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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Contingency contractor optimization Phase 2, model description and formulation

The goal of Phase 2 the OSD ATL Contingency Contractor Optimization project is to create a prototype of a tool for the contingency contractor element of total force planning during the Support for Strategic Analysis (SSA). An optimization model was developed to determine the optimal mix of military, Department of Defense (DoD) civilians and contractors that accomplishes a set of user defined mission requirements at the lowest possible cost while honoring resource limitations and manpower use rules. Additional features allow the model to understand the variability of the Total Force Mix when there is uncertainty in mission requirements and recommend where investments in manpower capabilities might minimize the overall total force costs in future operations.

Gearhart, Jared L.↗
DOE OSTI2013

NREL Innovations Help Drive Wind Industry Transformation [Fact Sheet]

For nearly 30 years, NREL has helped the wind turbine industry through design and research innovations. The comprehensive capabilities of the National Wind Technology Center (NWTC), ranging from specialized computer simulation tools to unique test facilities, has been used to design, develop, and deploy several generations of advanced wind energy technology.

17 WIND ENERGY↗
DOE OSTI2020

High-temperature thermal energy storage with thermophotovoltaic energy conversion (Final Report)

This project began with a simple concept: that thermal energy storage paired with thermophotovoltaic power conversion could be a cost-effective solution to the challenge of renewables variability. Renewable energy sources such as solar and wind energy are clean, affordable, and abundant worldwide, but their variability presents a major problem for the incorporation of a large amount of these resources in global power systems. Systems with high penetrations of renewables frequently see periods of overproduction, where renewable energy is thrown away, and periods of underproduction, where expensive and polluting fossil fuel resources must be used to fill in the gaps. While energy storage technologies such as lithium ion batteries can help store energy from times of overproduction to times the energy is needed, current and projected future prices for these technologies are not low enough to support very renewables-heavy power grids. The research also focused on the techno-economics of using thermal energy storage and thermophotovoltaics to store the energy from solar and wind energy sources when they are available and release this energy back to the grid when it is needed. One of the biggest outcomes of this research was the conclusion that battery prices must drop 10x from their current values in order to meet this need, and this is unlikely to happen with current technologies such as lithium ion batteries.

14 SOLAR ENERGY↗
DOE OSTI2023

A Systems Approach to Increasing Carbon Flux to Seed Oil for Biofuels and Bioproducts Production in Camelina sativa (Final Report)

To combat climate change and alleviate the dependency of the United States on fossil fuels, the transition to biofuel crops has long been proposed as a crucial part of the long-term solution. Camelina sativa has emerged as one of the leading commercially viable options for biofuel and bioproduct production for the U.S. Camelina has the advantages of low agronomic inputs and natural resistance to diverse biotic and abiotic stresses relative to other oilseed crops, and Camelina oil-based blends have been tested and approved as liquid transportation fuels. A major limitation in the widespread adoption of Camelina as a viable industrial oilseed crop is its modest oil yields. This project directly investigated possible paths towards increasing oil, by employing tissue-specific and whole plant systems approaches to identify major regulatory bottlenecks. We developed a new high-throughput method for the identification of multi-gene transformants in polyploid species like Camelina sativa and used this to determine that, contrary to what mathematical models suggested, introduction of the microbial Entner-Doudoroff (ED) pathway into Camelina sativa did not result in significant seed oil increases. We developed flux maps providing accurate and statistically robust models of central carbon metabolism in Camelina, including of cultured Camelina embryos. This knowledge was used in the capacitation of a number of junior researchers in gaining knowledge on approaches used for quantitative flux map analyses. We identified several novel Camelina transcription factor genes regulating fatty acid biosynthesis that showed variable effects on seed oil accumulation in transgenic plants. Among a number of community resources, we also developed a knowledge base web resource (CamRegBase) to integrate Camelina gene regulatory information. Together, research outcomes from this project have contributed to a much better understanding of the regulation and bottlenecks to engineer seed oil production in Camelina.

09 BIOMASS FUELS↗
DOE OSTI2023

The Fermi-LAT Lightcurve Repository

The Fermi Large Area Telescope (LAT) lightcurve repository (LCR) is a publicly available, continually updated library of gamma-ray lightcurves of variable Fermi-LAT sources generated over multiple timescales. The Fermi-LAT LCR aims to provide publication-quality lightcurves binned on timescales of 3, 7, and 30 days for 1525 sources deemed variable in the source catalog of the first 10 yr of Fermi-LAT observations. The repository consists of lightcurves generated through full likelihood analyses that model the sources and the surrounding region, providing fluxes and photon indices for each time bin. The LCR is intended as a resource for the time-domain and multimessenger communities by allowing users to search LAT data quickly to identify correlated variability and flaring emission episodes from gamma-ray sources. We describe the sample selection and analysis employed by the LCR and provide an overview of the associated data access portal.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

RADAI: A Large-Scale Realistic Dataset for Radiation Detection Algorithm Development

Open, realistic datasets are essential for developing and benchmarking radiation detection algorithms, yet they remain scarce. The Radiological Anomaly Detection and Identification (RADAI) project was develop to create datasets that meet the training and testing needs for sophisticated radiation detection algorithms. The RADAI dataset is a large-scale synthetic resource that integrates high-fidelity Monte Carlo simulations with realistic urban scenarios to capture both background variability and source signatures. RADAI models construction-material NORM, people and vehicles, urban clutter, and dynamic environmental effects such as cosmic-ray and rain-induced transients, and they provide list-mode detector data with motion and response modeling suitable for algorithm training and evaluation. The RADAI project resulted in three publicly-released complementary datasets together with an online scoring portal for standardized performance assessment and an open software toolkit that supports data access, augmentation, model development, and evaluation. These resources enable reproducible comparisons across methods and promote rigorous studies at the scale required by contemporary machine learning. By grounding algorithm development in realistic, well-documented conditions, RADAI supports progress toward more robust detection, identification, and localization in complex urban environments.

Ghawaly, James M. [Division of Computer Science an↗
DOE OSTI2024

Resource Adequacy in Decarbonizing Power Systems

Decarbonization of the power sector is instrumental to reducing emissions worldwide. Following the 13th Clean Energy Ministerial conference (CEM13) in 2022, several governments signaled their intention to develop power sector decarbonization action plans. The 21st Century Power Partnership (21CPP), in coordination with all Clean Energy Ministerial power workstreams and collaborators, is providing technical support on critical focus areas as these countries prepare their action plans. Countries will present the action plans at the upcoming CEM14 in India. Brought to you by the Clean Energy Solutions Center and 21CPP, this webinar will focus on resource adequacy and grid flexibility, key themes in the CEM14 action plans and critical topics for integrating variable renewable energy into the grid while ensuring system reliability. Global energy experts will discuss how grid planners can ensure stable supply while rapidly decarbonizing the power system and how various policies can increase the power grid's flexibility.

emissions↗
DOE OSTI2025

Hybrid Quantum Networks with Discrete Polarizations and Continuous Quadrature Variables

Final Scientific/Technical Report for DOE Project DE-SC0022069. Quantum communication and computation systems have evolved along two largely independent paradigms: discrete-variable (DV) systems that encode information in qubits such as photon polarizations or photon-number states, and continuous-variable (CV) systems that encode information in optical field quadratures. Each approach offers distinct advantages—DVs provide low error rates and compatibility with single-photon platforms, while CVs support deterministic operations and efficient quantum state manipulation. A fundamental challenge for building a scalable Quantum Internet lies in interfacing these two regimes into a unified hybrid architecture that can coherently distribute and process quantum information across heterogeneous quantum nodes. This project aims to develop and demonstrate a hybrid optical quantum network that seamlessly integrates DV and CV systems. Specifically, we investigate a new class of hybrid entanglement between the discrete polarizations of single photons and the continuous quadrature variables of optical cat states, overcoming incompatibilities in existing DV–CV demonstrations. Using this new entanglement resource, the team investigates a multi-node hybrid quantum local area network (Q-LAN) testbed capable of DV–CV entanglement generation, swapping, and distribution across fiber links.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

MEP Metric Correlations with Socioeconomic and Built Environment Factors [Slides]

NREL's Mobility Energy Productivity tool, or MEP, quantifies the ability of an area's transportation system to connect individuals to goods, services, employment opportunities, and other activities while accounting for time, cost, and energy. However, the MEP tool itself does not examine correlations between mobility energy productivity and other sociodemographic and built environment variables relevant to the urban and transportation planning space. Examining these correlations could have two possible implications -- first, understanding what factors correlate with mobility energy productivity could help urban planners make equitable decisions in allocating transportation resources. Second, as the MEP has not been calculated for all urban areas in the US and is computationally expensive, if other publicly available variables were predictive enough of MEP then a simple model could be used to predict MEP instead of having to compute it for an area for which it has not been updated. A statistical analysis to investigate both of these questions is presented, with many significant associations found between the MEP and identified variables of interest.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Wave energy resource characterization at the US Navy's Wave Energy Test Site, Hawaii.

Numerical wave modeling is an important aspect of the Hawaii Natural Energy Institute (HNEI) at the University of Hawaii’s support to the operation of the Navy's Wave Energy Test Site (WETS). A system of third-generation spectral wave models was produced a 34-year wave hindcast dataset and is currently providing daily 7.5-day wave forecasts on a hierarchy of nested grids from global to island scales. The high-resolution wave hindcast around the Hawaiian Islands provides a wealth of information for characterization of wave resources in support of WEC developers, who may test at WETS. This dataset exhibits seasonal and interannual variability of wave conditions that make WETS quite well suited for testing of various WEC types. The daily 7.5-day wave forecast complements the buoy measurements to support planning of at-sea operations and day-to-day operation of WEC devices.

Numerical wave modeling, spectral wave model, 7.5-↗
DOE OSTI2025

Evaluating the impacts of Variable Message Signs on Airport Curbside Performance Using Microsimulation

Curbs play a vital role in facilitating vehicle access and egress for individuals at airports. Inefficiently allocating this resource hinders airport accessibility and productivity, resulting in congestion, longer travel times, and increased pollution. As airport demand fluctuates throughout the day and grows over time, airports face intensified curbside pressure. Yet, curb management research is significantly less robust at airports than in urban areas. Given the unbalanced nature of airport demand—riders tend to arrive simultaneously at specific entrances at certain hours—Variable Message Sign (VMS) arises as a cost-effective technology to divert vehicles from congested to underutilized curbs. Still, VMS implementation faces a significant challenge. Historically, airports have managed VMS heuristically and by intuition rather than an evidence-based approach. This research investigates the impacts of implementing VMS on curb performance at airports. By considering different driver compliance rates (DCR), we aim to determine when the sign should be turned on and off to diverge traffic to avoid undesired externalities while enhancing curb performance. Using a validated agent-based microsimulation model, VISSIM, we analyzed the Seattle-Tacoma (SeaTac) Airport as a case study. We modeled sixteen VMS management scenarios and a baseline where the message sign is not displayed, diverging vehicles between the departures and arrivals access levels at four different moments (early morning, morning, afternoon, and late night). We quantified the effects of VMS using seven metrics, including curb productivity index (CPI), curb accessibility (CA), queue length, queue duration, delay, vehicle counts, and emissions. The results of each scenario were compared against the baseline using absolute and relative changes and Repeated Measures ANOVA. Overall, VMS improved curb performance and traffic conditions at the airport, reducing emissions by 14.8% to 8.9%. Moreover, significant reductions in queue length (1,150 ft to 100 ft) and duration (15 to 144 minutes) were observed in the sending link under all VMS policies. However, impacts on the receiving link varied based on congestion, with significant increases in queue duration (9.8 to 24 min) when congested but no substantial changes in free flow. Notably, diverging vehicles to congested links resulted in non-significant results, and activating late and deactivating late VMS affected curb productivity (-5.8% to -61.4%), curb accessibility (-16.5% to -25.8%), cumulative counts (-33.4% to -59.4%), and vehicle delay (95.98% to 594.3%). Activating VMS before congestion begins in the sending link and deactivating before a queue forms in the receiving link yield the most significant improvements: 8.1% to 10.1% in CPI, 9.4% to9.6% in CA, -29.3% to -77.9% in total delay, -11.6% to -13.9% in total emissions, and 101% to 103% in cumulative counts. As the analysis was made with a wide range of time periods, access levels, driver compliance rates, and scenarios, we believe our findings can provide valuable insights into how airports should manage VMS. Our work introduces a novel approach to the scientific airport literature, as some of our metrics were previously unexplored. Additionally, we propose a methodology that other airports can adopt to maximize their curb performance.

Gutierrez, Jorge D.↗
DOE OSTI2016

Renewable Energy Resources Portfolio Optimization in the Presence of Demand Response

In this paper we introduce a simple cost model of renewable integration and demand response that can be used to determine the optimal mix of generation and demand response resources. The model includes production cost, demand elasticity, uncertainty costs, capacity expansion costs, retirement and mothballing costs, and wind variability impacts to determine the hourly cost and revenue of electricity delivery. The model is tested on the 2024 planning case for British Columbia and we find that cost is minimized with about 31% renewable generation. We also find that demand responsive does not have a significant impact on cost at the hourly level. The results suggest that the optimal level of renewable resource is not sensitive to a carbon tax or demand elasticity, but it is highly sensitive to the renewable resource installation cost.

Behboodi, Sahand↗
DOE OSTI2013

Flexible Coal: Evolution from Baseload to Peaking Plant (Brochure)

Twenty-first century power systems, with higher penetration levels of low-carbon energy, smart grids, and other emerging technologies, will favor resources that have low marginal costs and provide system flexibility (e.g., the ability to cycle on and off to follow changes in variable renewable energy plant output). Questions remain about both the fate of coal plants in this scenario and whether they can cost-effectively continue to operate if they cycle routinely. The experience from the CGS plant demonstrates that coal plants can become flexible resources. This flexibility - namely the ability to cycle on and off and run at lower output (below 40% of capacity) - requires limited hardware modifications but extensive modifications to operational practice. Cycling does damage the plant and impact its life expectancy compared to baseload operations. Nevertheless, strategic modifications, proactive inspections and training programs, among other operational changes to accommodate cycling, can minimize the extent of damage and optimize the cost of maintenance. CGS's cycling, but not necessarily the associated price tag, is replicable. Context - namely, power market opportunities and composition of the generation fleet - will help determine for other coal plants the optimal balance between the level of cycling-related forced outages and the level of capital investment required to minimize those outages. Replicating CGS's experience elsewhere will likely require a higher acceptance of forced outages than regulators and plant operators are accustomed to; however, an increase in strategic maintenance can minimize the impact on outage rates.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2014

Flexible Coal: An Example Evolution from Baseload to Peaking Plant (Presentation)

Twenty-first century power systems, with higher penetration levels of low-carbon energy, smart grids, and other emerging technologies, will favor resources that have low marginal costs and provide system flexibility (e.g., the ability to cycle on and off to follow changes in variable renewable energy plant output). Questions remain about both the fate of coal plants in this scenario and whether they can cost-effectively continue to operate if they cycle routinely. The experience from the CGS plant demonstrates that coal plants can become flexible resources. This flexibility - namely the ability to cycle on and off and run at lower output (below 40% of capacity) - requires limited hardware modifications but extensive modifications to operational practice. Cycling does damage the plant and impact its life expectancy compared to baseload operations. Nevertheless, strategic modifications, proactive inspections and training programs, among other operational changes to accommodate cycling, can minimize the extent of damage and optimize the cost of maintenance. CGS's cycling, but not necessarily the associated price tag, is replicable. Context - namely, power market opportunities and composition of the generation fleet - will help determine for other coal plants the optimal balance between the level of cycling-related forced outages and the level of capital investment required to minimize those outages. Replicating CGS's experience elsewhere will likely require a higher acceptance of forced outages than regulators and plant operators are accustomed to; however, an increase in strategic maintenance can minimize the impact on outage rates.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2014

Flexible Coal: An Example Evolution from Baseload to Peaking Plant (Presentation)

Twenty-first century power systems, with higher penetration levels of low-carbon energy, smart grids, and other emerging technologies, will favor resources that have low marginal costs and provide system flexibility (e.g., the ability to cycle on and off to follow changes in variable renewable energy plant output). Questions remain about both the fate of coal plants in this scenario and whether they can cost-effectively continue to operate if they cycle routinely. The experience from the CGS plant demonstrates that coal plants can become flexible resources. This flexibility - namely the ability to cycle on and off and run at lower output (below 40% of capacity) - requires limited hardware modifications but extensive modifications to operational practice. Cycling does damage the plant and impact its life expectancy compared to baseload operations. Nevertheless, strategic modifications, proactive inspections and training programs, among other operational changes to accommodate cycling, can minimize the extent of damage and optimize the cost of maintenance. CGS's cycling, but not necessarily the associated price tag, is replicable. Context - namely, power market opportunities and composition of the generation fleet - will help determine for other coal plants the optimal balance between the level of cycling-related forced outages and the level of capital investment required to minimize those outages. Replicating CGS's experience elsewhere will likely require a higher acceptance of forced outages than regulators and plant operators are accustomed to; however, an increase in strategic maintenance can minimize the impact on outage rates.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Machine Learning Models for Mapping Groundwater Pollution Risk: Advancing Water Security and Sustainable Development Goals in Georgia, USA

The widespread use of pesticides, such as atrazine and malathion, in agricultural systems raises significant concerns regarding the contamination of groundwater, which serves as a critical resource for drinking water. This study applies machine learning techniques to predict the concentrations of atrazine and malathion in groundwater across Georgia, USA, using 2019 data. A Random Forest classifier was employed to integrate various environmental and demographic factors, including pesticide application rates, precipitation, lithology, and population density, to predict pesticide contamination in groundwater. The models demonstrated high training accuracies of 100% and moderate average testing accuracy of 55% for atrazine and 60% for malathion across five iterations. The low test accuracy of the model, ranging from 50% to 75%, is likely due to overfitting, which can be attributed to the small dataset size and the complex nature of pesticide-contamination patterns, making it challenging for the model to generalize to unseen data. Feature importance analysis revealed that average pesticide usage emerged as the most influential factor for atrazine, while aquifer lithology and precipitation played crucial roles in both models. These results provide valuable insights into the dynamics of pesticide contamination, highlighting areas at greater risk of contamination. The findings underscore the importance of integrating environmental, geological, and agricultural variables for more effective groundwater management and sustainable agricultural practices, contributing to the protection of water resources and public health.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2010

Unit Commitment Considering Generation Flexibility and Environmental Constraints

This paper proposes a new framework for power system unit commitment process, which incorporates the generation flexibility requirements and environmental constraints into the existing unit commitment algorithm. The generation flexibility requirements are to address the uncertainties with large amount of intermittent resources as well as with load and traditional generators, which causes real-time balancing requirements to be variable and less predictable. The proposed flexibility requirements include capacity, ramp and ramp duration for both upward and downward balancing reserves. The environmental constraints include emission allowance for fossil fuel-based generators and ecological regulations for hydro power plants. Calculation of emission rates is formulated. Unit commitment under this new framework will be critical to the economic and reliable operation of the power grid and the minimization of its negative environmental impacts, especially when high penetration levels of intermittent resources are being approached, as required by the renewable portfolio standards in many states.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗