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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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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Exploring the Utility of the Planned CYGNSS Mission for Investigating the Initiation and Development of the Madden-Julian Oscillation

CYGNSS is a planned constellation consisting of multiple micro-satellites that leverage the Global Positioning System (GPS) to provide rapidly updated, high resolution (approx. 15-50 km, approx. 4 h) surface wind speeds (via bi-static scatterometry) over the tropical oceans in any weather condition, including heavy rainfall. The approach of the work to be presented at this conference is to utilize a limited-domain, cloud-system resolving model (Weather Research and Forecasting or WRF) and its attendant data assimilation scheme (Three-Dimensional Variational Assimilation or 3DVAR) to investigate the utility of the CYGNSS mission for helping characterize key convectiveto- mesoscale processes - such as surface evaporation, moisture advection and convergence, and upscale development of precipitation systems - that help drive the initiation and development of the Madden-Julian Oscillation (MJO) in the equatorial Indian Ocean. The proposed work will focus on three scientific objectives. Objective 1 is to produce a high-resolution surface wind dataset resolution (approx. 0.5 h, approx. 1-4 km) for multiple MJO onsets using WRF-assimilated winds and other data from the DYNAmics of the MJO (DYNAMO) field campaign, which took place during October 2011 - March 2012. Objective 2 is to study the variability of surface winds during MJO onsets at temporal and spatial scales of finer resolution than future CYGNSS data. The goal is to understand how sub-CYGNSS-resolution processes will shape the observations made by the satellite constellation. Objective 3 is to ingest simulated CYGNSS data into the WRF model in order to perform observing system simulation experiments (OSSEs). These will be used to test and quantify the potential beneficial effects provided by CYGNSS, particularly for characterizing the physical processes driving convective organization and upscale development during the initiation and development of the MJO. The proposed research is ideal for answering important questions about the CYGNSS mission, such as the representativeness of surface wind retrievals in the context of the complex airflow processes that occur during heavy precipitation, as well as the tradeoffs in retrieval accuracy that result from finer spatial resolution of the CYGNSS winds versus increased errors/noisiness in those data. Research plans and initial progress toward these objectives will be presented.

Lang, Timothy↗
NASA NTRS1976

Forest Classification Accuracy as Influenced by Multispectral Scanner Spatial Resolution

The author has identified the following significant results. A supervised classification within two separate ground areas of the Sam Houston National Forest was carried out for two sq meters spatial resolution MSS data. Data were progressively coarsened to simulate five additional cases of spatial resolution ranging up to 64 sq meters. Similar processing and analysis of all spatial resolutions enabled evaluations of the effect of spatial resolution on classification accuracy for various levels of detail and the effects on area proportion estimation for very general forest features. For very coarse resolutions, a subset of spectral channels which simulated the proposed thematic mapper channels was used to study classification accuracy.

Nalepka, R. F.↗
NASA NTRS2005

Sub-pixel Spatial Resolution Micro-roughness Measurements with Interlaced Stitching

In this paper we describe a method to increase the spatial resolution of surface micro-roughness measurements. As the surface specifications for precision optics become more demanding, the metrology instruments must cover a broad spatial frequency range. Generally, multiple instruments are used to cover the full range of the specifications. For example, a Fizeau interferometer would be used to test low spatial frequency surface errors, a white light interferometer would be used for mid spatial frequency errors, and an AFM would be used for high spatial frequency errors. For some precision optics, three instruments would be necessary. However, in many applications, an increase in the spatial resolution of a metrology instrument could negate the need for multiple instruments. A solution to increase the spatial resolution of micro-roughness measurements obtained using white light interferometry with "interlaced stitching" will be presented. In "interlaced stitching", multiple interferometric measurements are made as the optic under test (or the CCD array) is laterally shifted at sub-pixel increments. The measurements are then combined to construct a measurement with higher spatial resolution. Initial results obtained while implementing a similar process used to increase the spatial resolution of measurements made with a commercially available Fizeau interferometer will be presented.

Mooney, James T.↗
NASA NTRS1999

Polar Geophysics Products Derived from AVHRR: The "AVHRR Polar Pathfinder

This NOAA/NASA Pathfinder effort was established to locate, acquire, and process Advanced Very High Resolution Radiometer (AVHRR) imagery into geo-located and calibrated radiances, cloud masks, surface clear-sky broadband albedo, clear-sky skin temperatures, satellite viewing times, and viewing and solar geometry for the, high-latitude portions of the northern and southern hemispheres (all area north of 48N and south of 53S). AVHRR GAC data for August 1981 - July 1998 were acquired, with some gaps remaining, and processed into twice-daily 5-km grids, with some products also provided at 25-km resolution. AVHRR LAC data for 3.5 years of coverage in the northern hemisphere and 2.75 years of coverage in the southern hemisphere were processed into 1.25-km grids for the same suite of products. The resulting data sets are presently being transferred to the National Snow and Ice Data Center (NSIDC) for archiving and distribution. Using these data, researchers now have at their disposal an extensive AVHRR data set for investigations of high-latitude processes. In addition, the data lend themselves to development and testing of algorithms. The products are particularly relevant for climate research and algorithm development as applied to relatively long time periods and large areas.

Maslanik, James↗
NASA NTRS1983

A parallel-pipeline architecture of the fast polynomial transform for computing a two-dimensional cyclic convolution

It is pointed out that the two-dimensional cyclic convolution is a useful tool for many two-dimensional digital signal processing applications. Two important applications are related to spaceborne high-resolution synthetic aperture radar (SAR) processing and image processing. Nussbaumer and Quandalle (1978) showed that a radix-2 polynomial transform analogous to the conventional radix-2 FFT algorithm can be used to compute a two-dimensional cyclic convolution. On the basis of results reported by Arambepola and Rayner (1979), a radix-2 polynomial transform can be defined to compute a multidimensional cyclic convolution. Truong et al. (1981) used the considered ideas together with the Chinese Theorem to further reduce the complexity of the radix-2 fast polynomial transform (FPT). Reed et al. (1981) demonstrated that such a new FPT algorithm is significantly faster than the FFT algorithm for computing a two-dimensional convolution. In the present investigation, a parallel-pipeline architecture is considered for implementing the FPT developed by Truong et al.

Truong, T. K.↗
NASA NTRS1988

Dependence of warm and cold climate depiction on climate model resolution

Climate change simulations run with two different resolutions (8 deg by 10 deg and 4 deg by 5 deg) of the NASA Goddard Institute for Space Studies model are used to investigate radiative, dynamical, and regional sensitivities to model grid size. The results show that model resolution affected two key processes in the control runs, moist convection and the nonlinear transfer of kinetic energy into the zonal mean flow. It was found that the finer resolution model has more penetrative convection but less convection overall, with the results that its temperature and wind structure were altered with respect to the coarser grid model.

Rind, David↗
NASA NTRS2006

SI: The Stellar Imager

The ultra-sharp images of the Stellar Imager (SI) will revolutionize our view of many dynamic astrophysical processes: The 0.1 milliarcsec resolution of this deep-space telescope will transform point sources into extended sources, and simple snapshots into spellbinding evolving views. SI s science focuses on the role of magnetism in the Universe, particularly on magnetic activity on the surfaces of stars like the Sun. SI s prime goal is to enable long-term forecasting of solar activity and the space weather that it drives in support of the Living With a Star program in the Exploration Era by imaging a sample of magnetically active stars with enough resolution to map their evolving dynamo patterns and their internal flows. By exploring the Universe at ultra-high resolution, SI will also revolutionize our understanding of the formation of planetary systems, of the habitability and climatology of distant planets, and of many magnetohydrodynamically controlled structures and processes in the Universe.

Carpenter, Kenneth G.↗
NASA NTRS2007

Evaluating the Capacity of Global CO2 Flux and Atmospheric Transport Models to Incorporate New Satellite Observations

As we enter the new era of satellite remote sensing for CO2 and other carbon cyclerelated quantities, advanced modeling and analysis capabilities are required to fully capitalize on the new observations. Model estimates of CO2 surface flux and atmospheric transport are required for initial constraints on inverse analyses, to connect atmospheric observations to the location of surface sources and sinks, and ultimately for future projections of carbon-climate interactions. For application to current, planned, and future remotely sensed CO2 data, it is desirable that these models are accurate and unbiased at time scales from less than daily to multi-annual and at spatial scales from several kilometers or finer to global. Here we focus on simulated CO2 fluxes from terrestrial vegetation and atmospheric transport mutually constrained by analyzed meteorological fields from the Goddard Modeling and Assimilation Office for the period 1998 through 2006. Use of assimilated meteorological data enables direct model comparison to observations across a wide range of scales of variability. The biospheric fluxes are produced by the CASA model at lxi degrees on a monthly mean basis, modulated hourly with analyzed temperature and sunlight. Both physiological and biomass burning fluxes are derived using satellite observations of vegetation, burned area (as in GFED-2), and analyzed meteorology. For the purposes of comparison to CO2 data, fossil fuel and ocean fluxes are also included in the transport simulations. In this presentation we evaluate the model's ability to simulate CO2 flux and mixing ratio variability in comparison to in situ observations at sites in Northern mid latitudes and the continental tropics. The influence of key process representations is inferred. We find that the model can resolve much of the hourly to synoptic variability in the observations, although there are limits imposed by vertical resolution of boundary layer processes. The seasonal cycle and its interannual variations generally respond adequately, but discrepancies in the tropics suggest the need for a refinement of the soil moisture dependence of the respiration flux in CASA. Examples and inferences for interpretation of satellite data will be discussed. In general, the fidelity of these simulations leads us to anticipate incorporation of real-time, highly resolved remote sensing and other observations into quantitative analyses that will reduce uncertainty in the terrestrial CO2 sink and revolutionize our understanding of the key processes controlling atmospheric CO2 and its evolution with time.

Kawa, S. R.↗
NASA NTRS2002

Software for Partly Automated Recognition of Targets

The Feature Analyst is a computer program for assisted (partially automated) recognition of targets in images. This program was developed to accelerate the processing of high-resolution satellite image data for incorporation into geographic information systems (GIS). This program creates an advanced user interface that embeds proprietary machine-learning algorithms in commercial image-processing and GIS software. A human analyst provides samples of target features from multiple sets of data, then the software develops a data-fusion model that automatically extracts the remaining features from selected sets of data. The program thus leverages the natural ability of humans to recognize objects in complex scenes, without requiring the user to explain the human visual recognition process by means of lengthy software. Two major subprograms are the reactive agent and the thinking agent. The reactive agent strives to quickly learn the user's tendencies while the user is selecting targets and to increase the user's productivity by immediately suggesting the next set of pixels that the user may wish to select. The thinking agent utilizes all available resources, taking as much time as needed, to produce the most accurate autonomous feature-extraction model possible.

Opitz, David↗
NASA NTRS2003

Software for Partly Automated Recognition of Targets

The Feature Analyst is a computer program for assisted (partially automated) recognition of targets in images. This program was developed to accelerate the processing of high-resolution satellite image data for incorporation into geographic information systems (GIS). This program creates an advanced user interface that embeds proprietary machine-learning algorithms in commercial image-processing and GIS software. A human analyst provides samples of target features from multiple sets of data, then the software develops a data-fusion model that automatically extracts the remaining features from selected sets of data. The program thus leverages the natural ability of humans to recognize objects in complex scenes, without requiring the user to explain the human visual recognition process by means of lengthy software. Two major subprograms are the reactive agent and the thinking agent. The reactive agent strives to quickly learn the user s tendencies while the user is selecting targets and to increase the user s productivity by immediately suggesting the next set of pixels that the user may wish to select. The thinking agent utilizes all available resources, taking as much time as needed, to produce the most accurate autonomous feature-extraction model possible.

Opitz, David↗
NASA NTRS1987

Real-time data compressor for Eos-class missions

A conceptual design for a real-time VLSI compressor capable of processing rate up to one gigabit per second is presented. This scheme is capable of providing a three-to-one distortion-free data reduction factor to both the High Resolution Imaging Spectrometer and processed SAR imaging data. The design uses a VLSI parallel/piplined architecture capable of processing at a real time rate. The design consists of a parallel array of VLSI compressor modules. Each module is built on a single customized VLSI chip using existing state-of-the-art semiconductor technology.

Lee, Jun-Ji↗
NASA NTRS1991

Robot graphic simulation testbed

The objective of this research was twofold. First, the basic capabilities of ROBOSIM (graphical simulation system) were improved and extended by taking advantage of advanced graphic workstation technology and artificial intelligence programming techniques. Second, the scope of the graphic simulation testbed was extended to include general problems of Space Station automation. Hardware support for 3-D graphics and high processing performance make high resolution solid modeling, collision detection, and simulation of structural dynamics computationally feasible. The Space Station is a complex system with many interacting subsystems. Design and testing of automation concepts demand modeling of the affected processes, their interactions, and that of the proposed control systems. The automation testbed was designed to facilitate studies in Space Station automation concepts.

Cook, George E.↗
NASA NTRS2023

The Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) Project: A Review

The Southern Ocean serves as the primary gateway through which the intermediate, deep, and bottom waters of the ocean interact with the surface ocean (and thus the atmosphere), and it has a profound influence on the oceanic uptake of anthropogenic carbon and heat as well as nutrient resupply from the abyss to the surface. Yet it has been the least observed and understood region of the world ocean. The Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) project was implemented in 2014 with a goal to help remedy this deficit in observations and understanding. The SOCCOM project is based on two major advances that have the potential to transform understanding of the Southern Ocean. The first is the development of new biogeochemical sensors mounted on autonomous profiling floats that allow sampling of ocean biogeochemistry in 3-dimensional space. Floats may detect processes with a temporal resolution that ranges from hours to years. The second is that the climate modeling community finally has the computational resources and physical understanding to develop fully coupled climate models that can represent crucial, mesoscale processes in the Southern Ocean, as well as corresponding models that assimilate observations to produce a state estimate. The observational component, based on deployment of profiling floats with oxygen, nitrate, pH and bio-optical sensors, is generating vast amounts of new biogeochemical data that provide a year-round view of the Southern Ocean from the surface to 2000 m. The modeling effort is applying these observations and enhancing our understanding of the current ocean, and reducing uncertainty in projections of future carbon and nutrient cycles and climate. After nine years of operation, including a project renewal in the sixth year, the SOCCOM project has deployed more than 260 profiling floats. These floats have collected over 27,000 vertical profiles throughout the Southern Ocean. A data-assimilating biogeochemical state estimate model has been implemented. Here, the design of the SOCCOM project is reviewed and the scientific results that have been obtained are described. The project’s capability to help meet the observing system priorities outlined for a notional UN Decade for Ocean Sciences Southern Ocean observing system is assessed.

Jorge L. Sarmiento↗
NASA NTRS2016

Progress on the Fabrication of High Resolution and Lightweight Monocrystalline Silicon X-ray Mirrors

Monocrystalline silicon is an excellent X-ray mirror substrate material due to its high stiffness, low density, high thermal conductivity, zero internal stress, and commercial availability. Our work at NASA Goddard Space Flight Center focuses on identifying and developing a manufacturing process to produce high resolution and lightweight X-ray mirror segments in a cost and time effective manner. Previous efforts focused on demonstrating the feasibility of cylindrical silicon mirror polishing and lightweighting. Present efforts are aimed towards producing true paraboloidal and hyperboloidal mirror surfaces on the lightweight silicon segments. This paper presents results from these recent investigations, including a mirror which features a surface quality sufficient for a 3 arcsecond telescope.

X-ray optics↗
NASA NTRS2019

A Long-Term Vision for Space-Based Interferometry

The processes leading to the formation of planets; the extreme physics occurring near the event horizon of black holes; detailed studies of exoplanets through spectral-spatial mapping: new and unique insights into the physical processes involved across nearly the whole gamut of astrophysics await discovery at small angular scales. The fine spatial resolution needed to explore these processes, however, lies beyond the capabilities of current astronomical facilities and nearly all proposed future facilities. Interferometers can crack this angular resolution problem, and space-based interferometry missions promise to explore entirely new regions of scientific phase space, providing unique new insights into the physical processes lurking at small angular scales.

Rinehart, S. A.↗
NASA NTRS1985

Massively parallel processor

A brief description is given of the Massively Parallel Processor (MPP). Major applications of the MPP are in the area of image processing (where the operands are often very small integers) from very high spatial resolution passive image sensors, signal processing of radar data, and numerical modeling simulations of climate. The system can be programmed in assembly language or a high level language. Information on background, status, architecture, programming, hardware reliability, applications, and the MPP's development as a national resource for parallel algorithm research are presented in outline form.

Source record↗
NASA NTRS1981

Development of a ground signal processor for digital synthetic array radar data

A modified APQ-102 sidelooking array radar (SLAR) in a B-57 aircraft test bed is used, with other optical and infrared sensors, in remote sensing of Earth surface features for various users at NASA Johnson Space Center. The video from the radar is normally recorded on photographic film and subsequently processed photographically into high resolution radar images. Using a high speed sampling (digitizing) system, the two receiver channels of cross-and co-polarized video are recorded on wideband magnetic tape along with radar and platform parameters. These data are subsequently reformatted and processed into digital synthetic aperture radar images with the image data available on magnetic tape for subsequent analysis by investigators. The system design and results obtained are described.

Griffin, C. R.↗
NASA NTRS2005

Spatial Scaling of Snow Observations and Microwave Emission Modeling During CLPX and Appropriate Satellite Sensor Resolution

Accurate estimates of snow water equivalent and other properties play an important role in weather, natural hazard, and hydrological forecasting and climate modeling over a range of scales in space and time. Remote sensing-derived estimates have traditionally been of the "snapshot" type, but techniques involving models with assimilation are also being explored. In both cases, forward emission models are useful to understand the observed passive microwave signatures and developing retrieval algorithms. However, mismatches between passive microwave sensor resolutions and the scales of processes controlling subpixel heterogeneity can affect the accuracy of the estimates. Improving the spatial resolution of new passive microwave satellite sensors is a major desire in order to (literally) resolve such subpixel heterogeneity, but limited spacecraft and mission resources impose severe constraints and tradeoffs. In order to maximize science return while mitigating risk for a satellite concept, it is essential to understand the scaling behavior of snow in terms of what the sensor sees (brightness temperature) as well as in terms of the actual variability of snow. NASA's Cold Land Processes Experiment-1 (CLPX-1: Colorado, 2002 and 2003) was designed to provide data to measure these scaling behaviors for varying snow conditions in areas with forested, alpine, and meadow/pasture land cover. We will use observations from CLPX-1 ground, airborne, and satellite passive microwave sensors to examine and evaluate the scaling behavior of observed and modeled brightness temperatures and observed and retrieved snow parameters across scales from meters to 10's of kilometers. The conclusions will provide direct examples of the appropriate spatial sampling scales of new sensors for snow remote sensing. The analyses will also illustrate the effects and spatial scales of the underlying phenomena (e.g., land cover) that control subpixel heterogeneity.

Kim, Edward J.↗