SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Polarization-maintaining optical fibers, referred to as PANDA fibers, were subjected to Cobalt 60 radiation (300,000 Rad). The mechanical properties of the PANDA fibers were measured after exposure to gamma radiation and compared to non-irradiated PANDA fibers.
(1) Chandra Archive: SAO has maintained the interfaces through which HEASARC gains access to the Chandra Data Archive. At HEASARC's request, we have implemented an anonymous ftp copy of a major part of the public archive and we keep that archive up-to- date. SAO has participated in the ADEC interoperability working group, establishing guidelines or interoperability standards and prototyping such interfaces. We have provided an NVO-based prototype interface, intending to serve the HEASARC-led NVO demo project. HEASARC's Astrobrowse interface was maintained and updated. In addition, we have participated in design discussions surrounding HEASARC's Caldb project. We have attended the HEASARC Users Group meeting and presented CDA status and developments. (2) Chandra CALDB: SA0 has maintained and expanded the Chandra CALDB by including four new data file types, defining the corresponding CALDB keyword/identification structures. We have provided CALDB upgrades for the public (CIAO) and for Standard Data Processing. Approximately 40 new files have been added to the CALDB in these version releases. There have been in the past year ten of these CALDB upgrades, each with unique index configurations. In addition, with the inputs from software, archive, and calibration scientists, as well as CIAO/SDP software developers, we have defined a generalized expansion of the existing CALDB interface and indexing structure. The purpose of this is to make the CALDB more generally applicable and useful in new and future missions that will be supported archivally by HEASARC. The generalized interface will identify additional configurational keywords and permit more extensive calibration parameter and boundary condition specifications for unique file selection. HEASARC scientists and developers from SAO and GSFC have become involved in this work, which is expected to produce a new interface for general use within the current year. (3) DS9: One of the decisions that came from last year's HEADCC meeting was to make the ds9 image display program the primary vehicle for displaying line graphics (as well as images). The first step required to make this possible was to enhance the line graphics capabilities of ds9. SAO therefore spent considerable effort upgrading ds9 to use Tcl 8.4 so that the BLT line graphics package could be built and imported into ds9 from source code, rather than from a pre-built (and generally outdated) shared library. This task, which is nearly complete, allows us to extend BLT as needed for the HEAD community. Following HEADCC discussion concerning archiving and the display of archived data, we extended ds9 to support full access to many astronomical Web-based archives sites, including HEASARC, MAST, CHANDRA, SKYVIEW, ADS, NED, SIMBAD, IRAS, NVRO, SAO TDC, and FIRST. Using ds9's new internal Web access capabilities, these archives can be accessed via their Web page. FITS images, plots, spectra, and journal abstracts can be referenced, down-loaded, and displayed directly and easily in ds9. For more information, see: http://hea-www.harvard.edu/saord/ds9. Also after the HEADCC discussion concerning region filtering, we extended the Funtools sample implementation of region filtering as described in: http://hea-www.harvard.edu/saord/funtools/regions.html. In particular, we added several new composite regions for event and image filtering, including elliptical and box annuli. We also extended the panda (Pie AND Annulus) region support to include box pandas and elliptical pandas. These new composite regions are especially useful in programs that need to count photons in each separate region using only a single pass through the data. Support for these new regions was added to ds9. In the same vein, we developed new region support for filtering images using simple FITS image masks, i.e. 8-bit or 16-bit FITS images where the value of a pixel is the region id number for that pixel. Other important enhancements to DS9 this year, include supporor multiple world coordinate systems, three dimensional event file binning, image smoothing, region groups and tags, the ability to save images in a number of image formats (such as JPEG, TIFF, PNG, FITS), improvements in support for integrating external analysis tools, and support for the virtual observatory. In particular, a full-featured web browser has been implemented within D S 9 . This provides support for full access to HEASARC archive sites such as SKYVIEW and W3BROWSE, in addition to other astronomical archives sites such as MAST, CHANDRA, ADS, NED, SIMBAD, IRAS, NVRO, SA0 TDC, and FIRST. From within DS9, the archives can be searched, and FITS images, plots, spectra, and journal abstracts can be referenced, downloaded and displayed The web browser provides the basis for the built-in help facility. All DS9 documentation, including the reference manual, FAQ, Know Features, and contact information is now available to the user without the need for external display applications. New versions of DS9 maybe downloaded and installed using this facility. Two important features used in the analysis of high energy astronomical data have been implemented in the past year. The first is support for binning photon event data in three dimensions. By binning the third dimension in time or energy, users are easily able to detect variable x-ray sources and identify other physical properties of their data. Second, a number of fast smoothing algorithms have been implemented in DS9, which allow users to smooth their data in real time. Algorithms for boxcar, tophat, and gaussian smoothing are supported.
The analysis of mechanism telemetry requires a wide variety of tools to quickly and effectively assess spacecraft state, capture long-term trends in system performance, and identify and track anomalous events. Such analysis often requires spacecraft telemetry to first be transformed into derived fields and aggregated statistics before operators can begin their analysis. In past missions, aspects of this process have been automated, but operators were expected to use their own tools and procedures to understand and visualize the data, which led to redundant and inconsistent tools and processes. The Mech Data Tools Python library (MDT) was developed to provide a flexible, unified tool set for operators to extract and analyze mechanism telemetry over the life of the Mars 2020 surface mission. MDT consists of a set of configurable components that implement standard interfaces for ingesting input and producing output. Components can be chained together to form a data processing pipeline. Data are ingested from several sources within the greater Mars 2020 cloud infrastructure and stored in pandas DataFrames, which allows users to leverage the data manipulation capabilities present within the widely-used pandas library. Visualization capabilities are provided through the Plotly library, which generates interactive plots for users to interpret. Following the beginning of Mars 2020 surface operations, usage of MDT has spread to all mechanism-focused subsystems and has demonstrated great utility in analyzing early surface activities. This paper describes MDT’s evolution from heritage mechanism telemetry tools, the critical architecture decisions and challenges faced over MDT’s two years of development, and current applications of MDT in support of mechanism operations.
The pypromice Python package is for processing and handling observation datasets from automated weather stations (AWS). It is primarily aimed at users of AWS data from the Geological Survey of Denmark and Greenland (GEUS), which collects and distributes in situ weather station observations to the cryospheric science research community. Functionality in pypromice is primarily handled using two key open-source Python packages, xarray (Hoyer & Hamman, 2017) and pandas (The pandas development team, 2020). A defined processing workflow is included in pypromice for transforming original AWS observations (Level 0, L0) to a usable, CF-convention-compliant dataset (Level 3, L3) (Figure 1). Intermediary processing levels (L1,L2) refer to key stages in the workflow, namely the conversion of variables to physical measurements and variable filtering (L1), cross-variable corrections and user-defined data flagging and fixing (L2), and derived variables (L3). Information regarding the station configuration is needed to perform the processing, such as instrument calibration coefficients and station type (one-boom tripod or two-boom mast station design, for example), which are held in a toml configuration file. Two example configuration files are provided with pypromice , which are also used in the package’s unit tests. More detailed documentation of the AWS design, instrumentation, and processing steps are described in Fausto et al. (2021).
To locate noise sources in high-speed jets, the sound pressure fluctuations p/, measured at far field locations, were correlated with each of density p, axial velocity u, radial velocity v, puu and pvv fluctuations measured from various points in fully expanded, unheated plumes of Mach number 0.95, 1.4 and 1.8. The velocity and density fluctuations were measured simultaneously using a recently developed, non-intrusive, point measurement technique based on molecular Rayleigh scattering (Seasholtz, Panda, and Elam, AIAA Paper 2002-0827). The technique uses a continuous wave, narrow line-width laser, Fabry-Perot interferometer and photon counting electronics. The far field sound pressure fluctuations at 30 to the jet axis provided the highest correlation coefficients with all flow variables. The correlation coefficients decreased sharply with increased microphone polar angle, and beyond about 60 all correlation mostly fell below the experimental noise floor. Among all correlations < puu; p/> showed the highest values. Interestingly, , in all respects, were very similar to . The and correlations with 90deg microphone fell below the noise floor. By moving the laser probe at various locations in the jet it was found that the strongest noise source lies downstream of the end of the potential core and extends many diameters beyond. Correlation measurement from the lip shear layer showed a Mach number dependency. While significant correlations were measured in Mach 1.8 jet, values were mostly below the noise floor for subsonic Mach 0.95 jet. Various additional analyses showed that fluctuations from large organized structures mostly contributed to the measured correlation, while that from small scale structures fell below the noise floor.
A new, spectrally-resolved, Rayleigh scattering setup at NASA Ames is further developed to measure fluctuations in velocity and temperature. Using a combination of a continuous-wave laser, a stabilized Fabry-Perot interferometer (FPI), an EMCCD camera, and a photo-multiplier tube, the setup was demonstrated to provide fairly accurate measurements of time-averaged velocity, temperature, density and spectrum of density fluctuations in a high-speed free jet (Panda & White, 2018). This paper describes further progress in fast measurement of the Rayleigh-Brillouin spectrum via a 16-anode linear-array of photo-multiplier tube and a multi-channel, photo-electron counter. Rayleigh scattered light from a 0.4mm long probe volume was directly imaged through the FPI and was imaged on the linear array. Synchronous photo-electron counting over a series of short, contiguous gates provided time-evolution of the fringes at a 10 kHz sampling rate. Sample spectra collected from a Mach 0.98 jet show spectral content floating on high noise-floor. Efforts to collect longer time series of data and different schemes of extracting velocity and temperature information are now in progress.
The transmission characteristics of two Ar(+) laser wavelengths through a twenty meter Panda type Polarization Preserving Single Mode Optical Fiber (PPSMOF) were measured. The measurements were done with both single and multi-longitudinal mode radiation. In the single longitudinal mode case, a degrading Stimulated Brillouin Scattering (SBS) is observed as a backward scattering loss. By choosing an optimum coupling system and manipulating the input polarization, the threshold of the SBS onset can be raised and the transmission efficiency can be increased.
Launch vehicle designs typically make extensive use of cylindrical skin stringer construction. Structural analysis methods are well developed for preliminary design of this type of construction. This report describes an automated, iterative method to obtain a minimum weight preliminary design. Structural optimization has been researched extensively, and various programs have been written for this purpose. Their complexity and ease of use depends on their generality, the failure modes considered, the methodology used, and the rigor of the analysis performed. This computer program employs closed-form solutions from a variety of well-known structural analysis references and joins them with a commercially available numerical optimizer called the 'Design Optimization Tool' (DOT). Any ring and stringer stiffened shell structure of isotropic materials that has beam type loading can be analyzed. Plasticity effects are not included. It performs a more limited analysis than programs such as PANDA, but it provides an easy and useful preliminary design tool for a large class of structures. This report briefly describes the optimization theory, outlines the development and use of the program, and describes the analysis techniques that are used. Examples of program input and output, as well as the listing of the analysis routines, are included.
Micromechanical modeling of the composite mechanical properties of optical fibers was conducted. Good agreement was obtained between the values of Young's modulus obtained by micromechanics modeling and those determined experimentally for a single mode optical fiber where the wave guide and the jacket are physically coupled. The modeling was also attempted on a polarization-maintaining optical fiber (PANDA) where the wave guide and the jacket are physically decoupled, and found not to applicable since the modeling required perfect bonding at the interface. The modeling utilized constituent physical properties such as the Young's modulus, Poisson's ratio, and shear modulus to establish bounds on the macroscopic behavior of the fiber.
In this presentation, we will talk about the latest releases of HDF4 and HDF5 software and tools, new features available in HDF5, and roadmap for the HDF software. We will also solicit feedback from the users of HDF data and HDF application developers on new features and new tools. The talk will cover: Difference between 1.8 and 1.10 releases and how and when to move to the latest release Features of the recent HDF5 1.8.19, 1.10.1 and HDF 4.2.13 Overview of HDF View 3.0 and other enhancements to tools Supported compilers and systems Open discussion of new requirements and wish list of the HDF features Compression library for interoperability with h5py and Pandas and better floating-point data compression.
Unsteady pressure-sensitive paint (uPSP) is a significant new technology for high spatial resolution measurement of complex dynamic surface pressure loading on a wind tunnel model, to better define flight vehicle buffet and aeroacoustic loads. Compared with the very sparse surface pressure measurements of traditional sensors, the pressure sensitivity of uPSP light reflectivity provides a visual measure of surface pressure fluctuations over a wide area illuminated by high intensity light, captured by a high-speed digital camera. Panda et al (AIAA Journal, May 2019) have shown good data is recoverable up to 10 kHz. In cases where available uPSP luminescence is low for a painted wind tunnel test model, significant noise levels have been observed primarily due to the discrete photon arrival variability of low intensity light (termed “shot noise”). In this case, uPSP measurements can exhibit unusually low signal to noise ratio (SNR of 0.1 or less). This paper will report on latest work to recover calibrated uPSP measurements which are noise free over a useful dynamic range of 10-15 dB. It will be shown how the distinct spatial correlations of both the shot noise and the underlying aeroacoustic surface pressure play an important role in obtaining a reliable measurement.
Continuous atmospheric data analysis is an important factor for space launch vehicle design and operations. The balloon quality control tool was developed by NASA’s Marshall Space Flight Center (MSFC) Natural Environments Branch (NEB) for monitoring quality control processes and verifying the automated flags created on the balloon data sets analyzed. The data sets currently analyzed are comprised of high-resolution and low-resolution balloon data from NASA Kennedy Space Center (KSC), co-located on the United States Air Force’s Eastern range (ER) at the Cape Canaveral Air Force Station. The NEB was tasked to perform a quality assessment of these data sets and needed a tool to confirm the quality control (QC) flags produced from an automated process and add additional QC flags if necessary. This Graphical User Interface (GUI) was developed to visualize all of the data from these balloon sets, display any flags from the automated QC process, and add additional flags to variables if necessary. The GUI was developed in Python 3.6 utilizing different packages available such as pandas for data analysis and manipulation, NumPy for high-performance multidimensional array and tools to compute with and manipulate arrays, Matplotlib for plotting data and Tkinter to build the GUI.
Continuous atmospheric data analysis is an important factor for space launch vehicle design and operations. The balloon quality control tool was developed by NASA’s Marshall Space Flight Center (MSFC) Natural Environments Branch (NEB) for monitoring quality control processes and verifying the automated flags created on the balloon data sets analyzed. The data sets currently analyzed are comprised of high-resolution and low-resolution balloon data from NASA Kennedy Space Center (KSC), co-located on the United States Air Force’s Eastern range (ER) at the Cape Canaveral Air Force Station. The NEB was tasked to perform a quality assessment of these data sets and needed a tool to confirm the quality control (QC) flags produced from an automated process and add additional QC flags if necessary. This Graphical User Interface (GUI) was developed to visualize all of the data from these balloon sets, display any flags from the automated QC process, and add additional flags to variables if necessary. The GUI was developed in Python 3.6 utilizing different packages available such as pandas for data analysis and manipulation, NumPy for high-performance multidimensional array and tools to compute with and manipulate arrays, Matplotlib for plotting data and Tkinter to build the GUI.
A sensitive microprofilometer was used to determine the onset of yielding in the anvils of a supported opposed anvil device for the case of 3% cobalt-cemented tungsten carbide as the anvil material. In addition, it is shown how the commencement of yielding in boron carbide pistons, the yield strength being known, can be used to obtain the transition pressure to a conducting phase in gallium phosphide. The transition pressures of bismuth and gallium phosphide are obtained and it is found that these transitions are extremely close to the maximum attainable pressure in, respectively, a maraging steel and a 3% cobalt-cemented tungsten carbide.
The bibliographical listings in this publication are documentation products associated with the solar thermal power system project carried out by the Jet Propulsion Laboratory from 1976 to 1983. Documents listed are categorized as conference and journal papers, JPL external reports, JPL internal reports, or contractor reports. Alphabetical listings by title were used in the bibliography itself to facilitate location of the document by subject. Two indexes are included for ease of reference: one, an author index; the other, a topical index.
An aeroelastic stability of three-degree flap-lag-torsion blade in forward flight is examined. Quasisteady aerodynamics with a dynamic inflow model is used. The nonlinear time dependent periodic blade response is calculated using an iterative procedure based on Floquet theory. The periodic perturbation equations are solved for stability using Floquet transition matrix theory as well as constant coefficient approximation in the fixed reference frame. Results are presented for both stiff-inplane and soft-inplane blade configurations. The effects of several parameters on blade stability are examined, including structural coupling, pitch-flap and pitch-lag coupling, torsion stiffness, steady inflow distribution, dynamic inflow, blade response solution and constant coefficient approximation.
Bibliographical listings are documentation products associated with the Solar Thermal Power Systems Project carried out by the Jet Propulsion Laboratory from 1976 to 1986. Documents are categorized as conference and journal papers, JPL external reports, JPL internal reports, or contractor reports (i.e., deliverable documents produced under contract to JPL). Alphabetical listings by titles are used in the bibliography itself to facilitate location of the document by subject. Two indexes are included for ease of reference; an author index; and a topical index.
A finite element approach is presented for the modeling of rotorcraft undergoing elastic deformation in addition to large rigid body motion with respect to inertial space, with particular attention given to the coupling of the rotor and fuselage subsystems subject to large relative rotations. The component synthesis technique used here allows the coupling of rotors to the fuselage for different rotorcraft configurations. The formulation is general and applicable to any rotorcraft vibration, aeroelasticity, and dynamics problem.