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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Electrical Power System Sizing Within the Numerical Propulsion System Simulation

Electrified aircraft propulsion seeks to address ambitious goals in the commercial airline industry, including significant decreases in fuel burn, emissions, noise, and takeoff field length. In order to move these electrified propulsion concepts forward, analysis tools are needed that can model propulsion systems containing both gas turbine and power system components. This work presents the definition of an electric port, a set of electrical power systems tools, and simulation examples for the Numerical Propulsion System Simulation (NPSS) software. NPSS is the industry standard modeling and simulation package for aircraft propulsion systems, and the ability to design, size, integrate, and analyze electric power systems will enable industry efforts towards the development of electrified aircraft propulsion.

aircraft electrification↗
DOE OSTI2024

Bipolar Membrane Capacitive Deionization for the Selective Capture of Lithium Ions from Brines and Conversion to Lithium Hydroxide

Meeting the increasing demand for lithium in vehicle electrification and renewable energy storage requires innovations in lithium-ion (Li + ) separations. Traditional solar evaporation methods for lithium recovery are slow and consume tremendous volumes of water and secondary chemicals (acids and bases). This study introduces a bipolar membrane capacitive deionization (BPM-CDI) unit for direct lithium extraction and LiOH production without the external addition of acids and bases. Utilizing de-lithiated lithium-iron-phosphate (LFP) coated carbon cloth electrodes, the BPM-CDI unit demonstrates selective Li + capture over competing ions. Molecular dynamics simulations and H-cell experiments elucidate pH inversion mechanisms during Li + release, yielding LiOH. The BPM-CDI platform efficiently removes Li + from synthetic brines featuring 8x higher Mg 2+ concentrations (200 ppm Mg 2+ ) and 26x higher Na + concentrations (682 ppm Na + ), achieving a LiOH concentration of 124 ppm (36 ppm Li + ) after 8 cycles of recirculation. Post-mortem analysis confirms electrode integrity and stability. BPM-CDI integrated with selective electrodes is a promising electrochemical separation-reactor platform for lithium recovery while producing LiOH.

Kulkarni, Tanmay↗
DOE OSTI2025

Viability Assessment of Wind and Solar Renewable Energy Generation in Support of Nationwide Vehicle Electrification

In 2022, the U.S. transportation sector was the largest source of greenhouse gas emissions in the country, with the combination of passenger and commercial vehicles contributing 80% of these emissions. As adoption of passenger electric vehicles continues to climb, sights are being set on the electrification of heavy-duty commercial vehicle (HDCV) fleets. The sustainability of these shifts relies in part on the addition of significant renewable energy generation resources to both bolster the grid in the face of increased demand, and to prevent a shift in the source of greenhouse gas (GHG) emissions to the grid, as opposed to a true net reduction. Additionally, it is necessary to quantify the variations in economic viability across the country for these technologies as it pertains to their productive capabilities. Doing so will encourage investment and ensure that the transition to electrified HDCV fleets is commercially viable, as well as sustainable. In an effort to meet these goals, multiple computational frameworks are used to locate suitable land for renewable infrastructure development, and to quantify spatiotemporal variations in the potential energy generation and financial viability of development sites across the Unites States. First, the Oak Ridge Siting Analysis for power Generation Expansion tool (OR-SAGE) is used to assess the suitability of land for potential wind and solar energy development across the contiguous U.S. From there, resource data from the National Solar Radiation Database (NSRDB) and the Wind Integration National Dataset (WIND) are used in concert with the National Renewable Energy Laboratory (NREL) Renewable Energy Potential (ReV) model to calculate the variation in potential generation capacity for each resource. Additionally, the capital and operational expenditures are calculated for an example configuration of each renewable technology. These measures are then used to calculate the levelized cost of energy (LCOE) of potential sites. All of these results are then processed and analyzed to determine where in the U.S. solar and wind energy are most viable. This viability is based on available generation potential, consistency and stability of energy generation over time, and economic viability with respect to LCOE.

Miller, Brandon [ORNL] (ORCID:0009000300169201)↗
DOE OSTI2025

Global Regulations for Sustainable Battery Recycling: Challenges and Opportunities

With the rapid expansion of transportation electrification worldwide, the demand for electric vehicles (EVs) has increased dramatically, creating new and sustainable growth opportunities for the global economy. However, as the most expensive component of EVs, lithium-ion batteries pose significant sustainability challenges due to raw material consumption and supply chain constrains, as well as the complexities of end-of-life battery disposal and recycling. To address these concerns, many countries are actively establishing regulations to promote sustainable pathways for battery reuse and recycling. Despite these efforts, existing battery recycling regulations remain often inefficient and vary significantly across different countries in legal enforcement, producer responsibility, waste classification, recycling targets, design standards, public engagement, and financial incentives, particularly given the complexities of the global supply chain and resource distribution within the battery industry. Understanding these regulatory differences and establishing a unified framework are therefore crucial to ensuring sustainable and efficient battery recycling. This review provides a comprehensive analysis of the necessity of establishing robust regulations for sustainable development of battery recycling industry. The evolution and refinement of battery recycling regulations are deeply reviewed to identifying persistent gaps and challenges in key countries. Furthermore, we discuss the challenges associated with regulatory enforcement and propose strategies for developing a more cohesive legislative framework to ensure the effective utilization of retired batteries.

25 ENERGY STORAGE↗
DOE OSTI2026

Rural EVSE Planning and Analysis

The dataset includes detailed anonymized public charging station usage from several rural stations on the ChargePoint and Shell Recharge Solutions (formerly Greenlots) networks situated in and around Athens, Ohio, a rural Appalachian community. Both Level 2 and DC fast charging stations are represented. Historical data in the set date back to 2019; additional data will be uploaded semiannually until the project's completion in 2023. Each charging session recorded includes information on date and time, location, charging station level, session duration, energy delivered, and fuel savings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2002

Determination of Storm Flashing/Non-Flashing Condition From Convective and Environmental Observations

A simple and fundamental problem in cloud electrification is whether or not a cloud can be determined to be producing lightning or not producing lightning, based solely on knowledge of its microphysical (and perhaps environmental) state. A merged database of TRMM radar, microwave and lightning observations and NCEP reanalysis environmental parameters is used to answer this question, for the tropics. The formal skill of traditional, univariate rule-based approaches (e.g., 35 dBZ occurrence at 6 km altitude) is quantified (via the probability of detection (POD), false alarm rate (FAR) and critical skill index (CSI)). Under indiscriminate application to the tropics, peak rule-based CSI for categorization of flashing storms is approximately 50%, with peak POD approximately 67% and minimum FAR approximately 33%, with peak CSI found for radar reflectivity-based parameters at 7-7.5 km altitude (near -15C). Separation of land and ocean domains yields approximately 5-10% gains in CSI over land. Conventional multivariate categorization techniques (discriminant analysis) are then applied, and less conventional (neural network) categorization techniques are also discussed.

Boccippio, Dennis J.↗
NASA NTRS2003

Preliminary Optical And Electric Field Pulse Statistics From Storm Overflights During The Altus Cumulus Electrification Study

The Altus Cumulus Electrification Study (ACES) was conducted during the month of August, 2002 in an area near Key West, Florida. One of the goals of this uninhabited aerial vehicle (UAV) study was to collect high resolution optical pulse and electric field data from thunderstorms. During the month long campaign, we acquired 5294 lightning generated optical pulses with associated electric field changes. Most of these observations were made while close to the top of the storms. We found filtered mean and median 10-10% optical pulse widths of 875 and 830 microns respectively while the 50-50% mean and median optical pulse widths are 422 and 365 microns respectively. These values are similar to previous results as are the 10-90% mean and median rise times of 327 and 265 microns. The peak electrical to optical pulse delay mean and median were 209 and 145 microns which is longer than one would expect from theoretical results. The results of the pulse analysis will contribute to further validation of the Optical Transient Detector (OTD) and the Lightning Imaging Sensor (LIS) satellites. Pre-launch estimates of the flash detection efficiency were based on a small sample of optical pulse measurements associated with less than 350 lightning discharges collected by NASA U-2 aircraft in the early 1980s. Preliminary analyses of the ACES measurements show that we have greatly increased the number of optical pulses available for validation of the LIS and other orbital lightning optical sensors. Since the Altus was often close to the cloud tops, many of the optical pulses are from low-energy pulses. From these low-energy pulses, we can determine the fraction of optical lightning pulses below the thresholds of LIS, OTD, and any future satellite-based optical sensors such as the geostationary Lightning Mapping Sensor.

Mach, D. A.↗
NASA NTRSDate not supplied

Using Optical Lightning Detection Data from the 2017 GOES-R Post Launch Test Field Campaign Flights as an Evaluation of Convective Processes

The primary mechanisms for thunderstorm electrification and lightning production are widely understood and allow connections between lightning intensity and occurrence to be used to derive storm strength and forecast the probability of related weather phenomena. However, these assumed relationships between lightning and convective properties were discovered primarily using ground-based lightning sensors and measurements, meaning the true depth of insight from space or air based detections is widely unexplored. In 2017, a field campaign was launched to validate the instrumentation aboard the GOES-16 satellite. It involved flying a NASA-ER2 aircraft over multiple storms across the continental US and it included the Fly’s Eye GLM Simulator (FEGS) as a proxy for the Geostationary Lightning Mapper (GLM). Utilizing the data from this field campaign, one of the main goals of this project is to investigate how attributes of convection impact optical lightning detection and the subsequent assumptions that can be made in relation to convective dynamics and precipitation microphysics. Hydrometeor identification, 3D winds retrieval, and additional radar and LiDAR data analysis will be utilized alongside FEGS and interferometer data in order to observe these relationships. This presentation will be to lay out the initial conclusions from our analysis and to explore any new insights or contradictions within our findings.

Kaitlyn Wheeler↗
DOE OSTI2026

Using Machine Learning to Understand Electric and Hybrid Vehicles Ownership in Burdened and Nonburdened Communities

Transitioning to electric and hybrid vehicles (EHVs) for all communities is a pivotal step toward sustainable transportation and environmental conservation. This paper aims to understand the adoption of EHVs, focusing on burdened communities (BCs) in the United States. The EHV ownership-based analysis combines two datasets—behavioral data from the Puget Sound Regional Travel Survey integrated with BCs (Justice40) data covering transportation insecurity, environmental burden, social vulnerability, health vulnerability, and climate and disaster risk burden. After creating this unique database, descriptive analysis and modeling are used to analyze the data and predict EHV ownership in the future. Specifically, we use a new method that combines particle swarm optimization (PSO) with a stacking model named PSO-Stacking, which incorporates heterogeneous base learners of machine learning and deep learning. PSO applies a customized objective function to select the optimal hyperparameters for heterogeneous learners within the stacking model, effectively addressing challenges such as multicollinearity, data imbalance, nonlinearity, and overfitting. The proposed solution covers more accurate results than standard benchmark models for EHV ownership in BCs and non-BCs. In addition, the results of the PSO-Stacking method are explained using the local interpretable model-agnostic explanations technique. Results show a negative correlation between the BCs indicators, that is, higher transportation insecurity associated with lower EHV ownership. Furthermore, BCs have higher future climate risk scores, diesel particulate matter levels, and PM2.5 in the air than non-BCs because of higher conventional vehicle ownership. These communities are at higher risk and can benefit from electrification, EV infrastructure, and EV policies to address environmental challenges.

Aslam, Zeeshan [ORNL]↗
DOE OSTI2025

OR-AGENT framework – Architecting electrified heavy-duty drayage applications

The widespread adoption of zero-emission vehicles in heavy-duty (HD) commercial freight transportation faces considerable technoeconomic challenges. For heavy-duty trucks, ensuring high uptime, cost parity with diesel, and safety standards is especially critical as these vehicles operate over long distances with heavy loads, where any downtime or off-nominal behaviors significantly impacts logistics, productivity, and the total cost of ownership. Unlike traditional diesel refueling, BEV charging infrastructure must be co-optimized with vehicle deployment, operational demands, and grid capacity to ensure cost-effective and reliable freight operations. However, the lack of a standardized ownership and service model has led to a fragmented approach—where commercial vehicle operators may invest in, own, and maintain both vehicle/batteries and charging/energy infrastructure. This disconnect may exclude energy service providers from the equation, forcing fleet operators to explore ‘behind-the-fence’ energy solutions that increase capital investment, operational downtime, overhead costs, and, in some cases, net carbon emissions. To address these issues, this study introduces OR-AGENT (Optimal Regional Architecture Generation for Efficient National Transport), a comprehensive modeling framework that integrates powertrain architectures, charging infrastructures, and energy backbone systems into a cohesive strategy. In this paper, OR-AGENT is applied to develop an interconnected systems architecture for energy efficiency and resiliency enhancement of heavy-duty drayage vehicles at the Port of Savannah, GA. This framework showcases an interconnected systems approach to electrifying heavy-duty drayage vehicles at the Port of Savannah, GA. The study assessed BEVs with 400–1200 kWh battery capacities, accounting for seasonal variations in weather and freight routing. A diverse charging mix (150 kW–1250 kW) was evaluated alongside grid capacity constraints, cost, and carbon intensity analysis, leading to the development of a strategic microgrid/Distributed Energy Resources (DER) deployment architecture to ensure a reliable and sustainable transition. However, the findings also highlight the need for alternative zero-emission solutions for remaining trips, such as larger batteries, electrified roadways, hydrogen powertrains, or net-zero emission fuels. In conclusion, the findings are incorporated into a Total Cost of Ownership (TCO) model to identify optimal architectures for an interconnected electrified ecosystem.

Commercial vehicles↗
NASA NTRS2007

Electrification in Hurricanes over the Tropical Americas: Implication for Stratospheric Water Vapor

This study explores the relation between lightning activity and water vapor in the Tropical Tropopause Layer (TTL) over hurricane systems in the Tropical Americas. The hypothesis herein is that hurricanes that exhibit enhanced lightning activity are associated with stronger updrafts that can transport more moisture directly into the TTL (and subsequently into the tropical stratosphere) or even directly into the tropical stratosphere over this region. The TTL over the Tropical Americas, which includes the Caribbean and Gulf of Mexico, is of particular interest, because summertime cold point tropopause is the lowest in height and thus the warmest in temperature over the tropics. The latter condition implies higher saturation values and thus potential for more water vapor to enter the stratosphere. Climate forecast is very sensitive to stratospheric water vapor abundance, because of the key role that water vapor plays in regulating the chemical and radiative properties of the stratosphere. Given the potential for increases in hurricane intensity and frequency under predicted warmer conditions, it becomes essential to understand the effect of hurricanes on stratospheric water vapor. In this study, we use a combination of ground and space-borne observations as well as trajectory calculations. The observations include: cloud-to-ground (CG) lightning data from the U.S. National Lightning Detection Network (NLDN), geostationary infrared observations from the National Climatic Data Center Hurricane Satellite (HURSAT) data set, cloud properties from Aqua-MODIS, and water vapor from Aura-MLS. We analyze hurricanes from the 2005 season when Aura-MLS data are available, namely: Dennis, Emily, Katrina, Rita, and Wilma. Our analysis consists of examining CG lightning, cloud-top properties, and TTL water vapor (i.e., 100 and 147 mb) over the hurricane while it remains over water in the Tropical Americas region. We investigate daily as well as diurnal statistical properties. The hurricanes analyzed in this study showed that lightning activity is negatively correlated with minimum infrared brightness temperature and positively correlated with 100-mb water vapor. An examination of the maxima in water vapor observed over the hurricane not only shows larger magnitudes, but also larger differences between water vapor averages and water vapor maxima over the hurricane as lightning activity increases. Trajectory calculations are performed using the Flextra model in order to investigate the fate of the moister air masses found in the TTL.

Pittman, Jasna V.↗
DOE OSTI2025

Current state and future projections of drying processes in the US food and pulp and paper sectors: Energy, economic, and environmental assessment

The pulp and paper (P/P) and food sectors are the third- and fifth-largest industrial energy consumers in the United States, with total on-site energy consumption of 2,039 TBtu and 1,144 TBtu, respectively. Thermal drying processes for moisture removal, which are energy-intensive, play a critical role in both industries. This study is the first to evaluate state- and national-level US drying energy demand for these sectors from 2020 to 2050. To complete this evaluation, we developed a thermodynamic modeling framework integrated with economic and environmental models to compute product-specific drying energy intensity and estimate the sector-specific costs and emissions profiles associated with drying operations. The model-predicted energy intensity was validated against the literature. Using current and projected annual production volumes in these sectors, we estimated total drying energy use. Results indicate that drying accounts for 22 % of total energy consumption in the P/P sector and 10 % in the food sector. The estimated annual energy cost (2020) to operate thermal dryers is $\$$919 M in the P/P sector and $\$$417 M in the food sector. Additionally, drying contributes to 25 % of total CO 2 e emissions in the P/P sector (including biogenic) and 15 % of emissions in the food sector. Regional performance shows that the Southern US is the leading energy consumer for P/P drying, whereas the Midwest leads in food drying. This study presents both potential solutions to enhance drying efficiency and barriers to implementation. Energy efficiency improvements, low-carbon fuels, and electrification are discussed as key pathways for reducing costs and optimizing industrial drying processes.

3E analysis↗
DOE OSTI2026

EV Shuttle Bus Pilot

The EV Shuttle Bus Pilot dataset contains data and analysis from Hocking-Athens-Perry Community Action's demonstration of an electric bus on routes of their rural Athens Public Transit system. The vehicle used in the demonstration was a Ford E-450 cutaway equipped with an electric drivetrain, a 127-kWh battery system by Motiv Power Systems, and a cabin upfit by Turtle Top. Data gathered include route assignments, running time and distance, fuel economy, and charge cycles. A comparison of the vehicle's observed duty cycle with duty cycle modeling from other rural transit fleets in the National Transit Database is included to help better understand the rural adoption potential for this fleet technology.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Policy implications of net-zero emissions: A multi-model analysis of United States emissions and energy system impacts

Many countries, subnational jurisdictions, and companies are setting net-zero emissions goals; however, questions remain about strategies to reach these targets, policy measures, technology gaps, and economic impacts. Here, we investigate the potential policy implications of reaching economy-wide net-zero CO 2 emissions across the United States by 2050 using results from a multi-model comparison with 14 energy-economic models. Model results suggest that achieving net-zero CO 2 targets depends on policies that accelerate deployment of zero- and low-emitting technologies that have seen rapid cost reductions in recent years (including wind, solar, battery storage, and electric vehicles) as well as relatively nascent options (including carbon capture and storage, advanced biofuels, low-carbon hydrogen, advanced nuclear, and long-duration energy storage). While net-zero policies are likely to lower fossil fuel consumption, including considerable coal and petroleum reductions, achieving net-zero emissions does not necessarily mean phasing out all fossil fuels. Model results indicate that the Inflation Reduction Act’s energy and climate provisions amplify near-term decarbonization but that net-zero policies have larger impacts on long-run outcomes. Stringent climate policy can have large fiscal impacts on tax revenue and government spending—revenues from carbon pricing and subsidies for carbon removal range from 0.1 % to 3.7 % of GDP in 2050 across models. Each dollar per metric ton carbon price leads to a 0.06 % to 0.31 % reduction in economy-wide CO 2 emissions relative to a reference scenario with current policies. Spending on energy across the economy decreases relative to today for many models under reference and net-zero policies, especially as a share of GDP, due primarily to end-use electrification and energy efficiency.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Mauka Energy FEVER Tool Dataset

Mauka Energy’s dataset, developed under the Forestry Electric Vehicle Energy Routing (FEVER) project and funded by the U.S. Department of Energy’s Small Business Innovation Research program, is a high-resolution geospatial resource designed to support energy modeling for electric log trucks in complex forestry environments. The dataset integrates detailed spatial and road network data to enable accurate simulation of vehicle performance across varied terrain. At its core, the dataset incorporates lidar-derived elevation models, road alignments, and surface classifications from Oregon State University’s McDonald-Dunn Research Forest. These data capture fine-scale variations in slope, curvature, and surface conditions across forest road systems, allowing for vehicle-level analysis of energy consumption and recovery. The dataset also includes data collected on the surrounding public and private road networks in Benton County, Oregon, used in real-world haul routes. These connecting segments provide critical context for modeling transitions between forest operations and regional transportation infrastructure, incorporating attributes such as grade profiles, elevation change, and speed constraints. This combined dataset underpins the development of Mauka Energy’s rolldown tool, which quantifies energy use and regenerative braking potential on downhill and variable-grade segments. By leveraging high-resolution terrain and road data, the FEVER project enables more accurate assessment of electric vehicle feasibility and performance in forestry applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Behind-the-Meter Energy Storage and Generation in Support of Electrified Rental Car Centers

Electrification of rental car centers at major airports is expected to generate tens of MW in additional power loads. The magnitude of these loads poses challenges including high utility costs, expensive and lengthy distribution capacity upgrades, and disruptions to traditional operation. Behind-the-meter stationary battery storage and onsite photovoltaic generation offer a viable solution to these challenges without impacting the operation and business model of rental car companies, defined by minimal fleet inventory and short vehicle dwell time. Using data-driven syn-thetic charging loads for the rental car center at the Dallas/Fort Worth airport in the United States, we show that optimally-designed and controlled behind - the- meter resources can reduce the lifecycle cost of electrified rental centers by an average 41 % and reduce peak grid demand by 64 %, deferring the need for distribution upgrades or potentially avoiding it altogether.

battery storage↗
DOE OSTI2025

HOLISTIC ENERGY EFFICIENCY ANALYSIS OF ELECTRIFIED OFF-HIGHWAY MATERIAL HANDLER: FROM DRIVE CYCLE CHARACTERIZATION TO POWERTRAIN, HYDRAULIC, AND THERMAL SYSTEM PERFORMANCE

Three complexities surrounding the operation and testing of hybrid electric, heavy-duty nonroad machines have been addressed experimentally and using 1D simulation. Their resolutions have been intertwined with the development of a prototype machine that was proven to reduce fuel consumption in excess of 20%. A real-world drive cycle that leveraged hydraulic cylinder position was developed and utilized to ensure accurate reproduction of hydraulic work between the baseline and hybrid machines, while simultaneously maintaining less than 5% RMS error in position for main load handling functions. The newly developed, machine-specific drive cycle also contributed towards making equivalent comparisons in energy consumption between machine types through composite performance metrics that were extrapolated over a typical shift duration. Lastly, this work addressed thermal management energy consumption, a topic of increasing popularity when discussing electrified vehicles, by proposing a 1.4% energy savings through special mechanization and control of cooling system components.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Opportunities and Implications for Low-Cost Hydrogen Production from Water Electrolysis in a Decarbonizing Power Sector

Increased deployment of renewable power generation such as wind and solar photovoltaics along with electrification of transportation and other sectors are driving changes in the operation and economics of the electric power sector. Simultaneously, efforts to decarbonize other sectors of the economy such as steelmaking and heavy duty transportation will require significant amounts of electricity to drive electrons to molecules processes. Hydrogen production via water splitting electrolysis is a key near-term technology for decarbonization that interfaces between the power sector and decarbonization efforts in industrial sectors. This poster examines the implications for increased deployment of water electrolyzers in a rapidly evolving energy system. The economic opportunities for low-cost hydrogen production from electrolysis that are facilitated by highly renewable grids will be examined and discussed. Durability, cost, and operational strategies for electrolyzers interacting in these future energy systems are key to enabling hydrogen at scale. This poster will overview these considerations and ongoing work within the U.S. Department of Energy’s H2NEW consortium that is focused on addressing them.

electrolysis↗