Results for “real” — Page 5

NASA NTRS2012

Real Time Space Weather Support for Chandra X-Ray Observatory Operations

NASA launched the Chandra X-ray Observatory in July 1999. Soon after first light in August 1999, however, degradation in the energy resolution and charge transfer efficiency of the Advanced CCD Imaging Spectrometer (ACIS) x-ray detectors was observed. The source of the degradation was quickly identified as radiation damage in the charge-transfer channel of the front-illuminated CCDs, by weakly penetrating ( soft , 100 500 keV) protons as Chandra passed through the Earth s radiation belts and ring currents. As soft protons were not considered a risk to spacecraft health before launch, the only on-board radiation monitoring system is the Electron, Proton, and Helium Instrument (EPHIN) which was included on Chandra with the primary purpose of monitoring energetic solar particle events. Further damage to the ACIS detector has been successfully mitigated through a combination of careful mission planning, autonomous on-board radiation protection, and manual intervention based upon real-time monitoring of the soft-proton environment. The AE-8 and AP-8 trapped radiation models and Chandra Radiation Models are used to schedule science operations in regions of low proton flux. EPHIN has been used as the primary autonomous in-situ radiation trigger; but, it is not sensitive to the soft protons that damage the front-illuminated CCDs. Monitoring of near-real-time space weather data sources provides critical information on the proton environment outside the Earth s magnetosphere due to solar proton events and other phenomena. The operations team uses data from the Geostationary Operational Environmental Satellites (GOES) to provide near-real-time monitoring of the proton environment; however, these data do not give a representative measure of the soft-proton (< 1 MeV) flux in Chandra s high elliptical orbit. The only source of relevant measurements of sub-MeV protons is the Electron, Proton, and Alpha Monitor (EPAM) aboard the Advanced Composition Explorer (ACE) satellite at L1, with real-time data provided by NOAA s Space Weather Prediction Center. This presentation describes the radiation mitigation strategies to minimize the proton damage in the ACIS CCD detectors and the importance of real-time data sources that are used to protect the ACIS detector system from space weather events.

O'Dell, Stephen L.↗

NASA NTRS2014

Real-Time Global Flood Estimation Using Satellite-Based Precipitation and a Coupled Land Surface and Routing Model

A widely used land surface model, the Variable Infiltration Capacity (VIC) model, is coupled with a newly developed hierarchical dominant river tracing-based runoff-routing model to form the Dominant river tracing-Routing Integrated with VIC Environment (DRIVE) model, which serves as the new core of the real-time Global Flood Monitoring System (GFMS). The GFMS uses real-time satellite-based precipitation to derive flood monitoring parameters for the latitude band 50 deg. N - 50 deg. S at relatively high spatial (approximately 12 km) and temporal (3 hourly) resolution. Examples of model results for recent flood events are computed using the real-time GFMS (http://flood.umd.edu). To evaluate the accuracy of the new GFMS, the DRIVE model is run retrospectively for 15 years using both research-quality and real-time satellite precipitation products. Evaluation results are slightly better for the research-quality input and significantly better for longer duration events (3 day events versus 1 day events). Basins with fewer dams tend to provide lower false alarm ratios. For events longer than three days in areas with few dams, the probability of detection is approximately 0.9 and the false alarm ratio is approximately 0.6. In general, these statistical results are better than those of the previous system. Streamflow was evaluated at 1121 river gauges across the quasi-global domain. Validation using real-time precipitation across the tropics (30 deg. S - 30 deg. N) gives positive daily Nash-Sutcliffe Coefficients for 107 out of 375 (28%) stations with a mean of 0.19 and 51% of the same gauges at monthly scale with a mean of 0.33. There were poorer results in higher latitudes, probably due to larger errors in the satellite precipitation input.

global flood estimation↗

NASA NTRS2019

Rapidly Connecting You to the World: Improving NASA’s Worldview to Enhance Discovery and Access to Near Real-Time Imagery

The world around us is constantly in motion. Storms swirl, fires rage, volcanoes erupt and icebergs calve. NASA’s fleet of Earth Observing System (EOS) satellites are there to capture this. Within hours of satellite overpass, NASA’s Worldview (https://worldview.earthdata.nasa.gov) delivers this global, near-real time imagery through an interactive web map application. Provided through NASA’s Land Atmosphere Near real-time Capability for EOS (LANCE) (https://earthdata.nasa.gov/lance) via NASA’s Global Imagery Browse Services (GIBS) (https://earthdata.nasa.gov/gibs), the near real-time satellite imagery provides a launching point to discover where the latest wildfires, severe storms, volcanic eruptions, and calving ice shelves are happening. This poster will explore the newest near real-time satellite imagery and soon-to-be available imagery in Worldview, including imagery from geostationary satellites - GOES-East/West and Himawari-8. The poster will cover recent and future improvements to Worldview aimed to enhance the discovery and interaction with near real-time imagery and show how it is used by people from researchers, to meteorologists to the science-minded public around the world.

Wong, Min Minnie↗

NASA NTRS2020

Ellicott City Disasters II - Building a Real-Time Predictive Flood Model for Improving Early Warning Systems in Ellicott City, Maryland

As flood events in the United States grow in frequency and intensity, the uses of applied remote sensing analyses are increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP Ellicott City Disasters III project investigated the use of machine learning for applications in flood risk detection to support the improvement of early warning systems in Ellicott City, Maryland. To strengthen the efforts of the Howard County Office of Emergency Management (OEM) in building a more robust flood monitoring system, this term built on the predictive capability of the long-short term memory (LSTM) model created by the second term of this DEVELOP project to create a Sequentially Trained Real-time EstimAted Model (STREAM). Enhancements to the model included the integration of both real-time and predicted weather products from the National Weather Service to increase predictive capacity. These weather products were supplemented by stream gauge data from the OEM as well as real-time radar products. The resultant flood risk model was trained to evaluate input variables and predict stage height in Ellicott City in real time. The model, upgraded to predict stage height up to 8 hours in advance, was incorporated into an online dashboard in a user-friendly interface. The project demonstrated the potential for integration of open data and NASA Earth observations into a flood risk forecasting tool capable of informing real-time decision-making.

Erika Munshi↗

NASA NTRS2020

Ellicott City Disasters III: Building a Real-Time Statistical Flood Model for Improving Early Warning Systems in Ellicott City, Maryland

As flood events in the United States grow in frequency and intensity, the uses of applied remote sensing analyses are increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP Ellicott City Disasters III project investigated the use of machine learning for applications in flood risk detection to support the improvement of early warning systems in Ellicott City, Maryland. To strengthen the efforts of the Howard County Office of Emergency Management (OEM) in building a more robust flood monitoring system, this term built on the predictive capability of the long-short term memory (LSTM) model created by the second term of this DEVELOP project to create a Sequentially Trained Real-time EstimAted Model (STREAM). Enhancements to the model included the integration of both real-time and predicted weather products from the National Weather Service to increase predictive capacity. These weather products were supplemented by stream gauge data from the OEM as well as real-time radar products. The resultant flood risk model was trained to evaluate input variables and predict stage height in Ellicott City in real time. The model, upgraded to predict stage height up to 8 hours in advance, was incorporated into an online dashboard in a user-friendly interface. The project demonstrated the potential for integration of open data and NASA Earth observations into a flood risk forecasting tool capable of informing real-time decision-making.

Erika Munshi↗

NASA NTRS2017

Expanding NASA's Land, Atmosphere Near Real-Time Capability for EOS (LANCE)

NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE) is a virtual system that provides near real-time EOS data and imagery to meet the needs of scientists and application users interested in monitoring a wide variety of natural and man-made phenomena in near real-time. Over the last year: near real-time data and imagery from MOPITT, MISR, OMPS and VIIRS (Land and Atmosphere), the Fire Information for Resource Management System (FIRMS) has been updated and LANCE has begun the process of integrating the Global NRT flood, and Black Marble products. In addition, following the AMSU-A2 instrument anomaly in September 2016, AIRS-only products have replaced the NRT level 2 AIRS+AMSU products. This presentation provides a brief overview of LANCE, describes the new products that are recently available and contains a preview of what to expect in LANCE over the coming year.

NASA Lance↗

NASA NTRS2019

The Value of Near Real-Time Earth Observations for Improved Flood Disaster Response

Information is a critical resource in disaster response scenarios. Data regarding the geographic extent, severity, and socioeconomic impacts of a disaster event can help guide emergency responders and relief operations, particularly when delivered within hours of data acquisition. Information from remote observations provides a valuable tool for assessing conditions "on the ground" more quickly and efficiently. Here, we evaluate the social value of a near real-time flood impact system using a disaster response case study, and quantify the Value of Information (VOI) of satellite-based observations for rapid response using a hypothetical flooding disaster in Bangkok, Thailand. MODIS imagery from NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE) system is used to produce operational estimates of inundation depths and economic damages.These rapid Earth observations are coupled with a decision-analytical model to inform decisions on emergency vehicle routing. Emergency response times from vehicles routed using flood damage data are compared with baseline routes without the benefit of advance information on road conditions. Our results illustrate how the application of near real-time Earth observations can improve the response time and reduce potential encounters with flood hazards when compared with baseline routing strategies. Results indicate a potential significant economic benefit (i.e.,millions of dollars) from applying near real-time Earth observations for improved flood disaster response and management.

emergency response↗

NASA NTRSDate not supplied

Real-Time Pilot Inputs for Aircraft Dynamic Modeling

Real-time dynamic modeling and pilot displays are used to enable pilots to intuitively discover effective multi-axis inputs for aircraft dynamic modeling during flight tests. An F-16 nonlinear simulation flown by a pilot using a joystick and a laptop computer with real-time displays of relevant information is used to demonstrate the approach. Results show that pilots can use the real-time display to discover and implement effective and efficient multi-axis inputs for accurate dynamic modeling in flight. The real-time dynamic modeling results driving the pilot display can be used to certify that the acquired flight data are adequate for accurate dynamic modeling, thus avoiding postflight data analysis and modeling by an analyst to make that determination. Implications for pilot training and efficient flight testing are discussed.

Pilot Inputs↗

NASA NTRS1973

Algebraic criteria for positive realness relative to the unit circle.

A definition is presented of the circle positive realness of real rational functions relative to the unit circle in the complex variable plane. The problem of testing this kind of positive reality is reduced to the algebraic problem of determining the distribution of zeros of a real polynomial with respect to and on the unit circle. Such reformulation of the problem avoids the search for explicit information about imaginary poles of rational functions. The stated algebraic problem is solved by applying the polynomial criteria of Marden (1966) and Jury (1964), and a completely recursive algorithm for circle positive realness is obtained.

Siljak, D. D.↗

NASA NTRS1982

A Piecewise Linear State Variable Technique for Real Time Propulsion System Simulation

The emphasis on increased aircraft and propulsion control system integration and piloted simulation has created a need for higher fidelity real time dynamic propulsion models. A real time propulsion system modeling technique which satisfies this need and which provides the capabilities needed to evaluate propulsion system performance and aircraft system interaction on manned flight simulators was developed and demonstrated using flight simulator facilities at NASA Ames. A piecewise linear state variable technique is used. This technique provides the system accuracy, stability and transient response required for integrated aircraft and propulsion control system studies. The real time dynamic model includes the detail and flexibility required for the evaluation of critical control parameters and propulsion component limits over a limited flight envelope. The model contains approximately 7.0 K bytes of in-line computational code and 14.7 K of block data. It has an 8.9 ms cycle time on a Xerox Sigma 9 computer. A Pegasus-Harrier propulsion system was used as a baseline for developing the mathematical modeling and simulation technique. A hydromechanical and water injection control system was also simulated. The model was programmed for interfacing with a Harrier aircraft simulation at NASA Ames. Descriptions of the real time methodology and model capabilities are presented.

Mihaloew, J. R.↗

NASA NTRS1982

A comparative study of real-time spaceborne synthetic aperture radar processing techniques

A review of various spaceborne synthetic aperture radar (SAR) processing algorithms and their associated real-time SAR processor architectures is given in this paper. The processing complexity for each real-time SAR processor is presented next. A complexity comparison is then given based on the Seasat SAR parameters. It is shown that the frequency/time domain hybrid fast correlation and the two-stage fast Fourier transform (FET) approaches are the two most cost-effective choices for real-time spaceborne SAR processing. Finally, a discussion on future development trends in real-time spaceborne SAR processing is given.

Liu, K. Y.↗

NASA NTRS1983

A review of preflight estimates of real-gas effects on space shuttle aerodynamic characteristics

Preflight estimates of the hypersonic aerodynamic characteristics of the Shuttle orbiter were based on a diverse series of research studies using state of the art techniques developed by basic research in the 60's and 70's. Real-gas viscous calculations on simple shapes that were used to evaluate correlation parameters indicated that real-gas effects reduce aerodynamic forces and moments. Inviscid calculations on winged lifting shapes indicated reduced forces and a slight nose-up pitch resulted because of real-gas effects. Analysis of the extensive wind tunnel data base indicated viscous correlation parameters provided the most appropriate extrapolation technique for estimating flight aerodynamics. Variations because of changes in the ratio of specific heats, which was the only available experimental tool for evaluating real-gas effects, indicated that reduced loads and nose-up pitching moments would occur at high altitudes and Mach numbers but that the values would not exceed the tolerances and variations established about the aerodynamic design data book values derived from viscous correlations. During STS-1, nose-up pitching moments exceeded the established variations.

Woods, W. C.↗

NASA NTRS1984

RTMPL: A structured programming and documentation utility for real-time multiprocessor simulations

The NASA Lewis Research Center is developing and evaluating experimental hardware and software systems to help meet future needs for real time simulations of air-breathing propulsion systems. The Real Time Multiprocessor Simulator (RTMPS) project is aimed at developing a prototype simulator system that uses multiple microprocessors to achieve the desired computing speed and accuracy at relatively low cost. Software utilities are being developed to provide engineering-level programming and interactive operation of the simulator. Two major software development efforts were undertaken in the RTMPS project. A real time multiprocessor operating system was developed to provide for interactive operation of the simulator. The second effort was aimed at developing a structured, high-level, engineering-oriented programming language and translator that would facilitate the programming of the simulator. The Real Time Multiprocessor Programming Language (RTMPL) allows the user to describe simulation tasks for each processor in a straight-forward, structured manner. The RTMPL utility acts as an assembly language programmer, translating the high-level simulation description into time-efficient assembly language code for the processors. The utility sets up all of the interfaces between the simulator hardware, firmware, and operating system.

Arpasi, D. J.↗

NASA NTRS1982

A piecewise linear state variable technique for real time propulsion system simulation

The emphasis on increased aircraft and propulsion control system integration and piloted simulation has created a need for higher fidelity real time dynamic propulsion models. A real time propulsion system modeling technique which satisfies this need and which provides the capabilities needed to evaluate propulsion system performance and aircraft system interaction on manned flight simulators was developed and demonstrated using flight simulator facilities at NASA Ames. A piecewise linear state variable technique is used. This technique provides the system accuracy, stability and transient response required for integrated aircraft and propulsion control system studies. The real time dynamic model includes the detail and flexibility required for the evaluation of critical control parameters and propulsion component limits over a limited flight envelope. The model contains approximately 7.0 K bytes of in-line computational code and 14.7 K of block data. It has an 8.9 ms cycle time on a Xerox Sigma 9 computer. A Pegasus-Harrier propulsion system was used as a baseline for developing the mathematical modeling and simulation technique. A hydromechanical and water injection control system was also simulated. The model was programmed for interfacing with a Harrier aircraft simulation at NASA Ames. Descriptions of the real time methodology and model capabilities are presented.

Mihaloew, J. R.↗

NASA NTRS1983

Synchronization and fault-masking in redundant real-time systems

A real time computer may fail because of massive component failures or not responding quickly enough to satisfy real time requirements. An increase in redundancy - a conventional means of improving reliability - can improve the former but can - in some cases - degrade the latter considerably due to the overhead associated with redundancy management, namely the time delay resulting from synchronization and voting/interactive consistency techniques. The implications of synchronization and voting/interactive consistency algorithms in N-modular clusters on reliability are considered. All these studies were carried out in the context of real time applications. As a demonstrative example, we have analyzed results from experiments conducted at the NASA Airlab on the Software Implemented Fault Tolerance (SIFT) computer. This analysis has indeed indicated that in most real time applications, it is better to employ hardware synchronization instead of software synchronization and not allow reconfiguration.

Krishna, C. M.↗

NASA NTRS1987

Real time identification of large space structures

Identification of frequencies, damping ratios, and mode shapes of large space structures (LSSs) are examined in real time. Real time processing allows for quick updates of model processing after a reconfiguration of structural failure. Recursive lattice least squares (RLLS) was selected as the baseline algorithm for the identification. Simulation results on a one dimensional LSS demonstrated that it provides good estimates, was not ill-conditioned in the presence of under-excited modes, allowed activity by a supervisory control system which prevented damage to the LSS or excessive drift, and was capable of real-time processing for typical LSS models. A suboptimal version of RLLS, which is equivalent to simulated parallel processing, was derived. A NASTRAN model of the dual keel U.S. space station was used to demonstrate the input/identification algorithm package in a more realistic simulation. Because the first eight flexible modes were very close together, the identification was much more difficult than in the simple examples. Even so, the model was accurately identified in real time.

Voss, Janice E.↗

NASA NTRS1987

Validation of a real-time engineering simulation of the UH-60A helicopter

A real-time simulation of the UH-60A Black Hawk Helicopter based on the Sikorsky Gen Hel mathematical model is compared with flight test data and Sikorsky's nonreal-time computer program. An overview of the mathematical model is given, including a description of updates and expansion of the model by NASA. Also, real-time programming requirements and techniques are explained. The simulation displays very good agreement with flight test data and excellent with the nonreal-time program on which it is based. The large dedication of effort required to develop the real-time program suggests a need for development of generalized techniques for real-time simulation of high-fidelity physical models of rotorcraft.

Ballin, Mark G.↗

NASA NTRS1987

A multiprocessing architecture for real-time monitoring

A multiprocessing architecture for performing real time monitoring and analysis using knowledge-based problem solving techniques is discussed. To handle asynchronous inputs and perform in real time, the system consists of three or more separate processes which run concurrently on one or more processors and communicate via a message passing scheme. The Data Management Process gathers, compresses, scales and sends the incoming telemetry data to other tasks. The Inference Process consists of a proprietary high performance inference engine that runs at 1000 rules per second using telemetry data to perform real time analysis on the state and health of the Space Telescope. The multiprocessing architecture has been interfaced to a simulator and is able to process the incoming telemetry in real time.

Laffey, Thomas J.↗