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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Characterization Results for the September 2023 Tank Farm 3H Evaporator Overhead Sample

On an annual basis, Savannah River Mission Completion (SRMC) provides 2H and 3H evaporator overhead samples to Savannah River National Lab (SRNL) to be analyzed per Section 5.2 of the Effluent Treatment Project (ETP) Waste Compliance Plan (WCP) and the Waste Acceptance Criteria (WAC). This report presents the average characterization results for the September 2023 3H evaporator overhead sample. The sample was clear and colorless with no visible solids. The results provide measurements for cesium-137 ( 137 Cs), strontium-90 ( 90 Sr), and iodine-129 ( 129 I) with the radionuclide concentration limits specified by the WAC. These analyses were performed in duplicate, and all three measured radionuclide concentrations were within ETP WAC limits. A summary of the analytical results for this 3H evaporator overhead sample includes the following: The measured cesium-137 activity in the 3H evaporator overhead sample averaged 5.70E+01 dpm/mL, which is below the ETP WAC limit of 1.30E+03 dpm/mL. As seen through historical results, Cs-137 continues to present a decreasing activity since 2020. The strontium-90 activity in the 3H evaporator overhead sample averaged <2.16E00 dpm/mL, which is below the ETP WAC limit of 1.76E+02 dpm/mL. The iodine-129 activity in the 3H evaporator overhead sample averaged <9.08E-02 dpm/mL, which is below the ETP WAC limit of 1.00E+00 dpm/mL

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Characterization Results for the October 2024 Tank Farm 3H Evaporator Overhead Sample

On an annual basis, Savannah River Mission Completion (SRMC) provides 2H and 3H evaporator overhead samples to Savannah River National Lab (SRNL) to be analyzed per Section 5.2 of the Effluent Treatment Project (ETP) Waste Compliance Plan (WCP) and the Waste Acceptance Criteria (WAC). This report presents characterization results for the October 2024 3H evaporator overhead sample. The sample was clear and colorless with no visible solids. The results provide measurements for cesium-137 (137Cs), strontium-90 (90Sr), and iodine-129 (129I) with the radionuclide concentration limits specified by the WAC. These analyses were performed in duplicate, and a summary of the analytical results for this 3H evaporator overhead sample includes the following: The measured cesium-137 activity in the 3H evaporator overhead sample averaged 6.72E+01 dpm/mL, (3.90E+00 %RSD), which is below the ETP WAC limit of 1.30E+03 dpm/mL. The strontium-90 activity in the 3H evaporator overhead sample averaged <2.72E+00 dpm/mL, which is below the ETP WAC limit of 1.76E+02 dpm/mL. The iodine-129 activity in the 3H evaporator overhead sample averaged <1.63E-01 dpm/mL, which is below the ETP WAC limit of 1.00E+00 dpm/mL.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Zero-Power Wireless Infrared Digitizing Sensors for Large Scale Energy-Smart Farm

This project, funded by ARPA-E and led by Northeastern University, developed zeropower infrared digitizing sensors to optimize irrigation and enhance crop yields. Traditional water stress detection methods are costly and require frequent maintenance, limiting their effectiveness. Our research identified shortwave infrared (SWIR) transmittance as the most reliable indicator of plant water stress and developed plasmonically enhanced micromechanical photoswitches (PMPs) that operate with minimal power. The sensors offer low-cost, large-scale deployment, auto-calibration across different crops, and a 10-year battery life, significantly reducing maintenance costs. The system achieved 4x greater accuracy than conventional soil moisture sensors while ensuring economic feasibility. By enabling precision irrigation, this technology conserves water, enhances crop productivity, and lowers operational costs, making it a scalable solution for sustainable agriculture and global food security.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Activity-based Informed Curtailment: Using Acoustics to Design and Validate Smart Curtailment to Reduce Risk to Bats at Wind Farms

Rapid expansion of renewable energy infrastructure is a key part of any global strategy to reduce the pace and severity of anthropogenic climate change, although the potential impacts of renewable energy infrastructure on wildlife are also becoming increasingly apparent. Bats appear vulnerable to population-level impacts from the cumulative effect of turbine-related fatalities at commercial wind energy facilities in North America, particularly as the industry continues to expand to meet renewable energy generation targets. Turbine curtailment is the most widely used and consistently effective method to reduce bat fatality rates and involves pitching turbine blades parallel to prevailing winds to restrict turbine rotation when turbines would otherwise be operating and capable of producing power. Recognizing the need to expand the wind industry while managing risk to bats highlights the need to understand and manage turbine-related impacts to bats more aggressively and strategically than the current use of blanket curtailment allows.

17 WIND ENERGY↗
DOE OSTI2025

Design, Optimization, and Control of Floating Offshore Wind Farms for Optimal Energy Production (Final report)

The uncertainty and irregularity of ocean waves and the ocean environment is a major factor in the development of commercial scale floating wind turbines as the operation of floating structures in such an environment can lead to irregular and unpredictable loading, fatigue, and ultimately a reduction in the operational life of the turbine system which affects energy production over the lifetime of the turbine. Control solutions that can limit float motions and mitigate stressful events on the structure become essential for extending lifetime and limiting the operational uncertainty of a floating wind turbine. Digital twins are computational replicas of physical systems that operate in parallel with the operation of the physical system. Given advanced knowledge of a systems input, digital twins have the ability to predict the behavior of a system in advance, which can be valuable in the control of that system. In this project, we developed and assessed potential digital twin models developed in house and openly available (OpenFast) for use in the real time control of the six degree of freedom response motions of a floating wind turbine in ocean waves. Coupling these models with near-field real time irregular sea surface (wve) measurement/sensings and prediction models, we used the digital twin to predict how the floating turbine will respond to the incoming waves. Applying this information to a motion control system of the float, one can limit and control float motions to prevent undesirable loading events/large angular motions, thus increasing system life and ultimately contributing to optimizing energy production. Due to the computational intensity of operating a digital twin in real time, we investigated the use of artificial intelligence techniques to speed-up the processes of the digital twin, as well as the wave reconstruction/prediction models. Model tank testing at the University of Rhode Island and University of Maine both validated and demonstrated the developed techniques on simple float geometries and a scale model of the NREL 15 MW reference turbine.

17 WIND ENERGY↗
DOE OSTI2025

Characterization Results for the August 2025 Tank Farm 2H Evaporator Overhead Sample

On an annual basis, Savannah River Mission Completion (SRMC) provides 2H and 3H evaporator overhead samples to Savannah River National Lab (SRNL) to be analyzed per Section 5.2 of the Effluent Treatment Project (ETP) Waste Compliance Plan (WCP) and the Waste Acceptance Criteria (WAC). This report presents the average characterization results for the August 2025 2H evaporator overhead sample. The sample was clear and colorless with no visible solids. The results provide measurements for cesium-137 ( 137 Cs), strontium-90 ( 90 Sr), and iodine-129 ( 129 I) with the radionuclide concentration limits specified by the WAC. These analyses were performed in duplicate, and all three measured radionuclide concentrations were within ETP WAC limits. A summary of the analytical results for this 2H evaporator overhead sample includes the following: The measured cesium-137 activity in the 2H evaporator overhead sample averaged 3.02E+02 dpm/mL, which is below the ETP WAC limit of 1.30E+03 dpm/mL. The strontium-90 activity in the 2H evaporator overhead sample averaged 3.33E+00 dpm/mL, which is below the ETP WAC limit of 1.76E+02 dpm/mL. The iodine-129 activity in the 2H evaporator overhead sample averaged 1.20E-01 dpm/mL, which is below the ETP WAC limit of 1.00E+00 dpm/mL. Although the measurements for Cs-137 and Sr-90 are lower compared to previous years, the results remain within a similar range to past measurements and are well below the WAC limits. Iodine-129 indicates detectable results compared to previous years, which can be attributed to recent salt batch processing trending close to the WAC limit for saltstone production. However, these results are still below the ETP WAC limit.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Scaling Spectroradiometric Monitoring to an Algal Factory Farm

This report briefly summarizes the spectroradiometric approach adapted and deployed as part of Task 4.2 within the BETO-funded D evelopment of I ntegrated S creening, C ultivar O ptimization, and V erification R esearch (DISCOVR) project, specifically task 4, “Increase crop protection and culture stability.” The goals of this subtask were to monitor ponds cultivating a variety of DISCOVR strains at the Arizona Center for Algae Technology and Innovation (AzCATI) with spectroradiometric technology to: • Predict biomass concentrations with high temporal frequency. • Optimize automated analysis methods that enabled feedback for pond automation strategies • Identify pond crash indicators from primary (pest/predator) and indirect (change in algal host) spectroscopic signals with potential for early treatment/intervention • Provide recommendations for technology deployment at scale. This report fulfills the deliverable requirement for the final bullet “provide recommendations for technology deployment at scale”.

09 BIOMASS FUELS↗
DOE OSTI2026

Stereo-vision thermal imaging system for tracking flying animals in wind farm areas (CRADA #763) Abstract

CRADA 763: abstract ThermalTracker-3D (TT3D) is a stereo vision thermal imaging system that provides 3D flight information on detected birds, bats, and other flying targets. The system was initially developed for use in the siting and monitoring of offshore wind projects to establish pre-construction and operation collision risk data but can be applied to terrestrial wind energy projects as well as national security monitoring. This technology will reduce monitoring cost, decrease processing time, and provide more accurate data for wind energy developers/operators and regulatory agencies. While the current technology is at a high level of readiness, Technology Readiness Level (TRL) 7, there remain several barriers to commercialization, particularly around ease-of-use, that result in a low Adoption Readiness Level (ARL). The proposed work will advance commercialization readiness by streamlining calibration methods for built systems. This work will:1. 1. develop a software package for factory and dynamic calibration processes 2. test that package with existing prototype TT3D systems, and 3. conduct outreach with industry end-users.

ThermalTracker↗
DOE OSTI2021

Multi-Fidelity Active Subspaces for Wind Farm Uncertainty Quantification

Wind plants operate in stochastic environments characterized by complex turbulent flow dynamics and high-dimensional random variables. A key step in uncertainty quantification studies is sensitivity analysis and dimension reduction that can facilitate the development of surrogate models to be used for forward and inverse propagation or optimization under uncertainty. Prior work has shown active subspaces are an effective tool for identifying important directions in the space of stochastic inputs; however, they have only been applied to single-fidelity wind plant models. In this study, we investigate the efficacy of a multi-fidelity active subspace method for analyzing the uncertainty in wind plant power output. The multi-fidelity active subspace estimator offers the promise of increased accuracy in identifying active subspaces as compared to a single-fidelity estimator for the same computational cost, or a reduction in cost for the same accuracy. This makes the study of uncertainty in larger wind plants and with higher fidelity physics tractable. The multi-fidelity active subspace method is applied to gridded and existing wind plant layouts with single and multiple inflow conditions and its performance for surrogate modeling and uncertainty propagation is compared against a single-fidelity active subspace method. This multi-fidelity approach yields substantial computational speedups of 2x - 3.4x across the test cases along with acceptable accuracy in surrogate modeling and computing statistical moments.

active subspace↗
DOE OSTI2023

Developing a Vorticity-Velocity-Based Off-Body Solver to Perform Multifidelity Simulations of Wind Farms

Wind power has become a key player in satisfying the global energy needs. With increased market penetration, unanticipated unsteady loading induced failures, installation related reductions in power generation, and significant maintenance costs have underscored the need to predict the unsteady fluid-structure interactions related to turbine layout and off-design wind conditions. Contemporary turbine design tools are incapable of accounting for such loadings. As a result, researchers have started utilizing high-Performance-Computing (HPC) based Computational Fluid Dynamics (CFD) solvers, such as the U.S. Department of Energy sponsored ExaWind software package, to investigate these phenomena. Unfortunately, such HPC tools are computationally expensive for routine industrial use, often because of the sheer number of cells required to resolve the wake flowfield. This paper describes a preliminary effort to address this issue by developing a vorticity-velocity based CFD off-body solver, VorTran-M2-AMReX, that integrates directly with DOE's ExaWind wind turbine analysis system to perform accurate and reliable simulations of wind turbine/farm at a lower computational cost than ExaWind alone. This article summarizes work undertaken to date concerning the assembly of the proposed analysis tool, and provides preliminary validation and verification of the VorTran-M2-AMReX off-body solver.

adaptive mesh refinement↗
DOE OSTI2021

AgroIBIS VSF Farmed Pothole Ponding Model Runs

This data set includes modeled (AgroIBIS-VSF) output of crop yield for miscanthus and a corn/soybean rotation in .nc format. Input includes the precipitation scenarios (.csv) used to generate the runs, and supplemental observed yield monitor data (.csv) from the research area of interest.

Agricultural Hydrology (Drainage, Flooding, Irriga↗
DOE OSTI2022

From Farm to Flight: CoverCress as a Low Carbon Intensity Cash Cover Crop for Sustainable Aviation Fuel Production. A Review of Progress Towards Commercialization

Thlaspi arvense L. (Field Pennycress; pennycress) is being converted into a winter-annual oilseed crop that confers cover crop benefits when grown throughout the 12 million-hectares U.S. Midwest. To ensure a fit with downstream market demand, conversion involves not only improvements in yield and maturity through traditional breeding, but also improvements in the composition of the oil and protein through gene editing tools. The conversion process is similar to the path taken to convert rapeseed into Canola. In the case of field pennycress, the converted product that is suitable as a rotational crop is called CoverCress™ as marketed by CoverCress Inc. or golden pennycress if marketed by others. Off-season integration of a CoverCress crop into existing corn and soybean hectares would extend the growing season on established croplands and avoid displacement of food crops or ecosystems while yielding up to 1 billion liters of seed oil annually by 2030, with the potential to grow to 8 billion liters from production in the U.S. Midwest alone. The aviation sector is committed to carbon-neutral growth and reducing emissions of its global market, which in 2019 approached 122 billion liters of consumption in the U.S. and 454 billion liters globally. The oil derived from a CoverCress crop is ideally suited as a new bioenergy feedstock for the production of drop-in Sustainable Aviation Fuel (SAF), renewable diesel, biodiesel and other value-added coproducts. Through a combination of breeding and genomics-enabled mutagenesis approaches, considerable progress has been made in genetically improving yield and other agronomic traits. With USDA-NIFA funding and continued public and private investments, improvements to CoverCress germplasm and agronomic practices suggest that field-scale production can surpass 1,680 kg ha -1 (1,500 lb ac -1 ) in the near term. At current commodity prices, economic modeling predicts this level of production can be profitable across the entire supply chain. Two-thirds of the grain value is in oil converted to fuels and chemicals, and the other one-third is in the meal used as an animal feed, industrial applications, and potential plant-based protein products. In addition to strengthening rural communities by providing income to producers and agribusinesses, cultivating a CoverCress crop potentially offers a myriad of ecosystem services. The most notable service is water quality protection through reduced nutrient leaching and reduced soil erosion. Biodiversity enhancement by supporting pollinators’ health is also a benefit. While the efforts described herein are focused on the U.S., cultivation of a CoverCress crop will likely have a broader application to regions around the world with similar agronomic and environmental conditions.

09 BIOMASS FUELS↗
DOE OSTI2026

Offshore Wind Farm Turbine and Energy Storage Optimization

Abstract This paper evaluates the technical and economic feasibility of repurposing decommissioned offshore oil and gas platforms as electrical substations for offshore wind projects in the U.S. Gulf of America, a region characterized by relatively low and highly variable wind speeds, extensive legacy offshore infrastructure, and exposure to merchant electricity markets. A unified techno-economic framework is developed using the Repurposing Offshore Infrastructure for Continued Energy (ROICE) Economic Model (REM) to integrate Gulfspecific wind resource assessment, commercial wind turbine performance, offshore infrastructure cost modeling, and wholesale electricity market exposure. Gulf wind speed data are vertically extrapolated to turbine hub height and combined with manufacturer power curves to compute annual energy production and capacity factors across a broad portfolio of commercial turbines, enabling identification of turbine designs best suited for low-wind offshore environments. Hourly electricity price data from the Midcontinent Independent System Operator (MISO) day-ahead market are incorporated to characterize revenue potential, price volatility, and the temporal alignment between wind generation and market conditions. In addition, a conceptual framework for offshore battery energy storage system (BESS) integration is developed to support future investigation of market-responsive energy shifting at repurposed platforms. Results from the turbine evaluation demonstrate that machines with lower cut-in wind speeds and earlier ‘rated-power’ characteristics significantly outperform larger, industry-standard offshore turbines for the same net power under Gulf wind conditions, underscoring the need for region-specific technology selection. Market analysis further reveals substantial price variability and limited intrinsic alignment between wind production and high-price periods, motivating consideration of operational flexibility mechanisms. While storage optimization is not implemented in this study, the REM framework establishes a transparent and replicable foundation for co-evaluating turbine selection, infrastructure constraints, and market exposure, providing a practical pathway for assessing the potential role of repurposed offshore platforms in enabling economically viable offshore wind development in the Gulf of America.

02 PETROLEUM↗
DOE OSTI2026

Idealized simulations of wind farm interactions with intermittent turbulence in stable boundary layer conditions

Stable atmospheric boundary layer conditions typically correspond to weak turbulence levels, but intermittent periods of elevated turbulence can occur during otherwise quiescent conditions. The interaction between intermittent turbulence and wind turbines is not well understood because of sparse observations, as well as the difficulty in realistically resolving small-scale turbulence during strongly stable conditions with numerical simulations. In this study, an explicit filtering and reconstruction approach for large-eddy simulation (LES) is used to simulate weakly and strongly stable conditions, with surface cooling rates of −0.2 and −2.0 K h −1 , respectively. This approach can sustain resolved background turbulence at relatively coarse grid spacing and stronger stratification compared to conventional closures, permitting more realistic intermittent stable boundary layer (SBL) turbulence. The idealized LES capability of the Weather Research and Forecasting model is employed with turbine rotors parameterized using generalized actuator disks to examine (1) how the presence of turbine wakes affects SBL evolution and (2) the effect of intermittent turbulence on power production and wake recovery. Wakes increase mixing and deepen the SBL, with a stronger effect under strongly stable conditions, primarily because the SBL is shallower and closer to the top of the wind turbine rotor layer. Intermittent turbulence does not have a significant impact on mean power generation and wake recovery because the relevant intermittent turbulent structures in this study only affect the bottom half of the rotor disk. Power production is, however, more variable during periods of elevated turbulence, demonstrating the impact of SBL intermittency. This study uses an idealized configuration, focusing on LES model performance and physical understanding, with the goal of informing future simulations of the conditions observed during the American Wake Experiment.

Energy - Wind↗