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At least 1,153 records · Page 64

The Goldstone Solar System Radar: 1988-2003 Earth-based Mars Radar Observations

The Goldstone Solar System Radar (GSSR) has successfully collected radar echo data from Mars over the past 30 years. The older data provided local elevation information for Mars, along with radar scattering information with global resolution. Since the upgrade to the 70-m DSN antenna at Goldstone completed in 1986, Mars data has been collected during all but the 1997 Mars opposition. Radar data, and non-imaging delay- Doppler data in particular, requires significant data processing to extract elevation, reflectivity and roughness of the reflecting surface. The spatial resolution of these experiments is typically some 10 km in longitude by some 150 km in latitude. The interpretation of these parameters while limited by the complexities of electromagnetic scattering, do provide information directly relevant to geophysical and geomorphic analyses of Mars.

Haldemann, A. F. C.↗

Comparing Goldstone Solar System Radar Earth-based Observations of Mars with Orbital Datasets

The Goldstone Solar System Radar (GSSR) has collected a self-consistent set of delay-Doppler near-nadir radar echo data from Mars since 1988. Prior to the Mars Global Surveyor (MGS) Mars Orbiter Laser Altimeter (MOLA) global topography for Mars, these radar data provided local elevation information, along with radar scattering information with global coverage. Two kinds of GSSR Mars delay-Doppler data exist: low 5 km x 150 km resolution and, more recently, high (5 to 10 km) spatial resolution. Radar data, and non-imaging delay-Doppler data in particular, requires significant data processing to extract elevation, reflectivity and roughness of the reflecting surface. Interpretation of these parameters, while limited by the complexities of electromagnetic scattering, provide information directly relevant to geophysical and geomorphic analyses of Mars. In this presentation we want to demonstrate how to compare GSSR delay-Doppler data to other Mars datasets, including some idiosyncracies of the radar data. Additional information is included in the original extended abstract.

Haldemann, A. F. C.↗

Evolving the Technical Infrastructure of the Planetary Data System for the 21st Century

The Planetary Data System (PDS) was established in 1989 as a distributed system to assure scientific oversight. Initially the PDS followed guidelines recommended by the National Academies Committee on Data Management and Computation (CODMAC, 1982) and placed emphasis on archiving validated datasets. But overtime user demands, supported by increased computing capabilities and communication methods, have placed increasing demands on the PDS. The PDS must add additional services to better enable scientific analysis within distributed environments and to ensure that those services integrate with existing systems and data. To face these challenges the Planetary Data System (PDS) must modernize its architecture and technical implementation. The PDS 2010 project addresses these challenges. As part of this project, the PDS has three fundamental project goals that include: (1) Providing more efficient client delivery of data by data providers to the PDS (2) Enabling a stable, long-term usable planetary science data archive (3) Enabling services for the data consumer to find, access and use the data they require in contemporary data formats. In order to achieve these goals, the PDS 2010 project is upgrading both the technical infrastructure and the data standards to support increased efficiency in data delivery as well as usability of the PDS. Efforts are underway to interface with missions as early as possible and to streamline the preparation and delivery of data to the PDS. Likewise, the PDS is working to define and plan for data services that will help researchers to perform analysis in cost-constrained environments. This presentation will cover the PDS 2010 project including the goals, data standards and technical implementation plans that are underway within the Planetary Data System. It will discuss the plans for moving from the current system, version PDS 3, to version PDS 4.

Beebe, Reta F.↗

Onboard Science and Applications Algorithm for Hyperspectral Data Reduction

An onboard processing mission concept is under development for a possible Direct Broadcast capability for the HyspIRI mission, a Hyperspectral remote sensing mission under consideration for launch in the next decade. The concept would intelligently spectrally and spatially subsample the data as well as generate science products onboard to enable return of key rapid response science and applications information despite limited downlink bandwidth. This rapid data delivery concept focuses on wildfires and volcanoes as primary applications, but also has applications to vegetation, coastal flooding, dust, and snow/ice applications. Operationally, the HyspIRI team would define a set of spatial regions of interest where specific algorithms would be executed. For example, known coastal areas would have certain products or bands downlinked, ocean areas might have other bands downlinked, and during fire seasons other areas would be processed for active fire detections. Ground operations would automatically generate the mission plans specifying the highest priority tasks executable within onboard computation, setup, and data downlink constraints. The spectral bands of the TIR (thermal infrared) instrument can accurately detect the thermal signature of fires and send down alerts, as well as the thermal and VSWIR (visible to short-wave infrared) data corresponding to the active fires. Active volcanism also produces a distinctive thermal signature that can be detected onboard to enable spatial subsampling. Onboard algorithms and ground-based algorithms suitable for onboard deployment are mature. On HyspIRI, the algorithm would perform a table-driven temperature inversion from several spectral TIR bands, and then trigger downlink of the entire spectrum for each of the hot pixels identified. Ocean and coastal applications include sea surface temperature (using a small spectral subset of TIR data, but requiring considerable ancillary data), and ocean color applications to track biological activity such as harmful algal blooms. Measuring surface water extent to track flooding is another rapid response product leveraging VSWIR spectral information.

Chien, Steve A.↗

Accurate Assessment of Land-Atmosphere Coupling in Climate Models Requires High Frequency Data Output

Land-atmosphere (L-A) interactions are important for understanding convective processes, climate feedbacks, the development and perpetuation of droughts, heatwaves, pluvials, and other land-centred climate anomalies. Local L-A coupling (LoCo) metrics capture relevant L-A processes, highlighting the impact of soil and vegetation states on surface flux partitioning, and the impact of surface fluxes on boundary layer (BL) growth, development, and entrainment of air above the BL. A primary goal of the Climate Process Team on Coupling Land and Atmospheric Subgrid Parameterizations (CLASP) is parameterizing and characterizing the impact of subgrid heterogeneity in global and regional earth system models (ESMs) to improve the connection between land and atmospheric states and processes. A critical step in achieving that aim is the incorporation of L-A metrics, especially LoCo metrics, into climate model diagnostic process streams. However, because land-atmosphere interactions span time scales of minutes (e.g., turbulent fluxes), hours (e.g., BL growth and decay), days (e.g., soil moisture memory), and seasons (e.g., variability of behavioural regimes between soil moisture and latent heat flux), with multiple processes of interest happening in different geographic regions at different times of year, there is not a single metric that captures all the modes, means, and methods of interaction between the land and the atmosphere. And while monthly means of most of the LoCo-relevant variables are routinely saved from ESM simulations, data storage constraints typically preclude routine archival of the hourly data that would enable the calculation of all LoCo metrics. Here we outline a reasonable data request that would allow for adequate characterization of sub-daily coupling processes between the land and the atmosphere, preserving enough sub-daily output to describe, analyse, and better understand L-A coupling in modern climate models. A secondary request involves embedding calculations within the models to determine mean properties in and above the BL to further improve characterization of model behaviour. Higher-frequency model output will (i) allow for more direct comparison with observational field campaigns on process-relevant time scales, (ii) enable demonstration of inter-model spread in L-A coupling processes, and (iii) aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.

Kirsten L. Findell↗

A Koopman-based residual modeling approach for the control of a soft robot arm

Soft robots are challenging to model and control due to their poorly defined kinematics and nonlinear dynamics. Recently, Koopman operator theory has been shown capable of constructing control-oriented soft robot models from data. However, building these models requires extensive data collection and they do not necessarily generalize well outside of the training observations. This paper presents a more data-efficient and generalizable approach to soft robot modeling that first identifies a physics-based Koopman model then supplements it with a data-driven residual Koopman model. The resulting combined model is linear and thus compatible with real-time model-based control techniques such as Model Predictive Control (MPC). The efficacy of the approach is demonstrated on several simulated systems and on a real soft robot arm, where it is shown to generate models that are more accurate than purely physics-based models and require less data to construct than purely data-driven models. Using a model-based controller, the soft arm is able to successfully track end effector trajectories, perform a pick-and-place task, and write on a dry-erase board, showcasing the applicability of this framework to increase the capabilities of soft robotic systems.

Daniel Bruder↗

A conceptual design for an integrated data base management system for remote sensing data

The requirements of potential users were considered in the design of an integrated data base management system, developed to be independent of any specific computer or operating system, and to be used to support investigations in weather and climate. Ultimately, the system would expand to include data from the agriculture, hydrology, and related Earth resources disciplines. An overview of the system and its capabilities is presented. Aspects discussed cover the proposed interactive command language; the application program command language; storage and tabular data maintained by the regional data base management system; the handling of data files and the use of system standard formats; various control structures required to support the internal architecture of the system; and the actual system architecture with the various modules needed to implement the system. The concepts on which the relational data model is based; data integrity, consistency, and quality; and provisions for supporting concurrent access to data within the system are covered in the appendices.

Maresca, P. A.↗

Microgravity and Materials Processing Facility study (MMPF): Requirements and Analyses of Commercial Operations (RACO) preliminary data release

This requirements and analyses of commercial operations (RACO) study data release reflects the current status of research activities of the Microgravity and Materials Processing Facility under Modification No. 21 to NASA/MSFC Contract NAS8-36122. Section 1 includes 65 commercial space processing projects suitable for deployment aboard the Space Station. Section 2 contains reports of the R:BASE (TM) electronic data base being used in the study, synopses of the experiments, and a summary of data on the experimental facilities. Section 3 is a discussion of video and data compression techniques used as well as a mission timeline analysis.

Source record↗

Lunar Plant Experiment: Testing Plant Germination in Lunar Gravity and Ionizing Radiation

We present an open design for a first plant growth module on the Moon (LPX). The primary science goal of lunar habitat is to investigate germination and initial plant growth when subject to the combined effects of lunar gravity and lunar surface radiation. The LPX module has been designed to be a flexible base unit that can be adapted to fly to the lunar surface on a variety of landers and rovers. LPX has size and shape of a 1 Unit CubeSat (10 centimeters on a side) and a total mass of 0.3 kilograms. The base will contain a seed module holding around 50 Arabidopsis seeds and provide approximately 0.5 liters of normal air at standard pressure. By the action of a small pump, water will be released after landing to initiate germination. Images will document the germination, initial growth, phototropism, and circumnutation of the small plants while sunlight remains available. A CO2 sensor tracks the release of CO2 during germination and the subsequent uptake of CO2 by photosynthesis. Simulations indicate that the CO2 peak level will be an increase by 2250 parts per million after 2 earth-days and then decline to about 1000 parts per million after 7 earth-days. The camera and CO2 sensor interfaces are USB. The water pump initiation requires a 5-volt signal. After initiation of germination by the addition of water, the habitat must be maintained above 22 degrees Centigrade to allow for plant growth and below 27 degrees Centigrade to prevent damage to the plants. This relatively tight temperature tolerance will require thermal control systems using reflecting surfaces and insulation that must be specifically designed for each lander or rover. The plant growth unit will function to tilt angles of 20 degrees along any axis. Total image data volume required to gauge the plant growth rate and leaf area is 1 megabyte (minimum data required) to 40 megabytes (preferred data). The lid of the habitat will allow adequate sunlight for plant growth. To provide for optimum growth, light levels in the plant growth stage need to be between 75 and 150 micromoles per meter squared per second interval.

first plant growth↗

Detailed design specification for the ALT Shuttle Information Extraction Subsystem (SIES)

The approach and landing test (ALT) shuttle information extraction system (SIES) is described in terms of general requirements and system characteristics output products and processing options, output products and data sources, and system data flow. The ALT SIES is a data reduction system designed to satisfy certain data processing requirements for the ALT phase of the space shuttle program. The specific ALT SIES data processing requirements are stated in the data reduction complex approach and landing test data processing requirements. In general, ALT SIES must produce time correlated data products as a result of standardized data reduction or special purpose analytical processes. The main characteristics of ALT SIES are: (1) the system operates in a batch (non-interactive) mode; (2) the processing is table driven; (3) it is data base oriented; (4) it has simple operating procedures; and (5) it requires a minimum of run time information.

Clouette, G. L.↗

Earth radiation budget experiment and smart sensors

This paper presents the data analysis requirements for the Earth Radiation Budget Experiment and potential needs for a follow-on radiation budget system. The present requirements for determining the earth's radiation budget on scales from 250 by 250-km regions to global require two broadband measurements on each of three satellites. The instrument system is composed of wide- and medium-field-of-view radiometers and a narrow-field-of-view scanning radiometer. Modeled directional functions are required to interpret the data in terms of earth radiation fluxes. Meeting more stringent science requirements for a follow-on mission will require nine broadband channels with increased spatial and temporal sampling, resulting in six satellites and a fourfold increase in data transmission rates and ground-based data storage. Smart sensors can reduce the data and ground storage requirements by orders of magnitude with onboard processing, calibration, and attitude and ephemeris determination.

Young, G. R.↗

MODIS information, data and control system (MIDACS) level 2 functional requirements

The MODIS Information, Data and Control System (MIDACS) Level 2 Functional Requirements Document establishes the functional requirements for MIDACS and provides a basis for the mutual understanding between the users and the designers of the EosDIS, including the requirements, operating environment, external interfaces, and development plan. In defining the requirements and scope of the system, this document describes how MIDACS will operate as an element of the EOS within the EosDIS environment. This version of the Level 2 Requirements Document follows an earlier release of a preliminary draft version. The sections on functional and performance requirements do not yet fully represent the requirements of the data system needed to achieve the scientific objectives of the MODIS instruments and science teams. Indeed, the team members have not yet been selected and the team has not yet been formed; however, it has been possible to identify many relevant requirements based on the present concept of EosDIS and through interviews and meetings with key members of the scientific community. These requirements have been grouped by functional component of the data system, and by function within each component. These requirements have been merged with the complete set of Level 1 and Level 2 context diagrams, data flow diagrams, and data dictionary.

Han, D.↗

A Note on Interfacing Object Warehouses and Mass Storage Systems for Data Mining Applications

Data mining is the automatic discovery of patterns, associations, and anomalies in data sets. Data mining requires numerically and statistically intensive queries. Our assumption is that data mining requires a specialized data management infrastructure to support the aforementioned intensive queries, but because of the sizes of data involved, this infrastructure is layered over a hierarchical storage system. In this paper, we discuss the architecture of a system which is layered for modularity, but exploits specialized lightweight services to maintain efficiency. Rather than use a full functioned database for example, we use light weight object services specialized for data mining. We propose using information repositories between layers so that components on either side of the layer can access information in the repositories to assist in making decisions about data layout, the caching and migration of data, the scheduling of queries, and related matters.

Grossman, Robert L.↗

The rationale for an aeroassist flight experiment

The states of several technologies are reviewed which are critical to the design of an aeroassisted orbital transfer vehicle. In these technologies, advancements are needed which hinge on obtaining new flight data. While some of the work can be done with the wind tunnel and computational disciplines, much of the required new data are tied to finite chemical reaction rates, possible thermal nonequilibrium, high flow enthalpy, and strong viscous effects. Because these effects cannot be modeled adequately in ground-based facilities, computational methods lack adequate verification to allow committing to the design of an aeroassist vehicle. Thus a new flight experiment is being planned by NASA to gather the required data. The flight experiment and associated instrumentation which NASA is proposing is discussed briefly.

Jones, Jim J.↗

Digital Image Correlation Data Processing and Analysis Techniques to Enhance Test Data Assessment and Improve Structural Simulations

The NASA Shell Buckling Knockdown Factor Project (SBKF) was established in 2007 by the NASA Engineering and Safety Center (NESC) with the primary goal to develop new analysis-based buckling design factors (a.k.a. knockdown factors) and high-fidelity buckling simulations for selected launch-vehicle-like cylindrical shell structures. A series of tests are being conducted on large-scale metallic and composite cylindrical shells in order to provide validation data for these new factors and simulations. However, the validation of these new factors and simulations is quite demanding and requires test data that is commensurate with their fidelity. Traditional instrumentation, such as linear variable displacement transducers (LVDTs) and electrical-resistance strain gages serve a critical role in providing accurate displacement and strain measurements in these tests, but only allow for data to be recorded at a select number of point locations and are not sufficient to provide all the necessary validation data. Advanced measurement technologies can be used effectively to complement traditional instrumentation and gather additional data required to validate these structural simulations. In particular, three-dimensional digital image correlation (DIC) was implemented during SBKF cylinder testing to characterize the full-field displacement and strain behavior. Commercially available VIC-3DTM software and user-written data processing scripts were used to generate valuable data and insight into the complex buckling response of the cylinders that otherwise would be impossible to gather using traditional instrumentation. In addition, the measured data from DIC was used to verify measured test data obtained from other instrumentation, enhance test and analysis correlation, and help identify the root cause of anomalous test results that may have gone unexplained if only traditional instrumentation was used. Selected test results that demonstrate the use of DIC on the SBKF cylinders are presented and a portion of the data processing methods are described.

Gardner, Nathaniel W.↗