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NASA NTRS2005

Solid Freeform Fabrication of Composite-Material Objects

Composite solid freeform fabrication (C-SFF) or composite layer manufacturing (CLM) is an automated process in which an advanced composite material (a matrix reinforced with continuous fibers) is formed into a freestanding, possibly complex, three-dimensional object. In CLM, there is no need for molds, dies, or other expensive tooling, and there is usually no need for machining to ensure that the object is formed to the desired net size and shape. CLM is a variant of extrusion-type rapid prototyping, in which a model or prototype of a solid object is built up by controlled extrusion of a polymeric or other material through an orifice that is translated to form patterned layers. The second layer is deposited on top of the first layer, the third layer is deposited on top of the second layer, and so forth, until the stack of layers reaches the desired final thickness and shape. The elements of CLM include (1) preparing a matrix resin in a form in which it will solidify subsequently, (2) mixing the fibers and matrix material to form a continuous pre-impregnated tow (also called "towpreg"), and (3) dispensing the pre-impregnated tow from a nozzle onto a base while moving the nozzle to form the dispensed material into a patterned layer of controlled thickness. When the material deposited into a given layer has solidified, the material for the next layer is deposited and patterned similarly, and so forth, until the desired overall object has been built up as a stack of patterned layers. Preferably, the deposition apparatus is controlled by a computer-aided design (CAD) system. The basic CLM concept can be adapted to the fabrication of parts from a variety of matrix materials. It is conceivable that a CLM apparatus could be placed at a remote location on Earth or in outer space where (1) spare parts are expected to be needed but (2) it would be uneconomical or impractical to store a full inventory of spare parts. A wide variety of towpregs could be prepared and stored on spools until needed. Long-shelf-life towpreg materials suitable for such use could include thermoplastic-coated carbon fibers and metal-coated SiC fibers. When a spare part was needed, the part could be fabricated by CLM under control by a CAD data file; thus, the part could be built automatically, at the scene, within hours or minutes.

Wang, C. Jeff↗

NASA NTRS2019

TESS Science Processing Operations Center Pipeline and Data Products

TESS launched 18-4-2018 to conduct a two-year, near all-sky survey for at least 50 nearby exoplanets for which masses can be. TESS just completed surveying the southern hemisphere, identifying hundreds of candidate exoplanet systems and unveiling a plethora of exciting non-exoplanet astrophysics results, such as asteroseismology, asteroids, and supernova. The TESS Science Processing Operations Center (SPOC) at NASA Ames Research Center processes the image data downlinked from TESS every two weeks to generate a variety of data products hosted at the Mikulski Archive for Space Telescopes (MAST). For each ~1 month sector, the SPOC calibrates the image data for both 30-min Full Frame Images (FFIs) and up to 20,000 pre-selected 2-min target star postage stamps. Simple aperture photometry and systematic error-corrected flux time series are generated for the 2-min data. The data products also include co-trending basis vectors (CBVs) and calibration files, such as the Pixel Response Functions (PRF). The archival files are modeled after Kepler's for ease of use, and include Target Pixel Files (TPFs) containing original and calibrated 2-min image data, Light Curve files (LCs) containing the photometric time series for each 2-min target, as well as the Data Validation products. New products derived from the FFIs include light curves for the 2-min targets and CBVs. The TESS Mission is funded by NASA's Science Mission Directorate as an Astrophysics Explorer Mission.

Jenkins, Jon M.↗

NASA NTRS2022

VESIcal: An Open-source Thermodynamic Model Engine for Mixed Volatile (H2O-CO2) Solubility in Silicate Melts

Modeling the solubility of volatiles in silicate melts is fundamental to the interpretation of volcanic systems and has implications for magma dynamics, eruption style, and material transport between the mantle, crust, and atmosphere. Recent advancements in computational capabilities and access to computing tools has outpaced the functionality and extensibility of previously available modeling platforms. Here we present VESIcal (Volatile Equilibria and Saturation Index calculator), the first comprehensive modeling tool for H2O, CO2, and mixed (H2O-CO2) solubility in silicate melts that: a) allows users access to seven popular models, with easy inter-comparison between models; b) provides universal functionality for all models (e.g., functions for calculating saturation pressures, degassing paths, etc.); c) can process large datasets (1,000’s of samples) automatically; d) can output computed data into an Excel spreadsheet or CSV file for post-modeling analysis; e) integrates plotting capabilities directly within the tool; and f) provides all of this within the framework of a python library, making the tool extensible by the user and allowing any of the model functions to be incorporated into any other code capable of calling python.Here we will provide a demonstration of VESIcal and its capabilities with applications to various volcanic processes affected by volatiles. VESIcal represents the first tool capable of directly comparing multiple solubility models and equations of state. We find that commonly used models predict surprisingly different volatile solubilities, particularly for pure CO2 or mixed CO2-H2O fluids. Even for melt compositions that are well represented in the calibration datasets of multiple models (e.g., MORBs), calculated solubilities for pure CO2 and pure H2O can deviate from one another by factors of >2 leading to 2x deviations in calculated saturation pressures (e.g., 5 to 10 kbar). The solubility of CO2 predicted by different rhyolitic models also differs substantially, overwhelming other sources of uncertainty such as analytical errors on measurements of volatile contents or uncertainties in crustal density profiles. This highlights the importance of model choice when drawing geological conclusions based on volatiles in magmas.

Kayla Iacovino↗

NASA NTRS2024

Discrete Event Simulation-Based Timeline Validation Using R2U2

The Gateway Vehicle Systems Manager (VSM), the top-level software control system in a distributed, hierarchical Autonomous System Management Architecture is, like most modern spacecraft software control systems, heavily data-driven. For example, schedules (timelines) will be developed on the ground and, due to the high degree of autonomy, contain complex procedures involving conditional branching, variable timing, and resource contention resolution. In order to verify that an uploaded timeline will function correctly, it is necessary to explore the feasible set of possible executions. While it is possible to test a timeline using a mission simulation, the complexity of the system and duration of a timeline limits the number of trials and therefore the test coverage. To address this problem, the VSM team is using a discrete event system model that can rapidly generate from a timeline sets of event sequences using Monte Carlo techniques. To achieve rapid and trustworthy checking of the event sequences, we use an offline version of the runtime model checking tool R2U2. This presentation describes the approach the VSM team is using to implement the discrete event simulation and evaluate event sequences using R2U2. The presentation will discuss: 1. Description of the timelines by VSM in the context of VSM operations 2. Expansion of a timeline into a sequence of atomic events 3. Adjustment, in the Monte Carlo environment, of an event sequence to account for uncertainty, external events, and failures 4. Definition of R2U2 input and mission-time linear temporal logic files 5. Generation and use of R2U2 verdict sequences 6. Lessons learned and future work

Verification↗

NASA NTRS1994

SEQ-GEN: A comprehensive multimission sequencing system

SEQ-GEN is a user-interactive computer program used to plan and generate a sequence of commands for spacecraft. Desired activities are specified by the user of SEQ-GEN; SEQ-GEN in turn expands these activities, deriving the spacecraft commands necessary to accomplish the desired activities. SEQ-GEN models the effects on the spacecraft of the commands, predicting the state as a function of time, flagging any conflicts and rule violations. These states, conflicts, and violations are viewable both graphically and textually at the user's request. SEQ-GEN also displays the entire sequence graphically, showing each requested activity as a bar on its graphical timeline. SEQ-GEN immediately revalidates the sequence, updating its models and calculations along with its displays based on these changes. Because it has the ability to recalculate spacecraft states immediately, the user is able to perform 'what-if' sessions easily. SEQ-GEN, a multimission tool, is adaptable to any flight project. A flight project writes its adaptation files containing project unique information including in its simplest form, only spacecraft commands. For more involved projects the adaptation files may also contain flight and mission rules, description of the spacecraft and ground models, and the definition of activities. SEQ-GEN operates at whatever level of detail the adaptation files imply. Simple adaptations are straight forward to do. There is, however, no limit to the complexity of activity definitions or of spacecraft models: both may involve unlimited logical decision points. Commands and activities may involve any number of parameters of a wide variety of data types, including integer, float, time, boolean, and character strings. SEQ-GEN will be used by the Mars Pathfinder, Cassini, and VIM (Voyager Interstellar Mission) project in an effort to speed up adaptation time and to keep sequence generation costs down. SEQ-GEN is hosted on UNIX workstations. It uses MOTIF and X for windowing, and was designed and coded in an object-oriented style in the language C++.

Salcedo, Jose↗

NASA NTRS1999

Acceleration Measurement and Characterization in Support of the USMP-4 Payloads

One common characteristic of the USMP-4 experiments is that various effects of gravity make it difficult, if not impossible, to achieve usable results when performing the experiments on Earth's surface. Therefore, the investigators took advantage of the microgravity environment afforded by being in low-Earth orbit to perform their research. Interpretation of the experiment results both during the mission and upon post-mission analyses of data and samples required an understanding of the microgravity environment in which the experiments were conducted. To achieve that understanding, data were collected using the Orbital Acceleration Research Experiment (OARE) and two Space Acceleration Measurement Systems (SAMS). Data from those systems, combined with an assessment of mission and experiment activities, were used to characterize the microgravity environment that existed on Columbia during the mission. The text herein gives details about some characteristics of the environment that were noted during the mission and during post-mission data analysis. The disturbances studied include the Ku-band antenna 17 Hz dither; the effect of changing the Orbiter attitude deadband limits; the effects of different bicycle ergometer configurations; and the effect of IDGE (Isothermal Dendritic Growth Experiment) experiment fans and SAMS computer hard drives. Additional information about the microgravity environment is provided. Supplementary data plots representing the environment throughout the majority of the mission are available at the Uniform Resource Locator (URL). Data files for both SAMS and OARE are accessible via anonymous file transfer protocol from the file server.

Rogers, M. J. B.↗

NASA NTRS2004

Automated Classification of ROSAT Sources Using Heterogeneous Multiwavelength Source Catalogs

We describe an on-line system for automated classification of X-ray sources, ClassX, and present preliminary results of classification of the three major catalogs of ROSAT sources, RASS BSC, RASS FSC, and WGACAT, into six class categories: stars, white dwarfs, X-ray binaries, galaxies, AGNs, and clusters of galaxies. ClassX is based on a machine learning technology. It represents a system of classifiers, each classifier consisting of a considerable number of oblique decision trees. These trees are built as the classifier is 'trained' to recognize various classes of objects using a training sample of sources of known object types. Each source is characterized by a preselected set of parameters, or attributes; the same set is then used as the classifier conducts classification of sources of unknown identity. The ClassX pipeline features an automatic search for X-ray source counterparts among heterogeneous data sets in on-line data archives using Virtual Observatory protocols; it retrieves from those archives all the attributes required by the selected classifier and inputs them to the classifier. The user input to ClassX is typically a file with target coordinates, optionally complemented with target IDs. The output contains the class name, attributes, and class probabilities for all classified targets. We discuss ways to characterize and assess the classifier quality and performance and present the respective validation procedures. Based on both internal and external validation, we conclude that the ClassX classifiers yield reasonable and reliable classifications for ROSAT sources and have the potential to broaden class representation significantly for rare object types.

McGlynn, Thomas↗

NASA NTRS2012

Improved Aerodynamic Analysis for Hybrid Wing Body Conceptual Design Optimization

This paper provides an overview of ongoing efforts to develop, evaluate, and validate different tools for improved aerodynamic modeling and systems analysis of Hybrid Wing Body (HWB) aircraft configurations. Results are being presented for the evaluation of different aerodynamic tools including panel methods, enhanced panel methods with viscous drag prediction, and computational fluid dynamics. Emphasis is placed on proper prediction of aerodynamic loads for structural sizing as well as viscous drag prediction to develop drag polars for HWB conceptual design optimization. Data from transonic wind tunnel tests at the Arnold Engineering Development Center s 16-Foot Transonic Tunnel was used as a reference data set in order to evaluate the accuracy of the aerodynamic tools. Triangularized surface data and Vehicle Sketch Pad (VSP) models of an X-48B 2% scale wind tunnel model were used to generate input and model files for the different analysis tools. In support of ongoing HWB scaling studies within the NASA Environmentally Responsible Aviation (ERA) program, an improved finite element based structural analysis and weight estimation tool for HWB center bodies is currently under development. Aerodynamic results from these analyses are used to provide additional aerodynamic validation data.

Gern, Frank H.↗

NASA NTRS2012

Eclipse-Free-Time Assessment Tool for IRIS

IRIS_EFT is a scientific simulation that can be used to perform an Eclipse-Free- Time (EFT) assessment of IRIS (Infrared Imaging Surveyor) mission orbits. EFT is defined to be those time intervals longer than one day during which the IRIS spacecraft is not in the Earth s shadow. Program IRIS_EFT implements a special perturbation of orbital motion to numerically integrate Cowell's form of the system of differential equations. Shadow conditions are predicted by embedding this integrator within Brent s method for finding the root of a nonlinear equation. The IRIS_EFT software models the effects of the following types of orbit perturbations on the long-term evolution and shadow characteristics of IRIS mission orbits. (1) Non-spherical Earth gravity, (2) Atmospheric drag, (3) Point-mass gravity of the Sun, and (4) Point-mass gravity of the Moon. The objective of this effort was to create an in-house computer program that would perform eclipse-free-time analysis. of candidate IRIS spacecraft mission orbits in an accurate and timely fashion. The software is a suite of Fortran subroutines and data files organized as a "computational" engine that is used to accurately predict the long-term orbit evolution of IRIS mission orbits while searching for Earth shadow conditions.

Eagle, David↗

NASA NTRS2010

Nondestructive Crack Detection in a Fuel System Component

The paper discusses development of various NDE techniques to detect cracks in A40 steel poppets used in a valve of the fuel system of the Space Shuttle Orbiter. The valve assembly experiences a severe high cycle fatigue environment during its operation. Cracks were discovered at the radius of the poppet flange. Experience shows that very small cracks or material anomalies do not cause failure in a single operation event. While the design is being modified to eliminate the issue, NDE has been used to screen the poppets for cracks before every use. Several surface flaw detection techniques were considered and a few NDE techniques were developed to provide NDE screening for the flaw detection. The primary method used was the eddy current testing. In the eddy current technique, the X-Y channel test data from the eddy current instrument was recorded as computer files. A Matlab data review and plotting application was developed to analyze the data files. The Matlab application provides much higher resolution than the eddy current instrument that was used to acquire the data. Other techniques that were used included ultrasonic surface wave and magnetic particle testing. A probability of detection (POD) study was undertaken to determine the 90/95 size for the eddy current technique. This study used specimens with same geometry and material as the poppet. Fatigue cracks were grown in these specimens. Information on results of the NDE techniques and results of the POD study are provided.

Koshti, Ajay↗

NASA NTRS2007

Predicting Rocket or Jet Noise in Real Time

A semi-empirical theoretical model and a C++ computer program that implements the model have been developed for use in predicting the noise generated by a rocket or jet engine. The computer program, entitled the Realtime Rocket and Jet Engine Noise Analysis and Prediction Software, is one of two main subsystems of the Acoustic Prediction/Measurement Tool, which comprises software, acoustic instrumentation, and electronic hardware combined to afford integrated capabilities for real-time prediction and measurement of noise emitted by rocket and jet engines. [The other main subsystem, consisting largely of acoustic instrumentation and electronic hardware, is described in Wireless Acoustic Measurement System, which appears elsewhere in this section.] The theoretical model was derived from the fundamental laws of fluid mechanics, as first was done by M. J. Lighthill in his now famous theory of aerodynamically generated sound. The far-field approximation of the Lighthill theory is incorporated into this model. Many other contributions from various researchers have also been introduced into the model. The model accounts for two noise components: shear noise and self noise. The final result of the model is expressed in terms of a volume integral of the acoustic intensities attributable to these two components, subject to various directivity coefficients. The computer program was written to solve the volume integral. The inputs required by the program are two data files from a computational fluid dynamics (CFD) simulation of the flow of interest: the computational-grid file and the solution file. The CFD solution should be one that has been obtained for conditions that closely approximate those of an experimental test that is yet to be performed. In the current state of development of the model and software, it is recommended that the observation points lie along a radius at an angle >60 from the jet axis. The software provides, and is driven via, a graphical user interface, which facilitates its use. Optionally, the program accepts additional input in the form of data on the measured sound pressure level as a function of frequency at a given far-field location, preferably at an angle of 90 from the jet axis. The user is prompted to use default empirical constants or to choose constants based the measurement data. The user can view the results and compare them with other computational or experimental data. Once satisfied with the results, the user can save a graph of the results in a file that can be imported into documents.

Frendi, Kader↗

NASA NTRS2019

TESS Science Processing Operations Center Pipeline and Data Products

TESS (Transiting Exoplanet Survey Satellite) launched on 18-4-2018 to conduct a two-year, near all-sky survey for at least 50 nearby exoplanets for which masses can be obtained. TESS just completed surveying the southern hemisphere, identifying hundreds of candidate exoplanet systems and unveiling a plethora of exciting non-exoplanet astrophysics results, such as asteroseismology, asteroids, and supernova. The TESS Science Processing Operations Center (SPOC) at NASA Ames Research Center processes the image data downlinked from TESS every two weeks to generate a variety of data products hosted at the Mikulski Archive for Space Telescopes (MAST). For each approximately 1-month sector, the SPOC calibrates the image data for both 30-minute Full Frame Images (FFIs) and up to 20,000 pre-selected 2-minute target star postage stamps. Simple aperture photometry and systematic error-corrected flux-time series are generated for the 2-minute data. The data products also include co-trending basis vectors (CBVs) and calibration files, such as the Pixel Response Functions (PRF). The archival files are modeled after Kepler's for ease of use, and include Target Pixel Files (TPFs) containing original and calibrated 2-minute image data, Light Curve files (LCs) containing the photometric time series for each 2-minute target, as well as the Data Validation products. New products derived from the FFIs include light curves for the 2-minute targets and CBVs. The TESS Mission is funded by NASA's Science Mission Directorate as an Astrophysics Explorer Mission.

Science Pipeline↗

NASA NTRSDate not supplied

The NASA Open Science Data Repository: Biomedical Data, Analysis Tools, and Informatic Collaborations

Increased biomedical risks and challenges associated with deep space missions require knowledge discovery, health countermeasures, and biomedical support capabilities. Maximally open-access and reusable data is needed by developers, scientists, and engineers to develop these systems. The NASA Open Science Data Repository (OSDR) is a maximally open access and FAIR database (ie., findable, accessible, interoperable, and reusable), and meets various scientific, technical, and operational needs. It offers users and submitters the ability to upload, download, search, share, analyze, cite, and visualize data across ‘omics, physiological, phenotypic, payload, hardware, behavioral, bioimaging, video, and environmental monitoring telemetry datasets. OSDR is an expanded database, based upon the successes of NASA GeneLab. OSDR has >460 studies with datasets covering model organisms to non-NASA human astronauts. There are ~12 datasets from the Inspiration 4 (I4) mission, spanning metagenomics, comprehensive metabolic panels, clonal hematopoiesis, spatial transcriptomics, proteomics, and cytokine panels. In the interest of data privacy, two I4 datasets with raw files relating to the epitranscriptome, and a new request feature is live in OSDR (with a backend review process established) developed from industry norms. OSDR is collecting and curating biomedical human data from a new sub-orbital research flight and is open to more space life science/biomedical submissions from the international and commercial sectors. OSDR also recently began a collaboration with the European Space Agency (ESA) to collect and curate >200 terabytes of human and model organism data. The OSDR submission portal is designed to ingest and curate ~25 ‘omics and ~50 physiological-phenotypic-imaging assay data types. Tools available for OSDR users include: 1) an Environmental Data Application to compare radiation, CO2, relative humidity, temperature, and other telemetry across missions and subjects, 2) the RadLab database, a collaboration between NASA, ESA, the German and Italian Space Agencies, and the Bulgarian Academy of Sciences, and 3) a Multi-study visualization tool which enables users to look across and combine ‘omics datasets. There are ~600 volunteer OSDR Analysis Working Group (AWG) members providing feedback on scientific data/metadata standards and collaborating to mine-reuse OSDR in research. OSDR/GeneLab has enabled ~60 publications reusing data as of October 2023.

space biology↗

NASA NTRS2001

External Data and Attribute Hyperlink Programs for Promis*e(Registered Trademark)

External Data and Attribute Hyperlink are computer programs that can be added to Promis*e(trademark) which is a commercial software system that automates routine tasks in the design (including drawing schematic diagrams) of electrical control systems. The programs were developed under the Stennis Space Center's (SSC) Dual Use Technology Development Program to provide capabilities for SSC's BMCS configuration management system which uses Promis*e(trademark). The External Data program enables the storage and management of information in an external database linked to a drawing. Changes can be made either in the database or on the drawing. Information that originates outside Promis*e(trademark) can be stored in custom fields that can be added to the database. Although this information is not available in Promis*e(trademark) printed drawings, it can be associated with symbols in the drawings, and can be retrieved through the drawings when the software is running. The Attribute Hyperlink program enables the addition of hyperlink information as attributes of symbols. This program enables the formation of a direct hyperlink between a schematic diagram and an Internet site or a file on a compact disk, on the user's hard drive, or on another computer on a network to which the user's computer is connected. The user can then obtain information directly related to the part (e.g., maintenance, or troubleshooting information) associated with the hyperlink.

Derengowski, Rich↗

NASA NTRS2009

Desktop Application Program to Simulate Cargo-Air-Drop Tests

The DSS Application is a computer program comprising a Windows version of the UNIX-based Decelerator System Simulation (DSS) coupled with an Excel front end. The DSS is an executable code that simulates the dynamics of airdropped cargo from first motion in an aircraft through landing. The bare DSS is difficult to use; the front end makes it easy to use. All inputs to the DSS, control of execution of the DSS, and postprocessing and plotting of outputs are handled in the front end. The front end is graphics-intensive. The Excel software provides the graphical elements without need for additional programming. Categories of input parameters are divided into separate tabbed windows. Pop-up comments describe each parameter. An error-checking software component evaluates combinations of parameters and alerts the user if an error results. Case files can be created from inputs, making it possible to build cases from previous ones. Simulation output is plotted in 16 charts displayed on a separate worksheet, enabling plotting of multiple DSS cases with flight-test data. Variables assigned to each plot can be changed. Selected input parameters can be edited from the plot sheet for quick sensitivity studies.

Cuthbert, Peter↗

NASA NTRS2010

Development of a User Interface for a Regression Analysis Software Tool

An easy-to -use user interface was implemented in a highly automated regression analysis tool. The user interface was developed from the start to run on computers that use the Windows, Macintosh, Linux, or UNIX operating system. Many user interface features were specifically designed such that a novice or inexperienced user can apply the regression analysis tool with confidence. Therefore, the user interface s design minimizes interactive input from the user. In addition, reasonable default combinations are assigned to those analysis settings that influence the outcome of the regression analysis. These default combinations will lead to a successful regression analysis result for most experimental data sets. The user interface comes in two versions. The text user interface version is used for the ongoing development of the regression analysis tool. The official release of the regression analysis tool, on the other hand, has a graphical user interface that is more efficient to use. This graphical user interface displays all input file names, output file names, and analysis settings for a specific software application mode on a single screen which makes it easier to generate reliable analysis results and to perform input parameter studies. An object-oriented approach was used for the development of the graphical user interface. This choice keeps future software maintenance costs to a reasonable limit. Examples of both the text user interface and graphical user interface are discussed in order to illustrate the user interface s overall design approach.

Ulbrich, Norbert Manfred↗

NASA NTRS2017

The Profile Envision and Splice Tool (PRESTO): Developing an Atmospheric Wind Analysis Tool for Space Launch Vehicles Using Python

Tropospheric winds are an important driver of the design and operation of space launch vehicles. Multiple types of weather balloons and Doppler Radar Wind Profiler (DRWP) systems exist at NASA's Kennedy Space Center (KSC), co-located on the United States Air Force's (USAF) Eastern Range (ER) at the Cape Canaveral Air Force Station (CCAFS), that are capable of measuring atmospheric winds. Meteorological data gathered by these instruments are being used in the design of NASA's Space Launch System (SLS) and other space launch vehicles, and will be used during the day-of-launch (DOL) of SLS to aid in loads and trajectory analyses. For the purpose of SLS day-of-launch needs, the balloons have the altitude coverage needed, but take over an hour to reach the maximum altitude and can drift far from the vehicle's path. The DRWPs have the spatial and temporal resolutions needed, but do not provide complete altitude coverage. Therefore, the Natural Environments Branch (EV44) at Marshall Space Flight Center (MSFC) developed the Profile Envision and Splice Tool (PRESTO) to combine balloon profiles and profiles from multiple DRWPs, filter the spliced profile to a common wavelength, and allow the operator to generate output files as well as to visualize the inputs and the spliced profile for SLS DOL operations. PRESTO was developed in Python taking advantage of NumPy and SciPy for the splicing procedure, matplotlib for the visualization, and Tkinter for the execution of the graphical user interface (GUI). This paper describes in detail the Python coding implementation for the splicing, filtering, and visualization methodology used in PRESTO.

Orcutt, John M.↗

NASA NTRS2000

BOREAS RSS-16 AIRSAR CM Images: Integrated Processor Version 6.1 Level-3b

The BOREAS RSS-16 team used satellite and aircraft SAR data in conjunction with various ground measurements to determine the moisture regime of the boreal forest. RSS-16 assisted with the acquisition and ordering of NASA JPL AIRSAR data collected from the NASA DC-8 aircraft. The NASA JPL AIRSAR is a side-looking imaging radar system that utilizes the SAR principle to obtain high resolution images that represent the radar backscatter of the imaged surface at different frequencies and polarizations. The information contained in each pixel of the AIRSAR data represents the radar backscatter for all possible combinations of horizontal and vertical transmit and receive polarizations (i.e., HH, HV, VH, and VV). Geographically, the data cover portions of the BOREAS SSA and NSA. Temporally, the data were acquired from 12-Aug-1993 to 31-Jul-1995. The level-3b AIRSAR CM data are in compressed Stokes matrix format, which has 10 bytes per pixel. From this data format, it is possible to synthesize a number of different radar backscatter measurements. The data are stored in binary image-format files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗