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At least 181 records · Page 10

SAR terrain classifier and mapper of biophysical attributes

In preparation for the launch of SIR-C/X-SAR and design studies for future orbital SAR, a program has made considerable progress in the development of an SAR terrain classifier and algorithms for quantification of biophysical attributes. The goal of this program is to produce a generalized software package for terrain classification and estimation of biophysical attributes and to make this package available to the larger scientific community. The basic elements of the SAR (Synthetic Aperture Radar) terrain classifier are outlined. An SAR image is calibrated with respect to known system and processor gains and external targets (if available). A Level 1 classifier operates on the data to differentiate: urban features, surfaces and tall and short vegetation. Level 2 classifiers further subdivide these classes on the basis of structure. Finally, biophysical and geophysical inversions are applied to each class to estimate attributes of interest. The process used to develop the classifiers and inversions is shown. Radar scattering models developed from theory and from empirical data obtained by truck-mounted polarimeters and the JPL AirSAR are validated. The validated models are used in sensitivity studies to understand the roles of various scattering sources (i.e., surface trunk, branches, etc.) in determining net backscatter. Model simulations of sigma (sup o) as functions of the wave parameters (lambda, polarization and angle of incidence) and the geophysical and biophysical attributes are used to develop robust classifiers. The classifiers are validated using available AirSAR data sets. Specific estimators are developed for each class on the basis of the scattering models and empirical data sets. The candidate algorithms are tested with the AirSAR data sets. The attributes of interest include: total above ground biomass, woody biomass, soil moisture and soil roughness.

Ulaby, Fawwaz T.↗

Ongoing Development of NASA's Global Land Data Assimilation System

NASA's Global Land Data Assimilation System (GLDAS) produces global fields of land surface states (e.g., soil moisture and temperature) and fluxes (e.g., latent heat flux and runoff) by driving offline land surface models with observation-based inputs, using the Land Information System (LIS) software. Since production began in 2001, GLDAS has supported more than 100 scientific investigations and applications. Some examples are GEWEX and NASA Energy and Water Cycle Study (NEWS) global water and energy budget analyses, interpretations of hydrologic data derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission, and forecast model initiation studies at NOAA and NASA. At the same time, the GLDAS team has continued improve results through the development of new modeling and data assimilation techniques. Here we describe several recent and ongoing innovations. These include global implementation of a runoff routing procedure, GRACE data assimilation, advanced snow cover assimilation, and irrigation modeling.

Rodell, Matthew↗

Magellan mission planning and orbital operations

The goal of NASA's Magellan mission is to understand the geological and geophysical processes that have shaped the planet Venus. Through synthetic aperture radar, radiometric, altimetric, and gravity measurements, the scientific community hopes to improve its knowledge of the planet's topography and internal mass distribution. This paper provides an overview of the Magellan mission; describes the spacecraft sequence software design, development, and test; addresses the nominal operational flow of stored sequence design and generation; briefly describes the ground processing of engineering telemetry and imaging data; and then summarizes the Magellan operational experience with non-routine behavior of the spacecraft during the cruise and mapping portions of the prime mission.

Venus↗

Ground data systems resource allocation process

The Ground Data Systems Resource Allocation Process at the Jet Propulsion Laboratory provides medium- and long-range planning for the use of Deep Space Network and Mission Control and Computing Center resources in support of NASA's deep space missions and Earth-based science. Resources consist of radio antenna complexes and associated data processing and control computer networks. A semi-automated system was developed that allows operations personnel to interactively generate, edit, and revise allocation plans spanning periods of up to ten years (as opposed to only two or three weeks under the manual system) based on the relative merit of mission events. It also enhances scientific data return. A software system known as the Resource Allocation and Planning Helper (RALPH) merges the conventional methods of operations research, rule-based knowledge engineering, and advanced data base structures. RALPH employs a generic, highly modular architecture capable of solving a wide variety of scheduling and resource sequencing problems. The rule-based RALPH system has saved significant labor in resource allocation. Its successful use affirms the importance of establishing and applying event priorities based on scientific merit, and the benefit of continuity in planning provided by knowledge-based engineering. The RALPH system exhibits a strong potential for minimizing development cycles of resource and payload planning systems throughout NASA and the private sector.

Berner, Carol A.↗

Small Spacecraft for Planetary Atmospheric, Surface, and Interior Structure Using Radio Links

Scientific studies using spacecraft radio links have been conducted on almost every Solar System exploration mission in the past five decades and have led to numerous discoveries. Radio Science experiments have elucidated the thermal history of the Moon from high resolution gravitational field measurements, unveiled the interiors of Titan, Enceladus, Mercury, Phobos, Vesta and Ceres providing key evidence for identifying subsurface oceans on icy moons; sounded Titan, Saturn, and Pluto’s atmospheres, and refined models for the atmospheres, surfaces, and interior structure of Mars and Venus. A Juno experiment is in progress measuring the gravitational field of Jupiter to reveal its interior structures, as did a similar recent Cassini experiment with Saturn. Experiments at Mercury, the Jovian system, and other targets, are in development or planning phases. Over the next 30 years, significant advances in radio and laser link-science technologies, including nearly one order of magnitude improvement achievable in range-rate and range accuracy, could enable many new scientific breakthroughs. Future exploration concepts in many cases focus on applications of small spacecraft and can include spacecraft constellations for studies of atmospheric dynamics, interior structures, and surface properties. A set of science-enabling radio link technologies specific to small spacecraft instrumentation on future solar system missions are under study and development. Examples include field tests of radio scattering to determine soil properties, smallsat constellations for dense geographic and temporal atmospheric probing, small science-quality software-defined transponders, miniature ultra-stable oscillators, and advanced radio-metric calibrations at the Deep Space Network. This paper describes many of these technologies and their scientific applications.

Elliott, Harvey↗

Advanced flight experiment automation development

NASA's space science program suffers under operational constraints that severely limit scientific reactivity. We describe a possible extension to an existing system that enables space science to be conducted in a more reactive manner through advanced automation techniques that have recently been used in the Space Transportation System (STS)-based Spacelab. This automation allows sophisticated autonomous control of the experiment by monitoring and dynamically controlling the progress of the experiment protocol. This new approach permits intelligent conduct of experimental research investigations whether or not the crew is available or contact with the ground is possible. We describe an intelligent software assistant that can manage the conduct of the experiment autonomously, by providing responsive telepresence science, or by assisting the astronaut operator with scientific advice. The crew could be unavailable for short periods when the experiment has low priority, or for longer periods on partially tended Space Station. We suggest this system could be developed as a ground prototype using commercial hardware, versions of which have been flight qualified, in order to provide a natural transition path towards flight use. In order to make this demonstration most valuable, we propose not to select a particular Life Sciences experiment, but to include an experiment simulator representative of major scientific domains.

Groleau, Nicolas↗

Data processing for a cosmic ray experiment onboard the solar probes Helios 1 and 2: Experiment 6

The data processing system for the Helios experiment 6, measuring energetic charged particles of solar, planetary and galactic origin in the inner solar system, is described. The aim of this experiment is to extend knowledge on origin and propagation of cosmic rays. The different programs for data reduction, analysis, presentation, and scientific evaluation are described as well as hardware and software of the data processing equipment. A chronological presentation of the data processing operation is given. Procedures and methods for data analysis which were developed can be used with minor modifications for analysis of other space research experiments.

Mueller-Mellin, R.↗

FAST: A multi-processed environment for visualization of computational fluid

Three dimensional, unsteady, multizoned fluid dynamics simulations over full scale aircraft is typical of problems being computed at NASA-Ames on CRAY2 and CRAY-YMP supercomputers. With multiple processor workstations available in the 10 to 30 Mflop range, it is felt that these new developments in scientific computing warrant a new approach to the design and implementation of analysis tools. These large, more complex problems create a need for new visualization techniques not possible with the existing software or systems available as of this time. These visualization techniques will change as the supercomputing environment, and hence the scientific methods used, evolve ever further. Visualization of computational aerodynamics require flexible, extensible, and adaptable software tools for performing analysis tasks. FAST (Flow Analysis Software Toolkit), an implementation of a software system for fluid mechanics analysis that is based on this approach is discussed.

Bancroft, Gordon V.↗

FAST: A multi-processed environment for visualization of computational fluid dynamics

Three-dimensional, unsteady, multi-zoned fluid dynamics simulations over full scale aircraft are typical of the problems being investigated at NASA Ames' Numerical Aerodynamic Simulation (NAS) facility on CRAY2 and CRAY-YMP supercomputers. With multiple processor workstations available in the 10-30 Mflop range, we feel that these new developments in scientific computing warrant a new approach to the design and implementation of analysis tools. These larger, more complex problems create a need for new visualization techniques not possible with the existing software or systems available as of this writing. The visualization techniques will change as the supercomputing environment, and hence the scientific methods employed, evolves even further. The Flow Analysis Software Toolkit (FAST), an implementation of a software system for fluid mechanics analysis, is discussed.

Bancroft, Gordon V.↗

A NASA initiative: Software engineering for reliable complex systems

The objective is the development of methods, technology, and skills that will enable NASA to cost-effectively specify, build, and manage reliable software which can evolve and be maintained over an extended period. The need for such software is rooted in the increasing integration of software and computing components into NASA systems. Current NASA Software Engineering expertise was applied toward some of the largest reliable systems including: shuttle launch; ground support; shuttle simulation; minor control; satellite tracking; and scientific data systems. Unfortunately, no theory exists for reliable complex software systems. NASA is seeking to fill this theoretical gap through a number of approaches. One such approach is to conduct research on theoretical foundations for managing complex software systems. It includes: communication models, new and modified paradigms, and life-cycle models. Another approach is research in the theoretical foundations for reliable software development and validation. It focuses upon formal specifications, programming languages, software engineering systems, software reuse, formal verification, and software safety. Further approaches involve benchmarking a NASA software environment, experimentation within the NASA context, evolution of present NASA methodology, and transfer of technology to the space station software support environment.

Holcomb, Lee B.↗

A ranking algorithm for spacelab crew and experiment scheduling

The problem of obtaining an optimal or near optimal schedule for scientific experiments to be performed on Spacelab missions is addressed. The current capabilities in this regard are examined and a method of ranking experiments in order of difficulty is developed to support the existing software. Experimental data is obtained from applying this method to the sets of experiments corresponding to Spacelab mission 1, 2, and 3. Finally, suggestions are made concerning desirable modifications and features of second generation software being developed for this problem.

Grone, R. D.↗

The CCD/Transit Instrument (CTI) data-analysis system

The automated software system for archiving, analyzing, and interrogating data from the CCD/Transit Instrument (CTI) is described. The CTI collects up to 450 Mbytes of image-data each clear night in the form of a narrow strip of sky observed in two colors. The large data-volumes and the scientific aims of the project make it imperative that the data are analyzed within the 24-hour period following the observations. To this end a fully automatic and self evaluating software system has been developed. The data are collected from the telescope in real-time and then transported to Tucson for analysis. Verification is performed by visual inspection of random subsets of the data and obvious cosmic rays are detected and removed before permanent archival is made to the optical disc. The analysis phase is performed by a pair of linked algorithms, one operating on the absolute pixel-values and the other on the spatial derivative of the data. In this way both isolated and merged images are reliably detected in a single pass. In order to isolate the latter algorithm from the effects of noise spikes a 3x3 Hanning filter is applied to the raw data before the analysis is run. The algorithms reduce the input pixel-data to a database of measured parameters for each image which has been found. A contrast filter is applied in order to assign a detection-probability to each image and then x-y calibration and intensity calibration are performed using known reference stars in the strip. These are added to as necessary by secondary standards boot-strapped from the CTI data itself. The final stages involve merging the new data into the CTI Master-list and History-list and the automatic comparison of each new detection with a set of pre-defined templates in parameter-space to find interesting objects such as supernovae, quasars and variable stars. Each stage of the processing from verification to interesting image selection is performed under a data-logging system which both controls the pipe-lining of data through the system and records key performance monitor parameters which are built into the software. Furthermore, the data from each stage are stored in databases to facilitate evaluation, and all stages offer the facility to enter keyword-indexed free-format text into the data-logging system. In this way a large measure of certification is built into the system to provide the necessary confidence in the end results.

Cawson, M. G. M.↗

Development of a High Accuracy Angular Measurement System for Langley Research Center Hypersonic Wind Tunnel Facilities

Modern experimental and test activities demand innovative and adaptable procedures to maximize data content and quality while working within severely constrained budgetary and facility resource environments. This report describes development of a high accuracy angular measurement capability for NASA Langley Research Center hypersonic wind tunnel facilities to overcome these deficiencies. Specifically, utilization of micro-electro-mechanical sensors including accelerometers and gyros, coupled with software driven data acquisition hardware, integrated within a prototype measurement system, is considered. Development methodology addresses basic design requirements formulated from wind tunnel facility constraints and current operating procedures, as well as engineering and scientific test objectives. Description of the analytical framework governing relationships between time dependent multi-axis acceleration and angular rate sensor data and the desired three dimensional Eulerian angular state of the test model is given. Calibration procedures for identifying and estimating critical parameters in the sensor hardware is also addressed.

Newman, Brett↗

DLES Unreal Simulation Tool (DUST)

NASA’s future Artemis missions to the Moon seek to explore areas around the Lunar South Pole. Though humans have previously set foot on the lunar surface, the proposed region provides unique and challenging environments that require insight and investigation prior to arrival. Several teams throughout the agency are performing this site and mission planning, design, and analysis to support areas like the Human Landing System (HLS), surface mobility, habitation elements, and scientific exploration. The NASA Exploration Systems Simulation (NExSyS) team at Johnson Space Center is developing a graphical environment of the Lunar South Pole region. Lunar terrain information collected from the Lunar Reconnaissance Orbiter (LRO) is compiled and made available through Johnson Space Center’s Digital Lunar Exploration Sites (DLES) data sets. The DLES data is used to build this graphic environment. The process of ingesting and accurately modeling this information in a meaningful way for analysis creates its own challenges such as generating a performant model from the source data and the application of curvature. Additionally, the area around the Lunar South Pole experiences different lighting conditions than those observed from the Apollo missions. The need to use the lunar environmental data products provided by DLES combined with the capability to calculate date specific ephemerides in real-time has given rise to the development of the DLES Unreal Simulation Tool (DUST). DUST incorporates augmented terrain from the DLES product into a desktop application that allows exploration of the Lunar South Pole region and its complex lighting conditions. DUST leverages advanced capabilities in the recently released Unreal Engine 5 renderer by Epic Games such as double precision for positioning of planetary bodies and surface elements, multiple infinite light sources to represent the Sun and eventually Earthshine, high resolution shadow maps for dynamic shadow accuracy, real-time software ray-tracing for multi-surface bounce lighting to render sunlight reflected off surface elements and terrain features, and performance optimized level of detail shifting as the eyepoint changes in a scene. This paper details the DUST application, the technologies of the engine platform that enable scientific and engineering analysis, the unique techniques and processes developed to consume the DLES data sets, and how the tool is being used to support the Artemis program.

Lunar Visualization↗

Application of a data base management system to a finite element model

In today's software market, much effort is being expended on the development of data base management systems (DBMS). Most commercially available DBMS were designed for business use. However, the need for such systems within the engineering and scientific communities is becoming apparent. A potential DBMS application that appears attractive is the handling of data for finite element engineering models. The applications of a commercially available, business-oriented DBMS to a structural engineering, finite element model is explored. The model, DBMS, an approach to using the DBMS, advantages and disadvantages are described. Plans for research on a scientific and engineering DBMS are discussed.

Rogers, J. L., Jr.↗

A Look at the Impact of High-End Computing Technologies on NASA Missions

From its bold start nearly 30 years ago and continuing today, the NASA Advanced Supercomputing (NAS) facility at Ames Research Center has enabled remarkable breakthroughs in the space agency s science and engineering missions. Throughout this time, NAS experts have influenced the state-of-the-art in high-performance computing (HPC) and related technologies such as scientific visualization, system benchmarking, batch scheduling, and grid environments. We highlight the pioneering achievements and innovations originating from and made possible by NAS resources and know-how, from early supercomputing environment design and software development, to long-term simulation and analyses critical to design safe Space Shuttle operations and associated spinoff technologies, to the highly successful Kepler Mission s discovery of new planets now capturing the world s imagination.

Biswas, Rupak↗

The Science Discovery Engine: Connecting Heterogeneous Scientific Data and Information

Transformative science often occurs at the boundaries of different disciplines. Making interdisciplinary science data, software and documentation discoverable and accessible is essential to enabling transformative science. However, connecting this diverse and heterogeneous information is often a challenge due to several factors including the dispersed and sometimes isolated nature of data and the semantic differences between topical areas. NASA’s Science Discovery Engine (SDE) has developed several approaches to tackling these challenges. The SDE is a unified, insightful search experience that enables discovery of NASA’s open science data across five topical areas: astrophysics, biological and physical sciences, Earth science, heliophysics and planetary science. In this presentation, we will discuss our efforts to develop a systematic scientific curation workflow to integrate diverse content into a single search environment. We will also share lessons learned from our work to create a metadata crosswalk across the five disciplines.

Kaylin Bugbee↗

Concept Verification Test - Evaluation of Spacelab/Payload operation concepts

The Concept Verification Test (CVT) procedure is used to study Spacelab operational concepts by conducting mission simulations in a General Purpose Laboratory (GPL) which represents a possible design of Spacelab. In conjunction with the laboratory a Mission Development Simulator, a Data Management System Simulator, a Spacelab Simulator, and Shuttle Interface Simulator have been designed. (The Spacelab Simulator is more functionally and physically representative of the Spacelab than the GPL.) Four simulations of Spacelab mission experimentation were performed, two involving several scientific disciplines, one involving life sciences, and the last involving material sciences. The purpose of the CVT project is to support the pre-design and development of payload carriers and payloads, and to coordinate hardware, software, and operational concepts of different developers and users.

Mcbrayer, R. O.↗