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At least 541 records · Page 30

NASA's Research & Development in Airspace Management for Drones, Air Taxis, and Beyond

Today's National Airspace System is extremely safe. Multiple people and organizations are involved in the handling of flights at all phases. We are, however, at the dawn of a new era in aviation where new entrants are emerging from multiple domains. These new entrants will need to be integrated into the airspace safely and given the flexibility to scale. With that integration and flexibility comes the need and responsibility to develop concepts and systems that will work with the regulatory and operational needs of the Federal Aviation Administration while accounting for the needs of industry. NASA is at the leading edge of research, development, and testing across multiple domains to enable the realization of new entrants such as drones, air cargo and taxis, and high altitude vehicles. Addressing the potential for public good coming from these new capabilities is also a NASA focus area. While there has been considerable effort in the engineering aspects of this research, another thrust that is of importance is that of data integration and visualization. With respect to visualization, NASA Ames Research Center has been leading the advancement in data visualization for these new domains and has spent considerable efforts in the exploration of incorporating Augmented and Mixed Reality as a situation awareness platform. This presentation will outline the new developments in airspace integration and tie in NASA's efforts in visualizing the associated operational data.

airspace management↗

Erosive Augmentation of Solid Propellant Burning Rate: Motor Size Scaling Effect

Two different independent variable forms, a difference form and a ratio form, were investigated for correlating the normalized magnitude of the measured erosive burning rate augmentation above the threshold in terms of the amount that the driving parameter (mass flux or Reynolds number) exceeds the threshold value for erosive augmentation at the test condition. The latter was calculated from the previously determined threshold correlation. Either variable form provided a correlation for each of the two motor size data bases individually. However, the data showed a motor size effect, supporting the general observation that the magnitude of erosive burning rate augmentation is reduced for larger rocket motors. For both independent variable forms, the required motor size scaling was attained by including the motor port radius raised to a power in the independent parameter. A boundary layer theory analysis confirmed the experimental finding, but showed that the magnitude of the scale effect is itself dependent upon scale, tending to diminish with increasing motor size.

Strand, L. D.↗

Discoveries about Tropical Tropospheric Ozone from Satellite and SHADOZ (Southern Hemisphere Additional Ozonesondes) and a Future Perspective on NASA's Ozone Sensors

We have been producing near-real tropical tropospheric ozone ('TTO') data from TOMS since 1997 with Prof. Hudson and students at the University of Maryland. Maps for 1996-2000 for the operational Earth-Probe instrument reside at: . We also have archived 'TTO' data from the Nimbus 7/TOMS satellite (1979-1992). The tropics is a region strongly influenced by natural variability and anthropogenic activity and the satellite data have been used to track biomass burning pollution and to detect interannual variability and climate signals in ozone. We look forward to future ozone sensors from NASA; four will be launched in 2004 as part of the EOS AURA Mission. The satellite view of chemical-dynamical interactions in tropospheric ozone is not adequate to capture vertical variability. Thus, in 1998, NASA's Goddard Space Flight Center, NOAA's Climate Monitoring and Diagnostics Laboratory (CMDL) and a team of international sponsors established the SHADOZ (Southern Hemisphere ADditional OZonesondes) project to address the gap in tropical ozone soundings. SHADOZ augments launches at selected sites and provides a public archive of ozonesonde data from twelve tropical and subtropical stations at http://croc.nsfc.nasa.gov/shadoz. The stations are: Ascension Island; Nairobi, Kenya; Irene, South Africa; R,union Island; Watukosek, Java; Fiji; Tahiti; American Samoa; San Cristobal, Galapagos; Natal, Brazil, Malindi, Kenya; Paramaribo, Surinam. From the first 3-4 years of data (presently greater than 1700 sondes), the following features emerge: (a) highly variable tropospheric ozone; (b) a zonal wave-one pattern in tropospheric column ozone; (c) tropospheric ozone variability over the Indian and Pacific Ocean displays strong convective signatures.

Thompson, Anne↗

YAV-8B reaction control system bleed and control power usage in hover and transition

Using a calibrated Rolls-Royce Pegasus engine and existing aircraft instrumentation and pressure taps, total and individual nozzle reaction control system (RCS) bleed flow rates have been measured on a YAV-8B Harrier during typical short takeoff, transition, hover, and vertical landing maneuvers. RCS thrust forces were calculated from RCS nozzle total pressure measurements, and control power was determined from the moments produced by these thrusts and the aircraft's moments of inertia. These data document the characteristics of the YAV-8B RCS with its basic stability augmentation system (SAS) engaged. Advanced control system designs for the YAV-8B can be compared to the original SAS based on the total bleed use and the percentage of available bleed used. In addition, the peak and mean values of the bleed and control power data can be used for sizing the reaction controls for a future short takeoff and vertical landing (STOVL) aircraft.

Borchers, Paul F.↗

Anomaly Detection in Flight Operational Data Using Deep Learning

In this session, we demonstrate two recently developed deep learning models for anomaly detection in flight operational data by the Data Sciences Group at NASA Ames Research Center. The first model is Convolutional Variational Auto-Encoder (CVAE) [1], which is an unsupervised deep encoder-decoder model, designed specifically for finding anomalies in heterogeneous multivariate time series data. We will demonstrate its application to finding anomalies in streaming data from NASA’s Digital Information Platform’s Fuser source. CVAE identifies data instances that are not representative of expected nominal behavior as anomalous. Since it is an unsupervised approach, the flagged anomalies will need to be reviewed by the subject matter experts (SMEs) for validation and labeling and is designed to assist with vulnerability discovery within Safety Monitoring System programs. The second model is Robust and Explainable Semi-supervised Anomaly Detection (RESAD) model [2], which builds on CVAE to allow learning from both minimally labeled data (previously reviewed by the SMEs) as well as majority unlabeled data. RESAD takes advantage of graph theoretic techniques to propagate the labels from the labeled data to the unlabeled data based on a pre-defined similarity metric and structures the learned feature space from flight time-series so that data of the same class would cluster tightly together. This model characteristic is enabled by training with an augmented loss function and allows learning of a more informative feature space for down-stream tasks such as search and active learning. We demonstrate RESAD using data from the NASA DASHlink project [3].

anomaly detection↗

A data analysis expert system for large established distributed databases

A design for a natural language database interface system, called the Deductively Augmented NASA Management Decision support System (DANMDS), is presented. The DANMDS system components have been chosen on the basis of the following considerations: maximal employment of the existing NASA IBM-PC computers and supporting software; local structuring and storing of external data via the entity-relationship model; a natural easy-to-use error-free database query language; user ability to alter query language vocabulary and data analysis heuristic; and significant artificial intelligence data analysis heuristic techniques that allow the system to become progressively and automatically more useful.

Gnacek, Anne-Marie↗

Investigation of water vapor motion winds from geostationary satellites

Water vapor imagery from geostationary satellites has been available for over a decade. These data are used extensively by operational analysts and forecasters, mainly in a qualitative mode (Weldon and Holmes 1991). In addition to qualitative applications, motions deduced in animated water vapor imagery can be used to infer wind fields in cloudless regimes, thereby augmenting the information provided by cloud-drift wind vectors. Early attempts at quantifying the data by tracking features in water vapor imagery met with modest success (Stewart et al. 1985; Hayden and Stewart 1987). More recently, automated techniques have been developed and refined, and have resulted in upper-level wind observations comparable in quality to current operational cloud-tracked winds (Laurent 1993). In a recent study by Velden et al. (1993) it was demonstrated that wind sets derived from Meteosat-3 (M-3) water vapor imagery can provide important environmental wind information in data void areas surrounding tropical cyclones, and can positively impact objective track forecasts. M-3 was repositioned to 75W by the European Space Agency in 1992 in order to provide complete coverage of the Atlantic Ocean. Data from this satellite are being transmitted to the U.S. for operational use. Compared with the current GOES-7 (G-7) satellite (positioned near 112W), the M-3 water vapor channel contains a superior horizontal resolution (5 km vs. 16 km ). In this paper, we examine wind sets derived using automated procedures from both GOES-7 and Meteosat-3 full disk water vapor imagery in order to assess this data as a potentially important source of large-scale wind information. As part of a product demonstration wind sets were produced twice a day at CIMSS during a six-week period in March and April (1994). These data sets are assessed in terms of geographic coverage, statistical accuracy, and meteorological impact through preliminary results of numerical model forecast studies.

Velden, Christopher S.↗

Analysis of the Westland Data Set

The "Westland" set of empirical accelerometer helicopter data with seeded and labeled faults is analyzed with the aim of condition monitoring. The autoregressive (AR) coefficients from a simple linear model encapsulate a great deal of information in a relatively few measurements; and it has also been found that augmentation of these by harmonic and other parameters call improve classification significantly. Several techniques have been explored, among these restricted Coulomb energy (RCE) networks, learning vector quantization (LVQ), Gaussian mixture classifiers and decision trees. A problem with these approaches, and in common with many classification paradigms, is that augmentation of the feature dimension can degrade classification ability. Thus, we also introduce the Bayesian data reduction algorithm (BDRA), which imposes a Dirichlet prior oil training data and is thus able to quantify probability of error in all exact manner, such that features may be discarded or coarsened appropriately.

Wen, Fang↗

Model-based diagnostics for the SSME

This paper presents models to diagnose the condition of the Space Shuttle Main Engine (SSME). A qualitative physics based model derived from the thermodynamic processes and the flow characteristics underlying the SSME operation was developed to detect and isolate engine failures to the component level. This qualitative model was augmented with empirical models derived from the SSME test-stand data to rapidly detect faults which manifest themselves in engine parameter measurements as deviations from the nominal values. The empirical models integrated with the qualitative model offer the potential for building a complex modeling framework for performing comprehensive engine health monitoring.

Tulpule, S.↗

Biological Information Signal Processor

Biological Information Signal Processor (BISP) is computing system analyzing data on deoxyribonucleic acid (DNA) sequences for molecular genetic analysis. Includes coprocessors, specialized microprocessors complementing present and future computers by performing rapidly most-time-consuming DNA-sequence-analyzing functions, establishing relationships (alignments) between both global sequences and defining patterns in multiple sequences. Also includes state-of-art software and data-base systems on both conventional and parallel computer systems to augment analytical abilities of developmental coprocessors.

Chow, Edward T.↗

Thrust Augmentation of a Shrouded Nozzle

The test seeks to find the effectiveness of thrust augmentation due to air entrainment at the rocket nozzle exit. Shrouds are attached to the primary nozzle to entrain the ambient air for further expansion. Compressed air is used to simulate a propellant in the primary flow; therefore, combustion and afterburning are excluded. Perfect expansion is used in the primary (unshrouded) nozzle to further rule out the suspicion that the shrouds simply act as a nozzle extension in the event that thrust augmentation is observed. The goal is to find the effectiveness of thrust augmentation as the result of air entrainment alone. Thrust and flow data are recorded for different shrouds at over, fully, and under-expanded conditions. Recorded mass flow rate data will be used to calculate the entrainment rate. Results of this experiment will be verified with a computer code.

Liou, Larry↗

Lunar rover technology demonstrations with Dante and Ratler

Carnegie Mellon University has undertaken a research, development, and demonstration program to enable a robotic lunar mission. The two-year mission scenario is to traverse 1,000 kilometers, revisiting the historic sites of Apollo 11, Surveyor 5, Ranger 8, Apollo 17, and Lunokhod 2, and to return continuous live video amounting to more than 11 terabytes of data. Our vision blends autonomously safeguarded user driving with autonomous operation augmented with rich visual feedback, in order to enable facile interaction and exploration. The resulting experience is intended to attract mass participation and evoke strong public interest in lunar exploration. The encompassing program that forwards this work is the Lunar Rover Initiative (LRI). Two concrete technology demonstration projects currently advancing the Lunar Rover Initiative are: (1) The Dante/Mt. Spurr project, which, at the time of this writing, is sending the walking robot Dante to explore the Mt. Spurr volcano, in rough terrain that is a realistic planetary analogue. This project will generate insights into robot system robustness in harsh environments, and into remote operation by novices; and (2) The Lunar Rover Demonstration project, which is developing and evaluating key technologies for navigation, teleoperation, and user interfaces in terrestrial demonstrations. The project timetable calls for a number of terrestrial traverses incorporating teleoperation and autonomy including natural terrain this year, 10 km in 1995. and 100 km in 1996. This paper will discuss the goals of the Lunar Rover Initiative and then focus on the present state of the Dante/Mt. Spurr and Lunar Rover Demonstration projects.

Krotkov, Eric↗

Biological effects and physics of solar and galactic cosmic radiation, Part B; Proceedings of a NATO Advanced Study Institute on Biological Effects and Physics of Solar and Galactic Cosmic Radiation, Algarve, Portugal, Oct. 13-23, 1991

Since there is an increasing interest in establishing lunar bases and exploring Mars by manned missions, it is important to develop appropriate risk estimates and radiation protection guidelines. The biological effects and physics of solar and galactic cosmic radiation are examined with respect to the following: the radiation environment of interplanetary space, the biological responses to radiation in space, and the risk estimates for deep space missions. There is a need for a long-term program where ground-based studies can be augmented by flight experiments and an international standardization with respect to data collection, protocol comparison, and formulation of guidelines for future missions.

Swenberg, Charles E.↗

Remote and Ground Truth Spectral Measurement Comparisons of FORMOSAT III

FORMOSAT III are a set of six research satellites from Taiwan that were launched in April 2006. The satellites are in 800 km, 71 degree inclination orbits and separated by 24 degrees in ascending node. Laboratory spectral measurements were taken of outer surface materials on FORMOSAT III. From those measurements, a computer model was built to predict the spectral reflectance accounting for both solar phase angle and orientation of the spacecraft relative to the observer. However, materials exposed to the space environment have exhibited spectral changes including a darkening and a "reddening" of the spectra. This "reddening" is characterized by an increase in slope of the reflectance as the wavelength increases. Therefore, the model of pre-flight materials was augmented to include the presumed causative agent: space weathering effects. Remote data were collected on two of the six FORMOSAT satellites using the 1.6 meter telescope at the AMOS (Air Force Maui Optical and Supercomputing) site with the Spica spectrometer. Due to the separation in ascending node, observations were acquired of whichever one of the six satellites was visible on that specific night. Three nights of data were collected using the red (6000 - 9500 angstroms) filter and five nights of data were collected using the blue (3200 - 6600 angstroms) filter. A comparison of the data showed a good match to the pre-flight models for the blue filter region. The absorption feature near 5500 angstroms due to the copper colored Kapton multi-layer insulation (MLI) was very apparent in the remote samples and a good fit to the data was seen in all satellites observed. The features in the red filter regime agreed with the pre-flight model up through 7000 angstroms where the reddening begins and the slope of the remote sample increases. A comparison of the satellites showed similar features in the red and blue filter regions, i.e. the satellite surfaces were aging at the same rate. A comparison of the pre-flight model to the first month of remote measurements showed the amount by which the satellite had reddened. The second month of data observed a satellite at a higher altitude and was therefore, not compared to the first month. A third month of data was collected but of satellites at the lower altitude regime and can only be compared to the first month. One cause of the reddening that was ruled out in early papers was a possible calibration issue.

Abercromby, Kira Jorgensen↗

Use of Remote Sensing Data to Enhance NWS Storm Damage Toolkit

In the wake of a natural disaster such as a tornado, the National Weather Service (NWS) is required to provide a very detailed and timely storm damage assessment to local, state and federal homeland security officials. The Post ]Storm Data Acquisition (PSDA) procedure involves the acquisition and assembly of highly perishable data necessary for accurate post ]event analysis and potential integration into a geographic information system (GIS) available to its end users and associated decision makers. Information gained from the process also enables the NWS to increase its knowledge of extreme events, learn how to better use existing equipment, improve NWS warning programs, and provide accurate storm intensity and damage information to the news media and academia. To help collect and manage all of this information, forecasters in NWS Southern Region are currently developing a Storm Damage Assessment Toolkit (SDAT), which incorporates GIS ]capable phones and laptops into the PSDA process by tagging damage photography, location, and storm damage details with GPS coordinates for aggregation within the GIS database. However, this tool alone does not fully integrate radar and ground based storm damage reports nor does it help to identify undetected storm damage regions. In many cases, information on storm damage location (beginning and ending points, swath width, etc.) from ground surveys is incomplete or difficult to obtain. Geographic factors (terrain and limited roads in rural areas), manpower limitations, and other logistical constraints often prevent the gathering of a comprehensive picture of tornado or hail damage, and may allow damage regions to go undetected. Molthan et al. (2011) have shown that high resolution satellite data can provide additional valuable information on storm damage tracks to augment this database. This paper presents initial development to integrate satellitederived damage track information into the SDAT for near real ]time use by forecasters and decision makers.

Jedlove, Gary J.↗

Use of AI for Interpreting Technical Specifications for Power Uprates in Nuclear Power Plants

Powerpoint presentation. Background information provided on power plant uprates. Discussion of the current and proposed approaches to power plant uprates. Explanation of what data is used to draft a LAR. Methods such as retrieval augmented generation (RAG) and fine-tuning are discussed. Use case analysis is performed. Different failure types are examined. Conclusions are drawn from the analysis. Future work is proposed.

97 - MATHEMATICS AND COMPUTING↗