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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

The Grid Value of Ocean Current Energy in Florida

Ocean current energy technology has been proposed as a potential contributor to Florida's energy portfolio. There has been limited investigation of how this energy would be valued when integrated into the Florida electrical grid. This study assesses three future grid scenarios to evaluate the impact of adding zero-cost ocean current energy to each. The Resource Planning Model, a tool developed by the National Renewable Energy Laboratory, is used to identify the least-cost generation mix through 2050, with and without ocean current energy. The first scenario is a base case and assumes existing policies in which the addition of ocean current energy does not retire fossil-based technologies but variable generation technologies. In the second scenario, solar and storage technologies are lower cost, and the addition of ocean current generation enables those technologies along with wind to retire existing natural gas units earlier. In the third scenario, which requires a 95% reduction in carbon emissions from 2020 levels by 2050, ocean current energy can play a role in decarbonization along with other variable generation technologies. This analysis is intended to inform stakeholders on the opportunity, potential challenges, and overall value to the grid of ocean current technology from a reliability and availability focused perspective.

capacity expansion model↗
DOE OSTI2024

Image-Based Failure Assessment of Li-Ion Batteries

In energy storage materials, strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking during charge/discharge cycling, resulting in reduced performance and service life. In this work, a digital twin is created to investigate the performance of a heterogeneous Li-ion battery cathode and simulate degradation accumulation. Pixel-based model construction is used to represent the complex material geometries from microstructural images supplied by the National Renewable Energy Laboratory (NREL). Because of the expected large deformation and crack opening, the reproducing kernel particle method (RKPM), a meshfree method with discretization at the image pixels, is used to approximate the field variables: electrostatic potential, concentration, and displacement. An interface modified reproducing kernel (IM-RK) is constructed by scaling a smooth kernel function with an interface-distance function to achieve strategic discontinuity types (i.e. weak discontinuities for strain discontinuities and strong discontinuities for cracks) and alleviate Gibbs oscillations near these transition zones. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. IM-RK is additionally used to inform how crack evolution in turn affects the coupled electro-chemo-mechanical behavior of the Li-ion battery cathode.

image-based modeling↗
DOE OSTI2024

a priori uncertainty quantification of reacting turbulence closure models using Bayesian neural networks

While many physics-based closure model forms have been posited for the sub-filter scale (SFS) in large eddy simulation (LES), vast amounts of data available from direct numerical simulations (DNS) create opportunities to leverage data-driven modeling techniques. Albeit flexible, data-driven models still depend on the dataset and the functional form of the model chosen. Increased adoption of such models requires reliable uncertainty estimates both in the data-informed and out-of-distribution regimes. Here, in this work, we employ Bayesian neural networks (BNNs) to capture both epistemic and aleatoric uncertainties in a reacting flow model. In particular, we model the filtered progress variable scalar dissipation rate which plays a key role in the dynamics of turbulent premixed flames. We demonstrate that BNN models can provide unique insights about the structure of uncertainty of the data-driven closure models. We also propose a method for the incorporation of out-of-distribution information in a BNN, which can be used for out-of-distribution query detection. The efficacy of the model is demonstrated by a priori evaluation on a dataset consisting of a variety of flame conditions and fuels.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Interoperable, Inverter - Based Distributed Energy Resources Enable 100% Renewable and Resilient Utility Microgrids

As microgrids transition away from use of conventional generating resources and increasingly rely on renewable resources towards decarbonization goals, it is crucial to evaluate the capability inverter-based resources to provide microgrid stability and resilience. Particularly, microgrids with a high contribution of intermittent solar photo voltaic generation and higher load variability present unique challenges requiring fast voltage and frequency support. At the San Diego Gas & Electric Company(R) (SDG&E(R)) Borrego Springs Microgrid, a battery inverter was upgraded with grid-forming (GFM) capability to serve as island leader, transitioning responsibility away from diesel generators. An interoperable microgrid control scheme was developed, coordinating GFM and grid-following (GFL) inverters. Hardware-in-the-loop (HIL) simulations using relevant power and controller HIL interfaces between real-time simulators and field equipment are being conducted to de-risk field deployment.

battery energy storage↗
DOE OSTI2025

Downscaled Earth System Model Data for Resilient Energy System Planning

The second-generation Sup3rCC dataset provides high-resolution meteorological data generated through the downscaling of multiple earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). This downscaling is performed through application of a generative machine learning approach called Super-Resolution for Renewable Resource Data (sup3r). This dataset builds on the first-generation Sup3rCC data by applying improved bias correction methods and adding downscaled precipitation to the output variables. In this presentation, we explore the output characteristics of the dataset and various validation analyses. We also present and discuss plans for the integration of this data into power system planning models using a decision-making under deep uncertainty (DMDU) methodology.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Integrated thermal and biological conversion of microalgal proteins to lipids

Microalgal composition varies with cultivation strategy, and low-cost approaches often produce high-protein biomass. This presents challenges for biorefineries designed around static, lipid-rich feedstocks. In particular, hydrolysates from high-protein algae are nitrogen-rich and sugar-poor, limiting microbial conversion and reducing product yields. This study develops a sequential thermal conditioning and biological upgrading strategy to integrate high-protein hydrolysate processing within conventional lipid extraction and upgrading designs. Oxidative deconstruction was used to break down proteins into ammonium and short-chain carboxylates. Ammonium was subsequently removed to yield a nitrogen-depleted, carboxylate-rich medium suitable for microbial lipid production. Bioconversion trials with Cutaneotrichosporon oleaginosum showed lipid accumulation only from hydrolysates treated with both oxidative deconstruction and nitrogen removal, reaching 1.2 g/L lipids at 30 % intracellular content. This integrated approach enables protein-to-lipid conversion and improves flexibility to process variable algal feedstocks, advancing fuel-oriented microalgal biorefineries.

09 BIOMASS FUELS↗
DOE OSTI2025

Cost Projections for Utility-Scale Battery Storage: 2025 Update

In this work we describe the development of cost and performance projections for utility-scale lithium-ion battery systems, with a focus on 4-hour duration systems. The projections are developed from an analysis of recent publications that include utility-scale storage costs. The suite of publications demonstrates wide variation in projected cost reductions for battery storage over time. We present the suite of projected cost reductions collected from the literature as well as the low, mid, and high cost projections developed in this work. Storage cost projections are $\$$152/kWh, $\$$247/kWh, and $\$$349/kWh in 2035 and $\$$111/kWh, $\$$184/kWh, and $\$$333/kWh in 2050 for the low, mid, and high cases respectively. Battery variable operations and maintenance costs, lifetimes, and efficiencies are also discussed, with recommended values selected based on the publications surveyed.

25 ENERGY STORAGE↗
DOE OSTI2025

Standardization and best practices in single-cell testing for liquid alkaline water electrolysis

The increasing demand for efficient and sustainable hydrogen production has driven significant advancements in water electrolysis technologies. Among these, liquid alkaline water electrolysis (LAWE) stands out for its cost-effectiveness and scalability. This manuscript establishes best practices and standardized testing procedures for single-cell LAWE, focusing on the use of nickel foam as both anode and cathode substrates, while incorporating catalysts such as nickel-iron layered double hydroxide (NiFe-LDH) as the anode material and nickel-molybdenum on carbon (NiMo/C) as the cathode material. By providing detailed guidelines on material preparation, cell assembly, and performance evaluation, this work offers a comprehensive framework to improve reproducibility and ensure consistency. The results demonstrate that applying these best practices minimizes variability across different laboratories and experimental setups, laying the groundwork for more robust comparisons and accelerating progress in LAWE research.

08 HYDROGEN↗
DOE OSTI2025

Renewable hydrogen horizon: Geospatial techno-economic feasibility and life cycle greenhouse gas analysis in the Middle East and North Africa

Renewable hydrogen is receiving increasing attention for its potential as a flexible energy carrier in sectors such as transportation and industry. Specific cost and carbon intensity (CI) of renewable hydrogen production vary largely based on the location, owing to differences in renewable energy resources, as well as the supply chain dynamics. This study maps the techno-economic and life cycle greenhouse gas emissions of renewable hydrogen production in the Middle East and North Africa region, leveraging abundant solar and wind resources. The work investigates the variability in hydrogen costs and CI, optimally sizing proton-exchange membrane (PEM) electrolyzers to account for partial and cyclic loading, and explores standalone versus grid-connected systems. PEM capacity ratios of 52 %–63 % for photovoltaic (PV) systems and 28 %–82 % for wind systems were identified as optimal, with hydrogen production costs ranging from $\$3.8$-$\$4.8$/kg for PV and $2.0-$7.0/kg for wind. CIs span from 1.9 to 3.7 kg CO 2 ,eq /kg H 2 for PV and 0.4–7.7 kg CO 2,eq /kg H 2 for wind systems. The study highlights significant cost and CI reductions achievable with technological advancements and co-product revenue from oxygen and excess electricity sales.

Carbon Intensity↗
DOE OSTI2024

National Climate Database (NCDB)

The National Climate Database (NCDB) is a high resolution, bias-corrected climate dataset consisting of the three most widely used variables of solar radiation- global horizontal (GHI), direct normal (DNI), and diffuse horizontal irradiance (DHI)- as well as other meteorological data. The goal of the NCDB is to provide unbiased high temporal and spatial resolution climate data needed for renewable energy modeling. The NCDB is modeled using a statistical downscaling approach with Regional Climate Model (RCM)-based climate projections obtained from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX; linked below). Daily climate projections simulated by the Canadian Regional Climate Model 4 (CanRCM4) forced by the second-generation Canadian Earth System Model (CanESM2) for two Representative Concentration Pathways (RCP4.5 or moderate emissions scenario and RCP8.5 or highest baseline emission scenario) are selected as inputs to the statistical downscaling models. The National Solar Radiation Database (NSRDB) is used to build and calibrate statistical models.

Array↗
DOE OSTI2025

Storage-Induced Collapse of Lignin Macromolecular Structure and Its Impacts on the Biorefinery

Lignin plays a vital role in the economics of biorefineries, serving as a source of process energy and a feedstock for sustainable fuels and chemical production. While understanding lignin’s chemical composition is crucial, emerging evidence suggests that a more comprehensive understanding of its macromolecular structure is critical to explaining its complex behavior in the biorefinery. This study investigated the partial collapse of the lignin network in corn stover feedstock after harvest and storage as a result of the microbial digestion of hemicellulose. Fluorescence microscopy was used to detect the collapse of lignin in terms of lignin’s inter-molecular interaction and the re-orientation of lignin’s chromophores, by the changes in lignin’s fluorescence lifetime, anisotropy, and the number of effective emitters. With minimal sample perturbation, our in-situ microscopic results revealed lignin's coil-globule transition phenomena, which was only previously predicted by molecular dynamics modeling extracted lignin in solvent. This collapse of lignin macromolecular structure was confirmed by results from NMR, IR, Raman, and powder X-ray diffraction. We also investigated the impact of this storage-induced collapse on the downstream biorefinery processes. Our study revealed that the two major approaches for lignin valorization in the lignin-first biorefinery model, namely monomer extraction and milled wood lignin extraction, were negatively impacted by the lignin collapse. As changes during storage are a source of feedstock variability, our study highlights the importance of understanding the effect of feedstock handling on biorefinery operations and economics.

09 BIOMASS FUELS↗
DOE OSTI2025

2017 National Household Travel Survey - Arizona Add-On

# 2017 National Household Travel Survey – Arizona Add-On The Arizona add-on survey supplements the 2017 National Household Travel Survey (NHTS) with additional household samples and detailed travel behavior for an assigned travel day. ## Data Collection Agency The Federal Highway Administration conducted the NHTS and corresponding add-on surveys. ## Methodology This survey documents the demographic, attitudinal, and travel behavior for all members of 2,987 households, as collected from April 2016 to April 2017. Daily travel details provide insight into work and school commutes, non-emergency medical trips, shopping trips, and even how travel differs in the summer and on weekends as compared to a typical weekday when school is in session. When statistically weighted to adjust for survey biases, the data demographically represents all Americans and is appropriate for analysis at the national and census region levels. ## Survey Records Survey records include a total of 6,081 participants. ## Transportation Data The NHTS Arizona add-on data package contains a demographic and socioeconomic composition of 6,081 people from 2,987 households in Arizona, as well as detailed information on the travel behavior of each household for a designated 24-hour period. The survey logged more than 258,000 vehicle miles of travel by participants during 19,779 trips. For details on available data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/data-elements-2017.xlsx?sfvrsn=ad09b18c_3). Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

2017 National Household Travel Survey - Arizona Add-On

# 2017 National Household Travel Survey – Arizona Add-On The Arizona add-on survey supplements the 2017 National Household Travel Survey (NHTS) with additional household samples and detailed travel behavior for an assigned travel day. ## Data Collection Agency The Federal Highway Administration conducted the NHTS and corresponding add-on surveys. ## Methodology This survey documents the demographic, attitudinal, and travel behavior for all members of 2,987 households, as collected from April 2016 to April 2017. Daily travel details provide insight into work and school commutes, non-emergency medical trips, shopping trips, and even how travel differs in the summer and on weekends as compared to a typical weekday when school is in session. When statistically weighted to adjust for survey biases, the data demographically represents all Americans and is appropriate for analysis at the national and census region levels. ## Survey Records Survey records include a total of 6,081 participants. ## Transportation Data The NHTS Arizona add-on data package contains a demographic and socioeconomic composition of 6,081 people from 2,987 households in Arizona, as well as detailed information on the travel behavior of each household for a designated 24-hour period. The survey logged more than 258,000 vehicle miles of travel by participants during 19,779 trips. For details on available data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/data-elements-2017.xlsx?sfvrsn=ad09b18c_3). Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

2017 National Household Travel Survey - Arizona Add-On

# 2017 National Household Travel Survey – Arizona Add-On The Arizona add-on survey supplements the 2017 National Household Travel Survey (NHTS) with additional household samples and detailed travel behavior for an assigned travel day. ## Data Collection Agency The Federal Highway Administration conducted the NHTS and corresponding add-on surveys. ## Methodology This survey documents the demographic, attitudinal, and travel behavior for all members of 2,987 households, as collected from April 2016 to April 2017. Daily travel details provide insight into work and school commutes, non-emergency medical trips, shopping trips, and even how travel differs in the summer and on weekends as compared to a typical weekday when school is in session. When statistically weighted to adjust for survey biases, the data demographically represents all Americans and is appropriate for analysis at the national and census region levels. ## Survey Records Survey records include a total of 6,081 participants. ## Transportation Data The NHTS Arizona add-on data package contains a demographic and socioeconomic composition of 6,081 people from 2,987 households in Arizona, as well as detailed information on the travel behavior of each household for a designated 24-hour period. The survey logged more than 258,000 vehicle miles of travel by participants during 19,779 trips. For details on available data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/data-elements-2017.xlsx?sfvrsn=ad09b18c_3). Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

2017 National Household Travel Survey - Arizona Add-On

# 2017 National Household Travel Survey – Arizona Add-On The Arizona add-on survey supplements the 2017 National Household Travel Survey (NHTS) with additional household samples and detailed travel behavior for an assigned travel day. ## Data Collection Agency The Federal Highway Administration conducted the NHTS and corresponding add-on surveys. ## Methodology This survey documents the demographic, attitudinal, and travel behavior for all members of 2,987 households, as collected from April 2016 to April 2017. Daily travel details provide insight into work and school commutes, non-emergency medical trips, shopping trips, and even how travel differs in the summer and on weekends as compared to a typical weekday when school is in session. When statistically weighted to adjust for survey biases, the data demographically represents all Americans and is appropriate for analysis at the national and census region levels. ## Survey Records Survey records include a total of 6,081 participants. ## Transportation Data The NHTS Arizona add-on data package contains a demographic and socioeconomic composition of 6,081 people from 2,987 households in Arizona, as well as detailed information on the travel behavior of each household for a designated 24-hour period. The survey logged more than 258,000 vehicle miles of travel by participants during 19,779 trips. For details on available data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/data-elements-2017.xlsx?sfvrsn=ad09b18c_3). Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

2017 National Household Travel Survey - Arizona Add-On

# 2017 National Household Travel Survey – Arizona Add-On The Arizona add-on survey supplements the 2017 National Household Travel Survey (NHTS) with additional household samples and detailed travel behavior for an assigned travel day. ## Data Collection Agency The Federal Highway Administration conducted the NHTS and corresponding add-on surveys. ## Methodology This survey documents the demographic, attitudinal, and travel behavior for all members of 2,987 households, as collected from April 2016 to April 2017. Daily travel details provide insight into work and school commutes, non-emergency medical trips, shopping trips, and even how travel differs in the summer and on weekends as compared to a typical weekday when school is in session. When statistically weighted to adjust for survey biases, the data demographically represents all Americans and is appropriate for analysis at the national and census region levels. ## Survey Records Survey records include a total of 6,081 participants. ## Transportation Data The NHTS Arizona add-on data package contains a demographic and socioeconomic composition of 6,081 people from 2,987 households in Arizona, as well as detailed information on the travel behavior of each household for a designated 24-hour period. The survey logged more than 258,000 vehicle miles of travel by participants during 19,779 trips. For details on available data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/data-elements-2017.xlsx?sfvrsn=ad09b18c_3). Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

2017 National Household Travel Survey - Arizona Add-On

# 2017 National Household Travel Survey – Arizona Add-On The Arizona add-on survey supplements the 2017 National Household Travel Survey (NHTS) with additional household samples and detailed travel behavior for an assigned travel day. ## Data Collection Agency The Federal Highway Administration conducted the NHTS and corresponding add-on surveys. ## Methodology This survey documents the demographic, attitudinal, and travel behavior for all members of 2,987 households, as collected from April 2016 to April 2017. Daily travel details provide insight into work and school commutes, non-emergency medical trips, shopping trips, and even how travel differs in the summer and on weekends as compared to a typical weekday when school is in session. When statistically weighted to adjust for survey biases, the data demographically represents all Americans and is appropriate for analysis at the national and census region levels. ## Survey Records Survey records include a total of 6,081 participants. ## Transportation Data The NHTS Arizona add-on data package contains a demographic and socioeconomic composition of 6,081 people from 2,987 households in Arizona, as well as detailed information on the travel behavior of each household for a designated 24-hour period. The survey logged more than 258,000 vehicle miles of travel by participants during 19,779 trips. For details on available data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/data-elements-2017.xlsx?sfvrsn=ad09b18c_3). Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

2017 National Household Travel Survey - Arizona Add-On

# 2017 National Household Travel Survey – Arizona Add-On The Arizona add-on survey supplements the 2017 National Household Travel Survey (NHTS) with additional household samples and detailed travel behavior for an assigned travel day. ## Data Collection Agency The Federal Highway Administration conducted the NHTS and corresponding add-on surveys. ## Methodology This survey documents the demographic, attitudinal, and travel behavior for all members of 2,987 households, as collected from April 2016 to April 2017. Daily travel details provide insight into work and school commutes, non-emergency medical trips, shopping trips, and even how travel differs in the summer and on weekends as compared to a typical weekday when school is in session. When statistically weighted to adjust for survey biases, the data demographically represents all Americans and is appropriate for analysis at the national and census region levels. ## Survey Records Survey records include a total of 6,081 participants. ## Transportation Data The NHTS Arizona add-on data package contains a demographic and socioeconomic composition of 6,081 people from 2,987 households in Arizona, as well as detailed information on the travel behavior of each household for a designated 24-hour period. The survey logged more than 258,000 vehicle miles of travel by participants during 19,779 trips. For details on available data and variable definitions, see the [data dictionary](https://www.nrel.gov/media/docs/libraries/tsdc/data-elements-2017.xlsx?sfvrsn=ad09b18c_3). Transportation data are available as zipped files. [Download Winzip](http://www.winzip.com/downwz.htm).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗