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At least 613 records · Page 34

A Multi-mission Event-Driven Component-Based System for Support of Flight Software Development, ATLO, and Operations first used by the Mars Science Laboratory (MSL) Project

This viewgraph presentation reviews the architectural description of the Mission Data Processing and Control System (MPCS). MPCS is an event-driven, multi-mission ground data processing components providing uplink, downlink, and data management capabilities which will support the Mars Science Laboratory (MSL) project as its first target mission. MPCS is designed with these factors (1) Enabling plug and play architecture (2) MPCS has strong inheritance from GDS components that have been developed for other Flight Projects (MER, MRO, DAWN, MSAP), and are currently being used in operations and ATLO, and (3) MPCS components are Java-based, platform independent, and are designed to consume and produce XML-formatted data

Mission Data Processing and Control System (MPCS)↗

Quick-look guide to the crustal dynamics project's data information system

Described are the contents of the Crustal Dynamics Project Data Information System (DIS) and instructions on the use of this facility. The main purpose of the DIS is to store all geodetic data products acquired by the Project in a central data bank and to maintain information about the archive of all Project-related data. Access and use of the DIS menu-driven system is described as well as procedures for contacting DIS staff and submitting data requests.

Noll, Carey E.↗

Climate Change, Extreme Weather Events, and Fungal Disease Emergence and Spread

Empirical evidence from multiple sources show the Earth has been warming since the late 19th century. More recently, evidence for this warming trend is strongly supported by satellite data since the late 1970s from the cryosphere, atmosphere, oceans, and land that confirms increasing temperature trends and their consequences (e.g., reduced Arctic sea ice, rising sea level, ice sheet mass loss, etc.). At the same time, satellite observations of the Sun show remarkably stable solar cycles since the late 1970s, when direct observations of the Sun's total solar irradiance began. Numerical simulation models, driven in part by assimilated satellite data, suggest that future-warming trends will lead to not only a warmer planet, but also a wetter and drier climate depending upon location in a fashion consistent with large-scale atmospheric processes. Continued global warming poses new opportunities for the emergence and spread of fungal disease, as climate systems change at regional and global scales, and as animal and plant species move into new niches. Our contribution to this proceedings is organized thus: First, we review empirical evidence for a warming Earth. Second, we show the Sun is not responsible for the observed warming. Third, we review numerical simulation modeling results that project these trends into the future, describing the projected abiotic environment of our planet in the next 40 to 50 years. Fourth, we illustrate how Rift Valley fever outbreaks have been linked to climate, enabling a better understanding of the dynamics of these diseases, and how this has led to the development of an operational predictive outbreak model for this disease in Africa. Fifth, We project how this experience may be applicable to predicting outbreaks of fungal pathogens in a warming world. Lastly, we describe an example of changing species ranges due to climate change, resulting from recent warming in the Andes and associated glacier melt that has enabled amphibians to colonize higher elevation lakes, only to be followed shortly by the emergence of fungal disease in the new habitats.

Tucker, Compton J.↗

Zero to Integration in Eight Months, the Dawn Ground Data System Engineering Challange

The Dawn Project has presented the Ground Data System (GDS) with technical challenges driven by cost and schedule constraints commonly associated with National Aeronautics and Space Administration (NASA) Discovery Projects. The Dawn mission consists of a new and exciting Deep Space partnership among: the Jet Propulsion Laboratory (JPL), responsible for project management and flight operations; Orbital Sciences Corporation (OSC), spacecraft builder and responsible for flight system test and integration; and the University of California, at Los Angeles (UCLA), responsible for science planning and operations. As a cost-capped mission, one of Dawn s implementation strategies is to leverage from both flight and ground heritage. OSC's ground data system is used for flight system test and integration as part of the flight heritage strategy. Mission operations, however, are to be conducted with JPL s ground system. The system engineering challenge of dealing with two heterogeneous ground systems emerged immediately. During the first technical interchange meeting between the JPL s GDS Team and OSC's Flight Software Team, August 2003, the need to integrate the ground system with the flight software was brought to the table. This need was driven by the project s commitment to enable instrument engineering model integration in a spacecraft simulator environment, for both demonstration and risk mitigation purposes, by April 2004. This paper will describe the system engineering approach that was undertaken by JPL's GDS Team in order to meet the technical challenge within a non-negotiable eight-month schedule. Key to the success was adherence to an overall systems engineering process and fundamental systems engineering practices: decomposition of the project request into manageable requirements; definition of a structured yet flexible development process; integration of multiple ground disciplines and experts into a focused team effort; in-process risk management; and aggregation of the intermediate products to an integrated final product. In addition, this paper will highlight the role of lessons learned from the integration experience. The lessons learned from an early GDS deployment have served as the foundation for the design and implementation of the Dawn Ground Data System.

systems engineering↗

Zero to Integration in Eight Months, the Dawn Ground Data System Engineering Challenge

The Dawn Project has presented the Ground Data System (GDS) with technical challenges driven by cost and schedule constraints commonly associated with National Aeronautics and Space Administration (NASA) Discovery Projects. The Dawn mission consists of a new and exciting Deep Space partnership among: the Jet Propulsion Laboratory (JPL), manages the project and is responsible for flight operation; Orbital Sciences Corporation (OSC), is the spacecraft builder and is responsible for flight system test and integration; and the University of California, at Los Angeles (UCLA), is responsible for science planning and operations. As a cost-capped mission, one of Dawn's implementation strategies is to leverage from both flight and ground heritage. OSC's ground data system is used for flight system test and integration as part of the flight heritage strategy. Mission operations, however, are to be conducted with JPL's ground system. The system engineering challenge of dealing with two heterogeneous ground systems emerged immediately. During the first technical interchange meeting between the JPL's GDS Team and OSC's Flight Software Team, August 2003, the need to integrate the ground system with the flight software was brought to the table. This need was driven by the project's commitment to enable instrument engineering model integration in a spacecraft simulator environment, for both demonstration and risk mitigation purposes, by April 2004. This paper will describe the system engineering approach that was undertaken by JPL's GDS Team in order to meet the technical challenge within a non-negotiable eight-month schedule. Key to the success was adherence to fundamental systems engineering practices: decomposition of the project request into manageable requirements; integration of multiple ground disciplines and experts into a focused team effort; definition of a structured yet flexible development process; definition of an in-process risk reduction plan; and aggregation of the intermediate products to an integrated final product. In addition, this paper will highlight the role of lessons learned from the integration experience. The lessons learned from an early GDS deployment have served as the foundation for the design and implementation of the Dawn Ground Data System.

Ground Data System (GDS)↗

Comparison of the Seasonal Change in Cloud-Radiative Forcing from Atmospheric General Circulation Models and Satellite Observations

We compare seasonal changes in cloud-radiative forcing (CRF) at the top of the atmosphere from 18 atmospheric general circulation models, and observations from the Earth Radiation Budget Experiment (ERBE). To enhance the CRF signal and suppress interannual variability, we consider only zonal mean quantities for which the extreme months (January and July), as well as the northern and southern hemispheres, have been differenced. Since seasonal variations of the shortwave component of CRF are caused by seasonal changes in both cloudiness and solar irradiance, the latter was removed. In the ERBE data, seasonal changes in CRF are driven primarily by changes in cloud amount. The same conclusion applies to the models. The shortwave component of seasonal CRF is a measure of changes in cloud amount at all altitudes, while the longwave component is more a measure of upper level clouds. Thus important insights into seasonal cloud amount variations of the models have been obtained by comparing both components, as generated by the models, with the satellite data. For example, in 10 of the 18 models the seasonal oscillations of zonal cloud patterns extend too far poleward by one latitudinal grid.

Cess, R. D.↗

Assessment of Soil Moisture Data Requirements by the Potential SMAP Data User Community: Review of SMAP Mission User Community

NASA's Soil Moisture Active and Passive (SMAP) mission is planned for launch in October 2014 and will provide global measurements of soil moisture and freeze thaw state. The project is driven by both basic research and applied science goals. Understanding how application driven end-users will apply SMAP data, prior to the satellite's launch, is an important goal of NASA's applied science program and SMAP mission success. Because SMAP data are unique, there are no direct proxy data sets that can be used in research and operational studies to determine how the data will interact with existing processes. The objective of this study is to solicit data requirements, accuracy needs, and current understanding of the SMAP mission from the potential user community. This study showed that the data to be provided by the SMAP mission did substantially meet the user community needs. Although there was a broad distribution of requirements stated, the SMAP mission fit within these requirements.

applications↗

Near-wall similarity in the three-dimensional turbulent boundary layers. III - Shear-driven flow results

Ten of eleven proposed three-dimensional similarity models identified in the literature are evaluated with direct wall shear, velocity field, and pressure gradient data from a three-dimensional shear-driven boundary layer flow. Results define an upper limit on velocity vector skewing for each model's predictive ability. When combined with earlier results for pressure-driven flows, each model's predictive ability with and without pressure gradients is summarized. The utility of some two-dimensional type indirect wall shear measurement methods and wall shear inference methods from near-wall velocity measurements for three-dimensional flows is also discussed.

Pierce, F. J.↗

A Global Ozone Climatology from Ozone Soundings via Trajectory Mapping: A Stratospheric Perspective

This study explores a domain-filling trajectory approach to generate a global ozone climatology from sparse ozonesonde data. Global ozone soundings of 51,898 profiles at 116 stations over 44 years (1965-2008) are used, from which forward and backward trajectories are performed for 4 days, driven by a set of meteorological reanalysis data. Ozone mixing ratios of each sounding from the surface to 26 km altitude are assigned to the entire path along the trajectory. The resulting global ozone climatology is archived monthly for five decades from the 1960s to the 2000s with grids of 5 degree 5 degree 1 km (latitude, longitude, and altitude). It is also archived yearly from 1965 to 2008. This climatology is validated at 20 ozonesonde stations by comparing the actual ozone sounding profile with that found through the trajectories, using the ozone soundings at all the stations except one being tested. The two sets of profiles are in good agreement, both individually with correlation coefficients between 0.975 and 0.998 and root mean square (RMS) differences of 87 to 482 ppbv, and overall with a correlation coefficient of 0.991 and an RMS of 224 ppbv. The ozone climatology is also compared with two sets of satellite data, from the Satellite Aerosol and Gas Experiment (SAGE) and the Optical Spectrography and InfraRed Imager System (OSIRIS). Overall, the ozone climatology compares well with SAGE and OSIRIS data by both seasonal and zonal means. The mean difference is generally under 20 above 15 km. The comparison is better in the northern hemisphere, where there are more ozonesonde stations, than in the southern hemisphere; it is also better in the middle and high latitudes than in the tropics, where assimilated winds are imperfect in some regions. This ozone climatology can capture known features in the stratosphere, as well as seasonal and decadal variations of these features. Furthermore, it provides a wealth of detail about longitudinal variations in the stratosphere such as the spring ozone maximum over the Canadian Arctic. It also covers higher latitudes than current satellite data. The climatology shows clearly the depletion of ozone from the 1970s to the mid 1990s and ozone recovery in the 2000s. When this climatology is used as the upper boundary condition in an Environment Canada operational chemical forecast model, the forecast is improved in the vicinity of the upper tropospherelower stratosphere region. As this ozone climatology is neither dependent on a priori data or photochemical modeling, it provides independent information and insight that can supplement satellite data and model simulations and enhance our understanding of stratospheric ozone.

SAGE↗

Increasing Efficiency at the NTF by Optimizing Model AoA Positioning

The National Transonic Facility (NTF) at NASA Langley Research Center (LaRC) is a national resource for aeronautical research and development. The government, military and private industries rely on the capability of this facility for realistic flight data. Reducing the operation costs and keeping the NTF affordable is essential for aeronautics research. The NTF is undertaking an effort to reduce the time between data points during a pitch polar. This reduction is being driven by the operating costs of a cryogenic facility. If the time per data point can be reduced, a substantial cost savings can be realized from a reduction in liquid nitrogen (LN2) consumption. It is known that angle-of-attack (AoA) positioning is the longest lead-time item between points. In January 2005 a test was conducted at the NTF to determine the cause of the long lead-time so that an effort could be made to improve efficiency. The AoA signal at the NTF originates from onboard instrumentation then travels through a number of different systems including the signal conditioner, digital voltmeter, and the data system where the AoA angle is calculated. It is then fed into a closed loop control system that sets the model position. Each process along this path adds to the time per data point affecting the efficiency of the data taking process. Due to the nature of the closed loop feed back AoA control and the signal path, it takes approximately 18 seconds to take one pitch pause point with a typical AoA increment. Options are being investigated to reduce the time delay between points by modifying the signal path. These options include: reduced signal filtering, using analog channels instead of a digital volt meter (DVM), re-routing the signal directly to the AoA control computer and implementing new control algorithms. Each of these has potential to reduce the positioning time and together the savings could be significant. These timesaving efforts are essential but must be weighed against possible loss of data quality. For example, a reduction in filtering can introduce noise into the signal and using analog channels could result in some loss of accuracy. Data quality assessments need to be performed concurrently with timesaving techniques since data quality parameters are essential in maintaining facility integrity. This paper will highlight time saving efforts being undertaken or studied at the NTF. It will outline the instrumentation and computer systems involved in setting of the model pitch attitude then suggest changes to the process and discuss how these system changes would effect the time between data points. It also discusses the issue of data quality and how the potential efficiency changes in the system could affect it. Lastly, it will discuss the possibility of using an open loop control system and give some pros and cons of this method.

Crawford, Bradley L.↗

Viper Science Operations: Lunar Dynamic Science Table and ‘Tracker’ Tool.

Introduction: The NASA VIPER lunar rover mission [1] presents a unique operational paradigm within the history of robotic spaceflight. The proximity of the Moon to the Earth and the terrain elements (surface characteristics, light/shadow dynamics, communication links) of the Lunar South Polar landing site create unprecedented operational conditions between these two planetary bodies. Apollo era lunar science and exploration included humans in situ to operate instruments and assimilate observational inputs in real-time. Previous lunar orbital missions have worked to operational timescales, e.g., decisional timelines and communication exchanges, that were weeks in duration. Mars rover missions have worked to operational timescales, e.g., decisional timelines and communication exchanges between Mars and Earth, that were hours, days, and weeks in length. In the case of the VIPER mission, our operational decisioning for rover driving and instrument commanding will be compressed to minute-scale timeframes. These operational conditions will directly impact the workflow and speed with which the VIPER Science Team (VST) will be required to synthesize and analyze data and produce timely science-driven decisions throughout surface mission operations [2]. The VST in the VIPER Mission Science Center (MSC) and the Mission Operations Center (MOC) shall provide mission-enhancing scientific input to guide traverse planning and drill site confirmation/selection throughout surface operations. Further, the VST input will be of vital importance to the mission’s ability to maximize science return and to meet broader NASA objectives for future lunar ISRU and exploration activities. Specifically, the VST in the MSC and MOC will provide science-driven, consensus-based, timely input and decision-making to enhance mission operations and align mission science return with broader Agency goals. They will enable the characterization of the distribution (lateral and vertical extent, concentration, variability), form (chemical/physical state of these reservoirs of lunar water and key isotopes), and context (e.g., accessibility/overburden, environment, soil mechanics, trafficability, and temperatures) of lunar polar volatiles and water content for the VIPER mission. Additionally, the MSC will be selecting or reconfirming the location and path towards and from the third drill site (Drill Site Charlie) within each Science Station [6]. To enable scientific decision-making within the operational paradigm of the VIPER lunar rover mission requires detailed articulation of the VST’s scientific objectives and goals, and the operationalization of these objectives and goals through their association with specific data products, tasks, and decisional procedures. Further, defining and tracking scientific success metrics throughout surface operations will enable the VST to have a quantified understanding of the mission’s evolving ability to accomplish the stated scientific objectives and goals both during and after the mission. This abstract provides an overview of the methods and development activities towards defining, operationalizing, and tracking scientific objectives and goals throughout VIPER surface operations. Specifically, we focus on the VIPER Lunar Dynamic Science Table (LDST) and the VIPER “Tracker” tool.

Darlene Sze Shien Lim↗

The phytoplankton bloom in the northwestern Arabian Sea during the southwest monsoon of 1979

The present study investigates the biological variability of the northwestern Arabian Sea during the 1979 southwest monsoon by the synthesis of satellite ocean color remote sensing with an analysis of in situ hydrographic and meteorological data sets and the results of wind-driven modeling of upper-ocean circulation. The phytoplankton bloom peaked during August-September, extended from the Oman coast to about 65 deg E, and lagged behind the development of open-sea upwelling by at least 1 mo. The pigment distributions, hydrographic data, and model results all suggest that the boom was driven by spatially distinct upward nutrient fluxes to the euphotic zone forced by the physical processes of coastal upwelling and offshore Ekman pumping. Coastal upwelling was evident from May through September, yielded the most extreme concentrations of phytoplankton biomass, and, along the Arabian coast, was limited to the continental shelf in the promotion of high concentrations of phytoplankton.

Brock, John C.↗

Real-Time Science Decisioning During High Tempo-High Intensity Mission Operations and the Role of Analogs

Introduction: NASA’s VIPER mission presents a unique operational paradigm within the history of robotic spaceflight. The proximity of the Moon to the Earth and the terrain elements (surface characteristics, light/shadow dynamics, communication links) of the lunar South Polar landing site create unprecedented operational conditions between these two planetary bodies. Apollo era lunar science and exploration included humans in situ to operate instruments and assimilate observational inputs in real-time. Previous lunar orbital missions have worked to operational timescales, e.g., decisional timelines and communication exchanges, that were weeks in length. Mars rover missions have worked to operational timescales, e.g., decisional timelines and communication exchanges between Mars and Earth, that were hours, days, and weeks in length. In the case of the VIPER mission, our operational decisioning for rover driving and instrument commanding will be compressed to minute-scale timeframes. These operational conditions directly impact the manner and speed with which the VIPER Science Team (VST) is required to synthesize and analyze data and produce timely science-driven decisions throughout surface mission operations. The VST shall provide mission enhancing scientific input to guide rover traverse planning and drill site confirmation and selection throughout surface operations. Further, the VST input will be of vital importance to the mission’s ability to maximize science return and to meet broader NASA objectives for future lunar in-situ resource utilization (ISRU)and exploration activities. The VST co-located in the Mission Science Center (MSC) will be responsive to the tactical operational cadence of the Mission Operations Center (MOC) and will provide further strategic and Long-Term Planning (LTP) guidance to the mission. The VIPER Science Operations & Integration(SO&I)team has developed an architecture that is focused on the infusion of science-decisioning into the operational framework and execution cadence of VIPER. NASA analog research has played a significant role in the construction of the VIPER science operations systems. As an example, the SO&I team has led analog missions that have focused on bringing together expertise in the sciences (natural, applied and social) and in operations in service of learning how to build and hold together interdisciplinary work environments and what tools are needed to support high tempo, high intensity integrated decisioning. These experiences have provided an essential foundation of knowledge to the VIPER team. Those analogs that specifically influenced the VIPER science operations construct were identified through a process of comparative analysis to prioritize those that offered relevance in whole or in part, and those that did not. The analog research output that provided extensibility to the VIPER science operations architecture included remote teams of humans and robots in cooperation (synchronous and asynchronous) with simulated earthbound systems, engineering and science teams, and the integrated assembly of tools that supported scientific analysis and data synthesis and provided infrastructure for the remote testing framework. Analogs which included real-time data monitoring, synthesis, visualization and access in a democratized and operationalized manner were of particular interest to the development of the VIPER MSC toolset both in terms of the technology and the processes used to develop the supporting infrastructure. We anticipate that each subsequent mission to the lunar south pole, whether with robots or humans, will be able to optimize science and exploration return by evolving strategies to infuse real-time collaborative science-decisioning. Furthermore, these efforts will result in a foundation for science operations development in support of human-robotic exploration of deep space and Mars. NASA analogs can continue to provide the opportunity to prepare, test and iterate on the operational concepts and tools that will support these ever-expanding space exploration efforts. Our presentation will include an overview of the VIPER Science Operations & Integration development process and specifics on what aspects of analog research have had a significant impact on our work systems.

D S S Lim↗

DIOGENES: Expert system for extraction of data system requirements

AA The initial operations concept expresses information about system objectives, and defines the system users, system interfaces, and operational performance constraints. We have developed a prototype expert system which has established the feasibility of automating a scenario-driven methodology for deriving top-level specifications and preliminary designs for user data systems. This scenario-driven methodology uses an initial design, an initial operations concept, and user scenarios as the starting point for system definition. The top-level initial design is a functional description of the system in the form of an annotated data flow diagram. The initial operations concept expresses informationabout system objectives, and defines the system users, system interfaces, and operational performance constraints. The user scenarios are detailed time-lined descriptions of user activities, developed by prospective end users. These scenarios, along with the initial design and operations concept, are analyzed and iterated by the expert system to form a consistent set. The resulting User Scenario-Operation Set plays a key role in the development of requirements and system tests.

Hobbs, Robert W.↗

Free vibration and dynamic response analysis of spinning structures

The proposed effort involved development of numerical procedures for efficient solution of free vibration problems of spinning structures. An eigenproblem solution procedure, based on a Lanczos method employing complex arithmetic, was successfully developed. This task involved formulation of the numerical procedure, FORTRAN coding of the algorithm, checking and debugging of software, and implementation of the routine in the STARS program. A graphics package for the E/S PS 300 as well as for the Tektronix terminals was successfully generated and consists of the following special capabilities: (1) a dynamic response plot for the stresses and displacements as functions of time; and (2) a menu driven command module enabling input of data on an interactive basis. Finally, the STARS analysis capability was further improved by implementing the dynamic response analysis package that provides information on nodal deformations and element stresses as a function of time. A number of test cases were run utilizing the currently developed algorithm implemented in the STARS program and such results indicate that the newly generated solution technique is significantly more efficient than other existing similar procedures.

Source record↗

Improved canopy reflectance modeling and scene inference through improved understanding of scene pattern

The Li-Strahler reflectance model, driven by LANDSAT Thematic Mapper (TM) data, provided regional estimates of tree size and density within 20 percent of sampled values in two bioclimatic zones in West Africa. This model exploits tree geometry in an inversion technique to predict average tree size and density from reflectance data using a few simple parameters measured in the field (spatial pattern, shape, and size distribution of trees) and in the imagery (spectral signatures of scene components). Trees are treated as simply shaped objects, and multispectral reflectance of a pixel is assumed to be related only to the proportions of tree crown, shadow, and understory in the pixel. These, in turn, are a direct function of the number and size of trees, the solar illumination angle, and the spectral signatures of crown, shadow and understory. Given the variance in reflectance from pixel to pixel within a homogeneous area of woodland, caused by the variation in the number and size of trees, the model can be inverted to give estimates of average tree size and density. Because the inversion is sensitive to correct determination of component signatures, predictions are not accurate for small areas.

Franklin, Janet↗

Canopy reflectance modeling in a tropical wooded grassland

The Li-Strahler canopy reflectance model, driven by LANDSAT Thematic Mapper (TM) data, provided regional estimates of tree size and density in two bioclimatic zones in Africa. This model exploits tree geometry in an inversion technique to predict average tree size and density from reflectance data using a few simple patameters measured in the field and in the imagery. Reflectance properties of the trees were measured in the study sites using a pole-mounted radiometer. The measurements showed that the assumptions of the simple Li-Strahler model are reasonable for these woodlands. The field radiometer measurements were used to calculate the normalized difference vegetation index (NDVI), and the integrated NDVI over the canopy was related to crown volume. Predictions of tree size and density from the canopy model were used with allometric equations from the literature to estimate woody biomass and potential foliar biomass for the sites and for the regions. Estimates were compared with independent measurements made in the Sahelian sites, and to typical values from the literature for these regions and for similar woodlands. In order to apply the inversion procedure regionally, an area must first be stratified into woodland cover classes, and dry-season TM data were used to generate a stratum map of the study areas with reasonable accuracy. The method used was unsupervised classification of multi-data principal components images.

Simonett, David↗