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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

A Study of the Swelling and Bursting of the High Pressure Coupling (HPC) of a Two-Stage Light Gas Gun

• Need for data at muzzle velocities of 7.0 km/s and above to simulate impacts of space debris and naturally occurring meteoroids • The two-stage light gas gun is a well known way of achieving these velocities • There is a danger of significant swelling and even bursting of the HPC (high pressure coupling). • A consistent picture of the swelling and bursting of the HPCs of two Ames two-stage light gas guns is developed, based on the following: 1. Experimental measurements of the swelling and bursting of the HPCs of two two-stage light gas guns. 2. Stress-strain calculations of the swelling and bursting of thick walled steel tubes. 3. Experimental measurements swelling and bursting of thick walled steel tubes. 4. CFD calculations of the maximum pressures in the HPC of a two-stage light gas gun using the code LGGUN. • It is shown that model developed predicts swelling and bursting that agrees reasonably well with measured data. • Hence, it is suggested that the model could be used in the design of a two-stage light gas guns to assess the risk of swelling and bursting and to give maximum suggested operating conditions for an existing gun.

Ballistic Range↗
NASA NTRSDate not supplied

Data Science and the Knowledge Discovery Adventure

This talk will cover the important steps involved in the data science and knowledge discovery process: • Initial fact gathering (interview domain experts, review reports, articles, state-of-the-art) • Identify the problem (prediction, classification, statistical analysis, etc.) • Survey supporting data sources • Understand the data (numerical, categorical, text, sampling rate, data quality issues, etc.) • Selecting relevant features and sources • Acquire the data (set up agreements with the data stewards, APIs to download, etc.) • Merge data sources (temporal, spatial, common key, other ontologies...) • Feature Engineering (non linear domain knowledge or physics-based relationships) • Build data processing pipeline (may need to tap into data stream, develop parallel processing algorithm, federated learning etc.) • Build model and test (tune hyper-parameters, cross validation.) • Analyze/Validate results (do the results make sense. Does it answer the original question). • Deploy/Publish (Monitor and assess benefits)

Data science↗
NASA NTRSDate not supplied

What Went Wrong: A Survey of Wildfire UAS Mishaps through Named Entity Recognition

Increasingly, unmanned aircraft systems (UAS) are being applied to wildfire incidents for tasks such as mapping, aerial ignition, and delivery. As a result, aviation incident reporting systems for wildfires are beginning to accumulate data related to UAS mishaps in wildfire response. In this research, we apply state-of-the-art natural language processing (NLP) techniques to develop a custom Named Entity Recognition (NER) model which extracts entities relevant to safety analysts. The custom NER model is built by fine-tuning an existing Bidirectional Encoder Representations from Transformers (BERT) model, resulting in a generalizable NER model that can extract engineering relevant entities including failure modes, causes, effects, control processes, and recommendations from failure-relevant text. This model performs passably, with a weighted average f1 score of 0.33 across entity types, indicating more labeled training data is needed. Extracted entities are used to form a Failure Modes and Effects Analysis (FMEA)-style survey of wildfire UAS mishaps reported using the SAFECOM system. Similar mishaps are manually clustered and reported as single rows within an FMEA. Foreach cluster, we compute frequency, severity, and overall riskin accordance with FAA standards. This methodology can beapplied as part of a broader safety management system totrack trends in mishaps (e.g., likelihood, severity) and discoverknowledge (e.g., causes, effects) that can be utilized to improvesafety outcomes and system performance.

Machine Learning↗
NASA NTRSDate not supplied

Conjunction Assessment and Deconfliction Paradigm for Co-Located Satellite Constellations With on-Spacecraft “Autonomous” Flight Dynamics Control

Satellite constellations that employ on-spacecraft flight dynamics and conjunction assessment (CA) approaches face particular challenges. First, they must arrange to obtain and upload to the constellation satellite close approach information, such as Conjunction Data Messages, so that their on-board systems will have the data they need to make informed CA decisions. Second, given current latencies in obtaining CA screening information, such systems often cannot obtain dedicated screenings of their proposed maneuvers before they are executed. Third, they usually cannot engage in real time with owner/operators (O/Os) with whom they may come into conjunction, relying instead on pre-arranged courses of action that may or may not fit a given situation well. Despite these difficulties, it is nonetheless possible, as operators such as SpaceX have demonstrated, to operate safely using on-board CA calculations, in the presence of a largely collaborative operating environment. The situation breaks down, however, when two constellations that operate with such a paradigm are placed in the same orbital region and will experience conjunctions with each other. Each may have a vague idea of where the other’s satellites are, or perhaps even a somewhat precise idea if they exchange O/O ephemerides, but neither will know the other’s more immediate maneuver intentions, especially for situations in which they are in a high-risk conjunction with each other and a mitigation maneuver is required. As there is no formalized way for these automated systems to ascertain each other’s intentions for this type of conjunction, it is quite possible that each spacecraft may choose a maneuver that results in the two objects’ colliding. An opportunity to develop a solution to this problem was presented by the NASA “Starling” project, a small experimental constellation developed to demonstrate autonomous satellite control and constellation reconfiguration and for which a launch was obtained that, serendipitously, will place this constellation close to the SpaceX Starlink constellation. Because the NASA constellation is experimental, an extended mission part of the mission has been negotiated to implement and test mechanisms for resolving the problem of co-located constellations with on-board flight dynamics control. For the last eighteen months, a consortium among NASA Ames (the Starling satellite providers), NASA CARA (the Agency organization responsible for conjunction assessment), Space X, and the Department of Commerce (in observer status) has met regularly to assemble a concept of operations for a robust solution to this problem and has developed a prototype ground node that will serve as a needed CA screening and information dispensary. The approach and methods, as well as the active employment of the developed ground node, will be tested both in simulation before actual use and then in actual spacecraft operations, which are anticipated to begin in January 2024. This paper will describe the co-located autonomously-controlled constellation problem and the developed solution in detail, outlining what ground node (i.e., government) infrastructure and features are required, what particular capabilities are needed by the constellations themselves in order to make use of this deconfliction paradigm, and the migration path forward to allow such a capability set to be incorporated by the Department of Commerce’s space traffic coordination system.

Conjunction Assessment↗
NASA NTRS2023

Exploring the Arctic Ocean With Sailing Robots

The Arctic Ocean is changing rapidly as the planet warms, but studying it presents challenges: it’s a remote area that is often covered by sea ice. As CHELLE GENTEMANN, MARISOL GARCÍA-REYES and JORGE VAZQUEZ-CUERVO explain, using autonomous solar-powered sailing robots is a safe, reliable and climate-friendly way to collect the data we need.

Arctic↗
NASA NTRSDate not supplied

Development and Application of a Novel Calorimetry Technique for the Study of Lithium-Ion Cell Thermal Runaway

Lithium-ion battery technology is widely used and is attractive due to demonstrated specific energies in the 200-300 W-hr/kg range. The excellent, mass-efficient energy storage capability of lithium-ion batteries has led to their use on many aerospace platforms. However, lithium-ion batteries can exhibit thermal runaway behavior wherein stored electrochemical energy is released rapidly as a result of thermal or mechanical failure, electrochemical abuse, internal or external short circuiting. A single cell undergoing thermal runaway within a battery has the potential to induce thermal runaway in adjacent cells if heat dissipation is not properly managed and can result in a catastrophic failure of the battery. Designing batteries that are resistant to thermal runaway propagation requires an understanding of, not only, total energy yield but also the means by which that energy is liberated from the cell. While Accelerating Rate Calorimetry and other techniques provide total thermal runaway energy yield, they do not provide the fractional breakdown of energy liberated via conduction through the cell casing from that which is vented from the cell as hot gases and effluents. Such data are needed to inform battery thermal design and analysis. To measure the total energy yield, the fraction conducted through the cell casing, and the fraction lost due to gases and effluents, NASA developed Fractional Thermal Runaway Calorimetry (FTRC). Two calorimeters have been developed and demonstrated, the Small-format- and Large-format Fractional Thermal Runaway Calorimeters (S-FTRC and L-FTRC, respectively). The technique has been successfully applied to small- and large-format cells (2.4-3.5 Ah and >100 Ah capacity, respectively) and has given new insights into Li-ion cell thermal runaway. Development of the calorimeters is discussed and results from the initial thermal runaway testing campaigns are presented.

Lithium-Ion Cell↗
NASA NTRSDate not supplied

Towards an Aviation Large Language Model by Fine-tuning and Evaluating Transformers

In the aviation domain, there are many applications for machine learning and artificial intelligence tools that utilize natural language. For example, there is a desire to know the commonalities in written safety reports such as voluntary post incidents reports or aerial wildfire operations reports to better understand the risks present. Another use-case is the possibility of extracting airspace procedures and constraints currently written in documents such as Letters of Agreement. These applications can benefit from the use of state-of-the-art natural language processing techniques when adapted to the language/phraseology specific to the aviation domain. This paper evaluates the viability of adaptation of NLP tools to the aviation domain by fine-tuning transformer based models using aviation data sets. In 2018, a novel language model based on neural units (also called transformers) was created and became known as “Bidirectional Encoder Representations from Transformers” or BERT. This architecture combined with large amounts of English training data and innovative semi-supervised training tasks set the standard for what would later emerge as Large Language Models. The performance of these models was further improved by hyperparameter tuning and refinement of the semi-supervised training task and resulted in “Robustly Optimized BERT Pre-training Approach through hyperparameter tuning” or RoBERTa models. These pre-trained Large Language Models proved to be useful for a wide variety of natural language processing tasks such as text classification and question answering through a process called fine-tuning. The transformer architecture with pre-trained weights served as the basis with the last few layers replaced with layers fine-tuned to perform a new task e.g., a layer that provides a label for the entire input text. This process of fine-tuning can also be used to adapt the models to new domains; e.g., BioBERT started with the pre-trained BERT model and was completed by additional fine-tuning and training on biomedical documents. Transformer-based architectures can also be used to create rich representations of text called embeddings which can serve as the input to other machine learning models. This allows simpler algorithms such as logistic regression to use context-rich representations of the text while still remaining quick to train and evaluate. In the world of aviation, there is a growing demand for natural language processing and understanding but the domain presents unique challenges. Due to the technical content (and specialized language) of most aviation documents, fine-tuning pre-trained Large Language Models to specific tasks has not met the benchmark on natural language processing tasks set by simpler models trained from scratch on the data. To address this deficiency, this paper evaluates the improvements from fine-tuning a Large Language Model on a large set of aviation documents using the original semi-supervised training tasks before performing specific natural language tasks. In fine-tuning, a domain-specific dataset is used on the original training task but with the pre-trained Large Language Model instead of starting from a random initialization. This approach allows the model to be adapted to the specific domain language without discarding the information gained from training on general English data. This paper utilized two major dataset types to train and assess the RoBERTa fine-tuning performance. The first are 7,057 Letters of Agreement which are Federal Aviation Administration (FAA) documents that formalize airspace operations across the national airspace system. They contain many examples of ‘aviation English’ using domain specific terminology and phrasing which serves as a representative basis to perform the semi-supervised fine-tuning. The second type is the 494 document classification labels to be used for evaluation. This down-stream evaluation aims to show the performance of the fine-tuned model, better understand how much data is needed for an effective fine-tuning, and how fine-tuning can be adapted for different applications in-the domain. After semi-supervised training, evaluation begins by encoding the documents for classification using the fine-tuned RoBERTa model. Then a logistic regression classifier is trained to label the document type and compared against our ground truth labels. This currently leads to a 82.8% accuracy on 10-fold cross validation showing improvement over baseline RoBERTa which achieved 81.0%. We plan to measure the improvements on additional tasks and it is expected that these improvements will lead to more robust models that can tackle the natural language processing challenges present in aviation datasets.

ATM↗
NASA NTRS2024

Mars Climate Monitoring Mission

For future missions to Mars, Nasa wants a better understanding of the regular weather patterns on Mars. Current models of martian weather are not up to the task of predicting weather that could impair future martian prospects. To improve our models, we need accurate data, measured directly from orbiters or surface stations, like rovers or probes. One solution is to send a web of permanent surface weather stations to various locations on the surface, in order to get accurate data about large-scale martian weather patterns. Such data could be used to improve our models which could greatly aid in improving the safety of future exploration. Such a mission, though, would have countless moving parts, from launch till landing. We created this short animation to demonstrate how such a mission might be carried out, what it might tell us, and how that information could prove critically useful for future martian exploration, including human missions to the surface.

Mars↗
NASA NTRS2024

Zonal and Regional Jupiter Brightness Trends from the Hubble Outer Planet Atmospheres Legacy Program

The Hubble Outer Planet Atmospheres Legacy (OPAL) program began in 2014 and has observed Jupiter yearly from 2015 to 2024. Using high spatial resolution imaging from the Hubble Wide Field Camera 3, brightness trends were investigated focusing on the unique UV capability and absolute calibration consistency of the Hubble Space Telescope. From these data, a 4- to 5- year period is observed at 24° N, particularly in the blue (F395N) and methane gas absorption (FQ889N) filters. Additionally, several wavelengths show a potential seasonal periodicity, especially at the equator, but more years of data are needed to confirm this trend over multiple Jupiter years. Variability in Oval BA and the Great Red Spot brightness is not cyclical, but these two anticyclonic features show changes on a yearly timescale.

Amy A Simon↗
NASA NTRS2004

Lapin Data Interchange Among Database, Analysis and Display Programs Using XML-Based Text Files

The purpose was to investigate and evaluate the interchange of application- specific data among multiple programs each carrying out part of the analysis and design task. This has been carried out previously by creating a custom program to read data produced by one application and then write that data to a file whose format is specific to the second application that needs all or part of that data. In this investigation, data of interest is described using the XML markup language that allows the data to be stored in a text-string. Software to transform output data of a task into an XML-string and software to read an XML string and extract all or a portion of the data needed for another application is used to link two independent applications together as part of an overall design effort. This approach was initially used with a standard analysis program, Lapin, along with standard applications a standard spreadsheet program, a relational database program, and a conventional dialog and display program to demonstrate the successful sharing of data among independent programs. See Engineering Analysis Using a Web-Based Protocol by J.D. Schoeffler and R.W. Claus, NASA TM-2002-211981, October 2002. Most of the effort beyond that demonstration has been concentrated on the inclusion of more complex display programs. Specifically, a custom-written windowing program organized around dialogs to control the interactions have been combined with an independent CAD program (Open Cascade) that supports sophisticated display of CAD elements such as lines, spline curves, and surfaces and turbine-blade data produced by an independent blade design program (UD0300).

Source record↗
NASA NTRS2005

Lapin Data Interchange Among Database, Analysis and Display Programs Using XML-Based Text Files

The purpose of grant NCC3-966 was to investigate and evaluate the interchange of application-specific data among multiple programs each carrying out part of the analysis and design task. This has been carried out previously by creating a custom program to read data produced by one application and then write that data to a file whose format is specific to the second application that needs all or part of that data. In this investigation, data of interest is described using the XML markup language that allows the data to be stored in a text-string. Software to transform output data of a task into an XML-string and software to read an XML string and extract all or a portion of the data needed for another application is used to link two independent applications together as part of an overall design effort. This approach was initially used with a standard analysis program, Lapin, along with standard applications a standard spreadsheet program, a relational database program, and a conventional dialog and display program to demonstrate the successful sharing of data among independent programs. Most of the effort beyond that demonstration has been concentrated on the inclusion of more complex display programs. Specifically, a custom-written windowing program organized around dialogs to control the interactions have been combined with an independent CAD program (Open Cascade) that supports sophisticated display of CAD elements such as lines, spline curves, and surfaces and turbine-blade data produced by an independent blade design program (UD0300).

Source record↗
NASA NTRS1992

Sensitivity of wildlife habitat models to uncertainties in GIS data

Decision makers need to know the reliability of output products from GIS analysis. For many GIS applications, it is not possible to compare these products to an independent measure of 'truth'. Sensitivity analysis offers an alternative means of estimating reliability. In this paper, we present a CIS-based statistical procedure for estimating the sensitivity of wildlife habitat models to uncertainties in input data and model assumptions. The approach is demonstrated in an analysis of habitat associations derived from a GIS database for the endangered California condor. Alternative data sets were generated to compare results over a reasonable range of assumptions about several sources of uncertainty. Sensitivity analysis indicated that condor habitat associations are relatively robust, and the results have increased our confidence in our initial findings. Uncertainties and methods described in the paper have general relevance for many GIS applications.

Stoms, David M.↗
NASA NTRSDate not supplied

Bringing Research to New Heights: How CASEI Integrates Data Curation, Discovery, and Education in Earth and Atmospheric Science

A challenging aspect of any project is finding all the relevant data and information needed to address the research objective. Searching for data and its contextual metadata can become overwhelming for both undergraduate and graduate students, potentially hindering their work and affecting the scientific discoveries that could be made in the long run. To ease this, the NASA Airborne Data Management Group (ADMG), part of the Interagency Implementation and Advanced Concepts Team (IMPACT), has developed the new Catalog of Archived Suborbital Earth science Investigations (CASEI). CASEI includes a web portal that users, be they professionals or students, can use to search, browse, discover, and locate relevant observations associated with NASA’s airborne and field campaigns. Users are able to query data in a variety of ways (via keywords, locations, timeframe, etc) from one online portal, minimizing the amount of time needed to search. CASEI also allows access to key contextual metadata and data from a wide array of Earth and Atmospheric Science topics such as aerosols and boundary layer processes, as well as ice and glacial properties or processes. Users are able to access the data via DOI links to data set landing pages. This presentation will demonstrate how CASEI can be used for classwork and student research. Teachers can provide CASEI to their students as a tool for their studies, or use it to find data themselves while constructing their curriculums. Additionally, users can leverage CASEI to learn about NASA’s Earth and Atmospheric Science research efforts and to find data relevant for assignments or other research projects. The metadata in CASEI has been carefully curated, and highlights important information about the campaigns and their data. Students can explore and learn about the scientific objectives of the campaigns, as well as descriptions of the campaign’s best research days. Having access to contextual metadata in an easy to understand way can help plant the seeds of new ideas in students at any point in their academic journey. From class projects to theses/dissertations and other research, CASEI is a valuable emerging tool for data discovery, giving access to all users and guiding researchers to NASA’s unique airborne data to answer the burning Earth Science questions of our time.

education↗
NASA NTRS2014

Centering a DDR Strobe in the Middle of a Data Packet

The Orion CEV Northstar ASIC (application- specific integrated circuit) project required a DDR (double data rate) memory bus driver/receiver (DDR PHY block) to interface with external DDR memory. The DDR interface (JESD79C) is based on a source synchronous strobe (DQS\) that is sent along with each packet of data (DQ). New data is provided concurrently with each edge of strobe and is sent irregularly. In order to capture this data, the strobe needs to be delayed and used to latch the data into a register. A circuit solves the need for training a DDR PRY block by incorporating a PVT-compensated delay element in the strobe path. This circuit takes an external reference clock signal and uses the regular clock to calibrate a known delay through a data path. The compensated delay DQS signal is then used to capture the DQ data in a normal register. This register structure can be configured as a FIFO (first in first out), in order to transfer data from the DDR domain to the system clock domain. This design is different in that it does not rely upon the need for training the system response, nor does it use a PLL (phase locked loop) or a DLL (delay locked loop) to provide an offset of the strobe signal. The circuit is created using standard ASIC building blocks, plus the PVT (process, voltage, and temperature) compensated delay line. The design uses a globally available system clock as a reference, alleviating the need to operate synchronously with the remote memory. The reference clock conditions the PVT compensated delay line to provide a pre-determined amount of delay to any data signal that passes through this delay line. The delay line is programmed in degrees of offset, so that one could think of the clock period representing 360deg of delay. In an ideal environment, delaying the strobe 1/4 of a clock cycle (90deg) would place the strobe in the middle of the data packet. This delayed strobe can then be used to clock the data into a register, satisfying setup and hold requirements of the system.

Johnson, Michael↗
NASA NTRS1974

Procedures and results related to the direct determination of gravity anomalies from satellite and terrestrial gravity data

The equations needed for the incorporation of gravity anomalies as unknown parameters in an orbit determination program are described. These equations were implemented in the Geodyn computer program which was used to process optical satellite observations. The arc dependent parameter unknowns, 184 unknown 15 deg and coordinates of 7 tracking stations were considered. Up to 39 arcs (5 to 7 days) involving 10 different satellites, were processed. An anomaly solution from the satellite data and a combination solution with 15 deg terrestrial anomalies were made. The limited data samples indicate that the method works. The 15 deg anomalies from various solutions and the potential coefficients implied by the different solutions are reported.

Rapp, R. H.↗
NASA NTRS1984

Measurements of vertical velocity over flat terrain by ST radar and other related uses of the radar data set

The need to study vertical velocity measurements from an ST radar located on the plains, far from the mountains is pointed out, as all presently available clear-air radars are located in or near mountains. The construction and operation of a VHF Doppler (ST) radar in the midwestern part of the United States to make meteorological measurements is also discussed. While primary interest is in measuring the synoptic-scale vertical velocities in the troposphere and lower stratosphere, it should be stressed, however, that the radar data set generated during the radar experiment would have many other valuable uses of interest to us and others some of whom are listed below. The required radar parameters, approximate costs, and recommended mode of operation are also detailed.

Green, J. L.↗
NASA NTRS1976

Program on Earth Observation Data Management Systems (EODMS)

An assessment was made of the needs of a group of potential users of satellite remotely sensed data (state, regional, and local agencies) involved in natural resources management in five states, and alternative data management systems to satisfy these needs are outlined. Tasks described include: (1) a comprehensive data needs analysis of state and local users; (2) the design of remote sensing-derivable information products that serve priority state and local data needs; (3) a cost and performance analysis of alternative processing centers for producing these products; (4) an assessment of the impacts of policy, regulation and government structure on implementing large-scale use of remote sensing technology in this community of users; and (5) the elaboration of alternative institutional arrangements for operational Earth Observation Data Management Systems (EODMS). It is concluded that an operational EODMS will be of most use to state, regional, and local agencies if it provides a full range of information services -- from raw data acquisition to interpretation and dissemination of final information products.

Eastwood, L. F., Jr.↗