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Program to Categorize and Count Observations Performed by the Mars Reconnaissance Orbiter

NASA’s Jet Propulsion Laboratory, Pasadena, California CreateMEPReport.pl software is designed to read through a description of observations scheduled to be taken by the instruments onboard the Mars Reconnaissance Orbiter (MRO) spacecraft to categorize the observations, and then present totals for the categories by instrument. Previously, this function was done in a spreadsheet, but this was prone to error and was extremely complicated.

Posted in: Briefs

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Anomaly Detection in Large Sets of High-Dimensional Symbol Sequences (sequenceMiner)

Ames Research Center, Moffett Field, California SequenceMiner was developed to address the problem of detecting and describing anomalies in large sets of high-dimensional symbol sequences. sequenceMiner works by performing unsupervised clustering (grouping) of sequences using the normalized longest common subsequence (LCS) as a similarity measure, followed by a detailed analysis of outliers to detect anomalies. sequenceMiner utilizes a new hybrid algorithm for computing the LCS that has been shown to outperform existing algorithms by a factor of five. sequenceMiner also includes new algorithms for outlier analysis that provide comprehensible indicators as to why a particular sequence was deemed to be an outlier. This provides analysts with a coherent description of the anomalies identified in the sequence, and why they differ from more normal sequences.

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Time-Scaled Activity Diagram Simulator

NASA’s Jet Propulsion Laboratory, Pasadena, California The Time-Scaled Activity Diagram Simulator software simulates and animates time-tagged events as an overlay on activity and internal block diagrams in MagicDraw as a plugin application. “Events” are quite generic and include atomic actions, compound actions, signal and message exchanges, invocations, and more. Events are specified in a schedule in a text file, which is ingested by the plug-in application. Concurrent and synchronized execution specified in the event schedule is illustrated within and across diagrams. Events correspond to nodes and edges of hierarchical activity models and corresponding structural decomposition. This software can be used to visually communicate the execution and timeline of any collection of scheduled events, including business, software, and spacecraft processes and procedures, and is applicable to most if not all missions.

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General-Use Nodal Network Solver (GUNNS)

GUNNS is a flow system modeling software package that combines nodal analysis and the hydraulic-electric analogy to simulate fluid, electrical, and thermal systems. Lyndon B. Johnson Space Center, Houston, Texas Crewed space vehicle training has always required highfidelity models of vehicle systems. Many of these systems, particularly of the “flow” variety, benefit from modeling the system as a whole, rather than relying only on the interactions between individual components. In general, system properties (temperatures, voltages, flow rates, etc.) are modeled both internal to and between physical components (valves, batteries, etc.). Lacking knowledge of the system atlarge, integration of flows between individual components is extremely difficult without incurring model instability and errors. The same analogous problem applies among fluid, thermal, and electrical systems. Nodal analysis is a method commonly used in industry to avoid this problem by representing these systems as a simultaneous system of equations.

Posted in: Briefs, TSP

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Modularized SIR-to-NetCDF Conversion Command-Line Tool

NASA’s Jet Propulsion Laboratory, Pasadena, California This innovation reads in a proprietary formatted binary data format known as Scatterometer Image Reconstruction (SIR), and converts these data files to netCDF-classic format. This software is provided as a command-line tool for Linux/UNIX-based systems, and includes built-in regression testing and command line options. The software is configured to output the netCDF files using a metadata conformance to Attribute Convention for Dataset Discovery (ACDD) and Climate and Forecasting (CF) version 1.6. This software is initially tested and designed for SIR files created for datasets originating from QuikSCAT and SeaWinds on ADEOS-II.

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Discovery Through Eigenbasis Modeling of Uninteresting Data

The system learns only what to ignore, reducing the possibility of missing the items of interest. NASA’s Jet Propulsion Laboratory, Pasadena, California When presented with a new data set, a common initial goal is to explore its contents in a discovery mode to find items of interest. However, each user who views the data set may have a different scientific goal in mind, and therefore a different desired prioritization of the items for examination. Further, as the users explore more of the data set, they accumulate concrete examples of what is or is not of interest. The goal of this work was to formalize this iterative approach to understanding large data sets, and instantiate it with methods capable of the necessary adaptation as the system iteratively acquires user feedback.

Posted in: Briefs, TSP

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Obstacle Avoidance Methods

NASA’s Jet Propulsion Laboratory, Pasadena, California Obstacle avoidance is a difficult problem due to the non-convex state constraints. Therefore, the feasible state space needs to be convexified, or split, into convex regions at which point the search for an optimal solution among those convex regions is done. Methods for obstacle avoidance include two mixed integer linear programming (MILP) methods (obstacle related method and path-related method) and a state-constraint convexification method.

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