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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 NTRS1987

Acquisition-Management Program

NASA Acquisition Management Subsystem (AMS) program integrated NASA-wide standard automated-procurement-system program developed in 1985. Designed to provide each NASA installation with procurement data-base concept with on-line terminals for managing, tracking, reporting, and controlling contractual actions and associated procurement data. Subsystem provides control, status, and reporting for various procurement areas. Purpose of standardization is to decrease costs of procurement and operation of automatic data processing; increases procurement productivity; furnishes accurate, on-line management information and improves customer support. Written in the ADABAS NATURAL.

Avery, Don E.↗

NASA NTRS1992

Automation of the targeting and reflective alignment concept

The automated alignment system, described herein, employs a reflective, passive (requiring no power) target and includes a PC-based imaging system and one camera mounted on a six degree of freedom robot manipulator. The system detects and corrects for manipulator misalignment in three translational and three rotational directions by employing the Targeting and Reflective Alignment Concept (TRAC), which simplifies alignment by decoupling translational and rotational alignment control. The concept uses information on the camera and the target's relative position based on video feedback from the camera. These relative positions are converted into alignment errors and minimized by motions of the robot. The system is robust to exogenous lighting by virtue of a subtraction algorithm which enables the camera to only see the target. These capabilities are realized with relatively minimal complexity and expense.

Redfield, Robin C.↗

NASA NTRS2001

Improvements in AVHRR Daytime Cloud Detection Over the ARM NSA Site

Clouds play an important role in the radiation budget over Arctic and Antarctic. Because of limited surface observing capabilities, it is necessary to detect clouds over large areas using satellite imagery. At low and mid-latitudes, satellite-observed visible (VIS; 0.65 micrometers) and infrared (IR; 11 micrometers) radiance data are used to derive cloud fraction, temperature, and optical depth. However, the extreme variability in the VIS surface albedo makes the detection of clouds from satellite a difficult process in polar regions. The IR data often show that the surface is nearly the same temperature or even colder than clouds, further complicating cloud detection. Also, the boundary layer can have large areas of haze, thin fog, or diamond dust that are not seen in standard satellite imagery. Other spectral radiances measured by satellite imagers provide additional information that can be used to more accurately discriminate clouds from snow and ice. Most techniques currently use a fixed reflectance or temperature threshold to decide between clouds and clear snow. Using a subjective approach, Minnis et al. (2001) found that the clear snow radiance signatures vary as a function of viewing and illumination conditions as well as snow condition. To routinely process satellite imagery over polar regions with an automated algorithm, it is necessary to account for this angular variability and the change in the background reflectance as snow melts, vegetation grows over land, and melt ponds form on pack ice. This paper documents the initial satellite-based cloud product over the Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) site at Barrow for use by the modeling community. Cloud amount and height are determined subjectively using an adaptation of the methodology of Minnis et al. (2001) and the radiation fields arc determined following the methods of Doelling et al. (2001) as applied to data taken during the Surface Heat and Energy Budget of the Arctic (SHEBA). The procedures and data produced in this empirically based analysis will also facilitate the development of the automated algorithm for future processing of satellite data over the ARM NSA domain. Results are presented for May, June, and July 1998. ARM surface data are use to partially validate the results taken directly over the ARM site.

Chakrapani, V.↗

NASA NTRS2006

In-Vacuum Photogrammetry of a Ten-Meter Square Solar Sail

Solar sailing is a promising, future in-space propulsion method that uses the small force of reflecting sunlight to accelerate a large, reflective membrane without expendable propellants. One of two solar sail configurations under development by NASA is a striped net approach by L'Garde, Inc. This design uses four inflatably deployed, lightweight booms supporting a network of thin strings onto which four quadrants of ultrathin aluminized membranes are attached. The NASA Langley Research Center (LaRC) provided both experimental and analytical support to L'Garde for validating the structural characteristics of this unique, ultralightweight spacecraft concept. One of LaRC's responsibilities was to develop and apply photogrammetric methods to measure sail shape. The deployed shape provides important information for validating the accuracy of finite-element modeling techniques. Photogrammetry is the science and art of calculating 3D coordinates of targets or other distinguishing features on structures using images. A minimum of two camera views of each target is required for 3D determination, but having four or more camera views is preferable for improved reliability and accuracy. Using retroreflective circular targets typically provides the highest measurement accuracy and automation. References 3 and 4 provide details of photogrammetry technology, and reference 5 discusses previous experiences with photogrammetry for measuring gossamer spacecraft structures such as solar sails. This paper discusses the experimental techniques used to measure a L Garde 10-m solar sail test in vacuum with photogrammetry. The test was conducted at the NASA-Glenn Space Power Facility (SPF) located at Plum Brook Station in Sandusky, Ohio. The SPF is the largest vacuum chamber in the United States, measuring 30 m in diameter by 37 m in height. High vacuum levels (10(exp -6) torr) can be maintained inside the chamber, and cold environments (-195 C) are possible using variable-geometry cryogenic cold walls. This test used a vacuum level of approximately 1 torr (sufficient for structural static/dynamic characterization) and instead of using the cryogenic cold walls, used local LN2 cold plates underneath each of the four cold-rigidizable solar sail booms instead.

Pappa, Richard S.↗

NASA NTRS2009

Formal Methods for Automated Diagnosis of Autosub 6000

This is a progress report on applying formal methods in the context of building an automated diagnosis and recovery system for Autosub 6000, an Autonomous Underwater Vehicle (AUV). The diagnosis task involves building abstract models of the control system of the AUV. The diagnosis engine is based on Livingstone 2, a model-based diagnoser originally built for aerospace applications. Large parts of the diagnosis model can be built without concrete knowledge about each mission, but actual mission scripts and configuration parameters that carry important information for diagnosis are changed for every mission. Thus we use formal methods for generating the mission control part of the diagnosis model automatically from the mission script and perform a number of invariant checks to validate the configuration. After the diagnosis model is augmented with the generated mission control component model, it needs to be validated using verification techniques.

Ernits, Juhan↗

NASA NTRS2010

Mars Terrain Generation

A suite of programs for the generation of disparity maps from stereo image pairs via correlation, and conversion of those disparity maps to XYZ maps, has been updated. This suite implements an automated method of deriving terrain from stereo images for use in the ground data system for in-situ (lander and rover) cameras. This differs from onboard correlation by concentrating more on accuracy than speed, since near-real-time is not a requirement on the ground. The final result is an XYZ value for every point in the image that passes several quality checks. A priori geometric camera calibration information is required for this suite to operate. The suite is very flexible, enabling its use in many special situations, such as non-linearized images required for applications like the Phoenix arm camera, or long-baseline stereo, where the rover moves between left and right images.

Deen, Robert G.↗

NASA NTRS2013

Analysis-Driven Design Optimization of a SMA-Based Slat-Cove Filler for Aeroacoustic Noise Reduction

Airframe noise is a significant component of environmental noise in the vicinity of airports. The noise associated with the leading-edge slat of typical transport aircraft is a prominent source of airframe noise. Previous work suggests that a slat-cove filler (SCF) may be an effective noise treatment. Hence, development and optimization of a practical slat-cove-filler structure is a priority. The objectives of this work are to optimize the design of a functioning SCF which incorporates superelastic shape memory alloy (SMA) materials as flexures that permit the deformations involved in the configuration change. The goal of the optimization is to minimize the actuation force needed to retract the slat-SCF assembly while satisfying constraints on the maximum SMA stress and on the SCF deflection under static aerodynamic pressure loads, while also satisfying the condition that the SCF self-deploy during slat extension. A finite element analysis model based on a physical bench-top model is created in Abaqus such that automated iterative analysis of the design could be performed. In order to achieve an optimized design, several design variables associated with the current SCF configuration are considered, such as the thicknesses of SMA flexures and the dimensions of various components, SMA and conventional. Designs of experiment (DOE) are performed to investigate structural response to an aerodynamic pressure load and to slat retraction and deployment. DOE results are then used to inform the optimization process, which determines a design minimizing actuator forces while satisfying the required constraints.

Scholten, William↗

NASA NTRS2020

DEVELOP Poster: Louisville Urban Development

Greenness and land surface temperature (LST) have been extensively correlated to urban public health. Chronic diseases such as diabetes, asthma, and cardiovascular illnesses have been linked to regions of high LST and areas lacking urban green spaces. One of our partners, the University of Louisville Envirome Institute, champions the importance of urban green spaces. Their research has pioneered efforts in increasing the area and accessibility of urban parks and greenspaces as a way to improve public health and combat environmental inequality. Louisville, Kentucky, is currently working to plant and manage urban trees. Our team used NASA Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) imagery to calculate the Normalized Difference Vegetation Index (NDVI) in Louisville at the census tract level and automated the process for use in other cities. The New York University School of Medicine’s City Health Dashboard displays public health metrics across 500 US cities and will use our methods to complete the NDVI analysis for all of these locations plus an additional 293 cities they are adding to their dashboard in the near future. Our NDVI and LST calculations will allow cites across the US to make informed decisions about reducing environmental inequality by focusing on areas with low NDVI and high LST.

Urban Development↗

NASA NTRSDate not supplied

Reducing Barriers in Space Weather Research and Operations with Next-Generation Simulation Services at the Community Coordinated Modeling Center (CCMC)

Space weather forecasting capabilities are becoming increasingly important to the health of advanced technological infrastructure. The Community Coordinated Modeling Center (CCMC, https://ccmc.gsfc.nasa.gov) serves as a key liaison in the US space weather program between the research and operations communities by providing a wide range of tools and capabilities that help to evaluate, compare, exercise, and archive the results of simulations of a growing list of space weather models. With its unique toolset, CCMC supports space weather research and model development that advances our understanding of space weather phenomena and improves forecasting skill, while also facilitating development of space weather applications and deployment of operational capabilities. Guided by experience from over 20 years of providing simulation services, feedback from its research, operational and educational users world-wide, recommendations from CCMC Advisory Group and Programmatic Review Panel, the CCMC has begun work on the next generation system for its simulation services and model output archives. The new system has been envisioned to employ state-of-the-art technologies and standards to provide a user-oriented experience while improving ease of access, transparency, interoperability with partner systems, and enhancing reliability by incorporating advanced automation for performance monitoring and intelligent failover. In the presentation, we will give an overview of the current CCMC ecosystem and discuss updates to some of the key services of the system, including Runs-on-Request, Instant Runs, and Continuous Runs. We will also describe how a planned expansion and standardization of data archival activities will enhance the role of CCMC as a world-class provider of heliophysics information for the research and analysis of space weather. It is our hope that this evolution of the services can further reduce the barriers and burdens on researchers, forecasters and decision makers who rely on CCMC for their daily research and operations.

Space Weather↗

NASA NTRS2002

Mining Marketing Data

MarketMiner(R) Products, a line of automated marketing analysis tools manufactured by MarketMiner, Inc., can benefit organizations that perform significant amounts of direct marketing. MarketMiner received a Small Business Innovation Research (SBIR) contract from NASA's Johnson Space Center to develop the software as a data modeling tool for space mission applications. The technology was then built into the company current products to provide decision support for business and marketing applications. With the tool, users gain valuable information about customers and prospects from existing data in order to increase sales and profitability. MarketMiner(R) is a registered trademark of MarketMiner, Inc.

Source record↗

NASA NTRS2019

EARTHDATA PUB: A Data Publication Workflow Solution for NASA’s EOSDIS

Each NASA Distributed Active Archive Center (DAAC) faces the challenge of dealing with an increasingly diverse number of publishable data products from diverse data producers. Data producers, on the other hand, may experience pain points when interacting with the EOSDIS for the first time or when publishing different data at different DAACs. As a result, there has been a growing need to develop a common software framework that serves as a common interface for data producers, rigorously defines the data publication procedure for DAAC staff, facilitates the management of various data publication processes, and tracks the progress of data publication. This software should also account for the different configurations at different DAACs. Currently, two primary data publication workflow and tracking tools exist in operation at the EOSDIS: Semi-Automated ingest System (SAuS) and Data Publication workflow Portal (DAPPeR). However, neither tool is cloud-ready. Automated data processing could be managed by Cumulus, an EOSDIS cloud-based data ingest, archive and management system. However, Cumulus does not support manual tasks or on-premise implementations. We propose to develop the Earthdata Publication Minimum Viable Product (Earthdata Pub MVP) -- a cloud-hosted solution that works with both cloud and on-premise systems and implements the communications and exchange requirements generated by the Earthdata Pub information architecture team.

Rice, Justin L.↗

NASA NTRS2020

Air Traffic Management TestBed Data Exchange Model

The Air Traffic Management (ATM) TestBed is a Platform as a Service that is being developed by the National Aeronautics and Space Administration (NASA) to help design, configure, integrate, run, and monitor air traffic simulations. The platform is designed to provide cloud services including back-end, big-data analytics tools, on-demand computing resource management, data storage, and communication middleware. The ATM TestBed reduces the time to test concepts and technologies, supports interactions among various methods such as human-in-the-loop and automation-in-the-loop simulations, and enables collaborative simulations by sharing technologies and tools in the ATM community. In order to allow easier access to simulation components, TestBed provides a messaging support layer for connectivity using a consistent set of input/output interfaces. In addition, a standard data format is introduced to facilitate communication between the components. The data exchange model, supported in the messaging support layer, standardizes the format of the information to be exchanged among the components. This document describes the messaging data model currently developed in TestBed and provides data dictionaries for references to component developers as well as simulation engineers.

air traffic simulation↗

NASA NTRS2021

Southwest Water Resources: Monitoring Surface Water Extents of Remote Stock Ponds in the Southwestern United States Using Earth Observing Systems for Enhanced Water Resources Management

Due to increasingly frequent and severe drought conditions in the southwestern US, land managers and livestock producers need to monitor stock ponds with increasing regularity. The ability to assess stock pond water levels with Earth observing satellite systems would enhance monitoring efforts of partners at the US Forest Service, Arizona Department of Game and Fish, and the Diablo Trust. This study employed Landsat 8 Operational Land Imager (OLI), Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), and Sentinel-2 Multispectral Instrument (MSI) to monitor surface water extent for hundreds of critical stock ponds in Arizona. Using methods adapted from previously developed image processing workflows, this project conducted a time-series analysis to capture seasonal and interannual variations in surface water area between 2013 to 2021. In addition, end users can monitor the surface water extent of stock ponds through the developed Google Earth Engine software tool called Surface Water Identification and Forecasting Tool (SWIFT). SWIFT incorporates the Automated Water Extraction Index, Modified Normalized Difference Water Index, and Tasseled Cap-Wetness Index for optical imagery and the incidence angle, VV and VH polarization bands for Sentinel-1 imagery to detect small water bodies in the study area with an overall accuracy range of 88-93%. These tools will empower our partners to monitor the extents of water in their stock ponds remotely, enabling them to develop data-informed and sustainable management solutions for decades to come.

Rainey Aberle↗

NASA NTRS2022

Integrating FRET with Copilot: Automated Translation of Natural Language Requirements to Runtime Monitors

Runtime verification (RV) enables monitoring systems at runtime, to detect property violations early and limit their potential consequences. To provide the level of assurance required for ultra-critical systems, monitor specifications must faithfully reflect the original mission requirements, which are often written in ambiguous natural language. This paper presents an end-to-end framework to capture requirements in structured natural language and generate monitors that capture their semantics faithfully. We leverage NASA’s Formal Requirement Elicitation Tool (FRET), and the RV system Copilot. We extend FRET with mechanisms to capture additional information needed to generate monitors, and introduce OGMA, a new tool to bridge the gap between FRET and Copilot. With this framework, users can write requirements in an intuitive format and obtain real-time C monitors suitable for use in embedded systems. Our tool chain is available as open source.

FRET↗

NASA NTRS1981

A comparison of two methods for classifying forestland

Two methods of developing land-cover classifications using Landsat multispectral data were compared. The first method, called P-1, uses a semi-automated approach to develop training statistics which characterize the land-cover types. The second, called multicluster blocks, depends more on analyst interaction to produce the training statistics used by the classifier. The results showed that P-1 performed as well as the multicluster-blocks approach on a mountainous study area in southwestern Colorado. These results may interest any resource discipline which has available to it ground-checked or photointerpreted information. P-1 can use this information directly to output a land-cover classification with little analyst interaction.

Nelson, R. F.↗

NASA NTRS1982

The status of two- and three-dimensional testing in the University of Southampton transonic self-streamlining wind tunnel

An automated test section was used to develop a flexible walled testing technique which eliminates some sources of uncertainty in boundary interference effects which exist in conventional transonic test sections. The flexible floor and ceiling of the test section were adjusted to contours which produce a constant Mach number distribution along each wall with no model present. These aerodynamically straight contours form the basis for all streamlining. The wall data are to contain information on the models performance and on lift. Two dimensional validation testing has continued with a cambered NPL 9510 section. Lift data up to Mach 0.87 are compared with reference data. Drag information on a NACA 0012-64 section is presented to indicate the powerful effects of streamlining. Preliminary three dimensional testing in the two dimensional test section has demonstrated that model and support blockage can be relieved by wall contouring.

Wolf, S. W. D.↗

NASA NTRS1992

Knowledge-based assistance for science visualization and analysis using large distributed databases

Within this decade, the growth in complexity of exploratory data analysis and the sheer volume of space data require new and innovative approaches to support science investigators in achieving their research objectives. To date, there have been numerous efforts addressing the individual issues involved in inter-disciplinary, multi-instrument investigations. However, while successful in small scale, these efforts have not proven to be open and scaleable. This proposal addresses four areas of significant need: scientific visualization and analysis; science data management; interactions in a distributed, heterogeneous environment; and knowledge-based assistance for these functions. The fundamental innovation embedded within this proposal is the integration of three automation technologies, namely, knowledge-based expert systems, science visualization and science data management. This integration is based on the concept called the Data Hub. With the Data Hub concept, NASA will be able to apply a more complete solution to all nodes of a distributed system. Both computation nodes and interactive nodes will be able to effectively and efficiently use the data services (access, retrieval, update, etc.) with a distributed, interdisciplinary information system in a uniform and standard way. This will allow the science investigators to concentrate on their scientific endeavors, rather than to involve themselves in the intricate technical details of the systems and tools required to accomplish their work. Thus, science investigators need not be programmers. The emphasis will be on the definition and prototyping of system elements with sufficient detail to enable data analysis and interpretation leading to publishable scientific results. In addition, the proposed work includes all the required end-to-end components and interfaces to demonstrate the completed concept.

Handley, Thomas H., Jr.↗

NASA NTRS1996

Cloud identification using genetic algorithms and massively parallel computation

As a Guest Computational Investigator under the NASA administered component of the High Performance Computing and Communication Program, we implemented a massively parallel genetic algorithm on the MasPar SIMD computer. Experiments were conducted using Earth Science data in the domains of meteorology and oceanography. Results obtained in these domains are competitive with, and in most cases better than, similar problems solved using other methods. In the meteorological domain, we chose to identify clouds using AVHRR spectral data. Four cloud speciations were used although most researchers settle for three. Results were remarkedly consistent across all tests (91% accuracy). Refinements of this method may lead to more timely and complete information for Global Circulation Models (GCMS) that are prevalent in weather forecasting and global environment studies. In the oceanographic domain, we chose to identify ocean currents from a spectrometer having similar characteristics to AVHRR. Here the results were mixed (60% to 80% accuracy). Given that one is willing to run the experiment several times (say 10), then it is acceptable to claim the higher accuracy rating. This problem has never been successfully automated. Therefore, these results are encouraging even though less impressive than the cloud experiment. Successful conclusion of an automated ocean current detection system would impact coastal fishing, naval tactics, and the study of micro-climates. Finally we contributed to the basic knowledge of GA (genetic algorithm) behavior in parallel environments. We developed better knowledge of the use of subpopulations in the context of shared breeding pools and the migration of individuals. Rigorous experiments were conducted based on quantifiable performance criteria. While much of the work confirmed current wisdom, for the first time we were able to submit conclusive evidence. The software developed under this grant was placed in the public domain. An extensive user's manual was written and distributed nationwide to scientists whose work might benefit from its availability. Several papers, including two journal articles, were produced.

Buckles, Bill P.↗