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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Microwave radiative transfer through horizontally inhomogeneous precipitating clouds

Recent advances in cloud microphysical models have led to realistic three-dimensional distributions of cloud constituents. Radiative transfer schemes can make use of this detailed knowledge in order to study the effects of horizontal as well as vertical inhomogeneities within clouds. This study looks specifically at the differences between three-dimensional radiative transfer results and those obtained by plane parallel, independent pixel approximations in the microwave spectrum. A three-dimensional discrete ordinates method as well as a backward Monte Carlo method are used to calculate realistic radiances emerging from the cloud. Analyses between these models and independent pixel approximations reveal that plane parallel approximations introduce two distinct types of errors. The first error is physical in nature and is related to the fact that plane parallel approximations do not allow energy to leak out of dense areas into surrouding areas. In general, it was found that these errors are quite small for emission-dominated frequencies (37 GHz and lower) and that physical errors are highly pronounced only at scattering frequencies (85 GHz) where large deviations and biases up to 8 K averaged over the entire cloud were found. The second error is more geometric in nature and is related to the fact that plane parallel approximations cannot accommodate physical boundaries in the horizontal dimension for off-nadir viewing angles. The geometric errors were comparable in magnitude for all frequencies. Their magnitude, however, depends on a number of factors including the scheme used to deal with the edge, the nature of the surface, and the viewing angle.

Roberti, Laura↗
NASA NTRS1990

Mechanical system diagnostics using vibration testing techniques

The 'Cepstrum' technique of vibration-path identification allows the recovery of the transfer function of a system with little knowledge as to its excitation force, by means of a mathematical manipulation of the system output in conjunction with subtraction of part of the output and suitable signal processing. An experimental program has been conducted to evaluate the usefulness of this technique in the cases of simple, cantilever-beam and free-free plate structures as well as in that of a complex mechanical system. On the basis of the transfer functions thus recovered, it was possible to evaluate the shifts in the resonance frequencies of a structure due to the presence of defects.

Mcleod, Catherine D.↗
NASA NTRS1992

NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 23: Information technology and aerospace knowledge diffusion: Exploring the intermediary-end user interface in a policy framework

Federal attempts to stimulate technological innovation have been unsuccessful because of the application of an inappropriate policy framework that lacks conceptual and empirical knowledge of the process of technological innovation and fails to acknowledge the relationship between knowled reproduction, transfer, and use as equally important components of the process of knowledge diffusion. It is argued that the potential contributions of high-speed computing and networking systems will be diminished unless empirically derived knowledge about the information-seeking behavior of the members of the social system is incorporated into a new policy framework. Findings from the NASA/DoD Aerospace Knowledge Diffusion Research Project are presented in support of this assertion.

Pinelli, Thomas E.↗
DOE OSTI2024

Investigating explainable transfer learning for battery lifetime prediction under state transitions

Battery lifetime prediction at early cycles is crucial for researchers and manufacturers to examine product quality and promote technology development. Machine learning has been widely utilized to construct data-driven solutions for high-accuracy predictions. However, the internal mechanisms of batteries are sensitive to many factors, such as charging/discharging protocols, manufacturing/storage conditions, and usage patterns. These factors will induce state transitions, thereby decreasing the prediction accuracy of data-driven approaches. Transfer learning is a promising technique that overcomes this difficulty and achieves accurate predictions by jointly utilizing information from various sources. Hence, we develop two transfer learning methods, Bayesian Model Fusion and Weighted Orthogonal Matching Pursuit, to strategically combine prior knowledge with limited information from the target dataset to achieve superior prediction performance. From our results, our transfer learning methods reduce root-mean-squared error by 41% through adapting to the target domain. Furthermore, the transfer learning strategies identify the variations of impactful features across different sets of batteries and therefore disentangle the battery degradation mechanisms and the root cause of state transitions from the perspective of data mining. These findings suggest that the transfer learning strategies proposed in our work are capable of acquiring knowledge across multiple data sources for solving specialized issues.

25 ENERGY STORAGE↗
DOE OSTI2025

Impacts of Biomass Feedstock Pre-Processing on Heat and Mass Transfer During Pyrolysis Using X-Ray Computed Tomography and Multiscale Modeling

Knowledge of the transport properties of biomass particles such as porosity, tortuosity, and permeability is paramount for high-fidelity modeling of biomass pyrolysis due to the heat and mass transfer limitations imposed by particle microstructure. X-ray computed tomography (XCT) is a non-destructive imaging method that enables full 3D reconstructions of the biomass particle microstructure with high resolution, permitting direct calculation of porosity, tortuosity, and permeability from real particle geometries. In this study, XCT imaging revealed the 3D microstructures of particles and chars from pyrolytic conversion of cylindrically cut or milled/pelletized loblolly pine samples. The porosity, tortuosity, and permeability were calculated directly from the XCT geometries via open-source microstructural analysis tool MATBOX+TauFactor (https://github.com/NREL/MATBOX_Microstructure_analysis_toolbox) and computational fluid dynamics (CFD) simulations using our solver, Mesoflow (https://github.com/NREL/mesoflow). These properties were used in a reactor scale model developed in COMSOL of the single particle reactor at NREL to investigate the impact of feedstock pre-processing on biomass conversion during pyrolysis with rigorous experimental validation.

biomass↗
NASA NTRSDate not supplied

Harnessing Artificial Intelligence for Medical Diagnosis and Treatment During Space Exploration Missions

From May 8th to June 9th, 2023, I had the opportunity to participate in an experiential learning experience at Johnson Space Center in Houston, TX with Exploration Medical Capability (ExMC), an element of the NASA Human Research Program. During this research experience, I was not only able to work on the above titled research project, but also gain an immense exposure to the field of aerospace medicine, make numerous connections within the field, tour NASA facilities, as well as travel to the Aerospace Medical Association Annual Conference (AsMA) in New Orleans. To briefly introduce my project, it is well understood that the medical capabilities available to crew medical officers (CMOs) on the International Space Station will be different than the capabilities available and needed during deep space exploration missions to the Moon, Mars, and beyond. Ground support is particularly limited due to distance, communication delays (or lack of communication), and lack of resupply. Therefore, to support medical care by CMOs on these missions, robust clinical decision support systems (CDSSs) must be designed. The recent publication and public launch of generative artificial intelligence (AI) tools based upon large language models (LLM) such as ChatGPT provides the opportunity to create a smart assistant for onboard triage, diagnosis, and treatment of medical conditions. Ultimately, the overall purpose of the project was to research what AI tools currently exist or are in development, and to see how they might be implemented onboard during exploration class spaceflights of the future. The ExMC element is actively developing several tools to be used in preparation for and during deep space exploration missions. One of those tools, known as IMPACT, is a probabilistic risk assessment model which can be used to propose a desired medical system (based on mass and volume) and suggest the clinical outcomes likely to occur for a design reference mission (DRM). The group recently presented the IMPACT model and a DRM of interest titled “Modified Long Duration Lunar Orbital and Lunar Surface” (mLDLOLS) at the recent AsMA conference. The mLDLOLS mock mission is a 9 month and 6-day deep space exploration mission consisting of time in Moon’s orbit (3 months on the Gateway space station), on the lunar surface (3 months within habitat), and another 3 months on Gateway before return to Earth. For this DRM, IMPACT ultimately outlined a preferred medical system that was then associated with medical conditions considered to be most likely based on frequency, most likely to cause astronaut task time loss (TTL), most likely to cause return to definitive care (RTDC), and most likely cause loss of crew life (LOCL). IMPACT also highlighted the medical capabilities/skills that would be required to care for those medical conditions, such as performing a history of present illness or musculoskeletal exam with ultrasound. The primary objective of the project was to perform a survey of the AI tools and systems applicable to the conditions outlined for the proposed mLDLOLS mission. Using PubMed (including most relevant MeSH terms) and Google Scholar, we then created a robust annotated bibliography organized by condition. The 56-page and over 500 reference annotated bibliography was subsequently used to create a review outline that would become the basis for drafting of a future publication. For the review outline, we took those medical conditions researched within the annotated bibliography (condition-based approach) and deployed a systems-based approach, combining those medical conditions and related tools into ten categories. These categories included general/all-purpose CDSSs, tools to diagnose or manage respiratory, dermatologic, neurologic, auditory and vestibular, ophthalmic, musculoskeletal, infection-associated, and gynecologic conditions, as well as tools that could be deployed in the setting of trauma/emergency. With the completion of the 30-page outline, we then began drafting the review paper. To conclude the research experience, I presented the findings from our survey to the ExMC Clinical and Science team. With these objectives, I ultimately learned about the number of AI tools that exist today to assist medical professionals with the triage, diagnosis, and management of several medical conditions. These tools can span from chatbot assistants to help triage knee pain to vision transformer models that can identify ophthalmic conditions based on ocular surface images captured with a cell phone. We also highlighted the current gaps that exist in the literature alongside the advancements that are needed to make the desired CDSS for deep space exploration missions. With this experience, I certainly confirmed an existing career goal and identified several additional skills needed to become an aerospace medical doctor including knowledge of critical care in an extreme medicine setting, aerospace engineering and human integration systems, artificial intelligence, machine learning, and risk models. I also identified numerous transferable skills for this career goal including the basic knowledge of medicine (MD), deployment of the scientific method for critical thought about new scientific questions (PhD), review of published literature, including creating an annotated bibliography (PhD), as well as detailed scientific writing (PhD). The results of my research will likely guide the design of an all-encompassing onboard medical assistant for use during deep space exploration missions of the future. I plan on sharing the outcomes from this experience with my peers at a student seminar in the Fall semester on August 30th. During the seminar, I will detail the project, my experience at NASA and AsMA, as well as offer best practice guidelines for students entertaining similar experiences or careers. In conclusion, I would like to thank the WVU School of Medicine, Research and Graduate Education office, as well as NASA ExMC for the unwavering support of this life-changing experience.

Ryan A. Lacinski↗
NASA NTRS1993

NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 35: The US government technical report and aerospace knowledge diffusion: Results of an on-going investigation

The U.S. government technical report is a primary means by which the results of federally funded research and development (R&D) are transferred to the U.S. aerospace industry. However, little is known about this information product in terms of its actual use, importance, and value in the transfer of federally funded (U.S.) R&D. To help establish a body of knowledge, the U.S. government technical report is being investigated as part of the NASA/DOD Aerospace Knowledge Diffusion Research Project. In this paper, we summarize the literature on technical reports and provide a model that depicts the transfer of federally funded aerospace R&D via the U.S. government technical report. We present results from two surveys (one of five studies) of our investigation of aerospace knowledge diffusion vis-a-vis the U.S. government technical report and close with a brief overview of on-going research into the use of the U.S. government technical report as a rhetorical device for transferring federally funded aerospace R&D.

Pinelli, Thomas E.↗
DOE OSTI2025

Impact of Domain Knowledge on the Property Prediction of Specialized Machine Learning Models

Developing transferable machine learning models is trending in data-driven materials research. However, how to apply such models to a specific research domain remains unclear. Here, in this work, we choose high-entropy materials as a platform with a specialized data set containing 145,323 DFT-relaxed materials. This data set is used to explore the role of domain-specific knowledge in training effective models. Our tests with three representative graph neural network architectures indicate the model complexity has much smaller influence on performance than the data itself. Specifically, the consideration of low-energy atomic ordering, structures with diverse elemental coverage, and high-order interactions significantly influences the model performance. We also find that domain knowledge-driven sampling can greatly enhance unsupervised learning techniques. This research highlights that developing specialized data sets is more beneficial than further complicating deep learning architectures. Additionally, physics-inspired sampling algorithms are crucially needed for better machine learning models for a specific materials research domain.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A Field Guide to Corralling the Chaos: A Conceptual Framework for Using Models to Guide Opportunistic Field Studies of Natural Disturbances

Watersheds regulate biogeochemical processes and provide ecosystem services to human societies, but disturbances can fundamentally alter these processes across space and time. Determining when and where to sample to capture disturbance impacts in watersheds remains a central challenge. Manipulation studies and long-term monitoring are often constrained by scope, and opportunistic studies often lack pre-disturbance data needed to statistically determine disturbance impacts. We identify a persistent knowledge gap: the absence of a clear, transferable framework to guide opportunistic disturbance research where pre-disturbance data collection is not a feasible option. To address this gap, we present a conceptual framework that intentionally integrates modeling and empirical observation in an iterative, stepwise model–experiment workflow. We demonstrate its application through two contrasting case studies: wildfire impacts on headwater streams using a pre-disturbance preparedness approach, and saltwater flooding impacts on coastal forests using an ‘ex-post-facto’ approach. From these applications, we assess strengths, limitations, and the critical role of team science for transferability across disturbance types and study designs. Broadly, this framework offers a scalable path towards more rigorous, timely, and actionable disturbance science that can inform watershed management, hazard risk reduction, and ecosystem resilience.

Coastal Biogeochemistry↗
NASA NTRS1988

An expert system for probabilistic description of loads on space propulsion system structural components

LDEXPT, an expert system that generates probabilistic characterizations of the loads spectra borne by spacecraft propulsion systems' structural components, is found by recent experience at NASA-Lewis to be useful in the cases of components representative of the Space Shuttle Main Engine's turbopumps and fluid transfer ducting. LDEXPT is composed of a knowledge base management system and a rule base management system. The ANLOAD load-modeling module of LDEXPT encompasses three independent probabilistic analysis techniques.

Spencer, B. F., Jr.↗
NASA NTRS1992

Swept shock/boundary layer interaction experiments in support of CFD code validation

Research on the topic of shock wave/turbulent boundary-layer interaction was carried out during the past three years at the Penn State Gas Dynamics Laboratory. This report describes the experimental research program which provides basic knowledge and establishes new data on heat transfer in swept shock wave/boundary-layer interactions. An equilibrium turbulent boundary-layer on a flat plate is subjected to impingement by swept planar shock waves generated by a sharp fin. Five different interactions with fin angle ranging from 10 deg to 20 deg at freestream Mach numbers of 3.0 and 4.0 produce a variety of interaction strengths from weak to very strong. A foil heater generates a uniform heat flux over the flat plate surface, and miniature thin-film-resistance sensors mounted on it are used to measure the local surface temperature. The heat convection equation is then solved for the heat transfer distribution within an interaction, yielding a total uncertainty of about +/- 10 percent. These experimental data are compared with the results of numerical Navier-Stokes solutions which employ a k-epsilon turbulence model. Finally, a simplified form of the peak heat transfer correlation for fin interactions is suggested.

Settles, G. S.↗
NASA NTRS1992

An evaluation of training effectiveness of an intelligent tutoring system

The study evaluated the training effectiveness of an intelligent tutoring system (ITS) for the Remote Manipulator System (RMS). The study examined how well individuals learn the training content and skills from the RMS ITS and to what extent the content and skills learned using the ITS transfer to RMS task performance in the SES, a high fidelity simulator. Three astronauts completed 8 2-hour ITS sessions addressing movement in three coordinate systems, grapple, ungrapple, berth, and unberth procedures, and singularities and reach limits. Their performance was also observed in an SES training session. Performance data were collected using multiple measures: ITS task performance, transfer performance on the SES, a conceptual knowledge test, an opinion survey completed by astronauts, and comments and observations from astronauts and trainers. Results indicated the RMS ITS to be moderately effective and provided evidence of the efficacy of ITS's, in general. Comments and suggestions are provided relating to how the ITS could be improved and to enable decision makers to judge the effectiveness of the RMS ITS.

Johnson, Debra Steele↗
NASA NTRS1993

Progress in modeling hypersonic turbulent boundary layers

A good knowledge of the turbulence structure, wall heat transfer, and friction in turbulent boundary layers (TBL) at high speeds is required for the design of hypersonic air breathing airplanes and reentry space vehicles. This work reports on recent progress in the modeling of high speed TBL flows. The specific research goal described here is the development of a second order closure model for zero pressure gradient TBL's for the range of Mach numbers up to hypersonic speeds with arbitrary wall cooling requirements.

Zeman, Otto↗
NASA NTRS1994

The future of interaction on the Internet

The federated collection of heterogeneous computers we collectively term the Internet has been the force behind revolutionary change, both in terms of actual practice and imagination of what might be. The raw numbers are staggering: IP registrations are now ten times that of only five years ago; and between 1992 - 1993 the amount of information being transferred tripled. Changes in three key areas: knowledge discovery; intelligent information access; and collaboration on the Internet are discussed.

Maybury, Mark T.↗
NASA NTRS1997

Fundamentals of Mold Free Casting: Experimental and Computational Studies

Researchers are developing the technology of 'Ballistic Particle Manufacturing' (BPM) in which individual drops are precisely layered onto a substrate, and the drops are deposited so as to prevent splatting. These individual drops will ultimately be combined to form a net-shape, three-dimensional object. Our understanding of controlled drop deposition as applied to BPM is far from complete. Process parameters include the size and temperature of the liquid metal drop, its impact velocity and trajectory, and the condition and temperature of the substrate. Quantitative knowledge of the fluid mechanics and heat transfer of drop deposition and solidification are necessary to fully optimize the manufacturing process and to control the material microstructure of the final part. The object of this study is to examine the dynamics of liquid metal drops as they impinge upon a solid surface and solidify under conditions consistent with BPM (i.e. conditions which produce non-splatting drops). A program of both numerical simulations and experiments will be conducted. Questions this study will address include the following: How do the deformation and solidification of the drop depend on the properties of the fluid drop and the solid substrate? How does the presence of previously deposited drops affect the impingement and solidification process? How does the impingement of the new drop affect already deposited material? How does the cooling rate and solidification of the drops influence the material microstructure?

Tryggvason, Gretar↗
NASA NTRS1998

National Space Biomedical Research Institute

The National Space Biomedical Research Institute (NSBRI) sponsors and performs fundamental and applied space biomedical research with the mission of leading a world-class, national effort in integrated, critical path space biomedical research that supports NASA's Human Exploration and Development of Space (HEDS) Strategic Plan. It focuses on the enabling of long-term human presence in, development of, and exploration of space. This will be accomplished by: designing, implementing, and validating effective countermeasures to address the biological and environmental impediments to long-term human space flight; defining the molecular, cellular, organ-level, integrated responses and mechanistic relationships that ultimately determine these impediments, where such activity fosters the development of novel countermeasures; establishing biomedical support technologies to maximize human performance in space, reduce biomedical hazards to an acceptable level, and deliver quality medical care; transferring and disseminating the biomedical advances in knowledge and technology acquired through living and working in space to the benefit of mankind in space and on Earth, including the treatment of patients suffering from gravity- and radiation-related conditions on Earth; and ensuring open involvement of the scientific community, industry, and the public at large in the Institute's activities and fostering a robust collaboration with NASA, particularly through Johnson Space Center.

Source record↗
NASA NTRS2000

National Space Biomedical Research Institute Annual Report

This report summarizes the activities of the National Space Biomedical Research Institute (NSBRI) during FY 2000. The NSBRI is responsible for the development of countermeasures against the deleterious effects of long-duration space flight and performs fundamental and applied space biomedical research directed towards this specific goal. Its mission is to lead a world-class, national effort in integrated, critical path space biomedical research that supports NASA's Human Exploration and Development of Space (HEDS) Strategic Plan by focusing on the enabling of long-term human presence in, development of, and exploration of space. This is accomplished by: designing, testing and validating effective countermeasures to address the biological and environmental impediments to long-term human space flight; defining the molecular, cellular, organ-level, integrated responses and mechanistic relationships that ultimately determine these impediments, where such activity fosters the development of novel countermeasures; establishing biomedical support technologies to maximize human performance in space, reduce biomedical hazards to an acceptable level, and deliver quality medical care; transferring and disseminating the biomedical advances in knowledge and technology acquired through living and working in space to the general benefit of mankind, including the treatment of patients suffering from gravity- and radiation-related conditions on Earth; and ensuring open involvement of the scientific community, industry and the public at large in the Institute's activities and fostering a robust collaboration with NASA, particularly through NASA's Lyndon B. Johnson Space Center. Attachment:Appendices (A,B,C,D,E,F,G,H,I,J,K,L,M,N,O, and P.).

Source record↗
NASA NTRS2005

National Space Biomedical Research Institute

NSBRI partners with NASA to develop countermeasures against the deleterious effects of long duration space flight. NSBRI's science and technology projects are directed toward this goal, which is accomplished by: 1. Designing, testing and validating effective countermeasures to address the biological and environmental impediments to long-term human space flight. 2. Defining the molecular, cellular, organ-level, integrated responses and mechanistic relationships that ultimately determine these impediments, where such activity fosters the development of novel countermeasures. 3. Establishing biomedical support technologies to maximize human performance in space, reduce biomedical hazards to an acceptable level and deliver quality medical care. 4. Transferring and disseminating the biomedical advances in knowledge and technology acquired through living and working in space to the general benefit of humankind; including the treatment of patients suffering from gravity- and radiation-related conditions on Earth. and 5. ensuring open involvement of the scientific community,industry and the public in the Institute's activities and fostering a robust collaboration with NASA, particularly through JSC.

Source record↗