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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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NASA NTRS1995

HBCUs Research Conference agenda and abstracts

The purpose of this Historically Black Colleges and Universities (HBCUs) Research conference was to provide an opportunity for principal investigators and their students to present research progress reports. The abstracts included in this report indicate the range and quality of research topics such as aeropropulsion, space propulsion, space power, fluid dynamics, designs, structures and materials being funded through grants from Lewis Research Center to HBCUs. The conference generated extensive networking between students, principal investigators, Lewis technical monitors, and other Lewis researchers.

Dutta, Sunil↗

NASA NTRS1997

HBCUs Research Conference Agenda and Abstracts

The purpose of this Historically Black Colleges and Universities (HBCUS) Research Conference was to provide an opportunity for principal investigators and their students to present research progress reports. The abstracts included in this report indicate the range and quality of research topics such as aeropropulsion, space propulsion, space power, fluid dynamics, designs, structures and materials being funded through grants from Lewis Research Center to HBCUS. The conference generated extensive networking between students, principal investigators, Lewis technical monitors, and other Lewis researchers.

Dutta, Sunil↗

NASA NTRS1998

HBCUs Research Conference Agenda and Abstracts

The purpose of this Historically Black Colleges and Universities (HBCUs) Research Conference was to provide an opportunity for principal investigators and their students to present research progress reports. The abstracts included in this report indicate the range and quality of research topics such as aeropropulsion, space propulsion, space power, fluid dynamics, designs, structures and materials being funded through grants from Lewis Research Center to HBCUs. The conference generated extensive networking between students, principal investigators, Lewis technical monitors, and other Lewis researchers.

Dutta, Sunil↗

NASA NTRS2000

HBCUs/OMUs Research Conference Agenda and Abstracts

The purpose of this Historically Black Colleges and Universities (HBCUs) Research Conference was to provide an opportunity for principal investigators and their students to present research progress reports. The Abstracts included in this report indicate the range and quality of research topics such as aeropropulsion, space propulsion, space power, fluid dynamics, designs, structures and materials being funded through grants from Glenn Research Center to HBCUs. The conference generated extensive networking between students, principal investigators, Glenn technical monitors, and other Glenn researchers.

Dutta, Sunil↗

NASA NTRS2001

HBCUs/OMUs Research Conference Agenda and Abstracts

The purpose of this Historically Black Colleges and Universities (HBCUs) Research Conference was to provide an opportunity for principal investigators and their students to present research progress reports. The abstracts included in this report indicate the range and quality of research topics such as aeropropulsion, space propulsion, space power, fluid dynamics, designs, structures and materials being funded through grants from Glenn Research Center to HBCUs. The conference generated extensive networking between students, principal investigators, Glenn technical monitors, and other Glenn researchers.

Dutta, Sunil↗

NASA NTRS2003

HBCUs/OMUs Research Conference Agenda and Abstracts

The purpose of this Historically Black Colleges and Universities (HBCUs/OMUs) Research Conference was to provide an opportunity for principal investigators and their students to present research progress reports. The abstracts included in this report indicate the range and quality of research topics such as aeropropulsion, space propulsion, space power, fluid dynamics, designs, structures and materials being funded through grants from Glenn Research Center to HBCUs. The conference generated extensive networking between students, principal investigators, Glenn technical monitors, and other Glenn researchers.

Dutta, Sunil↗

NASA NTRS2003

On Human Resource Diversity in Distributed Energy Technology

Kalu, A.↗

NASA NTRS2004

Decision Support Tool Evaluation Report for Coral Reef Early Warning System (CREWS) Version 7.0

The Coral Reef Early Warning System (CREWS) is operated by NOAA's Office of Oceanic and Atmospheric Research as part of its Coral Reef Watch program in response to the deteriorating global state of coral reef and related benthic ecosystems. In addition to sea surface temperatures (SSTs), the two most important parameters used by the CREWS network in generating coral reef bleaching alerts are 1) wind speed and direction and 2) photosynthetically available radiation (PAR). NASA remote sensing products that can enhance CREWS in these areas include SST and PAR products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and wind data from the Quick Scatterometer (QuikSCAT). CREWS researchers are also interested in chlorophyll, chromophoric dissolved organic matter (CDOM), and salinity. Chlorophyll and CDOM are directly available as NASA products, while rainfall (an available NASA product) can be used as a proxy for salinity. Other potential NASA inputs include surface reflectance products from MODIS, the Advanced Spaceborne Thermal Emission and Reflection Radiometer, and Landsat. This report also identifies NASA-supported ocean circulation models and products from future satellite missions that might enchance the CREWS DST.

D'Sa, Eurico↗

NASA NTRS2006

Estimating Total Electron Content Using 1,000+ GPS Receivers

A computer program uses data from more than 1,000 Global Positioning System (GPS) receivers in an Internet-accessible global network to generate daily estimates of the global distribution of vertical total electron content (VTEC) of the ionosphere. This program supersedes an older program capable of processing readings from only about 200 GPS receivers. This program downloads the data via the Internet, then processes the data in three stages. In the first stage, raw data from a global subnetwork of about 200 receivers are preprocessed, station by station, in a Kalman-filter-based least-squares estimation scheme that estimates satellite and receiver differential biases for these receivers and for satellites. In the second stage, an observation equation that incorporates the results from the first stage and the raw data from the remaining 800 receivers is solved to obtain the differential biases for these receivers. The only remaining error sources for which an account cannot be given are multipath and receiver noise contributions. The third stage is a postprocessing stage in which all the processed data are combined and used to generate new data products, including receiver differential biases and global and regional VTEC maps and animations.

Komjathy, Attila↗

NASA NTRS2011

Method of Simulating Flow-Through Area of a Pressure Regulator

The flow-through area of a pressure regulator positioned in a branch of a simulated fluid flow network is generated. A target pressure is defined downstream of the pressure regulator. A projected flow-through area is generated as a non-linear function of (i) target pressure, (ii) flow-through area of the pressure regulator for a current time step and a previous time step, and (iii) pressure at the downstream location for the current time step and previous time step. A simulated flow-through area for the next time step is generated as a sum of (i) flow-through area for the current time step, and (ii) a difference between the projected flow-through area and the flow-through area for the current time step multiplied by a user-defined rate control parameter. These steps are repeated for a sequence of time steps until the pressure at the downstream location is approximately equal to the target pressure.

Hass, Neal E.↗

NASA NTRS2017

Millimeter Wave Systems for Airports and Short-Range Aviation Communications: A Survey of the Current Channel Models at mmWave Frequencies

Millimeter-wave (mmWave) communications will play a key role in enhancing the throughput, reliability, and security of next generation wireless networks. These advancements are achieved through the large bandwidth available in this band and through the use of highly directional links that will be used to overcome the large pathloss at these frequencies. Although the terrestrial application of mmWave systems is advancing at a rapid pace, the use of mmWave communication systems in aviation systems or airports is still in its infancy. This can be attributed to the challenges related to radio technology and lack of development, and characterization of mmWave wireless channels for the aviation field and the airport environment. Consequently, one of our goals is to develop methodologies that support mmWave air to ground links, and various links at airports, by applying new localization schemes that allow for application of highly directional links that can be deployed over longer distances despite the high path loss at mmWave frequencies. However, a very thorough understanding of the mmWave channel models are needed to enable such new applications. To this end, in this paper, we present a survey of the current channel models in the mmWave band. The 3-dimensional statistical channel model is also reviewed and its parameters and typical characteristics for this model are identified and computed through simulation for the Boise metropolitan area.

air traffic management↗

NASA NTRS2018

Mission Configuration Tree for the James Webb Space Telescope (JWST)

The GSFC Mission Configuration web-based application is a means of documenting the structure of the many elements used in building each mission that NASA launches, as well as archiving the documents associated with each of these elements and keeping track of suppliers. This includes all available drawings, engineering orders, parts lists, block diagrams, and photos of each system, subsystem, and component. While the information for several of NASA's missions is being input into Mission Configuration, the ten weeks of this project focused on collecting information for the instrument systems of the James Webb Space Telescope. Documents were collected from a database called the Next Generation Integrated Network (NGIN) so that they can eventually be uploaded into the application. From these documents, including drawings and parts lists, a configuration tree was created in Microsoft Visio which showed the relationships between each system, subsystem, and component. When both these documents and the configuration tree are input into Mission Configuration, they will be place into a drill down tree structure, from which drawings and documents can be accessed directly. Mission Configuration also includes search functions that make all parts searchable by keywords such as vendor, part number, taxonomy, and alternate nomenclature. This application is an important resource for providing access to documents related to the components used on each mission. It has created a central repository for information which can be used to benefit Safety & Mission Assurance, but may also be useful across codes. The process of collecting the information and documents to put into Mission Configuration is also allowing for a concise breakdown of information from diverse formats, creating standardization which makes information more readily accessible, while retaining project-specific information that makes it more easily searchable.

Cain, Mary C.↗

NASA NTRS2013

Parameter Estimation for Compact Binary Coalescence Signals with the First Generation Gravitational-Wave Detector Network

Compact binary systems with neutron stars or black holes are one of the most promising sources for ground-based gravitational-wave detectors. Gravitational radiation encodes rich information about source physics; thus parameter estimation and model selection are crucial analysis steps for any detection candidate events. Detailed models of the anticipated waveforms enable inference on several parameters, such as component masses, spins, sky location and distance, that are essential for new astrophysical studies of these sources. However, accurate measurements of these parameters and discrimination of models describing the underlying physics are complicated by artifacts in the data, uncertainties in the waveform models and in the calibration of the detectors. Here we report such measurements on a selection of simulated signals added either in hardware or software to the data collected by the two LIGO instruments and the Virgo detector during their most recent joint science run, including a blind injection where the signal was not initially revealed to the collaboration. We exemplify the ability to extract information about the source physics on signals that cover the neutron-star and black-hole binary parameter space over the component mass range 1M25M and the full range of spin parameters. The cases reported in this study provide a snapshot of the status of parameter estimation in preparation for the operation of advanced detectors.

Aasi, J.↗

NASA NTRS2019

Vortex Radiometry: Fundamental Concepts

Vortex radiometers (VRs) enable communication systems to maximize data throughput by determining when to employ fade mitigation most efficiently. With this information, communication systems can optimize mitigation strategies before actual fades occur. Doing so maximizes the time over which the link is available, and therefore maximizes data throughput. This paper presents the fundamental concepts of vortex radiometry, including the creation of annular beam patterns through the use of orbital angular momentum (OAM). These concepts are simulated on a 100 Mbps (Megabits per second) GEO (Geosynchrous Earth Orbit)-to-ground Ka-Band communication link. During the simulation a noise source traverses across the link, and without VR capabilities the link is disrupted. However, when the situation is repeated with VR capabilities enabled, the antenna is able to increase receiver gain and maintain the link. VRs are uniquely suited to provide communication systems with the ability to optimize receiver parameters and maximize data throughput, making them critical to enabling next generation communication networks.

Orbital Angular Momentum↗

NASA NTRS2018

GEONEX: Progressive Conditional Generative Adversarial Training Using Transfer learning

Obtaining accurate segmentation on large scale images is an open problem in deep learning. The main problem is the amount of labeled data that exists for large scale images. Traditionally, the common solution to this problem is to crop the large images into smaller images to increase the amount of available data and train a Conditional Generative Adversarial Network (CGAN). CGANs are currently the state of the art in image to image translation and provide better accuracy than the traditional method of training a encoder based conv-net architecture to minimize the loss at each pixel. This method can produce noisy and discontinuous images with inaccurate results. We seek to solve this problem by utilizing the concepts of transfer learning and progressive training to create a CGAN that can segment large scale images with a limited amount of labeled data. In transfer learning we recognize that many learned features are applicable to many classes from multiple domains. This introduces the concept of feature reusability, which is the basis for finetuning. Progressive training got its start in training models on the same images at different resolutions. In this work we instead train a GAN on increasing image scales by transferring the weights from the smaller scales to the larger scales. The learned features at the smaller scales are continually reused and applied to larger scales to create a CGAN that can perform accurate segmentation on large scale images. We apply this method to detect building footprints on very high-resolution overhead imagery (e.g Digital Globe and high resolution airborne platforms).

GEONEX↗

NASA NTRSDate not supplied

Analyzing Natural Language Context in Human-Machine Teaming using Supervised Machine Learning

Building a foundation for trustworthiness and trust verification in multi-asset teaming is the research challenge of Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR). The Design Reference Mission (DRM) for ATTRACTOR is a search and rescue mission objective governed by a multi-member team consisting of human and machine operators. A crucial component to the effort is the communication between humans and autonomous agents throughout both planning and execution stages of the mission. Intuitive communication methods and modalities are posited as critical enablers for certifying trust and trustworthiness. This paper reports on the data collection and analysis conducted in support of the Human Informed Natural-language GANs Evaluation (HINGE)project to attain explainable and trusted communication between human-machine assets. Two identically curated image description datasets were acquired for HINGE, both consisting of two unique input modalities (typed vs. verbal) and retrieved in two distinct contexts (general vs. specific). The gathered datasets were assessed and compared using Parts-of-Speech (POS)features, sentence similarity metrics, and linguistic analysis. Then, the datasets were modeled and tested separately and in combination with one another using machine learning algorithms. The comparison and testing results reveal a superior dataset, by which a preferred context and input is understood, for generating image representations of missing persons using a Generative Adversarial Network (GAN).

Bryan A Barrows↗

NASA NTRS2020

Enabling Dynamic Vehicle Analyses With Improved Atmospheric Attenuation Models in Glenn Research Center Communication Analysis Suite

To aid in meeting the NASA objective of returning humans to the Moon, the Glenn Research Center’s Communication Analysis Suite was augmented with two distinct capabilities. The first capability added was the vehicle propagator. This allows the addition of dynamic aircraft and ground vehicles around any celestial body within the solar system during an analysis. This functionality interpolates the position and velocity of the vehicle relative to a celestial body at the time steps analyzed using the type of path and either a series of waypoints or a direction and duration of travel. The implications of this new capability include lunar rovers and/or drones, such as Dragonfly, where the vehicle propagator will analyze the communications architecture. The newly created vehicle propagator is now in use in communications studies for the 2024 lunar missions, simulating the movement of lunar rovers across the Moon’s southern pole. The second capability added was the augmentation of the atmospheric attenuation model. The previous model did not have a uniform low-elevation attenuation model due to the trigonometric approximation for path length and the exponential nature of low-elevation scintillation. User-defined weather parameters were also added to the updated atmospheric attenuation model. The previous model solely used tabular data based upon the season and location of the transmitting antenna. Multiple simulations of the same configuration now return different results based on the differing weather parameters. Cognitive communications analysis efforts can use this second capability to generate neural network training data based on differing weather conditions at utilized ground stations, a critical step in allowing neural networks to learn how weather parameters impact communications performance.

vehicle propagation↗

NASA NTRS2021

Spectral Synthesis for Geostationary Satellite-to-Satellite Translation

Earth-observing satellites carrying multispectral sensors are widely used to monitor the physical and biological states of the atmosphere, land, and oceans. These satellites have different vantage points above the Earth and different spectral imaging bands resulting in inconsistent imagery from one to another. This presents challenges in building downstream applications. What if we could generate synthetic bands for existing satellites from the union of all domains? We tackle the problem of generating synthetic spectral imagery for multispectral sensors as an unsupervised image-to-image translation problem modeled with a variational autoencoder (VAE) and generative adversarial network (GAN) architecture. Our approach introduces a novel shared spectral reconstruction loss to constrain the high-dimensional feature space of multispectral images. Simulated experiments performed by dropping one or more spectral bands show that cross-domain reconstruction outperforms measurements obtained from a second vantage point. Our proposed approach enables the synchronization of multispectral data and provides a basis for more homogeneous remote sensing datasets.

Geostationary satellites↗