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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Distributed Wind Market Report: 2023 Edition

The annual Distributed Wind Market Report provides stakeholders with market statistics and analysis along with insights into market trends and characteristics for wind technologies used as distributed energy resources. This report presents the distributed wind market from 2003 through 2022. Installed capacity, deployment trends, customer types, incentives, policies, installed costs, performance, and the future outlook for the distributed wind market are the key topics included in the report.

17 WIND ENERGY↗
DOE OSTI2023

Local-Scale Framework for Techno-Economic Analysis of Subsurface Hydrogen Storage

The energy sector is evolving toward increased reliance on renewable energy technologies to meet state, national, and organization decarbonization goals. This trend is creating challenges and opportunities with meeting current and future energy demand under the variable supply conditions that most renewables provide. Hydrogen (H 2 ) is a promising energy carrier that may meet the need for both on-demand and long-duration storage to maintain energy security and resilience. Underground hydrogen storage (UHS) is a method of storing H 2 in subsurface geological systems, such as depleted hydrocarbon reservoirs, salt caverns, saline aquifers, hard rock, and other engineered systems. UHS has the potential to store large quantities of H 2 over time, providing a reliable source of energy while minimizing surface footprints at a lower investment cost compared to surface storage. Earlier work estimated that, if converted and retrofitted, existing underground natural gas storage (UGS) facilities in the U.S. can store approximately 327 TWh, or 9.8 million metric tons, of pure H 2 . However, a shift to pure H 2 would decrease the collective working-gas energy of the UGS facilities by approximately 75% due to physical and chemical differences between natural gas and hydrogen. The same work also suggests that almost 75% of the existing UGS facilities in the U.S. could maintain current energy demand buffering using a blend of only 20% H 2 to 80% natural gas, by volume at surface conditions. If we can take advantage of the suite of mature technologies of existing UGS facilities and natural gas utility systems to accelerate the transition to a hydrogen economy in the U.S., a 20% H 2 blend could lead to a 6-7% reduction of greenhouse gas emissions for energy delivered through natural gas utility systems.

03 NATURAL GAS↗
DOE OSTI2023

How fluctuation intensity flux drives SOL expansion

Abstract Predictions of heat load widths λ q based on particle orbits alone are very pessimistic. This paper shows that pedestal peeling-ballooning (P-B) magnetohydrodynamic (MHD) turbulence broadens the stable scrape-off layer (SOL) by the transport, or spreading, of fluctuation energy from the pedestal. λ q is seen to increase with Γ ε , the fluctuation energy density flux. We elucidate the fundamental physics of the spreading process. Γ ε increases with pressure fluctuation correlation length. P-B turbulence is seen to be especially effective at spreading, on account of its large effective mixing length. Spreading is shown to be a multiscale process, which is enhanced by the synergy of large and small-scale modes. Pressure fluctuation skewness correlates well with the spreading flux–with the zero crossing of skewness and Γ ε spatially coincident–suggesting the role of coherent fluctuation structures and the presence of intermittency in λ q broadening. λ q ∼ B p − 1 scaling persists for the broadened SOL. We show that the spreading flux increases for increasing pedestal pressure gradient ∇ P 0 and for decreasing pedestal collisionality υ ped ∗ . This trend is due to the dominance of peeling modes for large ∇ P 0 and low υ ped ∗ . Ultimately, we see that a state of weak MHD turbulence, as for small ELMs, is very attractive for heat load management. Our findings have transformative implications for future fusion reactor designs and call for experimental investigations to validate the observed trends.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Near-term tropical cyclone risk and coupled Earth system model biases

Most current climate models predict that the equatorial Pacific will evolve under greenhouse gas–induced warming to a more El Niño-like state over the next several decades, with a reduced zonal sea surface temperature gradient and weakened atmospheric Walker circulation. Yet, observations over the last 50 y show the opposite trend, toward a more La Niña-like state. Recent research provides evidence that the discrepancy cannot be dismissed as due to internal variability but rather that the models are incorrectly simulating the equatorial Pacific response to greenhouse gas warming. This implies that projections of regional tropical cyclone activity may be incorrect as well, perhaps even in the direction of change, in ways that can be understood by analogy to historical El Niño and La Niña events: North Pacific tropical cyclone projections will be too active, North Atlantic ones not active enough, for example. Other perils, including severe convective storms and droughts, will also be projected erroneously. While it can be argued that these errors are transient, such that the models’ responses to greenhouse gases may be correct in equilibrium, the transient response is relevant for climate adaptation in the next several decades. Given the urgency of understanding regional patterns of climate risk in the near term, it would be desirable to develop projections that represent a broader range of possible future tropical Pacific warming scenarios—including some in which recent historical trends continue—even if such projections cannot currently be produced using existing coupled earth system models.

Science & Technology - Other Topics↗
DOE OSTI2023

WACCM6 Projections of Polar Mesospheric Cloud Abundance Over the 21st Century

Polar mesospheric clouds (PMC), or noctilucent clouds, can be observed over high latitudes with the naked eye from the ground or from space near the summer solstice. PMC are considered a direct and sensitive indicator of climate change and have been reported to appear more frequently in recent decades. How PMC will change in the future under the influence of natural variability and anthropogenic forcing is uncertain. In this study, we utilize model output from the Whole Atmosphere Community Climate Model under several shared socioeconomic pathway (SSP) scenarios and input the water vapor, temperature, and pressure information into a 0-d PMC model to project the trend and variation of PMC over the 21st century, and their relationship to future changes of temperature, water vapor, and the solar cycle. The 0-d model calculations indicate that PMC ice water content (IWC) will increase and PMC will extend to lower latitudes under high SSP scenarios. Under these scenarios, more mesospheric water vapor leads to an increased IWC of PMC over the polar region, and colder mesopause temperature leads to more PMC over the mid-latitudes. There is a significant anti-correlation between the solar cycle and PMC IWC over the 21st century, but the anti-correlation is not always significant on the decadal scale. Finally, methane oxidation in the stratosphere and water vapor entering from the troposphere are both responsible for future changes in mesospheric water vapor and thus PMC.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

CCUS Perspectives: Assessing Historical Contexts, Current Realities, and Future Prospects

CCUS technologies are crucial solutions for mitigating climate change by reducing CO2 emissions from industrial operations and energy sectors. This review critically examines the current state of CCUS technologies, and highlights advancements, challenges, regulatory frameworks, and future directions. It comprehensively analyzes carbon capture methods, such as pre-combustion, post-combustion, and oxy-fuel combustion capture, while comparing their efficiencies and limitations. The review also explores carbon utilization techniques, such as direct and indirect utilization, emphasizing their potential applications and technological constraints. Additionally, it assesses various carbon storage methods, focusing on geological, ocean, and mineralization storage, and discusses their capacity, feasibility, and environmental implications. The study reviews the policy and regulatory frameworks, economic viability, market trends, and environmental sustainability of CCUS. By identifying research gaps and recommending future research priorities, this review aims to guide the development of more efficient/effective, and cost-effective CCUS technology, ensuring their role in a sustaining low-carbon future. This review provides a forward-looking perspective, a critical and interdisciplinary analysis that assesses the current state of CCUS technologies, and further provides a roadmap for future development.

Energy & Fuels↗
DOE OSTI2024

U.S. Trends on MEA Architectures

The presentation discusses background, current industry status in the US, potential future novel pathways, and challenges to a broad understanding of and optimal decision about the architecture of PEM fuel cell MEAs. This is not an original research paper, it is my observation and perspective on technology status, as requested for the scope of the workshop.

ENGINEERING,MATERIALS SCIENCE↗
DOE OSTI2024

Forest Carbon Storage in the Western United States: Distribution, Drivers, and Trends

Abstract Forests are a large carbon sink and could serve as natural climate solutions that help moderate future warming. Thus, establishing forest carbon baselines is essential for tracking climate‐mitigation targets. Western US forests are natural climate solution hotspots but are profoundly threatened by drought and altered disturbance regimes. How these factors shape spatial patterns of carbon storage and carbon change over time is poorly resolved. Here, we estimate live and dead forest carbon density in 19 forested western US ecoregions with national inventory data (2005–2019) to determine: (a) current carbon distributions, (b) underpinning drivers, and (c) recent trends. Potential drivers of current carbon included harvest, wildfire, insect and disease, topography, and climate. Using random forests, we evaluated driver importance and relationships with current live and dead carbon within ecoregions. We assessed trends using linear models. Pacific Northwest (PNW) and Southwest (SW) ecoregions were most and least carbon dense, respectively. Climate was an important carbon driver in the SW and Lower Rockies. Fire reduced live and increased dead carbon, and was most important in the Upper Rockies and California. No ecoregion was unaffected by fire. Harvest and private ownership reduced carbon, particularly in the PNW. Since 2005, live carbon declined across much of the western US, likely from drought and fire. Carbon has increased in PNW ecoregions, likely recovering from past harvest, but recent record fire years may alter trajectories. Our results provide insight into western US forest carbon function and future vulnerabilities, which is vital for effective climate change mitigation strategies.

Environmental Sciences & Ecology↗
DOE OSTI2021

Life‐Cycle Assessment Considerations for Batteries and Battery Materials

Abstract Rechargeable batteries are necessary for the decarbonization of the energy systems, but life‐cycle environmental impact assessments have not achieved consensus on the environmental impacts of producing these batteries. Nonetheless, life cycle assessment (LCA) is a powerful tool to inform the development of better‐performing batteries with reduced environmental burden. This review explores common practices in lithium‐ion battery LCAs and makes recommendations for how future studies can be more interpretable, representative, and impactful. First, LCAs should focus analyses of resource depletion on long‐term trends toward more energy and resource‐intensive material extraction and processing rather than treating known reserves as a fixed quantity being depleted. Second, future studies should account for extraction and processing operations that deviate from industry best‐practices and may be responsible for an outsized share of sector‐wide impacts, such as artisanal cobalt mining. Third, LCAs should explore at least 2–3 battery manufacturing facility scales to capture size‐ and throughput‐dependent impacts such as dry room conditioning and solvent recovery. Finally, future LCAs must transition away from kg of battery mass as a functional unit and instead make use of kWh of storage capacity and kWh of lifetime energy throughput.

25 ENERGY STORAGE↗
DOE OSTI2023

Impact Analysis of Future Electric Vehicles Using Model of Real Distribution Feeders

Globally, the number of electric vehicles (EVs) continues to increase. This on-going trend poses challenges for power distribution systems. The inclusion of electric vehicle supply equipment (EVSE) should be compatible with a changing energy system, whose structure is becoming increasingly distributed. The impact of future EVs should be analyzed and considered in the system planning and upgrades. In this study, impact analysis of future EVs is conducted for a utility company of U.S. West Coast. Real data of distribution feeders is converted into the GridLAB-D model for running power flow analysis. An estimation of the additional loading of EVs in 2050 is provided by the utility company. Simple mitigation methods are tested to improve voltage profiles and complete this case study.

Xie, Jing↗
DOE OSTI2026

Gravity Well Commercial Economics Assessment: Potential Revenue and Cost: Cooperative Research and Development (Final Report)

In the Gravity Well Revenue Study, we evaluate the potential revenue from energy storage using historical energy-only electricity prices, forward-looking projections of hourly electricity prices, and actual reported revenue. This analysis examines the impact of storage duration and round-trip efficiency, as well as the location of the storage, on storage revenue within the current and projected U.S. power system. We also investigated the impact of round-trip efficiency on storage revenue. We found that the relationship between storage revenue and round-trip efficiency is nonlinear. The value of improved round-trip efficiency declines as round-trip efficiency increases. In the Gravity Well Future Cost Study, we applied learning curves to predict the future cost trajectory of Gravity Wells (GrWs). Two types of analysis were implemented. The first was a bottom-up analysis that used historical learning rates for cost components, such as motors and gearboxes, and cost categories (e.g., engineering and design, etc.) to determine the learning-by-doing based single-factor learning curve. The single factor learning curve expresses the relationship between the cost of GrW and the number of units deployed (or the cumulative capacity). In the second analysis, we predicted future GrW costs via a top-down approach. This approach accounts for historical cost trends in other renewable energy and storage technologies, which have similarities with GrWs. Using a multifactor learning curve that accounts for both intrinsic (cumulative capacity) and extrinsic (the elasticity in the price of steel) factors, we estimated the future cost of GrWs.

25 ENERGY STORAGE↗
DOE OSTI2020

Opportunities and Challenges in Metal Forming for Lightweighting: Review and Future Work

Abstract The purposes of this review are to summarize the historical progress in the last 60 years of lightweight metal forming, to analyze the state-of-the-art, and to identify future directions in the context of Cyber-physically enabled circular economy. In honoring the 100th anniversary of the establishment of the Manufacturing Engineering Division of ASME, this review paper first provides the impact of the metal forming sector on the economy and historical perspectives of metal forming research work published by the ASME Journal of Manufacturing Science and Engineering, followed by the motivations and trends in lightweighting. To achieve lightweighting, one needs to systematically consider: (1) materials and material characterization; (2) innovative forming processes; and (3) simulation tools for integrated part design and process design. A new approach for process innovation, i.e., the Performance-Constraints-Mechanism-Innovation (PCMI) framework, is proposed to systematically seek new processes. Finally, trends and challenges for the further development in circular economy are presented for future exploration.

Engineering↗
DOE OSTI2022

Opportunities for Renewable Energy, Storage, Vehicle Electrification, and Demand Response in Rajasthan's Power Sector

To support the government of Rajasthan and inform state policy makers, regulators, planners, and system operators on power system trends, NREL undertook a long-term capacity expansion planning study. We used NREL's flagship capacity expansion planning tool for the power sector called the Regional Energy Deployment System India (ReEDS-India) to understand the generation and transmission needs of Rajasthan through 2050. NREL's modeling framework includes co-optimized decisions about generation, energy storage, transmission, and reserves investments needed to meet future demand while maintaining reliable electricity supply. Scenario analysis was conducted to assess a range of potential future scenarios, providing insight for planning agencies, utilities, and local stakeholders about key trends and sources of uncertainty.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Single-atom automobile exhaust catalysts

Single-atom catalysts (SACs) with isolated metal centers are attracting great research interest because of their maximized metal utilization rates and unique structures. In the last decade, significant efforts have been made to design highly efficient and costeffective SACs with applications in automobile exhaust aftertreatment. SACs have not only demonstrated their high potential for improving the catalytic performance of current automobile exhaust catalysts but also provided an ideal platform for understanding the origins of catalyst reactivity. In this review, we summarize the general strategies for promoting the reactivity of metal SACs while maintaining their thermal stability during exhaust-abatement-related reactions. Highlights are provided on well-performed SACs for CO oxidation, unburnt hydrocarbon (HC) oxidation, and the selective catalytic reduction of NOx. The reaction mechanism and structure– performance relationship of SAC during these reactions are also discussed. Finally, perspectives are given on the trending research fields for designing more efficient single-atom automobile exhaust catalysts in the future.

Lu, Yubing↗
DOE OSTI2025

Adaptive anomaly detection for identifying attacks in cyber-physical systems: A systematic literature review

Modern cyberattacks in cyber-physical systems (CPS) rapidly evolve and cannot be deterred effectively with most current methods, which focus on characterizing past threats. Adaptive anomaly detection (AAD) is among the most promising techniques to detect evolving cyberattacks, with an emphasis on fast data processing and model adaptation. AAD has been researched extensively; however, to the best of our knowledge, our work is the first systematic literature review (SLR) on current research in this field. We present a comprehensive SLR, gathering 397 relevant papers and systematically analyzing 65 of them (47 research and 18 survey papers) on AAD in CPS from 2013 to November 2023. We introduce a novel taxonomy considering attack types, CPS application, learning paradigm, data management, and algorithms. Our findings show that most studies addressed either model adaptation or data processing, but rarely both simultaneously. This indicates a research gap in fully adaptive solutions. We also categorize algorithms, datasets, and attack characteristics, and summarize strengths and weaknesses across the literature. Our review provides a structured and accessible reference for researchers and practitioners, offering insights into key trends and highlighting limitations in current approaches. Finally, we outline several future research directions, including the need for integrated real-time processing and adaptive learning, explainability, and uncertainty quantification in AAD for CPS.

Adaptation↗
DOE OSTI2022

Recent advances and challenges in optimization models for expansion planning of power systems and reliability optimization

Optimization models for expansion planning of power systems aim to determine capacities, investment timing, and location of power systems to satisfy the power demands while minimizing the total cost. The models have become complex in recent years to reflect both regulations on conventional energy sources and the increasing penetration of renewable energy sources (RES). This paper reviews the basic concepts and optimization models for expansion planning of power systems. We first explain the definition and features of generation expansion planning (GEP), transmission expansion planning (TEP), and generation and transmission expansion planning (GTEP). To address the computational challenges of large-scale expansion planning problems, we review several simplifications including temporal and spatial aggregation, and decomposition methods. This paper also addresses power system reliability defined as the probability of satisfying the load demand while withstanding failures of components. Finally, the goal of this paper is to provide a research overview, discuss trends in expansion planning of power systems, and suggest directions for future research.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Machine learning for international freight transportation management: A comprehensive review

Machine learning (ML) offers a promising avenue for international freight transportation management (IFTM) given its capability to harness the power of data that have become increasingly available to freight transportation researchers and practitioners. This paper conducts a comprehensive investigation of the state-of-the-art in developing ML models for applications to different aspects of IFTM. We start by giving an overview of various fundamental ML methods. Then, how different ML methods have been employed, adapted, and applied to a multitude of subject areas in IFTM are discussed, including demand forecast, operation and asset maintenance, and vehicle trajectory and on-time performance prediction. The potential data sources that may be used to develop ML models are further examined. Subsequently, a synthesis of the exiting work is performed to identify the specific topics addressed in the existing research, ML methods used, the trends of research, and opportunities for further explorations. Four directions for future research are proposed in the end.

Data sources↗
DOE OSTI2021

A database of global storm surge reconstructions

Storm surges are among the deadliest coastal hazards and understanding how they have been affected by climate change and variability in the past is crucial to prepare for the future. However, tide gauge records are often too short to assess trends and perform robust statistical analyses. Here we use a data-driven modeling framework to simulate daily maximum surge values at 882 tide gauge locations across the globe. We use five different atmospheric reanalysis products for the storm surge reconstruction, the longest one going as far back as 1836. The data that we generate can be used, for example, for long-term trend analyses of the storm surge climate and identification of regions where changes in the intensity and/or frequency of storms surges have occurred in the past. It also provides a better basis for robust extreme value analysis, especially for tide gauges where observational records are short. The data are made available for public use through an interactive web-map as well as a public data repository.

54 ENVIRONMENTAL SCIENCES↗