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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 1,063 records · Page 59

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Integrated Methane Monitoring Platform Extension, Volume I: Final Technical Report

The IMMPE project, DE-FE0032284, was to enhance methane monitoring technologies and their applications across various natural gas asset classes. The scope included deploying advanced methane detection and monitoring technologies to identify and mitigate fugitive methane emissions, measuring emission rates, and assessing impacts. The findings included the successful mitigation of identified emissions and quantification of emission rates. A key outcome was the development of a comprehensive template and summary of recommendations for methane emissions monitoring, which is replicable for both upstream and downstream applications. Furthermore, the project emphasized the importance of education by providing training opportunities for technicians and regulators, thereby fostering awareness and promoting the adoption of cost-effective methane emissions monitoring and management techniques.

02 PETROLEUM↗

NASA NTRS1977

On the transfer of remote sensing technology to an operational data system

Data processing techniques for the transfer of remote sensing technology to an operational data system are evaluated. The study is aimed at developing a scheme for the improvement of the quantifying cost/performance ratio, noting the timeliness of the results, the ease of system development, system operating costs, and accuracy. The method is applicable to the Production Area and Yield Estimation System (PAYES) and the Large Area Crop Inventory Experiment (LACIE).

Tarbet, J. D.↗

NASA NTRSDate not supplied

Metadata Entry Optimization for NASA's Biological Institutional Scientific Collection (NBISC)

The NASA Biological Institutional Sample Collection (NBISC) at NASA’s Ames Research Center is a critical resource housing non-human samples collected from spaceflight missions and ground analog studies, primarily consisting of specimens from rats, mice, and select microbes. The primary objective of NBISC is to systematically receive, document, preserve, and facilitate access to these samples for the global scientific community. NBISC promotes international collaboration and maximizes the return on investment for precious tissues from spaceflight and analog experiments. Researchers can request physical samples through an online request form and subsequent written proposal review process. This study addresses two core research objectives: streamlining the NBISC sample lifecycle processes and strategizing for managing an influx of 50,000 tissue samples from a series of cosmic radiation analog experiments carried out at the NASA Space Radiation Laboratory (NSRL) by Drs. Eleanor Chang (Lawrence Berkeley Laboratory) and Polly Blakely (SRI). The Chang/Blakely studies investigated Harderian gland (HG) tumorigenesis in mice exposed to low dose and LET radiation comprising 8 different exposure protocols in over 4000 mice. NBISC sample metadata is stored in a Laboratory Information Management System (SLIMS). To streamline sample data entry, we customize python scripts using information extracted from the individual experimental protocols. The scripts automate entry into multiple SLIMS data fields including protocol name, unique sample barcode, tissue and sub-tissue information, freezer location, sample preservation method, etc. The semi-automated procedure significantly decreases the time spent on data entry by several orders of magnitude. Automation and data organization are essential, as they free up time for curation and promotion of the collection which, in turn, increase the accessibility of samples to the broader research community. NBISC benefits from streamlined data ingestion, and the methodologies developed here are applicable to other projects which use SLIMS including the NASA Biospecimen Sharing Program and GeneLab. As of Fall 2023, plans include transferring sample data from SLIMS to public facing repositories (OSDR and NLSP), expanding the reach of the Chang/Blakely sample collection. The Human Research Program Space Radiation Element plans to transfer non-human tissues from many more investigations to NBISC in the coming year.

Sample Repository↗

NASA NTRSDate not supplied

Metadata Entry Optimization For NASA's Biological Institutional Scientific Collection (NBISC)

Biospecimen↗

NASA NTRS1977

Experiment support system

The Experiment Support System is a switchboard system with displays and controls. It routes electrical power to experiments M092, M093, and M171 equipment; gaseous nitrogen to the Blood Pressure Measurement System; receives biomedical data from all related equipment; routes the conditioned data signals to the Airlock Module Telemetry System and also displays (in digital or analog from) portions of that data which the crewmen must see to complete the experiment successfully. The Experiment Support System is interfaced to the M131 control panel to transfer conditioned data to the Airlock Module Telemetry System.

Shannon, A. V.↗

NASA NTRS1997

Improved Flight Test Procedures for Flutter Clearance

Flight flutter testing is an integral part of flight envelope clearance. This paper discusses advancements in several areas that are being investigated to improve efficiency and safety of flight test programs. Results are presented from recent flight testing of the F/A-18 Systems Research Aircraft. A wingtip excitation system was used to generate aeroelastic response data. This system worked well for many flight conditions but still displayed some anomalies. Wavelet processing is used to analyze the flight data. Filtered transfer functions are generated that greatly improve system identification. A flutter margin is formulated that accounts for errors between a model and flight data. Worst-case flutter margins are computed to demonstrate the flutter boundary may lie closer to the flight envelope than previously estimated. This paper concludes with developments for a distributed flight analysis environment and on-line health monitoring.

Lind, Rick C.↗

NASA NTRS1995

The Next Generation of Space Telemetry and Telecommand Standards

Standardizing the exchange of data through communications channels that connect spacecraft with their ground systems reduces costs. Efficient coding and packetization promote the automated, error-free transfer of data.

Galileo Near Infrared Mapping Spectrometer NIMS Ju↗

DOE OSTI2023

Trust-Enhancing Probabilistic Transfer Learning for Sparse and Noisy Data Environments

There is an increasing aspiration to utilize machine learning (ML) for various tasks of relevance to national security. ML models have thus far been mostly applied to tasks and domains that, while impactful, have sufficient volume of data. For predictive tasks of national security relevance, ML models of great capacity (ability to approximate nonlinear trends in input-output maps) are often needed to capture the complex underlying physics. However, scientific problems of relevance to national security are often accompanied by various sources of sparse and/or incomplete data, including experiments and simulations, across different regimes of operation, of varying degrees of fidelity, and include noise with different characteristics and/or intensity. State-of-the-art ML models, despite exhibiting superior performance on the task and domain they were trained on, may suffer detrimental loss in performance in such sparse data environments. This report summarizes the results of the Laboratory Directed Research and Development project entitled Trust-Enhancing Probabilistic Transfer Learning for Sparse and Noisy Data Environments. The objective of the project was to develop a new transfer learning (TL) framework that aims to adaptively blend the data across different sources in tackling one task of interest, resulting in enhanced trustworthiness of ML models for mission- and safety-critical systems. The proposed framework determines when it is worth applying TL and how much knowledge is to be transferred, despite uncontrollable uncertainties. The framework accomplishes this by leveraging concepts and techniques from the fields of Bayesian inverse modeling and uncertainty quantification, relying on strong mathematical foundations of probability and measure theories to devise new uncertainty-aware TL workflows.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2002

Analysis of Atmospheric Aerosol Data Sets and Application of Radiative Transfer Models to Compute Aerosol Effects

This report is the final report for "Analysis of Atmospheric Aerosol Data Sets and Application of Radiative Transfer Models to Compute Aerosol Effects". It is a bibliographic compilation of 29 peer-reviewed publications (published, in press or submitted) produced under this Cooperative Agreement and 30 first-authored conference presentations. The tasks outlined in the various proposals are listed below with a brief comment as to the research performed. Copies of title/abstract pages of peer-reviewed publications are attached.

Schmid, Beat↗

NASA NTRS1984

Injection-induced turbulence in stagnation-point boundary layers

A theory is developed for the stagnation point boundary layer with injection under the hypothesis that turbulence is produced at the wall by injection. From the existing experimental heat transfer rate data obtained in wind tunnels, the wall mixing length is deduced to be a product of a time constant and an injection velocity. The theory reproduces the observed increase in heat transfer rates at high injection rates. For graphite and carbon-carbon composite, the time constant is determined to be 0.0002 sec from the existing ablation data taken in an arc-jet tunnel and a balistic range.

Park, C.↗

DOE OSTI2026

A ModEx Framework for Watershed Subsurface Investigation With Limited Geophysical Data Using Machine Learning and Hydrologic Modeling

Abstract Subsurface heterogeneity influences watershed hydrology strongly but remains difficult to characterize at catchment scales with sparse and costly field data. Geophysical surveys such as electromagnetic induction (EMI) provide local spatial subsurface images yet scaling them to watershed scales and converting EMI‐derived resistivity into hydraulic properties remains a challenge. We present a Model–Experiment (ModEx) framework that integrates limited EMI data with machine learning (ML) and hydrologic modeling to improve process representation and guide field investigations. Sparse EMI surveys were scaled to the catchment scale using a Random Forest model, and the resulting resistivity fields were combined with nearby borehole constraints to parameterize a hydrologic model. The EMI‐informed hydrological simulations improved predictions of streamflow sustained by subsurface flow and shallow saturation patterns. By combining EMI data and ML with hydrologic modeling, the ModEx framework guides future subsurface surveys, providing a transferable and efficient strategy for data–model integration across diverse watersheds. Plain Language Summary Mapping the underground network of soil and rock that controls water is essential for predicting floods and droughts, but seeing underground is difficult and expensive. We cannot drill everywhere, so scientists use geophysical tools to scan broad areas. There are two key challenges: these geophysical scans are often sparse across the whole watershed, and the geophysical data is hard to translate into water‐related properties. We used artificial intelligence to solve these problems. We taught a computer to find patterns linking the limited geophysical data to the land surface properties. This allowed it to fill in the gaps and create a complete, useful subsurface map for the entire watershed. This new map improves hydrologic simulations, leading to more accurate predictions of water movement in the watershed. It also helps scientists build better models with less data and generates a priority map showing where to measure next, making future investigations more efficient. Key Points Limited EMI scaled with ML improves catchment‐scale subsurface parameterization for hydrologic models The framework integrates hydrologic modeling with limited geophysical data to support subsurface investigation design ModEx framework offers a transferable data–model integration strategy that quantifies and reduces uncertainty guiding watershed studies

Chen, Hang↗

NASA NTRS2001

External Validity Considerations of a Biocybernetic System for Adaptive Automation

The report discusses the results of a research project aimed at generating a software application library termed the DAQ EEG Processor (or DEP) that collects and processes raw electroencephalographic data. The purpose of this system is to reduce raw EEG data in real time into information that is useful to researchers, such as power bands and indices of engagement. DEP improves upon existing EEG processing systems in that it can be seamlessly integrated into many software development environments to provide realtime data. DEP takes advantage of Microsoft Corporation's Component Object Model Technology (COM), which, in short, allows language independent, inter-application communication and transfer of data. According to the COM specification, COM objects can be written in different languages, run in different process spaces and on different platforms. As long as the objects adhere to the specification, they can communicate.

Scerbo, Mark W.↗

DOE OSTI2024

A Variable Eddington Factor Model for Thermal Radiative Transfer with Closure Based on Data-Driven Shape Function

Here, a new variable Eddington factor (VEF) model is presented for nonlinear problems of thermal radiative transfer (TRT). The VEF model is data-driven and acts on known (a-priori) radiation-diffusion solutions for material temperatures in the TRT problem. A linear auxiliary problem is constructed for the radiative transfer equation (RTE) whose emission source and opacities are evaluated at these known material temperatures. The solution to this RTE approximates the specific intensity distribution in phase-space and time. It is applied as a shape function to define the Eddington tensor for the presented VEF model. The shape function computed via the auxiliary RTE problem will capture some degree of transport effects within the TRT problem. The VEF moment equations closed with this approximate Eddington tensor will thus carry with them these captured transport effects. In this study, the temperature data comes from multigroup P 1 , P 1/3 , and flux-limited diffusion radiative transfer models. The proposed VEF model can be interpreted as a transport-corrected diffusion reduced-order model. Numerical results are presented on the Fleck-Cummings test problem which models a supersonic wavefront of radiation. The VEF model is shown to improve accuracy by 1–2 orders of magnitude compared to the considered radiation-diffusion model solutions to the TRT problem.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1990

FIRE extended time/limited area observations at Palisades, New York

Downwelling shortwave and longwave irradiation are being continuously monitored at Palisades, New York as part of the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE) Extended Time/Limited Area Initiative. In addition, fisheye (180 degree) sky photographs are taken at the times of NOAA 9 and LANDSAT satellite overpasses on select days, particularly when cirrus clouds are present. Measurements of incoming shortwave (0.28 to 2.80 microns) hemispheric and diffuse, hemispheric near infrared (0.7 to 2.80 microns), and downwelling hemispheric infrared (4.0 to 50.0 microns) irradiation have been made from a rooftop location on the grounds of the Lamont-Doherty Geological Observatory since December 1986. The three Eppley Precision Spectral Pyranometers and the Eppley Pyrgeometer used to measure these variables were calibrated with Colorado State University instruments at Madison, Wisconsin as part of the FIRE Intensive Laboratory. Pyrgeometer output contains an adjustment for body temperature but not for dome temperature. Data are transmitted to a Campbell CR-21 Digital Recorder, where one minute averages of ten second samples are stored and subsequently dumped to a cassette recorder. Using a Campbell C-20 Cassette Interface, these data are transferred to an Apple Macintosh computer for analysis and for archiving on floppy disks. In addition to the raw irradiances collected, variables derived from these data are generated and stored. These include: the ratio of near infrared irradiation to visible irradiation and the fraction of the full shortwave irradiation which is diffuse; and will soon include: shortwave transmissivity and optical depth in the shortwave. Sky photographs are taken with an Olympus OM2-N 35 mm camera and are timed to be coincident with overpassing NOAA and LANDSAT satellites. Palisades is within the field of view of the NOAA 9 daily in the middle to late afternoon. The satellite viewing angle is within 45 degrees of nadir over Palisades on approximately half of the passes.

Robinson, David A.↗

NASA NTRS1986

STAR - A computer language for hybrid AI applications

Constructing Artificial Intelligence application systems which rely on both symbolic and non-symbolic processing places heavy demands on the communication of data between dissimilar languages. This paper describes STAR (Simple Tool for Automated Reasoning), a computer language for the development of AI application systems which supports the transfer of data structures between a symbolic level and a non-symbolic level defined in languages such as FORTRAN, C and PASCAL. The organization of STAR is presented, followed by the description of an application involving STAR in the interpretation of airborne imaging spectrometer data.

Borchardt, G. C.↗

NASA NTRS2001

TAXI Interface Demultiplexes Proprietarily Formatted Data

The 'TAXI Direct-to-Disk' interface is a special purpose interface unit for demultiplexing of data from a Racal Storeplex (or equivalent) multichannel recorder onto one or more hard disks that reside in, and/or are controlled by, a personal computer (PC). The acronym 'TAXI' signifies transparent asynchronous transceiver interface. The TAXI interface was developed for original use in capturing data from instrumentation on a test stand in a NASA rocket testing facility. The installation of the TAXI interface, in conjunction with other modifications, causes the transfer of data to take place in real time, so that the data are immediately available for review during or after the test.

Newnan, Bruce G.↗

DOE OSTI2022

Preliminary Transfer Learning Results on Israel Data

In this preliminary report, we use publicly available data recorded in Israel to test and expand upon existing machine learning models for seismic-phase detection and arrival-time measurement. We downloaded 3-years of waveform data from Geofon, and cross referenced the waveforms to Israel bulletin picks (Schardong et al., 2021). The initial results using existing models directly generated ubiquitous false detections and that obscured detections of signals that are clearly visible in the waveforms. However, after applying transfer learning (tuning parameters in the existing ML models using one year of the Israel-network data), the results are encouraging, i.e. ML picks agree within a few tenths of a second with bulletin picks and the number of false detections is greatly reduced. The bulletin picks are a good starting point, but they cannot be considered ground-truth. To test potential improvement in picking using ML we would like to relocate the events using the ML picks to see if the events cluster more tightly at known mine locations. However, in order to constrain event locations, we need ML picks for the whole Israeli-Jordanian network, which requires waveforms that are not publicly available.

58 GEOSCIENCES↗

NASA NTRS1992

Space Shuttle earth observations photography - Data listing process

The data listing process of the electronic data base of the Catalogs of Space Shuttle Earth Observations Photography is described. Similar data are recorded for each frame in each role from the mission. At the end of each roll, a computer printout is checked for mistakes, glitches, and typographical errors. After the roll and frames have been corrected, the data listings are ready for transfer to the data base and for development of the catalog.

Lulla, Kamlesh↗