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Ensemble

Ensemble tools for different missions share a common look and feel, easing the transition of personnel between projects. NASA’s Jet Propulsion Laboratory, Pasadena, California Success in mission operations relies on achieving consensus amongst a wide variety of personnel with diverse backgrounds and education. Previously, NASA missions relied on disparate tools with a variety of inconsistent interfaces. These tools greatly influence how members of the mission communicate with each other, increasing confusion and reducing consensus. Ensemble provides a shared interface that helps scientists and engineers of differing disciplines to collaborate effectively. Within a single tool, Ensemble allows scientists and engineers to efficiently discuss objectives and understand the tradeoffs between exploration and discovery.

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Mars Science Laboratory Frame Manager

NASA’s Jet Propulsion Laboratory, Pasadena, California One of the highly desired enhancements to the Mars Exploration Rover (MER) and Phoenix flight missions was the centralized coordinate transform database maintained onboard. Without the database, there are quite a few operations that require cumbersome, error-prone manual calculations on the ground such as pointing a mast camera to an arm tool and driving the rover to the goal defined in a previous site. The Mars Science Laboratory (MSL) Frame Manager flight software implements a centralized frame tree database, which eliminates these cumbersome, error-prone calculations of coordinate entries for commands.

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SIVO-PyD: A Python Distribution for Scientific Computing Visualization

Goddard Space Flight Center, Greenbelt, Maryland SIVO-PyD gathers and automatically installs (in various computing platforms) a collection of Python-related packages for scientific computing and visualization. All of the packages in distribution are accessible within the Python framework. The distribution is self-contained and can be extended with minimal work.

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iPhone App to Facilitate Airborne Radar Operations

NASA’s Jet Propulsion Laboratory, Pasadena, California The Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) is an Earth imaging radar that flies on a Gulf-Stream Jet. Its mission is to collect data for NASA scientists who are using Synthetic Aperture Radar to develop methods for monitoring changes in the Earth’s surface. As with many other technologies, there is always the possibility of technological or human errors. Since smartphones are mobile, common, and powerful devices, they can be used to reduce the possibility of operator error when the radar is being configured for flight.

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Spherical Empirical Mode Decomposition

Goddard Space Flight Center, Greenbelt, Maryland The spherical empirical mode decomposition algorithm is an adaptation in the spherical space of the 2D empirical mode decomposition in Euclidian space. This algorithm is a signal analysis method for any spherical data, such as orbital measurements. The two primary advantages of this innovation are the absence of edge effects in the results, and the computational efficiency of the processing.

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Database Design for Storing Software Entity Metadata, User Identification, and License Terms

NASA’s Jet Propulsion Laboratory, Pasadena, California The NASA Space Telecommunications Radio System (STRS) specification cites a plan for an application repository, similar to an “app store,” but with a wide variety of licensing restrictions on access to different applications, and even different parts of an application package (for instance, wide access to descriptive documentation but limited access to source code). A method is needed to coordinate application artifact storage, license terms, and user access rights.

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Geometry Manipulation Protocol for CFD Applications, V1.0

Ames Research Center, Moffett Field, California Geometry Manipulation Protocol (GMP) is a library that serializes data types between XML and ANSI C data structures to support computational fluid dynamics (CFD) applications. This library currently provides a description of geometric configurations, general moving-body scenarios (prescribed and/or 6-DOF), and control surface settings. The interface consists of a general set of datatypes, along with rules for their interaction, and is designed to be flexible in order to evolve as future needs dictate. The specification is currently implemented with an XML file format, which is portable across platforms and applications. The motion specification is capable of describing general rigid body motions, and eliminates the need to write and compile new code within the application software for each dynamic configuration, allowing client software to automate dynamic simulations.

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