significantly impact recovery. Rather, the slow wake recovery is a consequence of mesoscale flow representation. This behavior is not limited to regions downstream of the wind farm but is less visible within the farm, where wake recovery occurs simultaneously with turbine-induced momentum extraction. These results highlight the need for improved representations of wake recovery both within and downstream of wind farms. While enhanced subgrid modeling, shear-driven TKE production, and refined WFP formulations may improve intra-farm dynamics, accurately capturing near-farm wake recovery downstream remains challenging, as WFPs do not act in this region.

17 WIND ENERGY↗

NASA NTRS2007

Symmetry, Statistics and Structure in MHD Turbulence

Here, we examine homogeneous MHD turbulence in terms of truncated Fourier series. The ideal MHD equations and the associated statistical theory of absolute equilibrium ensembles are symmetric under P, C and T. However, the presence of invariant helicities, which are pseudoscalars under P and C, dynamically breaks this symmetry. This occurs because the surface of constant energy in phase space has disjoint parts, called components: while ensemble averages are taken over all components, a dynamical phase trajectory is confined to only one component. As the Birkhoff-Khinchin theorem tells us, ideal MHD turbulence is thus non-ergodic. This non-ergodicity manifests itself in low-wave number Fourier modes that have large mean values (while absolute ensemble theory predicts mean values of zero). Therefore, we have coherent structure in ideal MHD turbulence. The level of non-ergodicity and amount of energy contained in the associated coherent structure depends on the values of the helicities, as well as on the presence, or not, of a mean magnetic field and/or overall rotation. In addition to the well known cross and magnetic helicities, we also present a new invariant, which we call the parallel helicity, since it occurs when mean field and rotation axis are aligned. The question of applicability of these results to real (i.e., dissipative) MHD turbulence is also examined. Several long-time numerical simulations on a 64(exp 3) grid are given as examples. It is seen that coherent structure begins to form before decay dominates over nonlinearity. The connection of these results with inverse spectral cascades, selective decay, and magnetic dynamos is also discussed.

Shebalin, John V.↗

NASA NTRS2017

Limiting Data Friction by Reducing Data Download Using Spatiotemporally Aligned Data Organization Through STARE

Current data processing practice limits the volume and variety of relevant geoscience data that can practically be applied to important problems. File archives in centralized data centers are the principal means by which Earth Science data are accessed. This approach, however, requires laborious search, retrieval, and eventual customization/adaptation for the data to be used. Such fractionation makes it even more difficult to share outcomes, i.e. research artifacts and data products, hampering reusability and repeatability, since end users generally have their own research agenda and preferences as well as scarce resources. Thus, while finding and downloading data files from central data centers are already costly for end users working in their own field, using data products from other disciplines rapidly becomes prohibitive. This curtails scientific productivity, limits avenues of study, and endangers quality and reproducibility. The Spatio-Temporal Adaptive Resolution Encoding (STARE) is a unifying scheme that facilitates the indexing, access, and fusion of diverse Earth Science data. STARE implements an innovative encoding of geo-spatiotemporal information, originally developed for aligning datasets with diverse spatiotemporal characteristics in an array database. The spatial component of STARE recursively quadfurcates a root polyhedron, producing a hierarchical scheme for addressing geographic locations and regions. The temporal component of STARE uses conventional date-time units as an indexing hierarchy. The additional encoding of spatial and temporal resolution information in STARE enables comparisons and conditional selections across diverse datasets. Moreover, spatiotemporal set-operations, e.g. union and intersection, are mapped to efficient integer operations with STARE. Applied to existing data models (point, grid, spacecraft swath) and corresponding granules, STARE indexes provide a streamlined description usable as geo-spatiotemporal metadata. When coupled with large scale, distributed hardware and software, STARE-based data access reduces pre-analysis data preparation costs by offering a convenient means to align different datasets spatiotemporally without specialized effort in parallel computing or distributed data management.

Kuo, Kwo-Sen↗

DOE OSTI2020

Tribal Renewable Energy: Bishop Paiute Tribe Youth Solar Job Training Development (Final Report)

This Project provided workshops and hands on opportunities for young tribal adults to gain education,training,and employment in the solar industry; including 1 youth to meet the eligibility requirements for the NABCEP Solar Installer Exam. 10 tribal youth, ages 16-24, attended workshops focused on learning solar fundamentals and then applied those learned skills to hands on training, installing solar on 2 tribal homes. GRID provided certificates authenticating their volunteer hours and skills learned. This program of youth training really excited the tribal leadership as well as the tribal youth. This opportunity was in alignment with the tribe’s Strategic Energy Plan, and supported tribal self-sufficiency, a path to economic development and for the youth it also represented the environmental stewardship the tribe believes in.

14 SOLAR ENERGY↗

DOE OSTI2025

Selection of Global Climate Model Data for Downscaling With Generative Machine Learning and Use in the Power Planning for Alignment of Climate and Energy Systems Project

The range of results from climate models and scenarios is important to the understanding of uncertainty in power planning analysis. A U.S. Department of Energy-funded analytic project called Power Planning for Alignment of Climate and Energy Systems is developing data and analytic methods to reflect the effects of climate change on key variables for power system planning, as part of the Grid Modernization Lab Consortium. This project will select and prepare global climate model results for use in power system planning models. A related report (Evaluation of Global Climate Models for Use in Energy Analysis) assesses the performance of various global climate models from the Coupled Model Intercomparison Project Phase 6 data archive for their historical skill with respect to energy system performance and for their future projections under multiple climate change scenarios. Building from that report, we describe the selection of a climate scenario (Shared Socioeconomic Pathway [SSP] 2-4.5) and five climate models: TaiESM1, EC-Earth3-CC, GFDL-CM4, EC-Earth3-Veg, and MPI-ESM1-2-HR. We describe the model selection criteria, which were based on the quality of the match between model results under historical conditions and on the representation of the range of future values for several variables. These results will be downscaled via an open-source generative machine learning method called Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1995

Consistency of time dilation in temporal profiles and spectra of gamma-ray bursts

If gamma-ray bursters are at cosmological distances-a possibility suggested by their isotropic distribution and spatial inhomogeneity-then the temporal profiles and spectra of more distant sources will be time dilated compared to those of relatively nearby sources. Analyses of bright and dim Burst and Transient Source Experiment (BATSE) gamma-ray bursts yield a relative time-dilation factor of 2.3 on timescales of pulses and event durations. We redshift the spectra of time intervals near the intensity peaks of the bright sample on a trial grid and compare with spectra of the dim sample. A redshift factor of order two-with wide latitude permitted-brings the spectra of the two brightness groups into alignment. Thus there is coarse agreement with the time-dilation factor found in the temporal domain.

Noriss, J. P.↗

NASA NTRS2023

Comparing Magnetopause Predictions From Two MHD Models During A Geomagnetic Storm and A Quiet Period

Magnetopause location is an important prediction of numerical simulations of the magnetosphere, yet the models can err, either under-predicting or over-predicting the motion of the boundary. This study compares results from two of the most widely used magnetohydrodynamic (MHD) models, the Lyon–Fedder–Mobarry (LFM) model and the Space Weather Modeling Framework (SWMF), to data from the GOES 13 and 15 satellites during the geomagnetic storm on 22 June 2015, and to THEMIS A, D, and E during a quiet period on 31 January 2013. The models not only reproduce the magnetopause crossings of the spacecraft during the storm, but they also predict spurious magnetopause motion after the crossings seen in the GOES data. We investigate the possible causes of the over-predictions during the storm and find the following. First, using different ionospheric conductance models does not significantly alter predictions of the magnetopause location. Second, coupling the Rice Convection Model (RCM) to the MHD codes improves the SWMF magnetopause predictions more than it does for the LFM predictions. Third, the SWMF produces a stronger ring current than LFM, both with and without the RCM and regardless of the LFM spatial resolution. During the non-storm event, LFM predicts the THEMIS magnetopause crossings due to the southward interplanetary magnetic field better than the SWMF. Additionally, increasing the LFM spatial grid resolution improves the THEMIS predictions, while increasing the SWMF grid resolutions does not.

magnetohydrodynamics↗

DOE OSTI2020

Origin of spin–orbit misalignments: the microblazar V4641 Sgr

ABSTRACT Of the known microquasars, V4641 Sgr boasts the most severe lower limit (>52°) on the misalignment angle between the relativistic jet axis and the binary orbital angular momentum. Assuming the jet and black hole spin axes coincide, we attempt to explain the origin of this extreme spin–orbit misalignment with a natal kick model, whereby an aligned binary system becomes misaligned by a supernova kick imparted to the newborn black hole. The model inputs are the kick velocity distribution, which we measure customized to V4641 Sgr, and the immediate pre/post-supernova binary system parameters. Using a grid of binary stellar evolution models, we determine post-supernova configurations that evolve to become consistent with V4641 Sgr today and obtain the corresponding pre-supernova configurations by using standard prescriptions for common envelope evolution. Using each of these potential progenitor system parameter sets as inputs, we find that a natal kick struggles to explain the origin of the V4641 Sgr spin–orbit misalignment. Consequently, we conclude that evolutionary pathways involving a standard common envelope phase followed by a supernova kick are highly unlikely for V4641 Sgr. An alternative interpretation is that the jet axis does not reliably trace the black hole spin axis. Our results raise concerns about compact object merger statistics gleaned from binary population synthesis models, which rely on unverified prescriptions for common envelope evolution and natal kicks. We also challenge the spin–orbit alignment assumption routinely invoked to measure black hole spin magnitudes.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Cost Analysis of Heavy-Duty Vehicle Proton Exchange Membrane Fuel Cell Stationary Power Plants

Heavy-duty PEM fuel cells could be a low-cost, low emission alternative to combustion turbines for re-electrifying hydrogen if used as part of a long duration grid energy storage systems. Many studies expect heavy duty PEM fuel cell production costs to reduce as manufacturing volumes ramp up and their expected durability of 25,000-30,000 hours aligns well with a 30-year life for hydrogen seasonal energy storage plants that would likely operate less than 10% of the year. The labor, material, and equipment costs associated with installing PEM fuel cells and their required balance of plant for stationary applications have not been thoroughly explored, however. This study performs a detailed design and cost analysis of a 100 MW stationary PEM fuel cell power plant, capturing costs such as cooling, power electronics, pipes, valves, fittings, cabling, conduit, concrete foundations, buildings, and land. It employs methods consistent with NLR's solar PV benchmarking cost analysis and annual technology baseline to derive the total installed costs of stationary PEM fuel cell plants that utilize heavy duty PEM fuel cells.

08 HYDROGEN↗

DOE OSTI2021

Atlantic Offshore Wind Transmission Literature Review and Gaps Analysis

In support of the national goal to deploy 30 gigawatts of offshore wind by 2030, DOE’s Wind Energy Technologies Office has published an Atlantic Offshore Wind Transmission Literature Review and Gaps Analysis. Transmission constraints— including both land-based transmission interconnections and offshore transmission—are expected to be one of the central challenges to meeting offshore wind deployment goals. Given current trends in offshore wind development, available technology, and state-level procurement goals, most of the first 30 GW of offshore wind are anticipated to be developed along the East Coast. This report summarizes current publicly available transmission analyses along the Atlantic Coast, as well as gaps in existing analyses. Improving understanding of offshore wind transmission options, establishing coordination and aligning processes among states and regions, and quantifying the long-term impacts of offshore wind transmission options will catalyze offshore wind energy’s growth and ensure adequate transmission and a reliable grid.

17 WIND ENERGY↗

DOE OSTI2022

End-Use Load Profiles for the U.S. Building Stock: Technical Advisory Group Meeting #11

A technical advisory group guided the End-Use Load Profiles dataset development to ensure that the direction and outcomes of the work were aligned with market needs. The technical advisory group included roughly 100 representatives from organizations that were likely to use the resulting load profiles in their work, including utility companies, utility program implementers, grid operators, consultancies, research centers, state regulatory agencies, and regional energy efficiency organizations. This is the presentation from TAG Meeting #11.

buildings↗

DOE OSTI2019

Impedance Measurement of Wind Turbines using a Multimegawatt Grid Simulator: Preprint

This paper presents the impedance measurements of a 4 MW wind turbine conducted using a multimegawatt grid simulator at the National Renewable Energy Laboratory in Colorado, United States. This paper describes different systems, including a 7 MVA grid simulator, a 5 MW dynamometer, a medium-voltage measurement system, and a real-time control system used for the automated impedance measurement of a utility-scale wind turbine. Different aspects of impedance measurement are discussed, including the selection of the magnitude of injected perturbation, measurement of frequency cross-coupling between the sequence impedance responses, and the alignment of the reference frame for sequence impedance measurement. The paper also demonstrates high-fidelity validation of an EMT simulation model of the wind turbine using impedance measurements.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

A Generic Primary-Control Model for Grid-Forming Inverters: Towards Interoperable Operation & Control

This paper outlines an architectural vision centered around the notion of interoperability to integrate grid-forming inverter-based resources in large-scale grids. With the underlying principle of interoperability guiding developments, we focus on modeling the characteristics of droop, virtual synchronous machine, and virtual oscillator controls. Emphasis is placed on these three controllers since they are leading grid-forming control candidates and are likely to be commonplace as primary-control schemes in future systems. We show that these controllers can each be considered as instantiations of a more generic model and that all these controllers exhibit similar droop-like relations between pertinent terminal variables in steady state. This commonality between controllers gives interoperability among them such that automatic synchronization, power sharing, and voltage regulation can be achieved. Simulation results validate the models and demonstrate how the steady-state droop characteristics of these control methods can be aligned with the aid of the developed modeling paradigm.

control↗

DOE OSTI2025

Hosting downscaled decision-relevant community data products in ESGF2-US

As regionally-relevant high-resolution Earth system data is increasingly relied upon across scientific, policy, and practitioner communities, there is an urgent need for coordinated and federated infrastructure to store, manage, standardize, and distribute decision-relevant community data products. Substantial effort is required to ensure that these products, which are often critical for regional impact assessments and decision-making, are findable, accessible, interoperable, and reusable. The Earth System Grid Federation US project (ESGF2-US) is addressing this challenge by expanding its open-source, distributed platform to support the hosting and dissemination of downscaled Earth system datasets. This expansion includes aligning new downscaled datasets with developing community standards for metadata and file structure, consistent with existing ESGF archives. This includes ensuring CF-compliance, applying CMORization where appropriate, and developing tools to streamline user access. In this paper, we highlight the technical and coordination work required to bring downscaled data into ESGF2-US and aim to inform the broader Earth system data user community about the growing availability and utility of these curated resources.

ESGF↗

NASA NTRSDate not supplied

Model-Specific Metadata for Enhancing Space Science Models

The Space Weather and Heliophysics modeling community, supported by the Community Coordinated Modeling Center (CCMC, https://ccmc.gsfc.nasa.gov), provides a collaborative platform for space weather models and data. Flexible metadata is vital for advancing scientific research and fostering collaboration. Our work in expressing complex simulations of the Space Weather Modeling Framework (SWMF), particularly Global Magnetosphere (GM) grid components, in terms of simple metadata records shows great promise in creating searchable and reusable units of knowledge. Such records can be readily utilized to support the process of scientific discovery, closely aligning with the goals outlined in the Open Science initiative. Our primary goal is to show the scalability and benefits of metadata-focused methodologies. This presentation highlights the potential for applying metadata methodologies to other complex models, improving usability, supplying efficient documentation and fostering interdisciplinary research.

space weather↗

DOE OSTI2026

High-Resolution South American Wind Resource Data Downscaled with Generative Machine Learning Conditioned on Near-Surface Observations

High-resolution historical wind data was developed for the entirety of South America using the innovative Super-Resolution for Renewable Resource Data (sup3r) machine learning framework. The publicly available Sup3rWind South America dataset represents a significant advancement in wind resource data generation, leveraging generative machine learning conditioned on near-surface observations from the Meteorological Assimilation Data Ingest System (MADIS) to efficiently and accurately downscale coarse reanalysis data from the European Centre for Medium-Range Weather Forecasts (ERA5). This approach produces fine-scale, spatially and temporally coherent wind and meteorological fields hundreds of times more computationally efficient than traditional numerical weather modeling methods, enabling access to high-fidelity wind information across both continental and offshore regions. Sup3rWind South America builds on the earlier Sup3rWind Ukraine dataset through improvements in model architecture and outputs conditioned on near-surface observation inputs. As with the Ukraine data release, this dataset includes wind speed, wind direction, temperature, relative humidity, and pressure at a horizontal resolution of ~2 km, representing a 15x spatial enhancement relative to the 31 km ERA5 grid. Wind speed and direction are provided at 5-minute resolution, a 12x temporal refinement compared to the hourly ERA5 data, while temperature, relative humidity, and pressure remain at hourly resolution. The data covers all years from 2005 to 2024. Before downscaling, ERA5 inputs were bias-corrected using long-term monthly means and a limited number of quality-controlled observations to align large-scale statistics with regional conditions. The resulting dataset is the first publicly available high-resolution timeseries wind record that provides full spatial coverage of South America. Model validation demonstrates strong agreement with observations across several statistical metrics, consistent with other state-of-the-art high-resolution wind resource datasets. The potential applications of Sup3rWind South America span renewable energy resource assessment, energy system modeling, and grid resilience analysis. The 20-year record and high spatial and temporal resolution support accurate estimation of long-term energy yield and the economic feasibility of potential wind development sites. Continuous coverage across both continental and offshore regions enables comprehensive site prospecting within exclusive economic zones. The 2 km, 5-minute resolution data provide the spatial and temporal variability required for power system simulation, operational planning, and regional risk assessments.

17 WIND ENERGY↗

DOE OSTI2024

A Framework for Identifying Building Energy Models of Localized Utility Service Areas Using Smart Meter Data

Bottom-up load modeling of buildings offers a versatile approach to simulating baseline demand and scenarios of future technology evolution and adoption at the individual building level. This capability is essential to understanding how future load shapes may change with the adoption of electric equipment and vehicles, particularly as it relates to grid planning and infrastructure investments. Traditionally, grid planning techniques have used historical load data to predict future load and infrastructure needs. However, with the anticipated rise in adoption of electrification technologies such as heat pumps and electric vehicles, historical data become less reliable predictors of the future. By employing ResStock, a high-fidelity building stock modeling tool, we can fine-tune electrification scenarios and aggregate models to represent varying geographic resolutions of the grid system, while considering the underlying features of homes. This may enable a more accurate and responsive approach to anticipate and plan for the evolving landscape of energy demands. We present a new framework that leverages building stock energy modeling to identify building models that align with the load shapes and housing attributes of buildings with AMI data. This approach applies two model layers: (1) a classification step that identifies the presence of air conditioning, electric heating, and electric water heating, and (2) an optimization routine that identifies building energy models aligning with load profile data from advanced metering infrastructure meters. This report demonstrates one approach to deploying this framework, and presents results for three test cases that use both modeled and AMI data to assess performance. For a test case using AMI data in Fort Collins, Colorado, we observed a median monthly electricity load CV-RMSE of 16.6%, and a top ten daily heating and cooling median absolute percent error of 7.7% and 8.3%, respectively. For each AMI meter, we identify a set of potential energy models so that downstream use-cases can account for uncertainty driven by variability of baseline technologies and occupant behavior, which impact the response to electrification and energy efficiency scenarios. Our results indicate that ResStock has potential as a scalable solution for modeling residential energy demand at local grid resolutions. Its performance depends on location-specific factors, underlying building characteristics, and the level of aggregation, offering a path towards more precise and adaptive distribution grid planning for the evolving energy landscape.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Utah FORGE: 2023 Large Upscaled Discrete Fracture Network Models

This dataset includes the data and a report on the large upscaled discrete fracture network modeling done for the Utah FORGE project in 2023. The FORGE modeling team is making five discrete fracture network (DFN) realizations of a large reservoir model available to researchers. These models have been upscaled to a continuum mesh or grid at resolutions of 10 meters and 20 meters providing reservoir properties for fracture porosity, permeability, and compressibility. The models are available in both the reference global coordinate frame and a local coordinate frame aligned with principal stress directions.

15 GEOTHERMAL ENERGY↗