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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

SIVB's 2024 In Vitro Biology Meeting Proceedings

SIVB's 2024 World Congress on In Vitro Biology took place in Saint Louis, Missouri, from June 8th to 12th, 2024. The conference featured renowned speakers from academic and non-academic institutions who will present recent advancements in critical areas like plant transformation, genome editing, synthetic biology, advanced breeding technologies, cellular agriculture, future food sources, chromosome engineering, epigenetics, artificial intelligence, and machine learning. The Society for In Vitro Biology (SIVB) has always considered the education and professional development of young researchers as an integral component of its mission. The 2024 World Congress program, along with SIVB’s student initiatives, was customized to foster scientific growth and professional development among students and young scientists empowering them in their professional journeys. The recording of the DOE supported "Single Cell RNA Sequencing" workshop was made publicly available at https://youtu.be/A0UnuYwefwg for easy retrieval and reference of all information shared during the live event, thereby increasing accessibility and knowledge transfer. Their are 14 articles in the proceedings and the full list of files is located at https://link.springer.com/journal/11626/volumes-and-issues/60-1/supplement.

10 SYNTHETIC FUELS↗
NASA NTRS1956

The Compressible Laminar Boundary Layer with Heat Transfer and Arbitrary Pressure Gradient

An approximate method for the calculation of the compressible laminar boundary layer with heat transfer and arbitrary pressure gradient, based on Thwaites' correlation concept, is presented. With the definition of dimensionless shear and heat-transfer parameters and an assumed correlation of these parameters in terms of a momentum parameter, a complete system of relations for calculating skin friction and heat transfer results. Knowledge of velocity or temperature profiles is not necessary in using this calculation method. When the method is applied to a convergent-divergent, axially symmetric rocket nozzle, it shows that high rates of heat transfer are obtained at the initial stagnation point and at the throat of the nozzle. Also indicated are negative displacement thicknesses in the convergent portion of the nozzle; these occur because of the high density within the lower portions of the cooled boundary layer. (author)

Cohen, Clarence B↗
NASA NTRS1975

Relationships among classes of self-oscillating transistor parallel inverters

It recently has been shown in the literature that many dc-to-square-wave parallel inverters which are widely used in power-conditioning applications can be grouped into one of two families. Each family is characterized by an equivalent RLC network. Based on this approach, a classification procedure is presented for self-oscillating parallel inverters which makes evident natural relationships which exist between various inverter configurations. By utilizing concepts from the basic theory of negative resistance oscillators and the principle of duality as applied to nonlinear networks, a chain of relationships is established which enables a methodical transfer of knowledge gained about one family of inverters to any of the other families in the classification array.

Wilson, T. G.↗
DOE OSTI2025

All Kitted Out

The Hydropower Knowledge Sharing and Succession Planning Toolkit, created by the National Renewable Energy Laboratory (NREL) in collaboration with the U.S. Department of Energy’s Water Power Technologies Office (WPTO), can help your organization effectively plan for workforce changes and share knowledge across employees. By proactively implementing knowledge sharing and succession planning strategies, hydropower organizations can safeguard institutional knowledge, enhance workforce resilience, and ensure long-term operational stability in an evolving industry landscape.

13 HYDRO ENERGY↗
DOE OSTI2025

Leveraging transfer learning and leaf spectroscopy for leaf trait prediction with broad spatial, species, and temporal applicability

Accurate and reliable prediction of leaf traits is crucial for understanding plant adaptations to environmental variation, monitoring terrestrial ecosystems, and enhancing comprehension of functional diversity and ecosystem functioning. Currently, various approaches (e.g., statistical, physical models) have been developed to estimate leaf traits through hyperspectral remote sensing and leaf spectroscopy. However, the absence of high-performing, transferable, and stable models across various domains of space, plant functional types (PFTs) and seasons hinder our ability to quantify and comprehend spatiotemporal variations in leaf traits. This study proposes robust and highly transferable models for better predicting leaf traits with hyperspectral reflectance. Initially, three datasets were assembled, pairing common leaf traits — chlorophyll (Chla+b), carotenoids (Ccar), leaf mass per area (LAM), equivalent water thickness (EWT) — with leaf spectra measurements collected across diverse geographic locations in the U.S. and Europe, PFTs, and seasons. Measurements were acquired using spectroradiometers (e.g., ASD FieldSpec 3/4/Pro and SVC HR-1024i) with integrating spheres, leaf clips, and contact probes. Here, we then developed transfer learning-based hybrid models that incorporated the domain knowledge of radiative transfer models (RTMs) through pretraining processes and were well-constrained by fine-tuning with field measurements. Through comparison with other state-of-the-art statistical models, including partial-least squares regression (PLSR) and Gaussian Process Regression (GPR), as well as pure physical models, we found that the proposed transfer learning models achieved better predictive performance and higher transferability. Specifically, compared to other statistical models and pure RTMs, the transfer learning model exhibited higher coefficient of determination (R 2 ) values with range of 0.01 to 0.79, lower normalized root mean square error (NRMSE) with range of 0.06 % to 33.25 % in model performance. Additionally, the models exhibited improved transferability, with higher R 2 values range from 0.04 to 0.32, lower NRMSE range from 0.08 % to 30.81 %. The findings underscore that transfer learning models through integrating domain knowledge from RTMs and limited observations, can harness the advantages of both RTMs and statistical models and serve as a promising approach for effectively predicting leaf traits.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1979

Spinoff 1979

Technology is knowledge, the technical "know-how" employed by a society to produce things that improve the quality of human life. Like other forms of knowledge, it is transferable; once developed, technology can be applied to uses different-and often remote-from the original application. Thus, the technology that NASA has developed in more than two decades of space and aeronautical research constitutes a valuable national resource, a bank of knowledge available for secondary utilization, or "spinoff." NASA mainline programs, by their challenging nature, are particularly demanding of technological advance; meeting their goals has forced extraordinary advancements in virtually every scientific and technological discipline. For that reason, the wealth of aerospace-generated knowledge available for transfer is exceptionally diverse, and much of it is readily applicable to secondary use over a broad spectrum of public needs and conveniences. Through its Congressionally mandated Technology Utilization Program, NASA seeks to promote wider use of this technological resource. The program provides a link between the technology bank and those in either the private or public sectors who might be able to re-use the technology productively. Its aim is to accelerate the transfer process, to bring to the marketplace sooner those spinoffs which might eventually occur in the normal course of events, and to gain thereby more immediate economic benefit in terms of new products and new jobs. The program has been remarkably successful. Since its inception 17 years ago, thousands of spinoff products and processes have emerged. Some of these innovations bring only moderate increments of economic gain or lifestyle improvement, but many others amount to significant public benefits, with economic values often running to millions of dollars. Collectively, spinoffs provide a substantial bonus return on the funds invested in aerospace research. This publication is intended to increase public awareness of the resource that is NASA's technology bank and its potential for further public benefit. It is devoted primarily to the NASA technology transfer process, but in the interests of perspective it also describes related areas of NASA endeavor. Section 1 consists of a resume of NASA's current mainline programs. These programs are producing direct public benefit through direct application of technology; at the same time, they are contributing to indirect benefit-spinoff-by generating new technology which may find secondary application in the future. Section 2 is the focal point of this volume. It contains a representative sampling of spinoff products and processes employed in various avenues of everyday life, and it describes briefly the NASA technology from which these transfers derived. Section 3 details the mechanisms of the technology transfer process, including the means by which NASA seeks to stimulate technology utilization. Also described are NASA's activities in a related area of technology transfer: provision of assistance to agencies interested in exploiting the benefit potential of satellite remote sensing technology.

Haggerty, James J.↗
NASA NTRS1937

Energy Loss, Velocity Distribution, and Temperature Distribution for a Baffled Cylinder Model, Special Report

In the design of a cowling a certain pressure drop across the cylinders of a radial air-cooled engine is made available. Baffles are designed to make use of this available pressure drop for cooling. The problem of cooling an air-cooled engine cylinder has been treated, for the most part, from considerations of a large heat-transfer coefficient. The knowledge of the precise cylinder characteristics that give a maximum heat-transfer coefficient should be the first consideration. The next problem is to distribute this ability to cool so that the cylinder cools uniformly. This report takes up the problem of the design of a baffle for a model cylinder. A study has been made of the important principles involved in the operation of a baffle for an engine cylinder and shows that the cooling can be improved 20% by using a correctly designed baffle. Such a gain is as effective in cooling the cylinder with the improved baffle as a 65% increase in pressure drop across the standard baffle and fin tips.

Brevoort, Maurice J.↗
NASA NTRS1974

Model wall and recovery temperature effects on experimental heat transfer data analysis

Basic analytical procedures are used to illustrate, both qualitatively and quantitatively, the relative impact upon heat transfer data analysis of certain factors which may affect the accuracy of experimental heat transfer data. Inaccurate knowledge of adiabatic wall conditions results in a corresponding inaccuracy in the measured heat transfer coefficient. The magnitude of the resulting error is extreme for data obtained at wall temperatures approaching the adiabatic condition. High model wall temperatures and wall temperature gradients affect the level and distribution of heat transfer to an experimental model. The significance of each of these factors is examined and its impact upon heat transfer data analysis is assessed.

Throckmorton, D. A.↗
DOE OSTI2025

Topography restoration in white-light interferometry using an instrument transfer function evaluated with binary pseudo-random arrays

Accurate knowledge of the instrument transfer function (ITF) is vital for topography measurements using white-light interferometry (WLI). To this end, we derive a complete set of analytical expressions for the power spectral density (PSD) of a discretely sampled binary pseudo-random array (BPRA) as a theoretical benchmark. We then determine the ITF by comparing this theoretical PSD with the measured PSD of the BPRA. For the Zygo ZeGage Pro HR with a objective, the determined ITF closely matches the nominal modulation transfer function (MTF). Accordingly, we integrate the nominal MTF into Fourier-domain restoration filters and apply them to practical WLI topography data, yielding restored topographies that show improved agreement with atomic force microscopy measurements. Overall, our integrated BPRA-based ITF measurement and filtering methodology offers a robust yet practical means of characterizing WLI performance and enhancing the accuracy of surface measurements.

Hirose, Shigenobu [Japan Agency for Marine Earth S↗
DOE OSTI2025

Round Robin Measurements of Molten Salt Properties for LiF-NaF-KF (FLiNaK) and NaCl-KCl Mixtures

The development, operation, and regulation of nuclear reactors that utilize molten salts as fuel or as heat transfer media require knowledge of the thermal properties of the salt systems and quantification of the corresponding uncertainties. Knowledge of molten salt properties is also necessary for applications in material synthesis, processing, separations, solar thermal power generation, and energy storage. A round robin was conducted with national laboratory and university participants from twenty-one laboratories in five countries to compare property measurements, to better understand uncertainties, and to identify possible best practices. Two salt mixtures, each from a common batch, were distributed to participants for evaluation: equimolar NaCl-KCl and 45.0LiF-13.7NaF-41.3KF mol % (FLiNaK). Measurements were performed to determine the major constituent composition, oxygen content, density, thermal expansivity, melting point, and thermal conductivity. Error analysis was performed on each measurement for uncertainty quantification for each type of property that was explored. Finally, the resulting discussion of the methodologies used in this work is meant to lay the groundwork for the development of standard methods and reference materials for future high-temperature property measurements on halide melts.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Rapid Adaptation of Chemical Named Entity Recognition Using Few-Shot Learning and LLM Distillation

Named entity recognition (NER) has been widely used in chemical text mining for the automatic identification and extraction of chemical entities. However, existing chemical NER systems primarily focus on scenarios with abundant training data, requiring significant human effort on annotations. This poses challenges for applications in the chemical field, such as catalysis, where many advancements have traditionally relied on trial-and-error investigations and incremental adjustment of variables. This hinders catalysis science and technology progress in addressing emerging energy and environmental crises. In this work, we propose a few-shot NER model that can quickly adapt to extract new types of chemical entities by using only a limited number of annotated examples. Our model employs a metric-learning approach to transfer entity similarity knowledge from high-resource chemical domains (with abundant annotations) to enable effective entity recognition in low-resource specialized domains (limited annotation). We validate the effectiveness of our model on a few-shot chemical NER benchmark built based on six existing chemical NER data sets. Experiments show that the proposed few-shot NER model can achieve reasonable performance with only 5 examples per entity type and shows consistent improvement as the number of examples increases. Furthermore, we demonstrate how the proposed model can be trained with large language model (LLM) annotated data, opening a new pathway for rapid adaptation of NER systems. Furthermore, our approach leverages the knowledge broadness of large language models for chemistry while distilling this knowledge into a lightweight model suitable for efficient and in-house use.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Integrating the Mobility Energy Productivity Metric Into the Delaware Department of Transportation Statewide Model

The Mobility Energy Productivity (MEP) metric quantifies the quality of mobility at a given location and evaluates how changes in the transportation system impact mobility over time, such as through infrastructure investments. This study demonstrates the integration of the MEP metric into the Delaware Department of Transportation's (DelDOT's) transportation planning process by utilizing data from its statewide travel demand model. Specifically, the study assesses MEP for the 2020 baseline conditions and three alternative scenarios - 2030, Churchman, and Old Orchard - across multiple travel modes, including driving, walking, biking, and transit. The findings highlight that mobility and accessibility in Delaware are primarily supported by the driving mode, while transit services remain relatively limited, often ranking below biking and walking in many areas. In the 2030 scenario, where network operations and opportunities expand as projected, overall statewide accessibility declines, although Kent and Sussex counties experience improvements. The results from the Churchman and Old Orchard scenarios indicate that local network enhancements can positively influence accessibility, though primarily at a localized level, demonstrating MEP's capability to capture regional accessibility changes. Further, the National Renewable Energy Laboratory team successfully transferred MEP operational knowledge to the DelDOT team through dockerization, enabling DelDOT to independently run MEP for various scenarios of interest. Integrating MEP into DelDOT's planning framework supports future project evaluations and decision-making by incorporating access to opportunities as a key dimension of transportation system assessment.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1982

Present challenges of research and technology politics

Research and technology in Germany are discussed. The rapid transfer of scientific knowledge and techniques from the laboratory to the manufacturing and industrial communities is identified as a priority. It is recommended that the government give maximum support to the aviation and space flight industries.

Bulow, A. V.↗
NASA NTRS1977

Spinoff 1977

The National Aeronautics & Space Administration has many missions but they can all be reduced to a common denominator: to explore Earth and its surroundings, conduct aeronautical research, and put the results to work for the benefit of mankind. At times the benefit may be dimly perceived. Take, for instance, last year's monumental triumph of exploration, the landing of robot spacecraft on Mars. How, some ask, does probing a neighbor planet improve the lot of Earth's people? In two ways: scientific gain and technological advancement. Though perhaps little understood, they are concrete benefits, assets as tangible as sunshine, more valuable than gold. Technological advancement, on the other hand, offers equally important but more immediate returns. Technology is science applied. It is the ability of a society to make things that improve the quality of human existence. It is compounded of intellect and skill, which draw upon the scientific base to bring forth new ideas, inventions, materials and processes. It is, in a word, knowledge. It builds like an inverted pyramid, each level broader than the one . before as successive generations contribute to the cumulative lore. Knowledge is readily transferable. If you build a better mousetrap, you may acquire experience in the course of the project that can be applied to a need totally unrelated to mouse-traping. This transfer process has been going on since the dawn of technology. In the last two decades it has accelerated enormously, spurred by the immense flow of aerospace-stimulated technology. There have been literally thousands of spinoffs, new products and processes that owe their origins to aerospace research. Collectively, they add up to significant gain in terms of personal convenience, human welfare, industrial efficiency, and economic value.

Haggerty, James J.↗
DOE OSTI2026

A transfer learning approach to energy-efficient control of small and medium-sized commercial buildings

Model-free reinforcement learning (RL) provides a data-driven and adaptive approach to optimize building energy use while satisfying occupant comfort. This powerful tool does not need any prior knowledge about the environment and system it is optimizing and can adapt its policy based on the changes in captures. Like any other data-driven tool, it faces high training costs due to the extensive agent-environment interactions required to capture long-term building dynamics and user comfort. Transfer learning, particularly policy distillation, offers a promising way to accelerate training by leveraging pretrained RL agents in different building and system types. Here, this study investigates online student distillation, in which the student model updates its neural network weights using outputs from teacher models. The work introduces a student distillation strategy designed for efficient knowledge transfer, along with a teacher selection method that ensures high-quality guidance. The approach is validated using a highly calibrated whole building energy model for a small/medium commercial building test facility. Results show substantial reductions in training time and data requirements while surpassing the performance of ASHRAE Guideline 36, an advanced rule-based control strategy. The distilled RL model required 45% less data and achieved 20% higher cumulative rewards than a state-of-the-art RL model, with faster convergence and lower energy consumption. These outcomes demonstrate that effective transfer learning enables a scalable and data-efficient energy management solution for commercial buildings.

ASHRAE guideline 36↗
DOE OSTI2025

A roadmap to understanding and anticipating microbial gene transfer in soil communities

Engineered microbes are being programmed using synthetic DNA for applications in soil to overcome global challenges related to climate change, energy, food security, and pollution. However, we cannot yet predict gene transfer processes in soil to assess the frequency of unintentional transfer of engineered DNA to environmental microbes when applying synthetic biology technologies at scale. This challenge exists because of the complex and heterogeneous characteristics of soils, which contribute to the fitness and transport of cells and the exchange of genetic material within communities. Here, we describe knowledge gaps about gene transfer across soil microbiomes. Here, we propose strategies to improve our understanding of gene transfer across soil communities, highlight the need to benchmark the performance of biocontainment measures in situ, and discuss responsibly engaging community stakeholders. We highlight opportunities to address knowledge gaps, such as creating a set of soil standards for studying gene transfer across diverse soil types and measuring gene transfer host range across microbiomes using emerging technologies. By comparing gene transfer rates, host range, and persistence of engineered microbes across different soils, we posit that community-scale, environment-specific models can be built that anticipate biotechnology risks. Such studies will enable the design of safer biotechnologies that allow us to realize the benefits of synthetic biology and mitigate risks associated with the release of such technologies.

bioccontainment↗