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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Estimating Volume, Biomass, and Carbon in Hedmark County, Norway Using a Profiling LiDAR

A profiling airborne LiDAR is used to estimate the forest resources of Hedmark County, Norway, a 27390 square kilometer area in southeastern Norway on the Swedish border. One hundred five profiling flight lines totaling 9166 km were flown over the entire county; east-west. The lines, spaced 3 km apart north-south, duplicate the systematic pattern of the Norwegian Forest Inventory (NFI) ground plot arrangement, enabling the profiler to transit 1290 circular, 250 square meter fixed-area NFI ground plots while collecting the systematic LiDAR sample. Seven hundred sixty-three plots of the 1290 plots were overflown within 17.8 m of plot center. Laser measurements of canopy height and crown density are extracted along fixed-length, 17.8 m segments closest to the center of the ground plot and related to basal area, timber volume and above- and belowground dry biomass. Linear, nonstratified equations that estimate ground-measured total aboveground dry biomass report an R(sup 2) = 0.63, with an regression RMSE = 35.2 t/ha. Nonstratified model results for the other biomass components, volume, and basal area are similar, with R(sup 2) values for all models ranging from 0.58 (belowground biomass, RMSE = 8.6 t/ha) to 0.63. Consistently, the most useful single profiling LiDAR variable is quadratic mean canopy height, h (sup bar)(sub qa). Two-variable models typically include h (sup bar)(sub qa) or mean canopy height, h(sup bar)(sub a), with a canopy density or a canopy height standard deviation measure. Stratification by productivity class did not improve the nonstratified models, nor did stratification by pine/spruce/hardwood. County-wide profiling LiDAR estimates are reported, by land cover type, and compared to NFI estimates.

Nelson, Ross↗
NASA NTRS1999

Apparent Endless Extraction of Energy from the Vacuum by Cyclic Manipulation of Casimir Cavity Dimensions

In 1983, Ambjorn and Wolfram produced plots of the energy density of the quantum mechanical electromagnetic fluctuations in a volume of vacuum bounded by perfectly conducting walls in the shape of a rectangular cavity of dimensions a(1), a(2), and a(3), as a function of the ratios a(2)/a(1) and a(3)/a(1). Portions of these plots are double-valued, in that they allow rectangular cavities with the same, value of a(2)/a(1), but different values of a(3)/a(1), to have the saint total energy. Using these double-valued regions of the plots, I show that it is possible to define a "Casimir Vacuum Energy Extraction Cycle" which apparently would allow for the endless extraction of energy from the vacuum in the Casimir cavity by cyclic manipulation of the Casimir cavity dimensions.

Forward, Robert L.↗
NASA NTRS1975

Vector plotting as an indication of the approach to flutter

A binary flexure-torsion analysis was made to check theoretically a method for predicting flutter which depends on plotting vectorially the amplitudes of response relative to the exciting force and extracting the relevant damping rate. The results of this calculation are given in graphs both of the vector plots themselves and of the estimated damping rate against forward speed. The estimated damping rates are compared with calculated values. The method has the advantage that in a flight flutter test damping can be estimated from continuous excitation records: the method is an extension of the Kennedy and Pancu technique used in ground resonance testing.

Broadbent, E. G.↗
NASA NTRS2016

A Possible Explanation for the Z-R Parameter Inconsistency when Comparing Stratiform and Convective Rainfall

The well-known Z-R power law Z A R(sup b) uses two parameters, A and b, in order to relate rainfall rate R to measured weather radar reflectivity Z. A common method used by researchers is to compute Z and R from disdrometer data and then extract the A-b parameter pair from a log-linear line fit to a scatter plot of Z-R pairs. Even though it may seem far more truthful to extract the parameter pair from a fit of radar Z(sub R) versus gauge rainfall rate R(sub G), the extreme difference in spatial and temporal sampling volumes between radar and rain gauge creates a slew of problems that can generally only be solved by using rain gauge arrays and long sampling averages. Disdrometer derived A-b parameters are easily obtained and can provide information for the study of stratiform versus convective rainfall. However, an inconsistency appears when comparing averaged A-b pairs from various researchers. Values of b range from 1.26 to 1.51 for both stratiform and convective events. Paradoxically the values of A fall into three groups: 150 to 200 for convective; 200 to 400 for stratiform; and 400 to 500 again for convective. This apparent inconsistency can be explained by computing the A-b pair using the gamma DSD coupled with a modified drop terminal velocity model, v(D) alpha D(sup beta) - w, where w is a somewhat artificial constant vertical velocity of the air above the disdrometer. This model predicts three regions of A, corresponding to w less than 0, w = 0, and w greater than 0, which approximately matches observed data.

gamma DSD↗
NASA NTRS2004

Computing and combustion

Coming into the Combustion Branch of the Turbomachinery and Propulsion Systems Division, there was not any set project planned out for me to work on. This was understandable, considering I am only at my sophmore year in college. Also, my mentor was a division chief and it was expected that I would be passed down the line. It took about a week for me to be placed with somebody who could use me. My first project was to write a macro for TecPlot. Commonly, a person would have a 3D contour volume modeling something such as a combustion engine. This 3D volume needed to have slices extracted from it and made into 2D scientific plots with all of the appropriate axis and titles. This was very tedious to do by hand. My macro needed to automate the process. There was some education I needed before I could start, however. First, TecPlot ran on Unix and Linux, like a growing majority of scientific applications. I knew a little about Linux, but I would need to know more to use the software at hand. I took two classes at the Learning Center on Unix and am now comfortable with Linux and Unix. I already had taken Computer Science I and II, and had undergone the transformation from Computer Programmer to Procedural Epistemologist. I knew how to design efficient algorithms, I just needed to learn the macro language. After a little less than a week, I had learned the basics of the language. Like most languages, the best way to learn more of it was by using it. It was decided that it was best that I do the macro in layers, starting simple and adding features as I went. The macro started out slicing with respect to only one axis, and did not make 2D plots out of the slices. Instead, it lined them up inside the solid. Next, I allowed for more than one axis and placed each slice in a separate frame. After this, I added code that transformed each individual slice-frame into a scientific plot. I also made frames for composite volumes, which showed all of the slices in the same XYZ space. I then designed an addition companion macro that exported each frame into its own image file. I then distributed the macros to a test group, and am awaiting feedback. In the meantime, a am researching the possible applications of distributed computing on the National Combustor Code. Many of our Linux boxes were idle for most of the day. The department thinks that it would be wonderful if we could get all of these idle processors to work on a problem under the NCC code. The client software would have to be easily distributed, such as in screensaver format or as a program that only ran when the computer was not in use. This project proves to be an interesting challenge.

Thompson, Daniel↗
NASA NTRS2004

Apparent I-Xe Cooling Rates of Chondrules Compared with Silicates from the Colomera Iron Meteorite

In I-Xe dating, a regular pattern of increasing Xe-129/128Xe-128 ratio with increasing extraction temperature is often observed. If one makes the crude assumption that the temperatures at which the Xe is extracted in the laboratory is approximately the same as the temperature at which those sites closed 4.6 Ga ago, a (zeroth order) model cooling rate can be found. In order to test and refine this model we can apply the cooling theory of Dodson to those extraction steps approaching the I-Xe isochrons. Using an Arrhenius plot for these temperature fractions, and assuming that an only single phase is involved, the effective diffusion parameters can be estimated (frequency factor and activation energy). From the apparent (zeroth order) cooling rate, the closure temperature can be estimated from the Dodson equation. This model closure temperature can then be compared with the actual laboratory temperature at which the isochron begins. The ratio of the closure temperature and the temperature corresponding to the start of the isochron provides the ratio of the two temperature scales, incorporation and extraction. The actual cooling rate is then given by the apparent (zeroth order) cooling rate times the temperature scale factor. Figure 1 shows Arrhenius plots for I-Xe data

Hohenberg, C. M.↗
NASA NTRS1992

New developments of a knowledge based system (VEG) for inferring vegetation characteristics

An extraction technique for inferring physical and biological surface properties of vegetation using nadir and/or directional reflectance data as input has been developed. A knowledge-based system (VEG) accepts spectral data of an unknown target as input, determines the best strategy for inferring the desired vegetation characteristic, applies the strategy to the target data, and provides a rigorous estimate of the accuracy of the inference. Progress in developing the system is presented. VEG combines methods from remote sensing and artificial intelligence, and integrates input spectral measurements with diverse knowledge bases. VEG has been developed to (1) infer spectral hemispherical reflectance from any combination of nadir and/or off-nadir view angles; (2) test and develop new extraction techniques on an internal spectral database; (3) browse, plot, or analyze directional reflectance data in the system's spectral database; (4) discriminate between user-defined vegetation classes using spectral and directional reflectance relationships; and (5) infer unknown view angles from known view angles (known as view angle extension).

Kimes, D. S.↗
NASA NTRS2003

Extraction of Qualitative Features from Sensor Data Using Windowed Fourier Transform

In this paper, we use Matlab to model the health monitoring of a system through the information gathered from sensors. This implies assessment of the condition of the system components. Once a normal mode of operation is established any deviation from the normal behavior indicates a change. This change may be due to a malfunction of an element, a qualitative change, or a change due to a problem with another element in the network. For example, if one sensor indicates that the temperature in the tank has experienced a step change then a pressure sensor associated with the process in the tank should also experience a step change. The step up and step down as well as sensor disturbances are assumed to be exponential. An RC network is used to model the main process, which is step-up (charging), drift, and step-down (discharging). The sensor disturbances and spike are added while the system is in drift. The system is allowed to run for a period equal to three time constant of the main process before changes occur. Then each point of the signal is selected with a trailing data collected previously. Two trailing lengths of data are selected, one equal to two time constants of the main process and the other equal to two time constants of the sensor disturbance. Next, the DC is removed from each set of data and then the data are passed through a window followed by calculation of spectra for each set. In order to extract features the signal power, peak, and spectrum are plotted vs time. The results indicate distinct shapes corresponding to each process. The study is also carried out for a number of Gaussian distributed noisy cases.

Amini, Abolfazl M.↗
NASA NTRS1997

Comparison Tools for Assessing the Microgravity Environment of Missions, Carriers and Conditions

The Principal Component Spectral Analysis and the Quasi-steady Three-dimensional Histogram techniques provide the means to describe the microgravity acceleration environment of an entire mission on a single plot. This allows a straight forward comparison of the microgravity environment between missions, carriers, and conditions. As shown in this report, the PCSA and QTH techniques bring both the range and median of the microgravity environment onto a single page for an entire mission or another time period or condition of interest. These single pages may then be used to compare similar analyses of other missions, time periods or conditions. The PCSA plot is based on the frequency distribution of the vibrational energy and is normally used for an acceleration data set containing frequencies above the lowest natural frequencies of the vehicle. The QTH plot is based on the direction and magnitude of the acceleration and is normally used for acceleration data sets with frequency content less than 0.1 Hz. Various operating conditions are made evident by using PCSA and QTH plots. Equipment operating either full or part time with sufficient magnitude to be considered a disturbance is very evident as well as equipment contributing to the background acceleration environment. A source's magnitude and/or frequency variability is also evident by the source's appearance on a PCSA plot. The PCSA and QTH techniques are valuable tools for extracting useful information from acceleration data taken over large spans of time. This report shows that these techniques provide a tool for comparison between different sets of microgravity acceleration data, for example different missions, different activities within a mission, and/or different attitudes within a mission. These techniques, as well as others, may be employed in order to derive useful information from acceleration data.

DeLombard, Richard↗
NASA NTRS2017

Framework for Processing Citizens Science Data for Applications to NASA Earth Science Missions

Citizen science (or crowdsourcing) has drawn much high-level recent and ongoing interest and support. It is poised to be applied, beyond the by-now fairly familiar use of, e.g., Twitter for natural hazards monitoring, to science research, such as augmenting the validation of NASA earth science mission data. This interest and support is seen in the 2014 National Plan for Civil Earth Observations, the 2015 White House forum on citizen science and crowdsourcing, the ongoing Senate Bill 2013 (Crowdsourcing and Citizen Science Act of 2015), the recent (August 2016) Open Geospatial Consortium (OGC) call for public participation in its newly-established Citizen Science Domain Working Group, and NASA's initiation of a new Citizen Science for Earth Systems Program (along with its first citizen science-focused solicitation for proposals). Over the past several years, we have been exploring the feasibility of extracting from the Twitter data stream useful information for application to NASA precipitation research, with both "passive" and "active" participation by the twitterers. The Twitter database, which recently passed its tenth anniversary, is potentially a rich source of real-time and historical global information for science applications. The time-varying set of "precipitation" tweets can be thought of as an organic network of rain gauges, potentially providing a widespread view of precipitation occurrence. The validation of satellite precipitation estimates is challenging, because many regions lack data or access to data, especially outside of the U.S. and in remote and developing areas. Mining the Twitter stream could augment these validation programs and, potentially, help tune existing algorithms. Our ongoing work, though exploratory, has resulted in key components for processing and managing tweets, including the capabilities to filter the Twitter stream in real time, to extract location information, to filter for exact phrases, and to plot tweet distributions. The key step is to process the "precipitation" tweets to be compatible with satellite-retrieved precipitation data. These key components for processing and managing "precipitation" tweets (and additional ones to be developed) are not limited to precipitation, nor are they limited to the Twitter social medium. Indeed, to maximize the value of our work for NASA earth science programs, these components should be generalized and be part of an overall framework for processing citizen science data for science research. In this paper, we outline such a framework.

earth science satellite data↗
NASA NTRS2001

Millimeter-Wave Radar Field Measurements and Inversion of Cloud Parameters for the 1999 Mt. Washington Icing Sensors Project

The Mount Washington Icing Sensors Project (MWISP) was a multi-investigator experiment with participants from Quadrant Engineering, NOAA Environmental Technology Laboratory (NOAA/ETL), the Microwave Remote Sensing Laboratory (MIRSL) of the University of Massachusetts (UMass), and others. Radar systems from UMass and NOAA/ETL were used to measure X-, Ka-, and W-band backscatter data from the base of Mt. Washington, while simultaneous in-situ particle measurements were made from aircraft and from the observatory at the summit. This report presents range and time profiles of liquid water content and particle size parameters derived from range profiles of radar reflectivity as measured at X-, Ka-, and W-band (9.3, 33.1, and 94.9 GHz) using an artificial neural network inversion algorithm. In this report, we provide a brief description of the experiment configuration, radar systems, and a review of the artificial neural network used to extract cloud parameters from the radar data. Time histories of liquid water content (LWC), mean volume diameter (MVD) and mean Z diameter (MZD) are plotted at 300 m range intervals for slant ranges between 1.1 and 4 km. Appendix A provides details on the extraction of radar reflectivity from measured radar power, and Appendix B provides summary logs of the weather conditions for each day in which we processed data.

Pazmany, Andrew L.↗
NASA NTRS1977

LANDSAT image interpretation aids

In the Large Area Crop Inventory Experiment, image interpretation aids were produced to assist in selecting and/or identifying representative samples of signatures in a given LANDSAT scene. The three methods employed are based on clustering techniques, information extraction, and aggregation of like spectral information on a two dimensional spectral plot.

Abotteen, R. A.↗
NASA NTRSDate not supplied

Extraction and Analysis of the Properties of Shape Memory Alloys

Shape Memory Alloys (SMA) are materials of high industrial importance, increasingly used for the aerospace applications. Use of SMA allows to simplify flight systems and reduce the total weight. Through the literature-based data mining, we extracted the computed SMA properties from the high-impact journals. We plotted the selected pairs of properties, found and parametrized correlations.

Jason Ernesto Diaz↗
NASA NTRS1977

Landsat image interpretation aids

In the Large Area Crop Inventory Experiment, image interpretation aids were produced to assist in selecting and/or identifying representative samples of signatures in a given Landsat scene. The three methods employed are based on clustering techniques, information extraction, and aggregation of like spectral information on a two-dimensional spectral plot.

Abotteen, R. A.↗
NASA NTRS1982

IUE data reduction: Wavelength determinations and line identifications using a VAX/750 computer

A fully automated, interactive system for determining the wavelengths of features in extracted IUE spectra is described. Wavelengths are recorded from video displays of expanded plots of individual orders using a movable cursor, and then corrected for IUE wavelength scale errors. The estimated accuracy of an individual wavelength in the final tabulation is 0.050 A. Such lists are ideally suited for line identification work using the method of wavelength coincidence statistics (WCS). The results of WCS studies of the ultraviolet spectra of the chemically peculiar (CP) stars iota Coronae Borealis and kappa Camcri. Aside from confirming a number of previously reported aspects of the abundance patterns in these stars, the searches produced some interesting, new discoveries, notably the presence of Hf in the spectrum of kappa Camcri. The implications of this work for theories designed to account for anomalous abundances in chemically peculiar stars are discussed.

Davidson, J. P.↗
NASA NTRS1978

The ATLAS integrated structural analysis and design software system

The ATLAS system provides an extensive set of integrated technical computer-program modules for the analysis and design of general structural configurations, as well as capabilities that are particularly suited for the aeroelastic design of flight vehicles. The system is based on the stiffness formulation of the finite element structural analysis method and can be executed in batch and interactive computing environments on CDC 6600/CYBER computers. Problem-definition input data are written in an engineering-oriented language using a free field format. Input-data default values, generation options, and data quality checks provided by the preprocessors minimize the amount of data and flowtime for problem definition/verfication. Postprocessors allow selected input and calculated data to be extracted, manipulated, and displayed via on-line and off-line prints or plots for monitoring and verifying problem solutions. The sequence and mode of execution of selected program modules are controlled by a common user-oriented language.

Dreisbach, R. L.↗
NASA NTRS1994

Geotail MCA plasma wave data analysis

NASA Grant NAG 5-2346 supports the data analysis effort at The University of Iowa for the GEOTAIL Multi-Channel Analyzer (MCA) which is a part of the GEOTAIL Plasma Wave Instrument (PWI). At the beginning of this reporting period we had just begun to receive our GEOTAIL Sirius data on CD-ROMs. Much programming effort went into adapting and refining the data analysis programs to include the CD-ROM inputs. Programs were also developed to display the high-frequency-resolution PWI Sweep Frequency Analyzer (SFA) data and to include in all the various plot products the electron cyclotron frequency derived from the magnitude of the magnetic field extracted from the GEOTAIL Magnetic Field (MGF) data included in the GEOTAIL Sirius data. We also developed programs to use the MGF data residing in the Institute of Space and Astronautical Science (ISAS) GEOTAIL Scientific Data Base (SDB). Our programmers also developed programs and provided technical support for the GEOTAIL data analysis efforts of Co-lnvestigator William W. L. Taylor at Nichols Research Corporation (NRC). At the end of this report we have included brief summaries of the NRC effort and the progress being made.

Anderson, Roger R.↗