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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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NASA - KAIA (Korea Agency for Infrastructure Technology Advancement) - KARI (Korea Aerospace Research Institute) collaboration surface air traffic management research has been ongoing since May 2015. In the first year collaboration, NASA's SOSS software has been transferred to KAIA and KARI teams to provide fast time simulation capability. Incheon International Airport model has been developed for SOSS.
The Science Activity Planner (SAP) software system includes an uplink-planning component, which enables collaborative planning of activities to be undertaken by an exploratory robot on a remote planet or on Earth. Included in the uplink-planning component is the SAP-Uplink Browser, which enables users to load multiple spacecraft activity plans into a single window, compare them, and merge them. The uplink-planning component includes a subcomponent that implements the Rover Markup Language Activity Planning format (RML-AP), based on the Extensible Markup Language (XML) format that enables the representation, within a single document, of planned spacecraft and robotic activities together with the scientific reasons for the activities. Each such document is highly parseable and can be validated easily. Another subcomponent of the uplink-planning component is the Activity Dictionary Markup Language (ADML), which eliminates the need for two mission activity dictionaries - one in a human-readable format and one in a machine-readable format. Style sheets that have been developed along with the ADML format enable users to edit one dictionary in a user-friendly environment without compromising
Collecting usability and user evaluations of novel software in spaceflight analog missions is challenging. For one such analog mission, we collected audio recordings of crew members as they completed their assigned self-scheduling task using novel software. Conversation analysis provided insight about collaborative nature of task and potential new evaluation measures.
This viewgraph presentation describes the SAVE tool and it's application to Core Flight Software (CFS). The contents include: 1) Fraunhofer-a short intro; 2) Context of this Collaboration; 3) CFS-Core Flight Software?; 4) The SAVE Tool; 5) Applying SAVE to CFS -A few example analyses; and 6) Goals.
The Earth Observing One (EO-1) satellite was launched in November 2000 as a one year technology demonstration mission for a variety of space technologies. After the first year, in addition to collecting science data from its instruments, the EO-1 mission has been used as a testbed for a variety of technologies which provide various automation capabilities and which have been used as a pathfinder for the creation of SensorWebs. A SensorWeb is the integration of variety of space, airborne and ground sensors into a loosely coupled collaborative sensor system that automatically provides useful data products. Typically, a SensorWeb is comprised of heterogeneous sensors tied together with a messaging architecture and web services. This paper provides an overview of the various technologies that were tested and eventually folded into normal operations. As these technologies were folded in, the nature of operations transformed. The SensorWeb software enables easy connectivity for collaboration with sensors, but the side benefit is that it improved the EO-1 operational efficiency. This paper presents the various phases of EO-1 operation over the past 12 years and also presents operational efficiency gains demonstrated by some metrics.
The international collaboration designing and constructing the Deep Underground Neutrino Experiment (DUNE) at the Long-Baseline Neutrino Facility (LBNF) has developed a two-phase strategy toward the implementation of this leading-edge, large-scale science project. The ambitious physics program of Phase I and Phase II of DUNE is dependent upon deployment and utilization of significant computing resources, and successful research and development of software (both infrastructure and algorithmic) in order to achieve these scientific goals. This submission discusses the computing resources projections, infrastructure support, and software development needed for DUNE during the coming decades as an input to the European Strategy for Particle Physics Update for 2026. The DUNE collaboration is submitting four main contributions to the 2026 Update of the European Strategy for Particle Physics process. This submission to the 'Computing' stream focuses on DUNE software and computing. Additional inputs related to the DUNE science program, DUNE detector technologies and R&D, and European contributions to Fermilab accelerator upgrades and facilities for the DUNE experiment, are also being submitted to other streams.
In 2014, a software development team from NASA's Ames Research Center (ARC), working in collaboration with mission teams at the Jet Propulsion Laboratory (JPL), set out to build a new software system for data visualization for missions. Our functional goal was to build a modular multi-mission software system that empowered users to build and compose their own visualizations of data across mission domains, with no programming required from the users to assemble these displays. Beyond the basic functional requirements for missions, we specified a requirement to make the software open source. This requirement was included to enable flexible use, and reduce or eliminate the proprietary nature of software that can impede collaboration. By making it open source, we also benefit from increased productivity and draw on the innovation of the open source developer community. We want to build and empower a community of contributors and enable broad use both inside and outside the space community to glean insights from cross domain usage. The open source software is called Open Mission Control Technologies, it is available on GitHub (https://github.com/nasa/openmct).
Pyomo is an open-source optimization modeling software that has undergone significant evolution since its inception in 2008. Pyomo has evolved to enhance flexibility, solver integration, and community engagement. Modern collaborative tools for open-source software have facilitated the development of new Pyomo functionality and improved our development process through automated testing and performance-tracking pipelines. However, Pyomo faces challenges typical of research software, including resource limitations and knowledge retention. The Pyomo team’s commitment to better development practices and community engagement reflects a proactive approach to these issues. We describe Pyomo’s development journey, highlighting both successes and failures, in the hopes that other open-source research software packages may benefit from our experiences.
The upcoming high-luminosity run of the CERN Large Hadron Collider (HL-LHC) will yield an unprecedented volume of data. In order to process this data, the ATLAS collaboration is evolving its offline software to be able to use heterogeneous resources such as graphical processing units (GPUs) and field-programmable gate arrays (FPGAs). To reduce conversion overheads, the event data model (EDM) should be compatible with the requirements of these resources. While the ATLAS EDM has long allowed representing data as a structure of arrays, further evolution of the EDM can enable more efficient sharing of data between CPU and GPU resources. Some of this work will be summarized here, including extensions to allow controlling how memory for event data is allocated and the implementation of jagged vectors.
To address the lack of user-friendly software needed to simplify the utilization of model data across Heliophysics, the Community Coordinated Modeling Center (CCMC) at NASA’s Goddard Space Flight Center has developed a model-agnostic method via Kamodo for users to easily access and utilize model data in their workflows. By abstracting away the broad range of file formats and the intricacies of interpolation on specialized grids, this approach significantly lowers the barrier to model data access and utilization for the community while adding exciting new capabilities to their tool boxes. This paper describes the direct interfaces to the model data, called model readers, and a basic introduction on how to use them. Additionally, we detail the planned approach for including custom interpolation codes, and include current progress on specialized visualization developments. The CCMC is maintaining Kamodo as an official NASA open-sourced software to enable and encourage community collaboration.
Astro-H is the x-ray/gamma-ray mission led by Japan with international participation, launched on February 17, 2016. Soon after launch, Astro-H was renamed Hitomi. The payload consists of four different instruments (SXS, SXI, HXI, and SGD) that operate simultaneously to cover the energy range from 0.3 keV up to 600 keV. On March 27, 2016, JAXA lost contact with the satellite and, on April 28, they announced the cessation of the efforts to restore mission operations. Hitomi collected about one months worth of data with its instruments. This paper presents the analysis software and the data processing pipeline created to calibrate and analyze the Hitomi science data, along with the plan for the archive. These activities have been a collaborative effort shared between scientists and software engineers working in several institutes in Japan and United States.
Astro-H (Hitomi) is an X-ray Gamma-ray mission led by Japan with international participation, launched on February 17, 2016. The payload consists of four different instruments (SXS, SXI, HXI and SGD) that operate simultaneously to cover the energy range from 0.3 keV up to 600 keV. This paper presents the analysis software and the data processing pipeline created to calibrate and analyze the Hitomi science data along with the plan for the archive and user support.These activities have been a collaborative effort shared between scientists and software engineers working in several institutes in Japan and USA.
In eastern regions of the United States, the American eel is a species of management and regulatory concern because of significant population declines, despite the species’ previous abundance in all tributaries of rivers flowing into the Atlantic Ocean. The American eel is also a candidate for listing under the U.S. Endangered Species Act. While hydropower construction and operation are only one of several factors contributing to this population decline, such a listing could impose additional regulatory challenges for a large number of hydropower projects. In this CRADA project, we improved technologies for identifying migrating eels with the goal of reducing the cost and time required for future American eel hydropower impact assessment and mitigation studies, while maintaining accuracy. We built on results from a previous FOA project (FOA# DE-FOA-0001662), led by the Electric Power Research Institute (EPRI), which developed a highly accurate, deep-learning method for identifying migrating eels from imaging sonar data. The current study aimed to further optimize this deep-learning model, originally designed for image classification, and to develop an object detection software capable of identifying fish from sonar videos in real time, enabling the detection of events like fish migrations and specific species, such as the American eel, at hydropower dams. The data conversion algorithms were packaged as software with a graphical user interface, and the software is evaluated by external collaborators. We focused on the American eel in this project and explored the transferability of the developed deep learning models to the sea lamprey, given the similar body shape and swimming behavior between the two species.
SMU personnel formed a portion of the overall “Time Integration” team within the FASTMath SciDAC-5 Institute, and we interacted very closely with team members from collaborating institutions. The major goals of our team within the FASTMath institute may be categorized into two groups: the development of advanced and application-aware time integration methods and software, and close interactions with DOE application scientists to facilitate their use of these new methods and software. The two goals are intimately linked, since our research and development of novel tools is informed by the needs of our application partners, who in turn benefit from subsequent mathematical and software advances. While the SMU personnel collaborated with the rest of the Time Integration FASTMath team on most of our shared deliverables within the larger FASTMath institute, SMU personnel primarily contributed to the following subset of those goals: ● expanding capabilities for higher-order and solve-decoupled multirate methods, ● enhancing support for temporal adaptivity within multirate methods, and ● adding structure-aware time integration methods. Each of these goals focused both on intellectual contributions through journal articles or research presentations, and on enhancements to the open-source SUNDIALS library of time integrators and nonlinear solvers, of which the SMU PI Reynolds is a core developer.
A potential application is outlined for high-speed and high-performance networks of the future. A discussion is presented of possible contents of the NSE (National Software Exchange) services to be offered by the NSE, mechanisms for controlling software quality, and types of collaboration that might involve the NSE. Services that must be provided by the NREN (National Research and Education Network) to provide adequate support for the NSE are identified.
The Collaborative Information Portal was enterprise software developed jointly by the NASA Ames Research Center and the Jet Propulsion Laboratory for NASA's Mars Exploration Rover mission. Mission managers, engineers, scientists, and researchers used this Internet application to view current staffing and event schedules, download data and image files generated by the rovers, receive broadcast messages, and get accurate times in various Mars and Earth time zones. This article describes the features, architecture, and implementation of this software, and concludes with lessons we learned from its deployment and a look towards future missions.
Topics covered include: Data Relay Board with Protocol for High-Speed, Free-Space Optical Communications; Software and Algorithms for Biomedical Image Data Processing and Visualization; Rapid Chemometric Filtering of Spectral Data; Prioritizing Scientific Data for Transmission; Determining Sizes of Particles in a Flow from DPIV Data; Faster Processing for Inverting GPS Occultation Data; FPGA-Based, Self-Checking, Fault-Tolerant Computers; Ultralow-Power Digital Correlator for Microwave Polarimetry; Grounding Headphones for Protection Against ESD; Lightweight Stacks of Direct Methanol Fuel Cells; Highly Efficient Vector-Inversion Pulse Generators; Estimating Basic Preliminary Design Performances of Aerospace Vehicles; Framework for Development of Object-Oriented Software; Analyzing Spacecraft Telecommunication Systems; Collaborative Planning of Robotic Exploration; Tools for Administration of a UNIX-Based Network; Preparing and Analyzing Iced Airfoils; Evaluating Performance of Components; Fuels Containing Methane of Natural Gas in Solution; Direct Electrolytic Deposition of Mats of MnxOy Nanowires; Bubble Eliminator Based on Centrifugal Flow; Inflatable Emergency Atmospheric-Entry Vehicles; Lightweight Deployable Mirrors with Tensegrity Supports; Centrifugal Adsorption Cartridge System; Ultrasonic Apparatus for Pulverizing Brittle Material; Transplanting Retinal Cells using Bucky Paper for Support; Using an Ultrasonic Instrument to Size Extravascular Bubbles; Coronagraphic Notch Filter for Raman Spectroscopy; On-the-Fly Mapping for Calibrating Directional Antennas; Working Fluids for Increasing Capacities of Heat Pipes; Computationally-Efficient Minimum-Time Aircraft Routes in the Presence of Winds; Liquid-Metal-Fed Pulsed Plasma Thrusters; Personal Radiation Protection System; and Attitude Control for a Solar-Sail Spacecraft.
Flight Awareness Collaboration Tool (FACT) is a software program that provides important information about winter weather operations to airline dispatchers.