SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Research capabilities on speech understanding, speech recognition, and voice control are described. Research activities and the activities which involve text input rather than speech are discussed.
The viewgraph presentation presents an overview of NASA's Supplier Outreach and Process Control (SOPC) and Supplier Risk Initiatives. The discussion of the SOPC examines its importance, current groups who are involved, provides a mission statement, and describes outreach activities and how suppliers are selected. The discussion of the Supplier Risk Initiative examines the variety of ways that integrity, availability, and assurance factor in to supplier risk and describes a new supplier rating program.
On the afternoon of May 17th, 2016, a major landslide event caused at least 92 deaths, with 109 still missing*. The site was rated highly susceptible to landslides in a new global landslide susceptibility map. GPM precipitation data suggest that both antecedent and current rainfall as well as complex topography played a role in the slope failures.
In 2017, the largest recorded dengue outbreak in Sri Lanka’s history occurred. Since then, dengue has continued to threaten national health across Sri Lanka. The development of an effective Early Warning System (EWS) for dengue outbreaks is essential for Sri Lanka’s Ministry of Health to take preventative measures. We propose the use of Graph Neural Networks as EWS. Using earth observational data from NASAs global satellites and dengue incidence data from Sri Lanka s Ministry of Health, we developed a series of traditional and graph representation EWS to forecast Dengue cases across Sri Lanka’s 25 districts between 2013 and 2022. We demonstrate empirically that Graph Neural Networks which incorporate spatiotemporal relations significantly outperform traditional EWS such as Autoregressive Integrated Moving Average (ARIMA), Random Forest, and Long Short-Term Memory (LSTM). Our source code is available on GitHub and will be provided in the final submission.
Standard Research Institute (SRI) has operated a NASA-sponsored team for four years. The SRI Team is concentrating on solving problems in the public transportation area and on developing methods for decreasing the time gap between the development and the marketing of new technology and for aiding the movement of knowledge across industrial, disciplinary, and regional boundaries. The SRI TAT has developed a methodology that includes adaptive engineering of the aerospace technology and commercialization when a market is indicated. The SRI Team has handled highway problems on a regional rather than a state basis, because many states in similar climatic or geologic regions have similar problems. Program exposure has been increased to encompass almost all of the fifty states.
SRI International (SRI) operates an upper-atmospheric research facility in Sondre Stromfjord (Sondrestrom), Greenland. In the past, the facility's remote location and limited logistical support imposed constraints on the research that could be carried out at the site. Campaigns involving multiple instruments were often constrained due to limited space, and experiments requiring coordination with other geographically separated facilities, though possible, were difficult. To provide greater access to the facility, an electronic connection between Sondrestrom and the mainland U.S.A. was established, providing access to the National Science Internet. SRI developed telescience software that sends data from the incoherent scatter radar at the Sondrestrom facility to SRI's offices in Menlo Park, California. This software uses the transmission control protocol (TCP/IP) to transmit the data in near real time between the two locations and the X window system to generate displays of the data in Menlo Park. This is in contrast to using the X window system to display data remotely across a wide-area network. Using CP to transport data over the long distance network has resulted in significantly improved network throughput and latency. While currently used to transport radar data, the telescience software is designed and intended for simultaneous use with other instruments at Sondrestrom and other facilities. Work incorporating additional instruments is currently in progress.
This document is Volume 3 of the final technical report on the work performed by SRI International (SRI) on SRI Project 8600. The document includes source listings for all software developed by SRI under this effort. Since some of our work involved the use of ST-II and the Sun Microsystems, Inc. (Sun) High-Speed Serial Interface (HSI/S) driver, we have included some of the source developed by LBL and BBN as well. In most cases, our decision to include source developed by other contractors depended on whether it was necessary to modify the original code. If we have modified the software in any way, it is included in this document. In the case of the Traffic Generator (TG), however, we have included all the ST-II software, even though BBN performed the integration, because the ST-II software is part of the standard TG release. It is important to note that all the code developed by other contractors is in the public domain, so that all software developed under this effort can be re-created from the source included here.
This presentation describes a project, formal verification of the microcode in the AAMP5 microprocessor, conducted to explore how formal techniques for specification and verification could be introduced into an industrial process. Sponsored by the Systems Validation Branch of NASA Langley and by Collins Commercial Avionics, a division of Rockwell International, it was conducted by Collins and the SRI International Computer Science Laboratory. The project consisted of specifying in the PVS language developed by SRI a portion of a Rockwell proprietary microprocessor, the AAMP5, at both the instruction set and register-transfer levels and using the PVS theorem prover to prove the microcode correct for a representative subset of instructions. While this presentation includes a brief technical overview, its emphasis is on the lessons learned in using PVS for an example of this size and the implications for using formal methods in an industrial setting. The central result of this project was to demonstrate the feasibility of formally specifying a commercial microprocessor and the use of mechanical proofs of correctness to verify microcode. This is particularly significant since the AAMP5 was not designed for formal verification, but to provide a more than three fold performance improvement, by pipelining instruction execution, while remaining object code compatible with the earlier AAMP2. As a consequence, the AAMP5 is one of the most complex microprocessors to which formal methods have been applied. Another key result was the discovery of both actual and seeded errors. Two actual microcode errors were discovered and corrected during development of the formal specification, illustrating the value of simply creating a precise specification. Two seeded errors were systematically uncovered while doing correctness proofs. One of these was an actual error that had been discovered after first fabrication but left in the microcode provided to SRI. The other error was designed to be unlikely to be detected by walkthroughs, testing, or simulation. Several other results emerged during the project, including the ease with which practicing engineers became comfortable with PVS, the need for libraries of general purpose theories, the usefulness of formal specification in revealing errors, the natural fit between formal specification and inspections, the difficulty of selecting the best style of specification for a new problem domain, the high level of assurance provided by proofs of correctness, and the need to engineer proof strategies for reuse.
In general terms, this project aimed at the analysis and design of techniques for very high-speed networking. The formal objectives of the project were to: (1) Identify switch and network technologies for wide-area networks that interconnect a large number of users and can provide individual data paths at gigabit/s rates; (2) Quantitatively evaluate and compare existing and proposed architectures and protocols, identify their strength and growth potentials, and ascertain the compatibility of competing technologies; and (3) Propose new approaches to existing architectures and protocols, and identify opportunities for research to overcome deficiencies and enhance performance. The project was organized into two parts: 1. The design, analysis, and specification of techniques and protocols for very-high-speed network environments. In this part, SRI has focused on several key high-speed networking areas, including Forward Error Control (FEC) for high-speed networks in which data distortion is the result of packet loss, and the distribution of broadband, real-time traffic in multiple user sessions. 2. Congestion Avoidance Testbed Experiment (CATE). This part of the project was done within the framework of the DARTnet experimental T1 national network. The aim of the work was to advance the state of the art in benchmarking DARTnet's performance and traffic control by developing support tools for network experimentation, by designing benchmarks that allow various algorithms to be meaningfully compared, and by investigating new queueing techniques that better satisfy the needs of best-effort and reserved-resource traffic. This document is the final technical report describing the results obtained by SRI under this project. The report consists of three volumes: Volume 1 contains a technical description of the network techniques developed by SRI in the areas of FEC and multicast of real-time traffic. Volume 2 describes the work performed under CATE. Volume 3 contains the source code of all software developed under CATE.
DARTnet provides an excellent environment for executing networking experiments. Since the network is private and spans the continental United States, it gives researchers a great opportunity to test network behavior under controlled conditions. However, this opportunity is not available very often, and therefore a support environment for such testing is lacking. To help remedy this situation, part of SRI's effort in this project was devoted to advancing the state of the art in the techniques used for benchmarking network performance. The second objective of SRI's effort in this project was to advance networking technology in the area of traffic control, and to test our ideas on DARTnet, using the tools we developed to improve benchmarking networks. Networks are becoming more common and are being used by more and more people. The applications, such as multimedia conferencing and distributed simulations, are also placing greater demand on the resources the networks provide. Hence, new mechanisms for traffic control must be created to enable their networks to serve the needs of their users. SRI's objective, therefore, was to investigate a new queueing and scheduling approach that will help to meet the needs of a large, diverse user population in a "fair" way.
A team of US Army Corps of Engineers, Omaha District and Engineering and Support Center, Huntsville, let Propulsion Laboratory (JPL), Stanford Research Institute (SRI), and Montgomery Watson is currently in the process of planning and conducting the largest ever survey at the Former Buckley Field (60,000 acres), in Colorado, by using SRI airborne, ground penetrating, Synthetic Aperture Radar (SAR). The purpose of this survey is the detection of surface and subsurface Unexploded Ordnance (UXO) and in a broader sense the site characterization for identification of contaminated as well as clear areas. In preparation for such a large-scale survey, JPL has been developing advanced algorithms and a high-performance restbed for processing of massive amount of expected SAR data from this site. Two key requirements of this project are the accuracy (in terms of UXO detection) and speed of SAR data processing. The first key feature of this testbed is a large degree of automation and a minimum degree of the need for human perception in the processing to achieve an acceptable processing rate of several hundred acres per day. For accurate UXO detection, novel algorithms have been developed and implemented. These algorithms analyze dual polarized (HH and VV) SAR data. They are based on the correlation of HH and VV SAR data and involve a rather large set of parameters for accurate detection of UXO. For each specific site, this set of parameters can be optimized by using ground truth data (i.e., known surface and subsurface UXOs). In this paper, we discuss these algorithms and their successful application for detection of surface and subsurface anti-tank mines by using a data set from Yuma proving Ground, A7, acquired by SRI SAR.
The objective of this joint NASA Ames/JPL/SRI project was to develop mixed-initiative planning and scheduling technology that would enable more effective and efficient planning of science missions. The original intent behind the project was to have all three organizations work closely on the overall research and technology development objectives. Shortly after the project began, however, the Ames and JPL project members made a commitment to develop and field an operational mixed-initiative planning and scheduling tool called MAPGEN for the 2003 Mars Exploration Rover (MER) mission [Ai-Chang et al. 2003]. Because of the tremendous amounts of time and effort that went into making that tool a success, the Ames and JPL personnel were mostly unavailable for collaboration on the joint objectives of the original proposal. Until November of 2002, SRI postponed work on the project in the hope that the Ames and JPL personnel would be able to find time for the planned collaborative research. During discussions between Dr. Karen Myers (the SRI institutional PI) and Dr. John Bresina (the project PI) during November of 2002, it was mutually agreed that SRI should work independently to achieve some of the research objectives for the project. In particular, Dr. Bresina identified explanation of plans and planner behavior as a critical area for research, based on feedback from demonstrating an initial prototype of MAPGEN to the operational community. For that reason, our focus from November of 2002 through the end of the project was on designing explanation methods to address this need.
Strain Rate Imaging (SRI) is a new echocardiographic technique that allows for the real-time determination of myocardial SR, which may be used for the early and accurate detection of coronary artery disease. We sought to study whether SR is affected by scan line alignment in a computer simulation and an in vivo experiment. Through the computer simulation and the in vivo experiment we generated and validated safe scanning sectors within the ultrasound scan sector and showed that while SRI will be an extremely valuable tool in detecting coronary artery disease there are potential pitfalls for the unwary clinician. Only after accounting for these affects due to angle dependency, can clinicians utilize SRI's potential as a valuable tool in detecting coronary artery disease.
A set of instruments designed to detect the occurance of electrical breakdown was flown on a synchronous-orbit satellite. The LeRC sensors were installed on cables inside the vehicle. Accordingly, they respond to signals coupled into the satellite wiring system. The SRI sensors were located on the exterior of the vehicle and detected the RF noise pulses associated with surface breakdowns. The results of the earlier SRI program are being used to design and develop a set of intrumentation suitable for inclusion as a general piggy-back package for the detection of the onset of satellite charging and breakdowns on synchronous orbit satellites.
Reflectance factor data were acquired with a Landsat band radiometer throughout two growing seasons for corn (Zea mays L.) canopies differing in planting dates, populations, and soil types. Agronomic data collected included leaf area index (LAI), biomass, development stage, and final grain yields. The spectral variable, greenness, was associated with 78 percent of the variation in LAI over all treatments. Single observations of LAI or greenness have limited value in predicting corn yields. The proportions of solar radiation intercepted (SRI) by these canopies were estimated using either measured LAI or greenness. Both SRI estimates, when accumulated over the growing season, accounted for approximately 65 percent of the variation in yields. Models which simulated the daily effects of weather and intercepted solar radiation on growth had the highest correlations to grain yields. This concept of estimating intercepted solar radiation using spectral data represents a viable approach for merging spectral and meteorological data for crop yield models.
Before disclosure in NASA Tech Briefs, reports of new technology are transmitted to the cognizant NASA Field Center Technology Utilization Office (TUO) where they are evaluated for novelty, technical validity and significance, and nonaerospace utility. If uncertainty exists regarding these criteria, the documentation may be forwarded to SRI International for evaluation before recommending publication. From November 1980 to November 1983, some 3,103 technologies were evaluated by SRI. Activities performed and progress made are summarized.
A SIFT reliable aircraft control computer system, designed to meet the ultrahigh reliability required for safety critical flight control applications by use of processor replications and voting, was constructed for SRI, and delivered to NASA Langley for evaluation in the AIRLAB. To increase confidence in the reliability projections for SIFT, produced by a Markov reliability model, SRI constructed a formal specification, defining the meaning of reliability in the context of flight control. A further series of specifications defined, in increasing detail, the design of SIFT down to pre- and post-conditions on Pascal code procedures. Mechanically checked mathematical proofs were constructed to demonstrate that the more detailed design specifications for SIFT do indeed imply the formal reliability requirement. An additional specification defined some of the assumptions made about SIFT by the Markov model, and further proofs were constructed to show that these assumptions, as expressed by that specification, did indeed follow from the more detailed design specifications for SIFT. This report provides an outline of the methodology used for this hierarchical specification and proof, and describes the various specifications and proofs performed.
SRI has assembled an airborne lidar/radiometric instrumentation suite for mapping cirrus cloud distribution and analyzing cirrus cloud optical properties. Operation of upward viewing infrared radiometers from an airborne platform provides the optimum method of measuring high altitude cold cloud radiative properties with minimum interference from the thermal emission by the earth's surface and lower atmospheric components. Airborne installed sensors can also operate over large regional areas including water, urban, and mountain surfaces and above lower atmospheric convective clouds and haze layers. Currently available sensors installed on the SRI Queen Air aircraft are illustrated. Lidar and radiometric data records are processed for real time viewing on a color video screen. A cirrus cloud data example is presented as a black and white reproduction of a color display of data at the aircraft altitude of 12,000 ft, the 8 to 14 micron atmospheric radiation background was equivalent to a blackbody temperature of about -60 C and, therefore, the radiometer did not respond strongly to low density cirrus cloud concentrations detected by the lidar. Cloud blackbody temperatures (observed by radiometer) are shown plotted against midcloud temperatures (derived from lidar observed cloud heights and supporting temperature profiles) for data collected on 30 June and 28 July.