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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

High Performance Database Management for Earth Sciences

The High Performance Database Research Center at Florida International University is completing the development of a highly parallel database system based on the semantic/object-oriented approach. This system provides exceptional usability and flexibility. It allows shorter application design and programming cycles and gives the user control via an intuitive information structure. It empowers the end-user to pose complex ad hoc decision support queries. Superior efficiency is provided through a high level of optimization, which is transparent to the user. Manifold reduction in storage size is allowed for many applications. This system allows for operability via internet browsers. The system will be used for the NASA Applications Center program to store remote sensing data, as well as for Earth Science applications.

Rishe, Naphtali↗
NASA NTRS1992

Satellite-derived surface latent heat fluxes in a rapidly intensifying marine cyclone

Surface latent heat fluxes are estimated in the vicinity of a rapidly deepening cyclone before and during its period of most rapid intensification. This was done with a bulk parameterization scheme and remotely sensed input data. A method is studied for estimating the difference in specific humidity between the surface and a ten meter height using the Special Sensor Microwave/Imager (SSM/I) observed integrated water vapor field and a sea surface temperature analysis. The surface latent heat flux fields generally have estimated errors below 40 pct. south of 40 deg. N and outside the region of high integrated water vapor values associated with frontal bands. The method of estimating surface latent heat fluxes for the case study was found to be usable in most regions of the Northwest Atlantic Ocean except for those locations directly adjacent to coastlines in instances of offshore flow and in the vicinity of surface fronts.

Miller, Douglas K.↗
NASA NTRS2015

Flight Deck Interval Management Avionics: Eye-Tracking Analysis

Interval Management (IM) is one NexGen method for achieving airspace efficiencies. In order to initiate IM procedures, Air Traffic Control provides an IM clearance to the IM aircraft's pilots that indicates an intended spacing from another aircraft (the target to follow - or TTF) and the point at which this should be achieved. Pilots enter the clearance in the flight deck IM (FIM) system; and once the TTF's Automatic Dependent Surveillance-Broadcast signal is available, the FIM algorithm generates target speeds to meet that IM goal. This study examined four Avionics Conditions (defined by the instrumentation and location presenting FIM information) and three Notification Methods (defined by the visual and aural alerts that notified pilots to IM-related events). Current commercial pilots flew descents into Dallas/Fort-Worth in a high-fidelity commercial flight deck simulation environment with realistic traffic and communications. All 12 crews experienced each Avionics Condition, where order was counterbalanced over crews. Each crew used only one of the three Notification Methods. This paper presents results from eye tracking data collected from both pilots, including: normalized number of samples falling within FIM displays, normalized heads-up time, noticing time, dwell time on first FIM display look after a new speed, a workload-related metric, and a measure comparing the scan paths of pilot flying and pilot monitoring; and discusses these in the context of other objective (vertical and speed profile deviations, response time to dial in commanded speeds, out-of-speed-conformance and reminder indications) and subjective measures (workload, situation awareness, usability, and operational acceptability).

Latorella, Kara↗
NASA NTRS2020

Dynamic Countermeasure Fabrics for Post-Spaceflight Orthostatic Intolerance

Aerospace orthostatic intolerance garments (OIG) have historically been pneumatic (e.g., NASA’s antigravity suit), an approach that inhibits mobility and requires connection to an air supply. Elastic compression garments, an alternative technology, are difficult to don/doff and cannot be worn in a noncompressive state, resulting in discomfort and usability challenges. This research evaluates a novel technology—contractile shape memory alloy (SMA) knitted actuators—that can enable low-profile, dynamic compression for an aerospace OIG. To characterize the functional capabilities of SMA knitted actuators, displacement control testing was conducted on 10 actuator samples with a range of geometric design parameters. Inactive (FI) and actuated forces (FA) were observed by repeatedly thermally cycling each sample at 0%, 15%, 30%, and 45% structural strain. Compression capabilities were approximated using medical compression hosiery standards and anthropometric data from a representative aerospace population (ANSUR 2012). Dynamic compression predictions reached 52 mmHg (single layer fabric) and 105 mmHg (double layer fabric) at the ankle. Low, inactive pressures (p, 20 mmHg) demonstrate that compression is controllable and can be dynamically increased upon actuation up to 33 mmHg in a single layer system and up to 67 mmHg in a double layer system. The results highlight the potential of SMA knitted actuators to enable low-profile, dynamic compression garments that can reach medically therapeutic pressures on an aerospace population to counteract OI symptoms. In addition to astronautic applications, this technology demonstrates widespread terrestrial medical and high-performance aircraft applicability.

Orthostatic intolerance↗
DOE OSTI2025

Heuristic Evaluation Methods Applied to a Predictive Maintenance Chatbot

The need for an accessible iterative approach for evaluating prospective artificial intelligence (AI)/ML based technologies in the nuclear industry is needed, given the nature of algorithms and rapid advancements. This paper explores existing heuristic design principles for user-centered design and evaluates them based on their relevancy and usefulness for evaluating AI/ ML based technologies. Researchers at the Idaho National Laboratory (INL) have developed a machine learning software application called VIsualization for PrEdictive maintenance Recommendation (VIPER), which is used to help users understand and engage with the tool to learn more about work orders, data used, predictive maintenance, and machine learning (ML) algorithms. Early user research studies used to access VIPER’s technology readiness level have occurred; however, there is room for further improvement of the software through heuristic evaluations along with other methods and user testing. This work describes the applicability of heuristic evaluation methods and cognitive walkthroughs to help ensure human readiness for prospective AI/ ML based applications, using VIPER as a candidate use case. This work supports industry in ensuring that prospective AI/ML based technologies are usable and useful for plant personnel at nuclear power plants, ultimately leading to their safe, reliable, and efficient use.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Heuristic Evaluation Methods Applied to a Predictive Maintenance Chatbot

The need for an accessible iterative approach for evaluating prospective artificial intelligence (AI)/ML based technologies in the nuclear industry is needed, given the nature of algorithms and rapid advancements. This paper explores existing heuristic design principles for user-centered design and evaluates them based on their relevancy and usefulness for evaluating AI/ ML based technologies. Researchers at the Idaho National Laboratory (INL) have developed a machine learning software application called VIsualization for PrEdictive maintenance Recommendation (VIPER), which is used to help users understand and engage with the tool to learn more about work orders, data used, predictive maintenance, and machine learning (ML) algorithms. Early user research studies used to access VIPER?s technology readiness level have occurred; however, there is room for further improvement of the software through heuristic evaluations along with other methods and user testing. This work describes the applicability of heuristic evaluation methods and cognitive walkthroughs to help ensure human readiness for prospective AI/ ML based applications, using VIPER as a candidate use case. This work supports industry in ensuring that prospective AI/ML based technologies are usable and useful for plant personnel at nuclear power plants, ultimately leading to their safe, reliable, and efficient use. PowerPoint for conference that was reviewed in PRS and LRS PRS/CON-25-05379 and INL/CON-25-82946

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

SAIL Field Campaign X-Band Precipitation Radar Seasonal Surface Hydrometeor Phase Classification Value-Added Product Report

The Surface Atmosphere Integrated Field Laboratory (SAIL) campaign generated an unprecedented, multisensory record of cold-season precipitation in the Upper Colorado River Basin (UCRB). To complement the Surface Quantitative Precipitation Estimation (SQUIRE) snow water equivalent (SWE) product derived from the Colorado State University (CSU) X-band radar, a hydrometeor phase classification data set was developed to systematically identify phase of the near-surface precipitation. The algorithm uses Corrected Moments in Antenna Coordinates (CMAC) fields with semi-supervised classification (SSC) and fuzzy-logic hydrometeor classification (FHC) methods and maps hydrometeor classes to a compact set of phase classes suitable for Quantitative Precipitation Estimation (QPE) and hydrologic applications. We used SQUIRE grid projections to mitigate beam-blockage issues by selecting the near-surface gates for each beam as well as to make it directly usable for the QPE products.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1975

A new image enhancement algorithm with applications to forestry stand mapping

The theory and applications are presented of a new image enhancement algorithm which refines computer classification maps of multispectral data. The refinement eliminates connected sets smaller than a prespecified size and merges them to the surrounding area. Conventional practices in forestry timber stand mapping requires small geographic areas to be absorbed by surrounding large areas to form homogeneous stands. This homogeneity is often incompatible with the statistical formulation of homogeneity. Elements within a timber stand which should be labeled as one feature often correspond to more than one class mapped by existing computer classification techniques. The new algorithm is designed to postprocess classification maps to result in more usable timber stand maps. The new image enhancement technique is compared with an accepted neighbor-checking postprocessing technique, demonstrating the superiority of the new technique for forestry stand mapping.

Kan, E. P.↗
NASA NTRS2024

Unsteady Surface Pressure Characterization on Launch Vehicle in Liftoff Configuration

Acquisition of unsteady pressure using remote scanners can provide practical advantages over making the same measurements directly using flush-mounted pressure transducers. However, pneumatic distortion of the signal is introduced by the tubing between the sensing module and surface port. This typically limits the usefulness of such measurements to averaged, steady data only, restricting the application of pressure scanners for unsteady pressure measurements in the wind tunnel and flight-testing applications. In this work, unsteady pressure on the surface of a 1.75%-scale model of the NASA Space Launch System Block 1B Cargo vehicle was remotely measured at the NASA Langley Research Center 14- by 22-Foot Subsonic Tunnel using an ESP pressure scanner. Subsequent reconstruction using an empirically-tuned, Wiener-filtered inverse transfer function produced excellent agreement compared to nearby surface-mounted transducers within a usable bandwidth of approximately 500 Hz. Interactions between the launch vehicle and the support tower produced strong oscillations that were absent in the vehicle-alone configuration, and it is likely that the wake interaction leads to a resonant flow response when the launch tower is immediately downstream of the vehicle.

Unsteady pressure↗
NASA NTRS2010

Speech Acquisition and Automatic Speech Recognition for Integrated Spacesuit Audio Systems

A voice-command human-machine interface system has been developed for spacesuit extravehicular activity (EVA) missions. A multichannel acoustic signal processing method has been created for distant speech acquisition in noisy and reverberant environments. This technology reduces noise by exploiting differences in the statistical nature of signal (i.e., speech) and noise that exists in the spatial and temporal domains. As a result, the automatic speech recognition (ASR) accuracy can be improved to the level at which crewmembers would find the speech interface useful. The developed speech human/machine interface will enable both crewmember usability and operational efficiency. It can enjoy a fast rate of data/text entry, small overall size, and can be lightweight. In addition, this design will free the hands and eyes of a suited crewmember. The system components and steps include beam forming/multi-channel noise reduction, single-channel noise reduction, speech feature extraction, feature transformation and normalization, feature compression, model adaption, ASR HMM (Hidden Markov Model) training, and ASR decoding. A state-of-the-art phoneme recognizer can obtain an accuracy rate of 65 percent when the training and testing data are free of noise. When it is used in spacesuits, the rate drops to about 33 percent. With the developed microphone array speech-processing technologies, the performance is improved and the phoneme recognition accuracy rate rises to 44 percent. The recognizer can be further improved by combining the microphone array and HMM model adaptation techniques and using speech samples collected from inside spacesuits. In addition, arithmetic complexity models for the major HMMbased ASR components were developed. They can help real-time ASR system designers select proper tasks when in the face of constraints in computational resources.

Huang, Yiteng↗
DOE OSTI2026

Operating advanced scientific instruments with AI agents that learn on the job

Advanced scientific user facilities, such as next generation X-ray light sources and self-driving laboratories, are revolutionizing scientific discovery by automating routine tasks and enabling rapid experimentation and characterizations. However, these facilities must continuously evolve to support new experimental workflows, adapt to diverse user projects, and meet growing demands for more intricate instruments and experiments. This continuous development introduces significant operational complexity, necessitating a focus on usability, reproducibility, and intuitive human-instrument interaction. In this work, we explore the integration of agentic AI, powered by Large Language Models (LLMs), as a transformative tool to achieve this goal. We present our approach to developing a human-in-the-loop pipeline for operating advanced instruments including an X-ray nanoprobe beamline and an autonomous robotic station dedicated to the design and characterization of materials. Specifically, we evaluate the potential of various LLMs as trainable scientific assistants for orchestrating complex, multi-task workflows, which also include multimodal data, optimizing their performance through optional human input and iterative learning. We demonstrate the ability of AI agents to bridge the gap between advanced automation and user-friendly operation, paving the way for more adaptable and intelligent scientific facilities.

Large Language Models↗
NASA NTRSDate not supplied

Using AI/ML to Address Satellite Cloud Remote Sensing Challenges

Various AI/ML tools, employed within the Clouds and the Earth's Radiant Energy System (CERES) Satellite Cloud and Radiation Property retrieval System (SatCORPS) project, are being used to mitigate satellite radiance artifacts and thereby yield more accurate cloud and radiation data products. Neural network and K-nearest neighbor approaches have been developed that enable us to better address common passive satellite remote sensing challenges, such as corrupted imagery, day/night cloud property discontinuities, solar terminator artifacts, inadequate knowledge of the land surface emission temperature (i.e., skin temperature), and poor assumptions about vertical cloud structure, that have otherwise proven difficult to solve using more conventional methods. Fixing these problems promotes a more consistent Earth radiation budget record. These efforts demonstrate effective use of AI/ML architecture to exploit complex, multivariate predictor relationships and produce usable output at satellite spatial and temporal resolutions that would otherwise be ignored or have large biases.

Benjamin Scarino↗
NASA NTRSDate not supplied

Development of a Safety Hazards Risk Assessment Tool for Uncrewed Aircraft System Traffic Management during Preflight Planning

Tremendous growth in the uncrewed and remotely piloted vehicle market is expected in low-altitude, uncontrolled airspace, resulting in potential decreases in safety without systems that support monitoring, assessing, and mitigating risk. At NASA, the System-Wide Safety (SWS) project has been developing a suite of data-driven tools to predict hazards so that the potential risks that these hazards pose can be mitigated. Services to predict various hazards have been developed, including battery capacity, proximity to static obstacles, population risks, global positioning system signal strength, radio frequency spectrum interference risk, and vertiport congestion. These services can monitor hazards along a flight path and if any risks posed by these hazards exceed a threshold, the uncrewed aircraft system (UAS) fleet manager can be alerted to mitigate the risk by modifying the flight path, changing the scheduled departure or arrival times, and/or diverting the vehicle to an alternate vertiport. These services were originally developed to monitor and assess risks during flight, but they have been adapted to assess hazard risks prior to departure so that a fleet manager can evaluate the potential risks for a fleet of UAS along their planned flight paths. These services have been integrated into a prototype tool called the Supplemental Data Service Provider-Consolidated Dashboard (SDSP-CD), developed at NASA Ames Research Center. The tool consists of a dashboard which provides a comprehensive overview for a number of risks and a map display that shows the details of the hazards along each flight’s path. Based on the findings from three previous studies, the SDSP-CD has been updated with new design elements and functions. In this paper, we describe lessons learned from the previous studies, changes made to the interface, and the feedback received during a follow-up usability study. Overall, participants reported that there is a substantial benefit of having a fleet manager use a consolidated dashboard to assess hazards for the vehicles in their fleet and to provide situational awareness to potential risks so that they can be mitigated prior to flight. Once the SDSP-CD matures, it will need to be integrated into flight and mission planning tools. Some initial thoughts on how this integration should be accomplished are shared in this paper. Finally, the functional differences between preflight vs. in-flight risk assessment and the differences in fleet manager vs. UAS pilot roles that may require different information and user interactions are discussed.

preflight↗
NASA NTRS2000

Separation of Atmospheric and Surface Spectral Features in Mars Global Surveyor Thermal Emission Spectrometer (TES) Spectra

We present two algorithms for the separation of spectral features caused by atmospheric and surface components in Thermal Emission Spectrometer (TES) data. One algorithm uses radiative transfer and successive least squares fitting to find spectral shapes first for atmospheric dust, then for water-ice aerosols, and then, finally, for surface emissivity. A second independent algorithm uses a combination of factor analysis, target transformation, and deconvolution to simultaneously find dust, water ice, and surface emissivity spectral shapes. Both algorithms have been applied to TES spectra, and both find very similar atmospheric and surface spectral shapes. For TES spectra taken during aerobraking and science phasing periods in nadir-geometry these two algorithms give meaningful and usable surface emissivity spectra that can be used for mineralogical identification.

Smith, Michael D.↗
NASA NTRS2017

The NASA Ames Life Sciences Data Archive: Biobanking for the Final Frontier

The NASA Ames Institutional Scientific Collection involves the Ames Life Sciences Data Archive (ALSDA) and a biospecimen repository, which are responsible for archiving information and non-human biospecimens collected from spaceflight and matching ground control experiments. The ALSDA also manages a biospecimen sharing program, performs curation and long-term storage operations, and facilitates distribution of biospecimens for research purposes via a public website (https:lsda.jsc.nasa.gov). As part of our best practices, a tissue viability testing plan has been developed for the repository, which will assess the quality of samples subjected to long-term storage. We expect that the test results will confirm usability of the samples, enable broader science community interest, and verify operational efficiency of the archives. This work will also support NASA open science initiatives and guides development of NASA directives and policy for curation of biological collections.

Biobank↗
NASA NTRS1996

Evolving the Reuse Process at the Flight Dynamics Division (FDD) Goddard Space Flight Center

This paper presents the interim results from the Software Engineering Laboratory's (SEL) Reuse Study. The team conducting this study has, over the past few months, been studying the Generalized Support Software (GSS) domain asset library and architecture, and the various processes associated with it. In particular, we have characterized the process used to configure GSS-based attitude ground support systems (AGSS) to support satellite missions at NASA's Goddard Space Flight Center. To do this, we built detailed models of the tasks involved, the people who perform these tasks, and the interdependencies and information flows among these people. These models were based on information gleaned from numerous interviews with people involved in this process at various levels. We also analyzed effort data in order to determine the cost savings in moving from actual development of AGSSs to support each mission (which was necessary before GSS was available) to configuring AGSS software from the domain asset library. While characterizing the GSS process, we became aware of several interesting factors which affect the successful continued use of GSS. Many of these issues fall under the subject of evolving technologies, which were not available at the inception of GSS, but are now. Some of these technologies could be incorporated into the GSS process, thus making the whole asset library more usable. Other technologies are being considered as an alternative to the GSS process altogether. In this paper, we outline some of issues we will be considering in our continued study of GSS and the impact of evolving technologies.

Condon, S.↗
DOE OSTI2025

Exploring Electrode-Level State-of-Charge and State-of-Health Dynamics in Lithium-Ion Battery Cells: Modeling and Experimental Identification

A computationally efficient model serves as a critical prerequisite for battery performance analysis and advanced battery management algorithm design. Although battery models that capture cell-level behavior have been widely explored in existing literature, electrode-level battery models have received much lesser attention till to date. However, such electrode-level models can significantly increase battery performance and life by enabling electrode-level health-conscious control. Such electrode-level control can effectively expand usable energy and power limits of the battery cells by utilizing the knowledge of individual electrodes' charge and health. In this context, this paper presents a comprehensive battery model developed with a reference electrode insertion that captures (i) electrode-level charge/discharge dynamics, (ii) stoichiometric and temporal dependencies of electrode-level resistances, (iii) solid electrolyte interface (SEI) layer growth as key degradation phenomenon, and (iv) capacity fade and resistance rise in each electrode due to nominal battery aging. The proposed model is identified, and a preliminary validation is performed utilizing terminal voltage and negative electrode potential data collected from a pouch cell under one continuous cycling and accelerated aging conditions where the cell experienced 14% capacity loss.

aging↗
NASA NTRS2015

Laser Spectroscopy Multi-Gas Monitor: Results of Technology Demonstration on ISS

Tunable diode laser spectroscopy (TDLS) is an up and coming trace and major gas monitoring technology with unmatched selectivity, range and stability. The technology demonstration of the 4 gas Multi-Gas Monitor (MGM), reported at the 2014 ICES conference, operated continuously on the International Space Station (ISS) for nearly a year. The MGM is designed to measure oxygen, carbon dioxide, ammonia and water vapor in ambient cabin air in a low power, relatively compact device. While on board, the MGM experienced a number of challenges, unplanned and planned, including a test of the ammonia channel using a commercial medical ammonia inhalant. Data from the unit was downlinked once per week and compared with other analytical resources on board, notably the Major Constituent Analyzer (MCA), a magnetic sector mass spectrometer. MGM spent the majority of the time installed in the Nanoracks Frame 2 payload facility in front breathing mode (sampling the ambient environment of the Japanese Experiment Module), but was also used to analyze recirculated rack air. The capability of the MGM to be operated in portable mode (via internal rechargeable lithium ion polymer batteries or by plugging into any Express Rack 28VDC connector) was a part of the usability demonstration. Results to date show unprecedented stability and accuracy of the MGM vs. the MCA for oxygen and carbon dioxide. The ammonia challenge (approx. 75 ppm) was successful as well, showing very rapid response time in both directions. Work on an expansion of capability in a next generation MGM has just begun. Combustion products and hydrazine are being added to the measurable target analytes. An 8 to 10 gas monitor (aka Gas Tricorder 1.0) is envisioned for use on ISS, Orion and Exploration missions.

Mudgett, Paul D.↗