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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry: Evaluation of Estimates Using Independent Data - Part 2

Rainfall rate estimates from space-borne k&ents are generally accepted as reliable by a majority of the atmospheric science commu&y. One-of the Tropical Rainfall Measuring Mission (TRh4M) facility rain rate algorithms is based upon passive microwave observations fiom the TRMM Microwave Imager (TMI). Part I of this study describes improvements in the TMI algorithm that are required to introduce cloud latent heating and drying as additional algorithm products. Here, estimates of surface rain rate, convective proportion, and latent heating are evaluated using independent ground-based estimates and satellite products. Instantaneous, OP5resolution estimates of surface rain rate over ocean fiom the improved TMI algorithm are well correlated with independent radar estimates (r approx. 0.88 over the Tropics), but bias reduction is the most significant improvement over forerunning algorithms. The bias reduction is attributed to the greater breadth of cloud-resolving model simulations that support the improved algorithm, and the more consistent and specific convective/stratiform rain separation method utilized. The bias of monthly, 2.5 deg. -resolution estimates is similarly reduced, with comparable correlations to radar estimates. Although the amount of independent latent heating data are limited, TMI estimated latent heating profiles compare favorably with instantaneous estimates based upon dual-Doppler radar observations, and time series of surface rain rate and heating profiles are generally consistent with those derived from rawinsonde analyses. Still, some biases in profile shape are evident, and these may be resolved with: (a) additional contextual information brought to the estimation problem, and/or; (b) physically-consistent and representative databases supporting the algorithm. A model of the random error in instantaneous, 0.5 deg-resolution rain rate estimates appears to be consistent with the levels of error determined from TMI comparisons to collocated radar. Error model modifications for non-raining situations will be required, however. Sampling error appears to represent only a fraction of the total error in monthly, 2S0-resolution TMI estimates; the remaining error is attributed to physical inconsistency or non-representativeness of cloud-resolving model simulated profiles supporting the algorithm.

Yang, Song↗
NASA NTRS1981

Characteristics of space and ground based total ozone observing systems investigated by intercomparison of Nimbus 4 Backscattered Ultraviolet /BUV/ data with Dobson and M-83 results

The Nimbus 4 Backscattered Ultraviolet (BUV) experiment data has been reprocessed to provide a near global data set covering the seven years from 1970 to 1977. The data set is the result of a three year effort by the Ozone Processing Team which included review and correction of the spacecraft ephemeris, instrument calibration, and processing algorithms. The accuracy of the resulting total ozone determinations compares well with that of ground based data. An important application of the global BUV data set is to use it in determining long term trends in global total ozone. However, in order to identify long term trends in ozone, it is necessary to eliminate first long-term drift in the instrument calibration. A follow on experiment, the Solar Backscattered Ultraviolet/Total Ozone Mapping Spectrometer, (SBUV/TOMS), was flown on Nimbus 7 launched in October 1978. The SBUV provides information about both total ozone and vertical ozone profiles for a 200 km square field of view.

Fleig, A. J.↗
NASA NTRS2003

Star Identification Using a Triplet Algorithm

The stars observed by onboard star trackers must be identified in order for the star tracker information to be used for attitude determination. Star identification associates the observed stars in the body frame with catalog stars, the positions of which in an inertial frame are well known. If the attitude is approximately known (from less accurate sensors) identification is relatively simple, but if there is no prior attitude knowledge (the Lost in Space problem) star identification is quite difficult. A new, reliable, and accurate star identification algorithm has been developed for use in a batch, ground-based attitude determination system. The identification algorithm uses input from one or more star trackers, each of which can observe three or more stars simultaneously. If observations are available at different times, rate data is used to relate them. The algorithm includes the following steps that are automatically performed: 1) Observations are examined to determine the optimal set of simultaneous star observations in a single tracker. 2) The selected optimal observations are identified using a triplet match. 3) The identified stars in the selected tracker at the selected time are used to compute an attitude at that time. 4) The rate data is refined by determination of biases that minimize the dispersion of repeated observations of the same stars. 5) The refined rate data is used to propagate the attitude to the times of each star observation. 6) The attitude at each time is used to associate all stars observed at that time, in each tracker, with catalog stars. The overall algorithm is very dependable at producing accurate star identification with no initial attitude input.

Hashmall, Joseph A.↗
NASA NTRS1992

Health management and controls for earth to orbit propulsion systems

Fault detection and isolation for advanced rocket engine controllers are discussed focusing on advanced sensing systems and software which significantly improve component failure detection for engine safety and health management. Aerojet's Space Transportation Main Engine controller for the National Launch System is the state of the art in fault tolerant engine avionics. Health management systems provide high levels of automated fault coverage and significantly improve vehicle delivered reliability and lower preflight operations costs. Key technologies, including the sensor data validation algorithms and flight capable spectrometers, have been demonstrated in ground applications and are found to be suitable for bridging programs into flight applications.

Bickford, R. L.↗
NASA NTRS2007

Application of the Hilbert-Huang Transform to the Search for Gravitational Waves

We present the application of a novel method of time-series analysis, the Hilbert-Huang Transform, to the search for gravitational waves. This algorithm is adaptive and does not impose a basis set on the data, and thus the time-frequency decomposition it provides is not limited by time-frequency uncertainty spreading. Because of its high time-frequency resolution it has important applications to both signal detection and instrumental characterization. Applications to the data analysis of the ground and space based gravitational wave detectors, LIGO and LISA, are described.

Camp, Jordan B.↗
NASA NTRS2015

Tactically Extensible and Modular Communications - X-Band TEMCOM-X

This paper will discuss a proposed CubeSat size (3U) telemetry system concept being developed at Marshall Space Flight Center (MSFC) in cooperation with the U.S. Department of the Army and Dynetics Corporation. This telemetry system incorporates efficient, high-bandwidth communications by developing flight-ready, low-cost, Protoflight software defined radio (SDR) and Electronically Steerable Patch Array (ESPA) antenna subsystems for use on platforms as small as CubeSats and unmanned aircraft systems (UASs). The current telemetry system is slightly larger in dimension of footprint than required to fit within a 0.5U CubeSat volume. Extensible and modular communications for CubeSat technologies will partially mitigate current capability gaps between traditional strategic space platforms and lower-cost small satellite solutions. Higher bandwidth capacity will enable high-volume, low error-rate data transfer to and from tactical forces or sensors operating in austere locations (e.g., direct imagery download, unattended ground sensor data exfiltration, interlink communications), while also providing additional bandwidth and error correction margin to accommodate more complex encryption algorithms and higher user volume.

Sims, William Herbert↗
NASA NTRS2009

General Purpose Data-Driven Monitoring for Space Operations

As modern space propulsion and exploration systems improve in capability and efficiency, their designs are becoming increasingly sophisticated and complex. Determining the health state of these systems, using traditional parameter limit checking, model-based, or rule-based methods, is becoming more difficult as the number of sensors and component interactions grow. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. System health can be monitored by comparing real-time operating data with these nominal characterizations, providing detection of anomalous data signatures indicative of system faults or failures. The Inductive Monitoring System (IMS) is a data-driven system health monitoring software tool that has been successfully applied to several aerospace applications. IMS uses a data mining technique called clustering to analyze archived system data and characterize normal interactions between parameters. The scope of IMS based data-driven monitoring applications continues to expand with current development activities. Successful IMS deployment in the International Space Station (ISS) flight control room to monitor ISS attitude control systems has led to applications in other ISS flight control disciplines, such as thermal control. It has also generated interest in data-driven monitoring capability for Constellation, NASA's program to replace the Space Shuttle with new launch vehicles and spacecraft capable of returning astronauts to the moon, and then on to Mars. Several projects are currently underway to evaluate and mature the IMS technology and complementary tools for use in the Constellation program. These include an experiment on board the Air Force TacSat-3 satellite, and ground systems monitoring for NASA's Ares I-X and Ares I launch vehicles. The TacSat-3 Vehicle System Management (TVSM) project is a software experiment to integrate fault and anomaly detection algorithms and diagnosis tools with executive and adaptive planning functions contained in the flight software on-board the Air Force Research Laboratory TacSat-3 satellite. The TVSM software package will be uploaded after launch to monitor spacecraft subsystems such as power and guidance, navigation, and control (GN&C). It will analyze data in real-time to demonstrate detection of faults and unusual conditions, diagnose problems, and react to threats to spacecraft health and mission goals. The experiment will demonstrate the feasibility and effectiveness of integrated system health management (ISHM) technologies with both ground and on-board experiments.

Iverson, David L.↗
NASA NTRS2014

Evolution of the JPSS Ground Project Calibration and Validation System

The Joint Polar Satellite System (JPSS) is the National Oceanic and Atmospheric Administrations (NOAA) next-generation operational Earth observation Program that acquires and distributes global environmental data from multiple polar-orbiting satellites. The JPSS Program plays a critical role to NOAAs mission to understand and predict changes in weather, climate, oceans, coasts, and space environments, which supports the Nation’s economy and protection of lives and property. The National Aerospace and Atmospheric Administration (NASA) is acquiring and implementing the JPSS, comprised of flight and ground systems on behalf of NOAA. The JPSS satellites are planned to fly in the afternoon orbit and will provide operational continuity of satellite-based observations and products for NOAA Polar-orbiting Operational Environmental Satellites (POES) and the Suomi National Polar-orbiting Partnership (SNPP) satellite. To support the JPSS Calibration and Validation (CalVal) node Government Resource for Algorithm Verification, Independent Test, and Evaluation (GRAVITE) services facilitate: Algorithm Integration and Checkout, Algorithm and Product Operational Tuning, Instrument Calibration, Product Validation, Algorithm Investigation, and Data Quality Support and Monitoring. GRAVITE is a mature, deployed system that currently supports the SNPP Mission and has been in operations since SNPP launch. This paper discusses the major re-architecture for Block 2.0 that incorporates SNPP lessons learned, architecture of the system, and demonstrates how GRAVITE has evolved as a system with increased performance. It is now a robust, stable, reliable, maintainable, scalable, and secure system that supports development, test, and production strings, replaces proprietary and custom software, uses open source software, and is compliant with NASA and NOAA standards.

Data Processing↗
NASA NTRS1976

Efficient computer algorithms for infrared astronomy data processing

Data processing techniques to be studied for use in infrared astronomy data analysis systems are outlined. Only data from space based telescope systems operating as survey instruments are considered. Resulting algorithms, and in some cases specific software, will be applicable for use with the infrared astronomy satellite (IRAS) and the shuttle infrared telescope facility (SIRTF). Operational tests made during the investigation use data from the celestial mapping program (CMP). The overall task differs from that involved in ground-based infrared telescope data reduction.

Pelzmann, R. F., Jr.↗
NASA NTRS2018

Satellite-Based View of the Aerosol Spatial and Temporal Variability in the Cordoba Region (Argentina) Using over Ten Years of High-Resolution Data

Space-based observations offer a unique opportunity to investigate the atmosphere and its changes over decadal time scales, particularly in regions lacking in situ and/or ground based observations. In this study, we investigate temporal and spatial variability of atmospheric particulate matter (aerosol) over the urban area of Córdoba (central Argentina) using over ten years (2003–2015) of high-resolution (1 km) satellite-based retrievals of aerosol optical depth (AOD). This fine resolution is achieved exploiting the capabilities of a recently developed inversion algorithm (Multiangle implementation of atmospheric correction, MAIAC) applied to the MODIS sensor datasets of the NASA-Terra and -Aqua platforms. Results of this investigation show a clear seasonality of AOD over the investigated area. This is found to be shaped by an intricate superposition of aerosol sources, acting over different spatial scales and affecting the region with different yearly cycles. During late winter and spring (August-October), local as well as near- and long-range transported biomass burning (BB) aerosols enhance the Córdoba aerosol load, and AOD levels reach their maximum values (>0.35 at 0.47 µm). The fine AOD spatial resolution allowed to disclose that, in this period, AOD maxima are found in the rural/agricultural area around the city, reaching up to the city boundaries pinpointing that fires of local and near-range origin play a major role in the AOD enhancement. A reverse spatial AOD gradient is found from December to March, the urban area showing AODs 40–80% higher than in the city surroundings. In fact, during summer, the columnar aerosol load over the Córdoba region is dominated by local (urban and industrial) sources, likely coupled to secondary processes driven by enhanced radiation and mixing effects within a deeper planetary boundary layer (PBL). With the support of modelled AOD data from the Modern-Era Retrospective Analysis for Research and Application (MERRA), we further investigated into the chemical nature of AOD. The results suggest that mineral dust is also an important aerosol component in Córdoba, with maximum impact from November to February. The use of a long-term dataset finally allowed a preliminary assessment of AOD trends over the Córdoba region. For those months in which local sources and secondary processes were found to dominate the AOD (December to March), we found a positive AOD trend in the Córdoba outskirts, mainly in the areas with maximum urbanization/population growth over the investigated decade. Conversely, a negative AOD trend (up to −0.1 per decade) is observed all over the rural area of Córdoba during the BB season, this being attributed to a decrease of fires both at the local and the continental scale.

aerosols↗
NASA NTRS2014

In-Situ and Remote-Sensing Data Fusion Using Machine Learning Techniques to Infer Urban and Fire Related Pollution Plumes

Airmass type characterization is key in understanding the relative contribution of various emission sources to atmospheric composition and air quality and can be useful in bottom-up model validation and emission inventories. However, classification of pollution plumes from space is often not trivial. Sub-orbital campaigns, such as SEAC4RS (Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys) give us a unique opportunity to study atmospheric composition in detail, by using a vast suite of in-situ instruments for the detection of trace gases and aerosols. These measurements allow identification of spatial and temporal atmospheric composition changes due to various pollution plumes resulting from urban, biogenic and smoke emissions. Nevertheless, to transfer the knowledge gathered from such campaigns into a global spatial and temporal context, there is a need to develop workflow that can be applicable to measurements from space. In this work we rely on sub-orbital in-situ and total column remote sensing measurements of various pollution plumes taken aboard the NASA DC-8 during 2013 SEAC4RS campaign, linking them through a neural-network (NN) algorithm to allow inference of pollution plume types by input of columnar aerosol and trace-gas measurements. In particular, we use the 4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research) airborne measurements of wavelength dependent aerosol optical depth (AOD), particle size proxies, O3, NO2 and water vapor to classify different pollution plumes. Our method relies on assigning a-priori ground-truth labeling to the various plumes, which include urban pollution, different fire types (i.e. forest and agriculture) and fire stage (i.e. fresh and aged) using cluster analysis of aerosol and trace-gases in-situ and auxiliary (e.g. trajectory) data and the training of a NN scheme to fit the best prediction parameters using 4STAR measurements as input. We explore our misclassification rates as related to our ground-truth labels, and with multi-layered pollution plume cases. The next step in our analysis is to optimize parameter selection for a scheme that can be applied to space-borne aerosol and trace-gas observation platforms such as OMI, and future geostationary satellites such as TEMPO and GEO-CAPE.

Neural-network↗
NASA NTRS1989

Remote Attitude Measurement Sensor (RAMS)

Remote attitude measurement sensor (RAMS) offers a low-cost, low-risk, proven design concept that is based on mature, demonstrated space sensor technology. The electronic design concepts and interpolation algorithms were tested and proven in space hardware like th Retroreflector Field Tracker and various star trackers. The RAMS concept is versatile and has broad applicability to both ground testing and spacecraft needs. It is ideal for use as a precision laboratory sensor for structural dynamics testing. It requires very little set-up or preparation time and the output data is immediately usable without integration or extensive analysis efforts. For on-orbit use, RAMS rivals any other type of dynamic structural sensor (accelerometer, lidar, photogrammetric techniques, etc.) for overall performance, reliability, suitability, and cost. Widespread acceptance and extensive usage of RAMS will occur only after some interested agency, such as OAST, adopts the RAMS concept and provides the funding support necessary for further development and implementation of RAMS for a specific program.

Davis, H. W.↗
NASA NTRS1993

Telerobot local-remote control architecture for space flight program applications

The JPL Supervisory Telerobotics (STELER) Laboratory has developed and demonstrated a unique local-remote robot control architecture which enables management of intermittent communication bus latencies and delays such as those expected for ground-remote operation of Space Station robotic systems via the Tracking and Data Relay Satellite System (TDRSS) communication platform. The current work at JPL in this area has focused on enhancing the technologies and transferring the control architecture to hardware and software environments which are more compatible with projected ground and space operational environments. At the local site, the operator updates the remote worksite model using stereo video and a model overlay/fitting algorithm which outputs the location and orientation of the object in free space. That information is relayed to the robot User Macro Interface (UMI) to enable programming of the robot control macros. This capability runs on a single Silicon Graphics Inc. machine. The operator can employ either manual teleoperation, shared control, or supervised autonomous control to manipulate the intended object. The remote site controller, called the Modular Telerobot Task Execution System (MOTES), runs in a multi-processor VME environment and performs the task sequencing, task execution, trajectory generation, closed loop force/torque control, task parameter monitoring, and reflex action. This paper describes the new STELER architecture implementation, and also documents the results of the recent autonomous docking task execution using the local site and MOTES.

Zimmerman, Wayne↗
NASA NTRS1999

Photon-Counting Multikilohertz Microlaser Altimeters

Spaceborne laser altimeters in planetary orbit typically use high energy (approximately 100 mJ) solid state lasers, large telescopes (50 to 100 cm), and high detection thresholds to achieve unambiguous surface returns with few or no ifalse alarmsi resulting from solar background noise. As a result of this conservative design philosophy, spacecraft prime power weight, or size constraints typically restrict operations to modest repetition rates on the order of a few tens of Hz which, at a typical ground velocity of 7 Km/sec, limits along-track spatial sampling to one sample every few hundred meters. The surface return rate of an Earth-orbiting altimeter can be increased by up to two orders of magnitude for a given laser output power by emitting the available photons in a high frequency (few KHz) train of low energy (< 1 mJ) pulses, as produced by passively Q-switched solid state "microlasers", and using single photon detection. while simultaneously using much smaller telescope diameters on the order of 10 cm. Simple onboard software algorithms, based on post-detection Poisson filtering techniques, can be employed to identify and extract the surface data from solar background noise prior to onboard data storage or transmission to a ground station. Under NASAis Instrument Incubator Program, we have begun the design and construction of a scanning airborne instrument to demonstrate the potential advantages of the technique for future space missions.

Degnan, John J.↗
NASA NTRS2004

Activities of NASA's Global Modeling Initiative (GMI) in the Assessment of Subsonic Aircraft Impact

The Intergovernmental Panel on Climate Change estimated a peak increase in ozone ranging from 7-12 ppbv (zonal and annual average, and relative to a baseline with no aircraft), due to the subsonic aircraft in the year 2015, corresponding to aircraft emissions of 1.3 TgN/year. This range of values presumably reflects differences in model input (e.g., chemical mechanism, ground emission fluxes, and meteorological fields), and algorithms. The model implemented by the Global Modeling Initiative allows testing the impact of individual model components on the assessment calculations. We present results of the impact of doubling the 1995 aircraft emissions of NOx, corresponding to an extra 0.56 TgN/year, utilizing meteorological data from NASA's Data Assimilation Office (DAO), the Goddard Institute for Space Studies (GISS), and the Middle Atmosphere Community Climate Model, version 3 (MACCM3). Comparison of results to observations can be used to assess the model performance. Peak ozone perturbations ranging from 1.7 to 2.2 ppbv of ozone are calculated using the different fields. These correspond to increases in total tropospheric ozone ranging from 3.3 to 4.1 Tg/Os. These perturbations are consistent with the IPCC results, due to the difference in aircraft emissions. However, the range of values calculated is much smaller than in IPCC.

Rodriquez, J. M.↗
NASA NTRS2011

Validation of Real-Time Data Processing for the Ground and Air-MSPI Systems

JPL is currently developing the multi-angle spectro-polarimetric imager (MSPI), targeted for the Aerosol-Cloud-Ecosystems (ACE) mission, as defined in the National Academies 2007 Decadal Survey. In preparation for the space instrument, the MSPI team has built two incremental camera systems (Ground- and Air-MSPI) to improve understanding of the proposed architecture. Ground-MSPI is a gimballed instrument used primarily for stationary observation and characterization of the imager and optics. The ER-2 based Air-MSPI operates in a step-and-stare mode, providing multi-angle imaging of a static target. This mode-of-operation simulates the observation scenario of the space instrument. Physically, MSPI is a pushbroom camera with a specialized frontend. Before imaging, light entering the camera passes through a pair of photoelastic modulators and a set of pattern polarizers. These optical elements act on the light to make polarimetric extraction computationally feasible. Calculating polarimetric parameters from the imager's data stream requires a real-time least-squares computation that produces coefficients of a truncated time-series expansion of the image. As reported in, the data processing algorithm can operate in real-time on a Xilinx Virtex-5 FPGA. Moving beyond verification with an onboard data source, the algorithm has been validated on a commercial development board interfaced with the ground camera. In addition, the algorithm has been instantiated within the Air-MSPI electronics board's FPGA, and in situ first-light has been achieved.

real-time data processing↗
NASA NTRS2020

Airborne Radiometry for Calibration, Validation, and Research in Oceanic, Coastal, and Inland Waters

Present-day ocean color satellite sensors, which principally provide reliable data on chlorophyll, sediments, and colored dissolved organic material in the open ocean, are not well suited for coastal and inland water studies for a variety of reasons, including coarse spatial and spectral resolution plus challenges with atmospheric correction. National Aeronautics and Space Administration (NASA) airborne mission concepts tested in 2011, 2013, 2017, and 2018 over Monterey Bay, CA, and nearby inland waters have demonstrated the feasibility of improving airborne monitoring and research activities in case-1 and case-2 aquatic ecosystems through the combined use of state-of-the-art above- and in-water measurement capabilities. These competencies have evolved through time to produce a sensor-web approach: imaging spectrometer, microradiometers, and a sun photometer (airborne) with their analogous algorithms, and with corresponding in-water radiometers and ground-based sun photometry. The NASA airborne instrument suite and mission concept demonstrations, leveraging high quality above- and in-water data, significantly improves the fidelity as well as the spatial and spectral resolution of observations for studying and monitoring water quality in oceanic, coastal, and inland water ecosystems. The goal of this series of projects was to develop and fly a portable airborne sensor suite for NASA science missions focusing on a gradient of water types from oligotrophic to turbid waters addressing the challenges of an optically complex coastal ocean zone and inland waters. The airborne radiometry in this range of aquatic conditions and sites has supported improved results of studies of water quality and biogeochemistry and provides capabilities for research areas such as ocean productivity and biogeochemistry; aquatic impacts of coastal landscape alteration; coastal, estuarine, and inland waters ecosystem productivity; atmospheric correction; and regional climate variability.

atmospheric correction↗
NASA NTRS1999

The Rondonia Lightning Detection Network: Network Description, Science Objectives, Data Processing/Archival Methodology, and First Results

A four station Advanced Lightning Direction Finder (ALDF) network was recently established in the state of Rondonia in western Brazil through a collaboration of U.S. and Brazilian participants from NASA, INPE, INMET, and various universities. The network utilizes ALDF IMPACT (Improved Accuracy from Combined Technology) sensors to provide cloud-to-ground lightning observations (i.e., stroke/flash locations, signal amplitude, and polarity) using both time-of-arrival and magnetic direction finding techniques. The observations are collected, processed and archived at a central site in Brasilia and at the NASA/ Marshall Space Flight Center (MSFC) in Huntsville, Alabama. Initial, non-quality assured quick-look results are made available in near real-time over the internet. The network will remain deployed for several years to provide ground truth data for the Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite which was launched in November 1997. The measurements will also be used to investigate the relationship between the electrical, microphysical and kinematic properties of tropical convection. In addition, the long-term observations from this network will contribute in establishing a regional lightning climatological data base, supplementing other data bases in Brazil that already exist or may soon be implemented. Analytic inversion algorithms developed at NASA/Marshall Space Flight Center (MSFC) are now being applied to the Rondonian ALDF lightning observations to obtain site error corrections and improved location retrievals. The processing methodology and the initial results from an analysis of the first 6 months of network operations will be presented.

Blakeslee, Rich↗