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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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The X-ray performance of the Advanced X-ray Astrophysics Facility TMA in the 0.277-6.4-keV range. The precise figure and smooth surface originally specified (which were expected from the in-process optical and mechanical measurements) are verified. The paper primarily describes the test equipment and methods used and gives examples of the detailed on-axis and off-axis data.
Enhancements to the real-time processing and display systems of the NASA Western Aeronautical Test Range are described. Display processing has been moved out of the telemetry and radar acquisition processing systems super-minicomputers into user/client interactive graphic workstations. Real-time data is provided to the workstations by way of Ethernet. Future enhancement plans include use of fiber optic cable to replace the Ethernet.
A preliminary Long Duration Exposure Facility (LDEF) Materials Data Base was developed by the LDEF Materials Special Investigation Group (MSIG). The LDEF Materials Data Base is envisioned to eventually contain the wide variety and vast quantity of materials data generated for LDEF. The data is searchable by optical, thermal, and mechanical properties, exposure parameters (such as atomic oxygen flux), and author(s) or principal investigator(s). The LDEF Materials Data Base was incorporated into the Materials and Processes Technical Information System (MAPTIS). MAPTIS is a collection of materials data which was computerized and is available to engineers, designers, and researchers in the aerospace community involved in the design and development of spacecraft and related hardware. This paper describes the LDEF Materials Data Base and includes step-by-step example searches using the data base. Information on how to become an authorized user of the system is included.
Optical techniques for measuring airdata parameters were demonstrated with promising results on high performance fighter aircraft. These systems can measure the airspeed vector, and some are not as dependent on special in-flight calibration processes as current systems. Optical concepts for measuring freestream static temperature and density are feasible for in-flight applications. The best feature of these concepts is that the air data measurements are obtained nonintrusively, and for the most part well into the freestream region of the flow field about the aircraft. Current requirements for measuring air data at high angle of attack, and future need to measure the same information at hypersonic flight conditions place strains on existing techniques. Optical technology advances show outstanding potential for application in future programs and promise to make common use of optical concepts a reality. Results from several flight-test programs are summarized, and the technology advances required to make optical airdata techniques practical are identified.
A general overview of the capabilities of the IODA ("Integrated Optical Design Analysis") exchange of data and modeling results between thermal, structures, optical design, and testing engineering disciplines. This presentation focuses on new features added to the software that allow measured test data to be imported into the IODA environment for post processing or comparisons with pretest model predictions. software is presented. IODA promotes efficient
The goal of this proposal is to detect or place sensitive upper limits on pulsations from the quiescent neutron-star X-ray binary Cen X-4. The observations were obtained on 1 March 2003. Unfortunately, due to problems with the standard pipeline processing of this observation, the data were not delivered until more than one year later, on 21 April 2004. No pulsations have yet been found in the data set. However, new optical spectra have been obtained which will lead to better constraints on the orbital period of Cen X-4 and which may enable detection of pulsations.
X-ray crystallography remains the primary method for determining the structure of macromolecules. The first requirement is to have crystals, and obtaining them is often the rate-limiting step. The numbers of crystallization trials that are set up for any one protein for structural genomics, and the rate at which they are being set up, now overwhelm the ability for strictly human analysis of the results. Automated analysis methods are now being implemented with varying degrees of success, but these typically cannot reliably extract intermediate results. By covalently modifying a subpopulation, less than or = 1 %, of a macromolecule solution with a fluorescent probe, the labeled material will add to a growing crystal as a microheterogeneous growth unit. Labeling procedures can be readily incorporated into the final stages of purification. The covalently attached probe will concentrate in the crystal relative to the solution, and under fluorescent illumination the crystals show up as bright objects against a dark background. As crystalline packing is more dense than amorphous precipitate, the fluorescence intensity can be used as a guide in distinguishing different types of precipitated phases, even in the absence of obvious crystalline features, widening the available potential lead conditions in the absence of clear "hits." Non-protein structures, such as salt crystals, will not incorporate the probe and will not show up under fluorescent illumination. Also, brightly fluorescent crystals are readily found against less fluorescent precipitated phases, which under white light illumination may serve to obscure the crystals. Automated image analysis to find crystals should be greatly facilitated, without having to first define crystallization drop boundaries and by having the protein or protein structures all that show up. The trace fluorescently labeled crystals will also emit with sufficient intensity to aid in the automation of crystal alignment using relatively low cost optics, further increasing throughput at synchrotrons. Preliminary experiments show that the presence of the fluorescent probe does not affect the nucleation process or the quality of the X-ray data obtained.
Black Hole X-ray Binaries are known to display distinct emission states that differ in their X-ray spectra, their X-ray timing properties (on times scales less than 1 s) and their radio emission. In recent years monitoring observations, specially with NASA's Rossi X-ray Timing Explorer (RXTE), have provided us with detailed empirical modeling of the phenomenology of the different states as well as a unification scheme of the long term evolution of black holes, transient and persistent, in terms of these states. Observations of the persistent High Mass X-ray Binary (HMXB) Cygnus X-l have been at the forefront of learning about black hole states since its optical identification through a state transition in 1973. In this talk I will present in depth studies of several different aspects of the accretion process in this system. The main data base for these studies is an ongoing RXTE and Ryle radio telescope bi-weekly monitoring campaign that started in 1997. I will discuss high-resolution timing results, especially power spectra, which first gave rise to the Lorentzian description now widely used for black hole and neutron star binaries, and time lags, which we found to be especially well suited to identify state transitions. The evolution of spectral, timing, and radio parameters over years will be shown, including the rms-flux relation and the observation of a clearly correlated radio/x-ray flare. We also observed Cygnus X-1 with INTEGRAL, which allowed us to extend timing and spectral studies to higher energies, with XMM, which provided strong constraints on the parameters of the 6.4 keV iron fluorescence line, and with Chandra, which provided the most in depth study to date of the stellar wind in this system. Models based on the physical conditions in the accretion region are still mainly concentrated on the one or other of the observational areas but they are expanding: as an example I will review results from a jet model for the quantitative description of the radio through X-ray spectra. I will conclude with an outlook on a truly multi-instrument observing campaign of Cygnus X-1 that was performed in 2008 April in order to better constrain the jet models mentioned above (and provide a unique data set for cross-calibration).
Aims. The Spectral Imaging of the Coronal Environment (SPICE) instrument is a high-resolution imaging spectrometer operating at extreme ultraviolet wavelengths. In this paper, we present the concept, design, and pre-launch performance of this facility instrument on the ESA/NASA Solar Orbiter mission. Methods. The goal of this paper is to give prospective users a better understanding of the possible types of observations, the data acquisition, and the sources that contribute to the instrument’s signal. Results. The paper discusses the science objectives, with a focus on the SPICE-specific aspects, before presenting the instrument’s design, including optical, mechanical, thermal, and electronics aspects. This is followed by a characterisation and calibration of the instrument’s performance. The paper concludes with descriptions of the operations concept and data processing. Conclusions. The performance measurements of the various instrument parameters meet the requirements derived from the mission’s science objectives. The SPICE instrument is ready to perform measurements that will provide vital contributions to the scientific success of the Solar Orbiter mission.
The magnetic-field conditions in astrophysical relativistic jets can be probed by multiwavelength polarimetry, which has been recently extended to X-rays. For example, one can track how the magnetic field changes in the flow of the radiating particles by observing rotations of the electric vector position angle Ψ. Here we report the discovery of a ΨX rotation in the X-ray band in the blazar Markarian 421 at an average flux state. Across the 5 days of Imaging X-ray Polarimetry Explorer observations on 4–6 and 7–9 June 2022, ΨX rotated in total by ≥360°. Over the two respective date ranges, we find constant, within uncertainties, rotation rates (80 ± 9° per day and 91 ± 8° per day) and polarization degrees (ΠX = 10% ± 1%). Simulations of a random walk of the polarization vector indicate that it is unlikely that such rotation(s) are produced by a stochastic process. The X-ray-emitting site does not completely overlap the radio, infrared and optical emission sites, as no similar rotation of Ψ was observed in quasi-simultaneous data at longer wavelengths. We propose that the observed rotation was caused by a helical magnetic structure in the jet, illuminated in the X-rays by a localized shock propagating along this helix. The optically emitting region probably lies in a sheath surrounding an inner spine where the X-ray radiation is released.
In 2017, the GOES-R PLT field campaign was conducted to validate new instruments on board GOES-16, including the Geostationary Lightning Mapper (GLM). A NASA ER-2 high altitude aircraft was equipped with a sensor suite including FEGS and an electric field change meter (EFCM) for complementary observations of lightning. As part of a modern reanalysis, we plan to combine aircraft and ground observations from the lightning instrumentation and polarimetric Doppler radars for a more complete characterization of optical lightning measurements in the context of convective properties. This presentation focuses on our initial efforts which include a reanalysis of the FEGS multi-spectral optical waveforms using an updated pulse detection algorithm and a comparison of detected pulses with coincident EFCM and Lightning Mapping Array (LMA) data. We will present on characteristics of discharge processes including leaders, strokes, and continuing current signatures as observed by the suite of aircraft and ground-based lightning instrumentation.
The most common instrument for low energy plasmas consists of a top-hat electrostatic analyzer geometry coupled with a microchannel-plate (MCP)-based detection system. While the electrostatic optics for such sensors are readily simulated and parameterized during the laboratory calibration process, the detection system is often less well characterized. Furthermore, due to finite resources, for large sensor suites such as the Fast Plasma Investigation (FPI) on NASA's Magnetospheric Multiscale (MMS) mission, calibration data are increasingly sparse. Measurements must be interpolated and extrapolated to understand instrument behavior for untestable operating modes and yet sensor inter-calibration is critical to mission success. To characterize instruments from a minimal set of parameters we have developed the first comprehensive mathematical description of both sensor electrostatic optics and particle detection systems. We include effects of MCP efficiency, gain, scattering, capacitive crosstalk, and charge cloud spreading at the detector output. Our parameterization enables the interpolation and extrapolation of instrument response to all relevant particle energies, detector high voltage settings, and polar angles from a small set of calibration data. We apply this model to the 32 sensor heads in the Dual Electron Sensor (DES) and 32 sensor heads in the Dual Ion Sensor (DIS) instruments on the 4 MMS observatories and use least squares fitting of calibration data to extract all key instrument parameters. Parameters that will evolve in flight, namely MCP gain, will be determined daily through application of this model to specifically tailored in-flight calibration activities, providing a robust characterization of sensor suite performance throughout mission lifetime. Beyond FPI, our model provides a valuable framework for the simulation and evaluation of future detection system designs and can be used to maximize instrument understanding with minimal calibration resources.
The NASA Orbital Debris Program Office (ODPO) has used various optical assets to acquire photometric data of Earth-orbiting objects to define the orbital debris environment. To better characterize and model optical data acquired from ground-based telescopes, the Optical Measurements Center (OMC) at NASA Johnson Space Center emulates illumination conditions seen in space by using equipment and techniques that parallel telescopic observations and source-target-sensor orientations. One of the OMC goals is to improve the size calculation used for optical data by developing an optical-based Size Estimation Model. The current size estimation requires applying a Lambertian phase function, a set albedo value, and range to the observed magnitude. The first step to improving the sampled brightness of laboratory targets is to remove aspect-angle dependencies. Then, the volume of possible object viewing angles is sampled at 21 combinations of azimuth and zenith angles for each solar phase angle. Finally, the acquired images are input into an image processing program that generates approximations for the object’s Bidirectional Reflectance Distribution Function (BRDF) and phase function. The BRDF is a radiometric concept that identifies an object’s material composition by matching a BRDF approximated with photometric data collected by ground-based telescopes with a BRDF generated experimentally from a known object in the laboratory. This paper discusses the validation of experimental BRDF and phase function approximations produced in the OMC and how the findings will be incorporated into ODPO models. A Lambertian sphere is imaged and the subsequent experimental functions are scrutinized to confirm that they correspond to an object that has an isotropic luminance. With the image processing algorithm validated, test objects with varying optical properties are then imaged to confirm that the produced photometric functions are both unique and repeatable. Once the validation is complete, the OMC will be used to evaluate a subset of fragments from a hypervelocity impact test of a mock-up satellite and assess the appropriate phase function and size estimates using BRDF measurements for a large volume of targets composed of various shapes, sizes, and materials.
This paper investigates the relationships between the image-gathering and image-processing systems for minimum mean-squared error estimation of scene characteristics. A stochastic optimization problem is formulated in which the objective is to determine a spatial characteristic of the scene rather than a feature of the already blurred, sampled, and noisy image data. The Wiener filter for the sampled image case is obtained as a special case, where the desired characteristics is scene restoration. Optimal edge detection is investigated. It is shown that the optimal edge detector compensates for the blurring introduced by the image-gathering optics, and, notably, that it is not circularly symmetric. The lack of circular symmetry is largely due to the geometric effects of the sampling lattice used in image acquisition.
One of the primary Atmospheric Radiation Measurement (ARM) Program objectives is to obtain measurements applicable to the development of models for better understanding of radiative processes in the atmosphere. We address this goal by building a three-dimensional (3D) characterization of the cloud structure and properties over the ARM Southern Great Plains (SGP). We take the approach of juxtaposing the cloud properties as retrieved from independent satellite and ground-based retrievals, and looking at the statistics of the cloud field properties. Once these retrievals are well understood, they will be used to populate the 3D characterization database. As a first step we determine the relationship between surface fractional sky cover and satellite viewing angle dependent cloud fraction (CF). We elaborate on the agreement intercomparing optical depth (OD) datasets from satellite and ground using available retrieval algorithms with relation to the CF, cloud height, multi-layer cloud presence, and solar zenith angle (SZA). For the SGP Central Facility, where output from the active remote sensing cloud layer (ARSCL) valueadded product (VAP) is available, we study the uncertainty of satellite estimated cloud heights and evaluate the impact of this uncertainty for radiative studies.
The Unsteady Pressure-Sensitive Paint (uPSP) Development Team outof NASA Ames Research Center (ARC) has spent the past five yearsimproving the systems and processes to advance the uPSP technology for production-level wind tunnel testing. Already considered turnkey for small-scale and research applications, development in acquisition, calibration, data transfer, and data processing were needed to be useful to customers testing at NASA wind tunnels. This development focused at ARC at the Unitary Plan Wind Tunnel (UPWT) 11-by 11-ft Transonic Wind Tunnel due to the large optical access of the test section and the NASA Advanced Supercomputer(NAS), also located at ARC. A Launch Vehicle Demonstration Test (LVDT) at the UPWT represents a milestone of this initial phase of development where several new improvements were demonstrated in a production wind tunnel environment for the first time. LVDT was conducted in April 2024 and used a 4% forebody Space Launch System (SLS) Block 1B model as the test article. Both a crew and cargo configuration were tested, with varying Mach numbers, pressures, model positions, and camera magnifications. This paper summarizes the details of the test and is part of a collection with four additional papers that provide greater detail on: high-speed lifetime methodology, spectral proper orthogonal decomposition analysis, quality of high-resolution data compared to Corcos model, and data quality, calibration, and uncertainty.
The primary objective of this planning document is to establish a long-term capability and validating oceanic biogeochemical satellite data. It is a pragmatic solution to a practical problem based primarily o the lessons learned from prior satellite missions. All of the plan's elements are seen to be interdependent, so a horizontal organizational scheme is anticipated wherein the overall leadership comes from the NASA Ocean Biology and Biogeochemistry (OBB) Program Manager and the entire enterprise is split into two components of equal sature: calibration and validation plus satellite data processing. The detailed elements of the activity are based on the basic tasks of the two main components plus the current objectives of the Carbon Cycle and Ecosystems Roadmap. The former is distinguished by an internal core set of responsibilities and the latter is facilitated through an external connecting-core ring of competed or contracted activities. The core elements for the calibration and validation component include a) publish protocols and performance metrics; b) verify uncertainty budgets; c) manage the development and evaluation of instrumentation; and d) coordinate international partnerships. The core elements for the satellite data processing component are e) process and reprocess multisensor data; f) acquire, distribute, and archive data products; and g) implement new data products. Both components have shared responsibilities for initializing and temporally monitoring satellite calibration. Connecting-core elements include (but are not restricted to) atmospheric correction and characterization, standards and traceability, instrument and analysis round robins, field campaigns and vicarious calibration sites, in situ database, bio-optical algorithm (and product) validation, satellite characterization and vicarious calibration, and image processing software. The plan also includes an accountability process, creating a Calibration and Validation Team (to help manage the activity), and a discussion of issues associated with the plan's scientific focus.
Remote retrieval of near-surface chlorophyll-a (Chla) concentration in small inland waters is challenging due to substantial optical interferences of various water constituents and uncertainties in the atmospheric correction (AC) process. Although various algorithms have been developed to estimate Chla from moderate-resolution terrestrial missions (∼10–60 m), the production of both accurate distribution maps and time series of Chla has proven challenging, limiting the use of remote analyses for lake monitoring. Here, we develop a support vector regression (SVR) model, which uses satellite-derived remote-sensing reflectance spectra () from Sentinel-2 and Landsat-8 images as input for Chla retrieval in a representative eutrophic prairie lake, Buffalo Pound Lake (BPL), Saskatchewan, Canada. Validated against in situ Chla from seven ice-free seasons (N ∼ 200; 2014–2020), the SVR model outperformed both locally tuned, -fed empirical models (Normalized Difference Chlorophyll Index, 2- and 3-band, and OC3) and Mixture Density Networks (MDNs) by 15–65%, while exhibiting comparable performance to a locally trained MDN, with an error of ∼35%. Comparison of Chla retrieval models, AC processors (iCOR, ACOLITE), and radiometric products (Rayleigh-corrected, surface, and top-of-atmosphere reflectance) showed that the best Chla maps and optimal time series (up to 100 mg m−3) were produced using a coupled SVR-iCOR system.