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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

38th JANNAF Combustion Subcommittee Meeting

This volume, the first of two volumes, is a collection of 55 unclassified/unlimited-distribution papers which were presented at the Joint Army-Navy-NASA-Air Force (JANNAF) 38th Combustion Subcommittee (CS), 26 th Airbreathing Propulsion Subcommittee (APS), 20th Propulsion Systems Hazards Subcommittee (PSHS), and 21 Modeling and Simulation Subcommittee. The meeting was held 8-12 April 2002 at the Bayside Inn at The Sandestin Golf & Beach Resort and Eglin Air Force Base, Destin, Florida. Topics cover five major technology areas including: 1) Combustion - Propellant Combustion, Ingredient Kinetics, Metal Combustion, Decomposition Processes and Material Characterization, Rocket Motor Combustion, and Liquid & Hybrid Combustion; 2) Liquid Rocket Engines - Low Cost Hydrocarbon Liquid Rocket Engines, Liquid Propulsion Turbines, Liquid Propulsion Pumps, and Staged Combustion Injector Technology; 3) Modeling & Simulation - Development of Multi- Disciplinary RBCC Modeling, Gun Modeling, and Computational Modeling for Liquid Propellant Combustion; 4) Guns Gun Propelling Charge Design, and ETC Gun Propulsion; and 5) Airbreathing - Scramjet an Ramjet- S&T Program Overviews.

Fry, Ronald S.↗
NASA NTRS2019

Progress and Challenges in Quantifying Wildfire Smoke Emissions, Their Properties, Transport, and Atmospheric Impacts

Wildfire is a natural and integral ecosystem process that is necessary to maintain species composition, structure, and ecosystem function. Extreme fires have been increasing over the last decades, which have a substantial impact on air quality, human health, the environment, and climate systems. Smoke aerosols can be transported over large distances, acting as pollutants that affect adjacent and distant downwind communities and environments. Fire emissions are a complicated mixture of trace gases and aerosols, many of which are short‐lived and chemically reactive, and this mixture affects atmospheric composition in complex ways that are not completely understood. We present a review of the current state of knowledge of smoke aerosol emissions originating from wildfires. Satellite observations, from both passive and active instruments, are critical to providing the ability to view the large‐scale influence of fire, smoke, and their impacts. Progress in the development of fire emission estimates to regional and global chemical transport models has advanced, although significant challenges remain, such as connecting ecosystems and fuels burned with dependent atmospheric chemistry. Knowledge of the impact of smoke on radiation, clouds, and precipitation has progressed and is an essential topical research area. However, current measurements and parameterizations are not adequate to describe the impacts on clouds of smoke particles (e.g., CNN, INP) from fire emissions in the range of representative environmental conditions necessary to advance science or modeling. We conclude by providing recommendations to the community that we believe will advance the science and understanding of the impact of fire smoke emissions on human and environmental health, as well as feedback with climate system.

I N Sokolik↗
NASA NTRS1992

Models of atmosphere-ecosystem-hydrology interactions: Approaches and testing

Interactions among the atmosphere, terrestrial ecosystems, and the hydrological cycle have been the subject of investigation for many years, although most of the research has had a regional focus. The topic is broad, including the effects of climate and hydrology on vegetation, the effects of vegetation on hydrology, the effects of the hydrological cycle on the atmosphere, and interactions of the cycles via material flux such as solutes and trace gases. The intent of this paper is to identify areas of critical uncertainty, discuss modeling approaches to resolving those problems, and then propose techniques for testing. I consider several interactions specifically to illustrate the range of problems. These areas are as follows: (1) cloud parameterizations and the land surface, (2) soil moisture, and (3) the terrestrial carbon cycle.

Schimel, David S.↗
DOE OSTI2023

The cost of direct air capture and storage can be reduced via strategic deployment but is unlikely to fall below stated cost targets

Carbon dioxide removal (CDR) is necessary to minimize the impact of climate change by tackling hard-toabate sectors and historical emissions. Direct air capture and storage (DACS) is an important CDR technology, but it remains unclear when and how DACS can be economically viable. Here, we use a bottom-up engineering-economic model together with top-down technological learning projections to calculate plant-level cost trajectories for four DACS technologies. Our analysis demonstrates that the costs of these technologies can plateau by 2050 at around $\$$100-600 t-CO 2 -1 mainly via capital cost reduction through aggressive deployment, but still exceed the optimistic targets defined by countries such as the US (i.e., $\$$100 t-CO 2 -1 ). A further analysis of existing policy mechanisms indicates that strong, project-catered policy support will be required to create market opportunities, accelerate DACS scale-up and lower the costs further. Our work suggests that strategic DACS deployment and operation must be coupled with strong policies to minimise the cost of DACS and maximise the opportunity to make a planet-scale climate impact.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Improving Text Classification with Large Language Model-Based Data Augmentation

Large Language Models (LLMs) such as ChatGPT possess advanced capabilities in understanding and generating text. These capabilities enable ChatGPT to create text based on specific instructions, which can serve as augmented data for text classification tasks. Previous studies have approached data augmentation (DA) by either rewriting the existing dataset with ChatGPT or generating entirely new data from scratch. However, it is unclear which method is better without comparing their effectiveness. This study investigates the application of both methods to two datasets: a general-topic dataset (Reuters news data) and a domain-specific dataset (Mitigation dataset). Our findings indicate that: 1. ChatGPT generated new data consistently enhanced model’s classification results for both datasets. 2. Generating new data generally outperforms rewriting existing data, though crafting the prompts carefully is crucial to extract the most valuable information from ChatGPT, particularly for domain-specific data. 3. The augmentation data size affects the effectiveness of DA; however, we observed a plateau after incorporating 10 samples. 4. Combining the rewritten sample with new generated sample can potentially further improve the model’s performance.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2020

A Physical Model of Moulin Evolution on the Greenland Ice Sheet

Nearly all proglacial water discharge from the Greenland Ice Sheet is routed englacially via moulins. Identification of these moulins in high-resolution imagery is a frequent topic of study, but the processes controlling how and where moulins form remain poorly understood. Because moulins may reasonably compose approximately 10-15% of the englacial-subglacial hydrologic system, the evolution and shape of moulins can alter both the timing and variability of meltwater inputs to the bed. This evolution can impact both the form of the subglacial hydrologic system and associated response of ice motion. Here, we develop a physical model of moulin formation and evolution to constrain the role of englacial processes in shaping the form and structure of the subglacial hydrologic system. Within this model, moulin geometry is controlled by a balance of viscous and elastic deformation and is dependent on that deformation, refreezing, and the dissipation of turbulent and sensible heat energy. All of which are dependent on the characteristics of the available supraglacial meltwater and the surrounding ice. We find moulin geometry is responsive to changes in these parameters over the course of hours to days, indicating that diurnal and multi-day variations in melt can substantially alter the geometry of a moulin and, consequently, the pressure-discharge relationship at the bed of the ice sheet. Therefore, there is no single moulin shape that can appropriately represent englacial storage across the Greenland Ice Sheet.

Andrews, Lauren C.↗
DOE OSTI2020

Evaporation Induced Entrainment of Contaminants from Evaporating and Burning Liquids.

This interim report details model development, theory, and a literature review focusing on the evaporation induced entrainment (sub-boiling) of contaminated liquids. Entrainment from a variety of sources is the topic of DOE Handbook 3010, and this report deals more broadly with fire related airborne sources of contaminants in hazardous operations. Relatively few studies have examined sub-boiling behavior in the past, however, it can be a phenomenon that presents a fire related risk under hazardous operations. Molecular dynamics simulations are used to infer the gaseous evolution of coordinated complexes, and a model for a water/plutonium/nitrate system is deduced from the simulation results by evaluating the statistical trends of the results. Questions remain as to the chemical reactivity and longevity of entrained species. A generalized computer model capability and simple analytical model assumptions are developed for predicting the results of these and other (boiling and solid entrainment) scenarios. Verification related predictions using these models are illustrated.

36 MATERIALS SCIENCE↗
DOE OSTI2025

REPACT tool: A Screening Model for Repurposing Natural Gas Pipelines

Presentation on Reuse of Existing Pipelines for Adapted Carbon Dioxide Transport (REPACT) Tool for the January 2025 FECM interagency CO2 Transport topic team Meeting. The tool enables the user to determine whether a pipeline that was originally deployed for natural gas transport can be reused for carbon dioxide (CO2) transport.

carbon dioxide (CO2)↗
NASA NTRS1985

Magnetospheric and ionospheric plasmas; Proceedings of the Ninth Symposium and Topical Meeting, Graz, Austria, June 25-July 7, 1984

Papers are presented on the physics of the magnetosphere-ionosphere connection, with attention given to theory and modeling, auroras, plasma dynamics and irregularities, waves and electron beams, the dynamics of the thermosphere, and planetary plasmas. Plasma circulation in the magnetosphere is also discussed; consideration is given to observations of magnetospheric convection from low altitudes, the structure and properties of the earth's plasmasphere, and the circulation of energetic ions of terrestrial origin in the magnetosphere.

Schmerling, E. R.↗
DOE OSTI2022

Quasi-Helmholtz decomposition, Gauss' laws and charge conservation for finite element particle-in-cell

Development of particle-in-cell (PIC) methods using finite element based methods (FEMs) have been a topic of renewed interest; this has largely been driven by (a) the ability of finite element methods to better model geometry, (b) better understanding of function spaces that are necessary to represent all Maxwell quantities, and (c) more recently, the fundamental rubrics that should be obeyed in space and time so as to satisfy Gauss' laws and the equation of continuity. In that vein, methods have been developed recently that satisfy these equations and are agnostic to time stepping methods. While this development is indeed a significant advance, it should be noted that implicit FEM transient solvers support an underlying null space that corresponds to a gradient of a scalar potential ∇Φ(r) (or t∇Φ(r) in the case of wave equation solvers). While explicit schemes do not suffer from this drawback, they are only conditionally stable with time step sizes that are mesh dependent and very small. Furthermore, the null space produces spurious charge that can corrupt the desired physics of a PIC simulation. The way to overcome this bottleneck, and indeed, satisfy all four Maxwell's equation is to use a quasi-Helmholtz formulation on a tessellation. In the re-formulation presented, we strictly satisfy the equation of continuity and Gauss' laws for both the electric and magnetic flux densities. Results illustrating the efficacy of this scheme will be demonstrated by analyzing non-neutral beams with space-charge and the adiabatic expansion of a neutral plasma with realistic parameters (Debye length and real mass ratios).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Overview of the physics basis for the ARC fusion power plant

Commonwealth Fusion Systems plans to build ARC as the first fusion power plant at a site in Chesterfield County, Virginia, USA by the early 2030s. We present an overview of analysis comprising the physics basis of the ARC V3A design, a high-magnetic-field tokamak with 𝐵 0 =11.4 T, 𝐼 𝑝 =12.0 MA, 𝑅 0 =4.62 m, 𝑎 =1.18 m. ARC V3A is designed to produce 𝑃 𝑓⁡𝑢⁢𝑠 ≈1.13 GW DT fusion power and deliver ⩾400 MW net electric power to the grid. This overview includes quantitative analysis of fundamental issues for design of and operational plasma scenarios for a tokamak power plant, and lays out the design targets and strategic choices for ARC, including empirical fusion performance projections, assessment of H-mode access, ion cyclotron resonance heating simulations, alpha particle physics and time-dependent full-pulse simulations. This is complemented by topical papers on fusion performance and transport, disruption physics, boundary physics and magnetohydrodynamic stability. Critically, these studies identify key model uncertainties and physics risks to be retired through SPARC operation. Due to the modular nature of ARC, early results from SPARC can be incorporated into the design of the first ARC as well as subsequent replacements of the ARC vacuum vessel.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Hybrid renewable energy systems

In the pursuit of ecologically sustainable and resilient energy systems, increasingly more attention is being devoted to a diversity of energy generation and storage methods. As the landscape of generation technology gains nuance and complexity, a wide-ranging set of technical questions has emerged, touching on topics that range from control and optimization of hybrid systems to finance and economic viability to multi-fidelity modeling and scientific machine learning. In the context of this special issue, hybrid renewable energy systems are any systems that consider the combined dynamics of more than one form of generation, storage, or grid subsystem. Research endeavors have delved into improving the flexibility of energy systems by utilizing existing resources, introducing novel operational strategies, deploying enhanced renewable forecasts, and exploring emerging technologies. In conclusion, the interconnection among various sectors has garnered heightened attention, not only due to the provision of additional tradable energy products but also for furnishing flexible headroom to system operators.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

A Review of Recent and Emerging Machine Learning Applications for Climate Variability and Weather Phenomena

Abstract Climate variability and weather phenomena can cause extremes and pose significant risk to society and ecosystems, making continued advances in our physical understanding of such events of utmost importance for regional and global security. Advances in machine learning (ML) have been leveraged for applications in climate variability and weather, empowering scientists to approach questions using big data in new ways. Growing interest across the scientific community in these areas has motivated coordination between the physical and computer science disciplines to further advance the state of the science and tackle pressing challenges. During a recently held workshop that had participants across academia, private industry, and research laboratories, it became clear that a comprehensive review of recent and emerging ML applications for climate variability and weather phenomena that can cause extremes was needed. This article aims to fulfill this need by discussing recent advances, challenges, and research priorities in the following topics: sources of predictability for modes of climate variability, feature detection, extreme weather and climate prediction and precursors, observation–model integration, downscaling, and bias correction. This article provides a review for domain scientists seeking to incorporate ML into their research. It also provides a review for those with some ML experience seeking to broaden their knowledge of ML applications for climate variability and weather.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Ground Source Heat Pump Screening Tool and Related Resources

This archive contains both a link to Oak Ridge National Laboratory's Ground Source Heat Pump (GSHP) Screening Tool and related resources documenting its development, technical features, and applications. The web-based screening tool is a techno-economic analysis resource designed to evaluate the feasibility, costs, and benefits of implementing GSHP systems in buildings across various U.S. climate zones. It is intended for use by building owners, HVAC system designers, and installers to support decision-making in residential and commercial applications, incorporating advanced modeling capabilities such as ground heat exchanger design. The included resources detail the tool's creation and use, covering topics such as innovative ground heat exchanger design methodologies, the development of an open library of g-functions for borehole configurations, and studies on GSHP performance and economic viability in retrofitting single-family homes.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

CEA/DAM - CEA/DEN - LANL - IAEA - IPHC Collaboration Meeting on Nuclear Data, Nuclear Reaction Theories, and Machine Learning (Summary Report)

Dupuis hosted our biennial CEA/NNSA collaboration meeting, and Kawano and Lovell of LANL and Tamagno of CEA/DEN (Cadarache) visited CEA/DAM to discuss current issues and further developments in nuclear reaction modeling, nuclear data evaluation, and relevant programs of modern computer science, especially the machine learning technology. The discussions included topics of our common interest such as neutron inelastic scattering, capture, and fission, with particular emphasis on the actinide nuclear data evaluations. We report briefly the summary of our discussions. We also had a half-day video meeting with Capote of IAEA and Kerveno of IPHC to discuss nuclear reactions on actinides.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Circularity Futures Workshop Series: Summary Report

The aim of this report is to synthesize key feedback received from the three-part Circularity Futures workshop series held in Spring 2024. The workshop series was conducted by the National Renewable Energy Laboratory (NREL) on behalf of U.S. Department of Energy, Office Energy Efficiency and Renewable Energy (EERE), and was broken into three workshops: Workshop 1 - Circularity Analysis Needs and Priorities; Workshop 2 - Circularity Metrics and Indicators; and Workshop 3 - Circularity Data. Together, the workshops focused on identifying the existing priorities and gaps in the circularity modeling space, understanding different stakeholders' use and interpretation of circularity metrics and indicators, identifying common data gaps and data quality challenges, and assessing the robustness of available solutions. The workshop series brought a diverse group of stakeholders - including representatives from U.S. government offices, national labs, nonprofit organizations, industry, and academia - to collect first-hand feedback on needs, priorities, challenges and opportunities in the circularity modeling and analysis space. The workshop discussions highlighted numerous common needs, priorities and challenges among the interviewed groups. Several topics were frequently discussed, including: 1) Circularity as a pathway for sustainable economic growth: While circularity is generally defined in terms of resource conservation and reducing wasteful disposal of materials, participants agreed that circular strategies should serve broader economic, environmental, and social goals. It is therefore crucial for circularity analysis to look beyond waste reduction and instead evaluate a variety of impact metrics such as cost savings, job creation, air quality, and pollutant emissions. Mutli-criteria decision-making frameworks may be useful for making sense of disparate metrics and evaluating tradeoffs between impact categories.; 2) Economic and social factors are not well understood: Underdevelopment of existing end-of-life (EOL) management infrastructure, inconsistent standardization codes and policy space in reusing recycled content, and suboptimal collection and sorting strategies collectively contribute to uncertainty about the economic potential of circular pathways. The latter observation is consistent among all technologies but more emphasized for renewable energy systems. Social impacts of circularity practices are less understood and less researched than other sustainability aspects.; 3) Inconsistent methods for assessing emerging technologies: LCA and TEA results vary widely depending on the assumptions made with regards to market adoption of new technologies. Emerging technologies suffer limited availability of data needed to conduct a robust circularity analysis. Yet, understanding projected impacts of proposed nascent technology is a key need for different stakeholder groups.; and 4) Lack of temporally and geospatially explicit data: There is a need for open data that represents variations in circularity technologies over time and location. The lack thereof leads to aggregated and potentially misrepresented results in circularity analysis. Sensitivity analyses should be included to verify whether options perceived as more sustainable align with real-world practices.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1980

Preliminary development of digital signal processing in microwave radiometers

Topics covered involve a number of closely related tasks including: the development of several control loop and dynamic noise model computer programs for simulating microwave radiometer measurements; computer modeling of an existing stepped frequency radiometer in an effort to determine its optimum operational characteristics; investigation of the classical second order analog control loop to determine its ability to reduce the estimation error in a microwave radiometer; investigation of several digital signal processing unit designs; initiation of efforts to develop required hardware and software for implementation of the digital signal processing unit; and investigation of the general characteristics and peculiarities of digital processing noiselike microwave radiometer signals.

Stanley, W. D.↗
NASA NTRS1985

International Symposium on Remote Sensing of Environment, 18th, Paris, France, October 1-5, 1984, Proceedings. Volumes 1, 2, & 3

Papers are presented on the applications of satellite technology, such as monitoring of agriculture, appraising of natural resources, and studying disasters. Topics discussed include, advances in remote sensing processes, multisensor imaging, and mapping. Extensive consideration is given to the processing, modeling, integrating, and evaluating of satellite data.

Source record↗