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At least 1,657 records · Page 92

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NASA NTRSDate not supplied

Enabling a Voice Management System for Space Applications

The sustainable missions beyond Low Earth Orbit (LEO) envisioned for NASA’s Artemis program will require autonomous capabilities. Moreover, Artemis mission crews will need a means to efficiently interact with a spacecraft’s autonomous systems. This interaction can be facilitated by voice and speech communications because voice-based controls enable users to interact hands- and eyes-free, allowing the user to better focus on critical tasks. The goal of our project was to explore the knowledge and technology needed to successfully design effective Voice User Interfaces (VUIs) for autonomous systems utilizing Human Centered Design (HCD) principles. The focus of the human factors’ aspect of engineering, pays close attention to psychological and physiological principles in the development of autonomous crew operation systems. A main objective was to understand how a crew member, through voice interaction, could efficiently and intuitively communicate with a notional autonomous vehicle system manager. This project was a part of the NASA Moon to Mars eXploration Systems and Habitation (M2M X-Hab) 2020 Academic Innovation Challenge. The work from the BLiSS Team, at the University of Michigan, resulted in the design of a system persona, Diego, to which an astronaut may quickly build trust with autonomous systems, to alleviate known stressors on mental health expected during long duration space missions. Optimal software to facilitate integration of the system persona into a reference Lunar orbiting Gateway station was defined. Additionally, a Speech to Text (STT) system and a Graphical User Interface (GUI) that could be implemented in future missions was developed on an Internet of Things (IOT) platform. The Voice User Interface (VUI) design for the M2M X-Hab 2020 project leveraged previous technology developed by the BLiSS team to incorporate a voice-based interface into NASA’s Platform for Autonomous Systems (NPAS) software. This required technologies to convert voice to text, conduct semantic interpretations, and convert responses from the autonomous system to text and to speech; additionally, the spacecraft background noise environment was assessed, a noise mitigation technique was developed, and a relatable personality for the autonomous system was developed in order to facilitate human-like conversations. The success of our effort was largely due to the diversity of the team that included expertise in Space Systems Engineering, Human Computer Interaction, Aerospace Engineering, Computer Science, Biomedical Engineering, and Applied Physics. The diverse perspectives fostered elaborate discussions, resulting in the conception of three main subsystems: (1) User-System, (2) NPAS-System, and (3) Environment-System. The VUI was unique and had to be efficient and intuitive. For this project, 5 subteams were formed, each with a separate objective, Voice Design team, Background Noise Mitigation team, Software Integration team and Graphical User Interface team. The BLiSS team crafted a personality for the VUI to enable human-like conversation and drive user adoption and trust. User surveys were completed and used to help determine the required VUI system personality traits by capturing perspectives and expectations of prospective “Artemis Generation Astronauts”. To further simulate human-like conversations, the system had to be able to quickly interpret user speech and be able to integrate with NASA’s NPAS platform for quick and reliable information transfer. The outcomes of our research were: (1) a working prototype user interface, that is compatible with NASA’s NPAS platform; (2) software that demonstrates the ability of the VUI system to interpret user requests and respond appropriately; (3) the capability to implement fully expanded conversations between user and system using intuitive communication in four request categories; and (4) software and hardware recommendations that optimize the system’s ability to operate in a noisy environment. Our research has laid the foundation for the development of VUI’s for autonomy, and provides a baseline for future VUI developments.

Voice user interface↗

NASA NTRSDate not supplied

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↗

NASA NTRS2022

A Systems Model for System-Wide Safety Safety Demonstrator (SD-1): Wildfire Response Operations

The aim of this internship-based project was to contribute to the ongoing development of a systems model for System-Wide Safety’s first Technical Challenge 5 (TC5) series Safety Demonstrator (SD-1), which will be a demonstration of an In-Time Aviation Safety Management System (IASMS) in emerging wildfire response operations. Using Models-Based Systems Engineering (MBSE) principles to develop the model, I organized and traced previously collected stakeholder needs from the Spring 2022 NASA System-Wide Safety Wildland Firefighting Operations Virtual Workshop (https://nari.arc.nasa.gov/sws-wildfire) to system elements, creating connections which can be used in the future by the project engineers to identify and address requirements gaps throughout the system design process. I also identified and modeled preliminary use case scenarios for aerial assets in the demonstrator and, building on previously produced preliminary high-level models of the 8 SD-1 Services, Functions, and Capabilities (SFCs) and their IASMS data flows, worked to model the Real-Time Risk Assessment (RTRA) tool as an implementation of Risk Assessment and Management that can take in multiple sets of data monitored by SFCs. Project deliverables include stakeholder requirements tables and matrices and systems model diagrams produced with MagicDraw software in the SysML Systems Modeling Language, with eventual plans to connect model diagrams to a Department of Defense Operational Viewpoint (OV-1) graphic, a high-level operational concept graphic that will be used to visualize the SD-1 scenarioin a future phase. The system model serves to provide a common understanding of the scope of and activities necessary for the completion of SD-1,and traces how stakeholder needs are to be addressed.

model-based systems engineering↗

NASA NTRS2022

AMD Radeon e9173 Low Power PCIE GPU Single Event Effects Test Report

The AMD Radeon Embedded e9170 Graphics Processing Unit (GPU), notably the e9173 Peripheral Component Interconnect Express (PCIE) variant, is of interest to Artemis generation programs with requirements for graphics rendering, compute, artificial intelligence (Ai) with a constraints-requiring piece-part procurement and power consumption of less than 50W. In addition to collecting heavy ion data on this device, a secondary purpose of this test campaign was to validate video capture hardware and software workflows used with GPU, microprocessor and system-on-chip device testing. Five (5) test patterns from the NEPP Processor Enclave (NPE) test suite were used with the e9173. The test patterns covered the operating system’s (OS) idle contribution towards the cross section, matrix math using tensorflow-rocm, two artificial intelligence models developed at NASA GSFC, and an industry standard GPU benchmarking application called Mesa GLXGears.

NASA Technical Memorandum (TM) test report for pos↗

NASA NTRS2023

Multi-Star Wavefront Control at the Occulting Mask Coronagraph Testbed: Monochromatic Laboratory Demonstration for the Roman Coronagraph Instrument

The Astro2020 decadal survey recommended the Habitable Worlds Observatory (HWO), NASA’s direct imaging flagship mission, with a goal to achieve a statistically robust mission yield of 25 or more potentially habitable exoplanets. One way to achieve is to increase the instrument effectiveness by introducing additional bright, nearby targets. A majority of Sun-like stars have a stellar companion that can introduce additional noise into the field of view of any high-contrast imaging instrument and enabling exoplanet discovery around binary stars represents a path to increased corona graphic instrument efficiency by increasing the available science target pool of bright nearby stars. This includes both of the Alpha Centauri A and B stars which would represent the top science target for direct imaging if companion leakage could be suppressed. Multi-Star Wavefront Control(MSWC) is a technique that removes stellar leakage from both stellar components, enabling direct imaging of exoplanets in many binary star systems which can potentially increase corona graphic instrument effectivenessWe present the latest testbed results obtained with MSWC as part of the technology development effort focusing on demonstrations conducted on the Occulting Mask Coronagraph (OMC) testbed at JPL during thevacuum test window last winter, with an additional vacuum test planned for this fall. The MSWC mask consists of a shaped pupil mask similar to the one used for the Wide-Field of View mode, but also includes a set of superimposed, regularly-spaced dots that serve as a diffraction grating. OMC has a layout similar to the RomanSpace Telescope coronagraph instrument and configured with a binary imaging mode with a MSWC mask using same design as the contributed mask for the Roman coronagraph. Our testbed results represent the first demonstrations of this technique using the recently installed full binary source. We present results demonstrating suppression in the Super-Nyquist regime for the 3rd diffraction order reaching 8.7e-9 contrast with the Roman pupil. In addition, we present results obtained with a physical binary source and running MSWC in a binary star regime demonstrating 9.6e-8 contrast for a geometry matching potential Alpha Centauri observations in a515 nm monochromatic wavelength (similar but bluer than for Band 1) using the 5th diffraction order. Planned demonstrations in the upcoming vacuum window this fall will focus on Band 3d and Band 4 using the full MSWC mode for an Alpha Centauri geometry.

Roman Coronagraph Instrument↗

NASA NTRS2023

NASA Orbital Debris Engineering Model ORDEM 3.2 – Software User Guide

This National Aeronautics and Space Administration (NASA) Orbital Debris Engineering Model (ORDEM) 3.2 Software User Guide accompanies delivery of the latest upgraded version of the model, ORDEM 3.2. The user guide also provides a top-level program description and a list of capabilities. It includes descriptions of runtime error and information codes, input/output file formats, runtimes for different orbit configurations, and how to use uncertainty files. ORDEM 3.2 supersedes the previous NASA Orbital Debris Program Office (ODPO) models – ORDEM 3.0 (Stansbery, et al. 2014) and ORDEM2000 (Liou, et al. 2002). The availability of new sensor and in situ data, re-analysis of older data, and development of new analytical techniques has enabled the construction of this more comprehensive and sophisticated model. An upgraded graphical user interface (GUI) is integrated with the software. This upgraded GUI uses project-oriented organization and provides the user with graphical representations of numerous output data products. For example, these range from the conventional flux vs. average debris size (or altitude bin) for chosen analysis orbits (or views) to the more complex color-contoured, two-dimensional (2-D) directional flux diagrams in local spacecraft elevation and azimuth. The current model, ORDEM 3.2, supports spacecraft as well as telescope/radar project assessments. ORDEM 3.2 contains updated debris populations covering low Earth orbit (LEO, up to 2000 km altitude) to geosynchronous orbit (GEO, up to 40,000 km altitude) and can assess debris calculations up to year 2050, extending coverage past the previous limit of 2035 in ORDEM 3.0. Although populations differ from its predecessor, ORDEM 3.2 is functionally the same as ORDEM 3.0 and can support ORDEM 3.0 projects through backward compatibility.

Andrew Vavrin↗

NASA NTRS2024

Digital Lunar Exploration Sites (DLES) Terrain Crafting

Humans will soon be returning to the surface of the Moon with NASA’s Artemis program. The Artemis program is an international collaboration that will consist of a complex series of space systems and missions to explore the lunar surface and pave the way for the future exploration of Mars. NASA and its partners rely heavily on simulation for lighting and navigation studies as well as training astronauts, flight controllers, and mission support staff. The NASA Exploration Systems Simulations (NExSyS) team in the Simulation and Graphics Branch (ER7) in the Engineering Directorate at NASA’s Johnson Space Center has built up many simulation products to support this effort, one of which is the Digital Lunar Exploration Sites (DLES). DLES is a collection of products used to simulate and render the lunar surface in a digital environment. We discussed and presented an overview of the DLES products at the 2022 IEEE Aerospace Conference in Big Sky, MT with a paper titled "Digital Lunar Exploration Sites". This “DLES Terrain Crafting” paper will expand on the information previously provided in “DLES” paper and dive deeper into the details of the terrain crafting process and the toolsets used to support this task. The best digital data currently available of the lunar surface is provided by the Lunar Reconnaissance Orbiter (LRO). Its Lunar Orbiter Laser Altimeter (LOLA) achieves an impressive resolution of 5m per pixel at the Lunar South Pole (LSP) and can generate datasets covering a large continuous region near the LSP. There are a few additional methods, such as Shape from Shading which can infer higher resolution data (up to 1m per pixel) from the LRO Narrow Angle Camera (NAC) images. However, surface-based simulations require higher-resolution data, and this paper will discuss the process of enhancing the terrain to meet that need. The process begins with capturing statistical data of craters in the regions of interest using images provided by the LRO NAC. This data is then used to scatter artificial features which are not captured in the truth data, resulting in an enhanced DEM with a much higher resolution of 20cm per pixel. Many tools were built up to assist in the creation of these artificial Digital Elevation Models (DEM), which this paper will discuss in detail. DEMs themselves are a very powerful representation of a planetary surface, and many operations and tools can utilize the data they contain. This paper includes a description of the rendering of the lunar surface in a graphics engine, generation of contact patches to simulate tire to ground interaction, and ray tracing utilities to model Line of Sight (LOS) interactions with the terrain. This paper will also explore some new tool sets currently under development which aim to utilize Machine Learning (ML) to assist in the identification of craters from LRO NAC imagery. While this is not a novel idea, the NExSyS team is developing a unique approach which may result in more robust identification of crater characteristics.

Artemis↗

DOE OSTI2013

Storyboard method of end-user programming with natural language configuration

A technique for end-user programming includes populating a template with graphically illustrated actions and then invoking a command to generate a screen element based on the template. The screen element is rendered within a computing environment and provides a mechanism for triggering execution of a sequence of user actions. The sequence of user actions is based at least in part on the graphically illustrated actions populated into the template.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Dynamic graph system for a semantic database

A method and system in a computer system for dynamically providing a graphical representation of a data store of entries via a matrix interface is disclosed. A dynamic graph system provides a matrix interface that exposes to an application program a graphical representation of data stored in a data store such as a semantic database storing triples. To the application program, the matrix interface represents the graph as a sparse adjacency matrix that is stored in compressed form. Each entry of the data store is considered to represent a link between nodes of the graph. Each entry has a first field and a second field identifying the nodes connected by the link and a third field with a value for the link that connects the identified nodes. The first, second, and third fields represent the rows, column, and elements of the adjacency matrix.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Computer systems and methods for the query and visualization of multidimensional databases

A computer displays a graphical user interface on its display. The graphical user interface includes a schema information region and a data visualization region. The schema information region includes multiple operand names, each operand corresponding to one or more fields of a multi-dimensional database that includes at least one data hierarchy. The data visualization region includes a columns shelf and a rows shelf. The computer detects user actions to associate one or more first operands with the columns shelf and to associate one or more second operands with the rows shelf. The computer generates a visual table in the data visualization region in accordance with the user actions. The visual table includes one or more panes. Each pane has an x-axis defined based on data for the one or more first operands, and each pane has a y-axis defined based on data for the one or more second operands.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Operator interface for vehicles

A control interface for drivetrain braking provided by a regenerative brake and a non-regenerative brake is implemented using a combination of switches and graphic interface elements. The control interface comprises a control system for allocating drivetrain braking effort between the regenerative brake and the non-regenerative brake, a first operator actuated control for enabling operation of the drivetrain braking, and a second operator actuated control for selecting a target braking effort for drivetrain braking. A graphic display displays to an operator the selected target braking effort and can be used to further display actual braking effort achieved by drivetrain braking.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2015

Computer systems and methods for the query and visualization of multidimensional databases

A computer displays a graphical user interface on its display. The graphical user interface includes a schema information region and a data visualization region. The schema information region includes a plurality of fields of a multi-dimensional database that includes at least one data hierarchy. The data visualization region includes a columns shelf and a rows shelf. The computer detects user actions to associate one or more first fields with the columns shelf and to associate one or more second fields with the rows shelf. The computer generates a visual table in the data visualization region in accordance with the user actions. The visual table includes one or more panes. Each pane has an x-axis defined based on data for the one or more first fields, and each pane has a y-axis defined based on data for the one or more second fields.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Exploratory Data analysis ENvironment eXtreme scale (EDENx)

EDENx is a multivariate data visualization tool that allows interactive user driven analysis of large-scale data sets with high dimensionality. EDENx builds on our earlier system, called EDEN to enable analysis of more dimensions and larger scale data sets. EDENx provides an initial overview of summary statistics for each variable in the data set under investigation. EDENx allows the user to interact with graphical summary plots of the data to investigate subsets and their statistical associations. These plots include histograms, binned scatterplots, binned parallel coordinate plots, timeline plots, and graphical correlation indicators. From the EDENx interface, a user can select a subsample of interest and launch a more detailed data visualization via the EDEN system. EDENx is best suited for high-level, aggregate analysis tasks while EDEN is more appropriate for detail data investigations.

Steed, Chad Allen↗

DOE OSTI2016

Dynamic graph system for a semantic database

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Neutron Source Facility Training Simulator Based on EPICS

A plant operator training simulator is developed for training the plant operators as well as for design verification of plant control system (PCS) and plant protection system (PPS) for the Kharkov Institute of Physics and Technology Neutron Source Facility. The simulator provides the operator interface for the whole plant including the sub-critical assembly coolant loop, target coolant loop, secondary coolant loop, and other facility systems. The operator interface is implemented based on Experimental Physics and Industrial Control System (EPICS), which is a comprehensive software development platform for distributed control systems. Since its development at Argonne National Laboratory, it has been widely adopted in the experimental physics community, e.g. for control of accelerator facilities. This work is the first implementation for a nuclear facility. The main parts of the operator interface are the plant control panel and plant protection panel. The development involved implementation of process variable database, sequence logic, and graphical user interface (GUI) for the PCS and PPS utilizing EPICS and related software tools, e.g. sequencer for sequence logic, and control system studio (CSS-BOY) for graphical use interface. For functional verification of the PCS and PPS, a plant model is interfaced, which is a physics-based model of the facility coolant loops implemented as a numerical computer code. The training simulator is tested and demonstrated its effectiveness in various plant operation sequences, e.g. start-up, shut-down, maintenance, and refueling. It was also tested for verification of the plant protection system under various trip conditions.

Park, Young Soo↗

DOE OSTI2017

Software-defined Quantum Networking Ecosystem

The software enables a user to perform modeling and simulation of software-defined quantum networks. The software addresses the problem of how to synchronize transmission of quantum and classical signals through multi-node networks and to demonstrate quantum information protocols such as quantum teleportation. The software approaches this problem by generating a graphical model of the underlying network and attributing properties to each node and link in the graph. The graphical model is then simulated using a combination of discrete-event simulators to calculate the expected state of each node and link in the graph at a future time. A user interacts with the software by providing an initial network model and instantiating methods for the nodes to transmit information with each other. This includes writing application scripts in python that make use of the software library interfaces. A user then initiates the application scripts, which invokes the software simulation. The user then uses the built-in diagnostic tools to query the state of the simulation and to collect statistics on synchronization.

Humble, Travis S.↗

DOE OSTI2017

EnergyPlus™

Originally developed in 1999, an updated version 8.8.0 with bug fixes was released on September 30th, 2017. EnergyPlus™ is a whole building energy simulation program that engineers, architects, and researchers use to model both energy consumption—for heating, cooling, ventilation, lighting and plug and process loads—and water use in buildings. EnergyPlus is a console-based program that reads input and writes output to text files. It ships with a number of utilities including IDF-Editor for creating input files using a simple spreadsheet-like interface, EP-Launch for managing input and output files and performing batch simulations, and EP-Compare for graphically comparing the results of two or more simulations. Several comprehensive graphical interfaces for EnergyPlus are also available. DOE does most of its work with EnergyPlus using the OpenStudio® software development kit and suite of applications. DOE releases major updates to EnergyPlus twice annually.

Source record↗

DOE OSTI2018

A Visual Atlas on Strategic Trade

Strategic trade concerns global trade flows of items with strategic military value. Items include goods with exclusive military use, but also dual-use items that can have both military and civil uses. Many countries require licenses for trade in strategic items as a measure of non-proliferation. For example, items listed for trade control by multilateral export control arrangements, such as the Nuclear Suppliers Group (NSG), typically are considered strategic goods. Analysts and officials involved in strategic trade control often lack quantitative global understanding of relevant trade patterns that would help them focus control and enforcement efforts, select companies for outreach and audit, target transactions for verification and inspection, and assess the potential economic impact of trade control policies. Many are unaware of available open source data on international trade that can inform these issues. Many do not know how to make use of such data or lack the tools necessary to do so. A book of charts dubbed a ‘Strategic Trade Atlas’ was developed to illustrate global trade flows of strategic goods and raise awareness of the availability and utility of open source trade data. The Atlas was prepared for the World Customs Organization (WCO) and its Member States to support their planning and execution of Strategic Trade Control Enforcement (STCE) operations. It offers macroscopic graphical representations of global trade flows classified under Harmonized System (HS) codes associated by the WCO with commodities described in its STCE Implementation Guide. While these HS codes are understood to also encompass many non-strategic items, they nevertheless provide a good overview of potentially strategic trade flows. These include HS codes covering nuclear and nuclear-related commodities listed by the NSG, such as uranium, heavy water, graphite, carbon fiber, nickel powder, beryllium, aluminum tubes, vacuum pumps, valves, machine tools, cameras, and many others. The Atlas uses trade data from the Base pour l’Analyse du Commerce International (BACI), a statistical elaboration of public UN Comtrade data. BACI data reconciles trade flows, taking into account asymmetries in import and export trade valuation. The data visualization approach facilitates rapid sense making, pattern recognition, and anomaly detection. Country-based profiles summarize vast amounts of data into readily understandable graphical representations of each country’s primary strategic imports and exports and their main trading partners. Commodity-based profiles provide a global view of major exporters, importers, and trade patterns for each commodity. These insights can inform the risk management approach employed by customs to allocate enforcement and compliance efforts.

customs controls↗