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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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At least 253 records · Page 14

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NASA NTRS2002

The Personal Satellite Assistant: An Internal Spacecraft Autonomous Mobile Monitor

This paper presents an overview of the research and development effort at the NASA Ames Research Center to create an internal spacecraft autonomous mobile monitor capable of performing intra-vehicular sensing activities by autonomously navigating onboard the International Space Station. We describe the capabilities, mission roles, rationale, high-level functional requirements, and design challenges for an autonomous mobile monitor. The rapid prototyping design methodology used, in which five prototypes of increasing fidelity are designed, is described as well as the status of these prototypes, of which two are operational and being tested, and one is actively being designed. The physical test facilities used to perform ground testing are briefly described, including a micro-gravity test facility that permits a prototype to propel itself in 3 dimensions with 6 degrees-of-freedom as if it were in an micro-gravity environment. We also describe an overview of the autonomy framework and its components including the software simulators used in the development process. Sample mission test scenarios are also described. The paper concludes with a discussion of future and related work followed by the summary.

Dorais, Gregory A.↗

DOE OSTI2024

Phase Selection Rules of Multi‐Principal Element Alloys

Abstract Computational prediction of phase stability of multi‐principal element alloys (MPEAs) holds a lot of promise for rapid exploration of the enormous design space and autonomous discovery of superior structural and functional properties. Regardless of many plausible works that rely on phenomenological theory and machine learning, precise prediction is still limited by insufficient data and the lack of interpretability of some machine learning algorithms, e.g., convolutional neural network. In this work, a comprehensive approach is presented, encompassing the development of a complete dataset that contains 72 387 density functional theory calculations, as well as a predictive global phenomenological descriptor. The phase selection descriptor, based on atomic electronegativity and valence electron concentration, significantly outperforms the widely used valence electron concentration, excelling in both accuracy (with an f1 score of 63% compared to 47%) and its ability to predict the HCP phase (0.48 recall compared to 0). The comprehensive data mining on the global design space of 61 425 quaternary MPEAs made from 28 possible metals, together with the phenomenological theory and physical interpretation, will set up a solid computational science foundation for data‐driven exploration of MPEAs.

Chemistry↗

NASA NTRS2003

F/A-18 Performance Benefits Measured During the Autonomous Formation Flight Project

The Autonomous Formation Flight (AFF) project at the NASA Dryden Flight Research Center (Edwards, California) investigated performance benefits resulting from formation flight, such as reduced aerodynamic drag and fuel consumption. To obtain data on performance benefits, a trailing F/A-18 airplane flew within the wing tip-shed vortex of a leading F/A-18 airplane. The pilot of the trail airplane used advanced station-keeping technology to aid in positioning the trail airplane at precise locations behind the lead airplane. The specially instrumented trail airplane was able to obtain accurate fuel flow measurements and to calculate engine thrust and vehicle drag. A maneuver technique developed for this test provided a direct comparison of performance values while flying in and out of the vortex. Based on performance within the vortex as a function of changes in vertical, lateral, and longitudinal positioning, these tests explored design-drivers for autonomous stationkeeping control systems. Observations showed significant performance improvements over a large range of trail positions tested. Calculations revealed maximum drag reductions of over 20 percent, and demonstrated maximum reductions in fuel flow of just over 18 percent.

Vachon, M. Jake↗

NASA NTRS1985

Autonomous spacecraft rendezvous and docking

A storyboard display is presented which summarizes work done recently in design and simulation of autonomous video rendezvous and docking systems for spacecraft. This display includes: photographs of the simulation hardware, plots of chase vehicle trajectories from simulations, pictures of the docking aid including image processing interpretations, and drawings of the control system strategy. Viewgraph-style sheets on the display bulletin board summarize the simulation objectives, benefits, special considerations, approach, and results.

Tietz, J. C.↗

DOE OSTI2022

Experimental validation of a high fidelity Monte Carlo neutron transport model of the MIT graphite exponential pile

High-fidelity modeling and simulation were performed for the MIT graphite exponential pile (MGEP) using Monte Carlo neutron transport codes OpenMC and MCNP, and the results were validated by experimental data. The MGEP is being used as the test bed for the design of an autonomous control system for the pile's neutron flux distribution. The main contribution of this work is to generate the training data sets of neutron flux distributions with different locations of control rods that perturb the neutron flux profiles. First, code -to-code cross verification between OpenMC and MCNP was performed to ensure consistency of the numerical modeling within statistical uncertainties. To validate the accuracy of this high-fidelity model, a series of neutron flux measurements were conducted using a Helium-3 (He-3) neutron detector on a mobile platform that is placed inside the pile. Second, the neutron flux profiles were measured in four vertical layers of interest, and compared to the corresponding simulation results. The comparison results shows that the root mean square error is less than 2.5% in the two upper layers, and less than 4.5% in all four measured layers. Here the results validated the accuracy of the modeling and simulation. Finally, the relative change of the neutron flux profiles from moving control rods was analyzed, which identified the layer that has the best sensitivity regarding the control rods movements. Thus, this work identified and provided training data sets of both simulated and experimental neutron flux profiles in the most sensitive layer, paving the path forward to the real-time experimental demonstration of the autonomous control system.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Improving Single-Stage Object Detectors for Nighttime Pedestrian Detection

We report Improving the reliability of nighttime pedestrian detection is a crucial challenge towards the design of robust autonomous systems. Not surprisingly, most pedestrian fatalities occur in low-illumination settings, thus emphasizing the need for new algorithmic advances. This work presents a novel pedestrian detection approach that makes a number of crucial modifications to the state-of-the-art YOLOV5-PANet architecture, in order to improve the reliability of features extracted from nighttime images. More specifically, the proposed architecture systematically incorporates powerful shuffle attention mechanisms and a transformer module to improve the feature learning pipeline. Instead of advocating the use of other sensing modalities that are better suited for nighttime detection, our approach relies only on conventional RGB cameras and is hence broadly applicable. Our empirical studies with nighttime pedestrian detection benchmarks show that with only minimal increase in model complexity, our approach provides significant improvements in detection efficacy over existing solutions. Finally, we explore the impact of post-hoc network pruning on the speed-accuracy trade-off of our approach and demonstrate that it is well suited for reduced memory/compute requirements.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Artificial Intelligence/Machine Learning Technologies for Advanced Reactors (Workshop Summary Report)

A workshop on artificial intelligence and machine learning (AI/ML) for advanced reactors (AR) was held October 5-6, 2021. The workshop was to be attended in-person at ANL but COVID restrictions forced the workshop to go virtual. The objectives of the workshop were to identify the most promising AI/ML opportunities for improving advanced reactor design, optimizing plant performance, and enhancing economic competitiveness and to develop an understanding of the scientific, engineering and licensing challenges facing their application. The workshop planning committee included GAIN, EPRI and NEI and members of three national laboratories (ANL, INL, and ORNL). The workshop was attended by more than 200 individuals representing academic and scientific institutions and the nuclear power industry. The definition put forth for an AI/ML system was one that perceives its environment and takes actions that maximize its chance of achieving its goals. In this report AI/ML refers to next generation algorithms that include deep learning, statistical analysis and data analytics and associated scientific computing and their potential application to the design, licensing, operation and maintenance of ARs. These methods typically incorporate models built from process data and may also include data generated by simulations that represent the behavior of a system. The workshop was organized in response to the growing interest in application of AI/ML for improving the economic competitiveness of nuclear energy. Increasingly more resources are being allocated to investigating the benefits of AI/ML methods. The DOE created the Artificial Intelligence & Technology Office to promote their development. And within the Office of Nuclear Energy, resources have been allocated to explore and understand the potential benefits of AI/ML. Additionally, the national laboratories are strategically positioned with DOE computing facilities such as Summit, Perlmutter, Aurora and Frontier that support large-scale simulations, hybrid HPC models with AI surrogates, and the exploration of new types of generative models emerging from multi-model data streams and sources. The workshop was organized with members of the AR community to understand the effort and to identify the level of interest and progress in this emerging technology. The workshop discussions focused on identifying opportunities for AI/ML across diverse areas of the nuclear industry and identifying current scientific and engineering challenges for advanced reactors that might be addressed through transformational uses of AI/ML. Discussion panels focused on four high-interest technical domains for advanced reactors: design, maintenance and operations, energy storage, and materials. The results of those discussions are summarized in this report. This includes opportunities that were identified for exploiting AI techniques and methods to improve the efficacy and efficiency of reactor analysis and to improve the operation and optimization of advanced reactors. Advanced reactor developers expressed an interest in learning more about AI/ML methods and their application. This included understanding whether ML methods can provide an advantage over existing nonlinear data regression methods for collapsing high-fidelity simulation results into faster running models. A consensus emerged that AR advances planned for the next decade will benefit from the use of AI/ML tools. The need exists to understand and model complex systems across length scales and modalities. AI/ML is a tool for discovery that can yield a set of engineering principles for use by nuclear engineers, licensing bodies, and operators to solve problems in plant design, safety analyses, autonomous operation, and predictive maintenance. While AI/ML represents a new set of tools, an awareness by the nuclear community of the full potential is still in the early stages so there is a need to increase awareness. It appears that the wide-spread adoption of AI/ML tools for ARs would be facilitated by future educational workshops that describe foundational methods and capabilities and describe successful applications.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS1975

Challenges of the Viking Mars Lander system

A number of natural constraints have led to a highly autonomous Lander system design. Almost all communications to and from the Lander are via the Orbiter. A functional description of the Lander mission is given, taking into account deorbit and descent, entry, terminal descent, landing, and landed operations. The challenges of the system design are considered along with the mechanical configuration and aspects of thermal control. Attention is given to science data return, aspects of reliability and redundancy, and details regarding the software.

Goodlette, J. D.↗

NASA NTRS1989

Concept synthesis of an equipment manipulation and transportation system EMATS

The European Columbus Scenario is established. One of the Columbus Elements, the Man Tended Free Flyer will be designed for fully autonomous operation in order to provide the environment for micro gravity facilities. The Concept of an autonomous automation system which perform servicing of facilities and deals with related logistic tasks is discussed.

Depeuter, W.↗

NASA NTRS1991

Project WISH: The Emerald City, phase 2

The purpose of the Permanently Manned Autonomous Space Oasis, designated Project WISH: The Emerald City, is to serve as permanent living quarters for space colonists. In addition, it will serve as a stopover for space missions and will be capable of restationing itself practically anywhere within the solar system to provide support for these missions. The station should be self-sufficient, with no specific dependence on any resources from Earth. The 1990 to 1991 design team continued work started by last year's class. Further studies were conducted in the areas of orbital mechanics, propulsion, attitude control, and human factors. Critical elements were identified in each of these areas, and guidelines were established for the design of the Emerald City. Using the knowledge gained from these studies, two particular missions of interest, a Saturn Envelope mission and an Earth to Mars mission, were examined. The size and mass estimates, along with the methodologies used in their determination, are considered to be the main accomplishments of phase 2.

Source record↗

NASA NTRS1994

Space Active Modular Materials Experiments (SAMMES): Low Earth Orbital mission aboard the Space Test Experiments STEP-3 platform

The requirement of satellite systems to survive in the space environment for 5 to 10 years to achieve greater cost effectiveness is discussed. Characterization of the orbital space environment and its effects on spacecraft systems have received considerable research attention. Instrumentation for long term measurement of key physical parameters characterizing the low Earth orbit (LEO) environment and its effects on degradation of spacecraft materials and solar arrays is reported. These measurements enable active, real time monitoring of the health of spacecraft and payload systems. SAMMES is designed to be autonomous, compact, low power, and lightweight.

Joshi, P.↗

NASA NTRS1997

Optimizing Aerobot Exploration of Venus

Venus Flyer Robot (VFR) is an aerobot; an autonomous balloon probe designed for remote exploration of Earth's sister planet in 2003. VFR's simple navigation and control system permits travel to virtually any location on Venus, but it can survive for only a limited duration in the harsh Venusian environment. To help address this limitation, we develop: (1) a global circulation model that captures the most important characteristics of the Venusian atmosphere; (2) a simple aerobot model that captures thermal restrictions faced by VFR at Venus; and (3) one exact and two heuristic algorithms that, using abstractions (1) and (2), construct routes making the best use of VFR's limited lifetime. We demonstrate this modeling by planning several small example missions and a prototypical mission that explores numerous interesting sites recently documented in the plane tary geology literature.

SPACE EXPLORATION↗

NASA NTRS2000

PROPULSE 980: A Hydrogen Peroxide Enrichment System

The PROPULSE 980 unit is a transportable processing plant that enriches aerospace grade hydrogen peroxide from 90% to 98% final concentration. The unit was developed by Degussa-H Is, in cooperation with Orbital, NASA Marshall Space Center, and NASA Stennis Space Center. The system is a self-contained unit that houses all of the process equipment, instrumentation and controls to perform the concentration operation nearly autonomously. It is designed to produce non-bulk quantities of 98% hydrogen peroxide. The enrichment unit design also maintains system, personnel and environmental safety during all aspects of the enrichment process and final product storage. As part of the Propulse 980 checkout and final buyoff, it will be disassembled at the Degussa-H Is Corporation plant in Theodore, AL, transported to the Stennis Space Center, reassembled and subjected to a series of checkout tests to verify design objectives have been met. This paper will summarize the basic project elements and provide an update on the present status of the project.

Boxwell, Robert↗

NASA NTRS2001

Multidisciplinary Concurrent Design Optimization via the Internet

A methodology is presented which uses commercial design and analysis software and the Internet to perform concurrent multidisciplinary optimization. The methodology provides a means to develop multidisciplinary designs without requiring that all software be accessible from the same local network. The procedures are amenable to design and development teams whose members, expertise and respective software are not geographically located together. This methodology facilitates multidisciplinary teams working concurrently on a design problem of common interest. Partition of design software to different machines allows each constituent software to be used on the machine that provides the most economy and efficiency. The methodology is demonstrated on the concurrent design of a spacecraft structure and attitude control system. Results are compared to those derived from performing the design with an autonomous FORTRAN program.

Woodard, Stanley E.↗

NASA NTRS2001

2001 Flight Mechanics Symposium

This conference publication includes papers and abstracts presented at the Flight Mechanics Symposium held on June 19-21, 2001. Sponsored by the Guidance, Navigation and Control Center of Goddard Space Flight Center, this symposium featured technical papers on a wide range of issues related to attitude/orbit determination, prediction and control; attitude simulation; attitude sensor calibration; theoretical foundation of attitude computation; dynamics model improvements; autonomous navigation; constellation design and formation flying; estimation theory and computational techniques; Earth environment mission analysis and design; and, spacecraft re-entry mission design and operations. Government, industry, and the academic community participated in the preparation and presentation of these papers.

Flight mechanics↗

NASA NTRS2004

Verification of NASA Emergent Systems

NASA is studying advanced technologies for a future robotic exploration mission to the asteroid belt. This mission, the prospective ANTS (Autonomous Nano Technology Swarm) mission, will comprise of 1,000 autonomous robotic agents designed to cooperate in asteroid exploration. The emergent properties of swarm type missions make them powerful, but at the same time are more difficult to design and assure that the proper behaviors will emerge. We are currently investigating formal methods and techniques for verification and validation of future swarm-based missions. The advantage of using formal methods is their ability to mathematically assure the behavior of a swarm, emergent or otherwise. The ANT mission is being used as an example and case study for swarm-based missions for which to experiment and test current formal methods with intelligent swam. Using the ANTS mission, we have evaluated multiple formal methods to determine their effectiveness in modeling and assuring swarm behavior.

Rouff, Christopher↗

NASA NTRS2008

Managing Complexity in Next Generation Robotic Spacecraft: From a Software Perspective

This presentation highlights the challenges in the design of software to support robotic spacecraft. Robotic spacecraft offer a higher degree of autonomy, however currently more capabilities are required, primarily in the software, while providing the same or higher degree of reliability. The complexity of designing such an autonomous system is great, particularly while attempting to address the needs for increased capabilities and high reliability without increased needs for time or money. The efforts to develop programming models for the new hardware and the integration of software architecture are highlighted.

Multi - threaded programming↗

NASA NTRS2010

AutoGNC Testbed

A simulation testbed architecture was developed and implemented for the integration, test, and development of a TRL-6 flight software set called Auto- GNC. The AutoGNC software will combine the TRL-9 Deep Impact AutoNAV flight software suite, the TRL-9 Virtual Machine Language (VML) executive, and the TRL-3 G-REX guidance, estimation, and control algorithms. The Auto- GNC testbed was architected to provide software interface connections among the AutoNAV and VML flight code written in C, the G-REX algorithms in MATLAB and C, stand-alone image rendering algorithms in C, and other Fortran algorithms, such as the OBIRON landmark tracking suite. The testbed architecture incorporates software components for propagating a high-fidelity truth model of the environment and the spacecraft dynamics, along with the flight software components for onboard guidance, navigation, and control (GN&C). The interface allows for the rapid integration and testing of new algorithms prior to development of the C code for implementation in flight software. This testbed is designed to test autonomous spacecraft proximity operations around small celestial bodies, moons, or other spacecraft. The software is baselined for upcoming comet and asteroid sample return missions. This architecture and testbed will provide a direct improvement upon the onboard flight software utilized for missions such as Deep Impact, Stardust, and Deep Space 1.

Carson, John M., III↗