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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Automation study for space station subsystems and mission ground support

An automation concept for the autonomous operation of space station subsystems, i.e., electric power, thermal control, and communications and tracking are discussed. To assure that functions essential for autonomous operations are not neglected, an operations function (systems monitoring and control) is included in the discussion. It is recommended that automated speech recognition and synthesis be considered a basic mode of man/machine interaction for space station command and control, and that the data management system (DMS) and other systems on the space station be designed to accommodate fully automated fault detection, isolation, and recovery within the system monitoring function of the DMS.

Source record↗
NASA NTRS1987

Spacecraft on-board SAR processing technology

This paper provides an assessment of the on-board SAR processing technology for Eos-type missions. The proposed Eos SAR sensor and flight data system are introduced, and the SAR processing requirements are described. The SAR on-board SAR processor architecture selection is discussed, and a baseline processor architecture using a frequency-domain processor for range correlation and a modular fault-tolerant VLSI time-domain parallel array for azimuth correlation are described. The mass storage and VLSI technologies needed for implementing the proposed SAR processing are assessed. It is shown that acceptable processor power and mass characteristics should be feasible for Eos-type applications. A proposed development strategy for the on-board SAR processor is presented.

Liu, K. Y.↗
NASA NTRS2004

Fault Tolerant Magnetic Bearing Testing and Conical Magnetic Bearing Development for Extreme Temperature Environments

During the six month tenure of the grant, activities included continued research of hydrostatic bearings as a viable backup-bearing solution for a magnetically levitated shaft system in extreme temperature environments (1000 F), developmental upgrades of the fault-tolerant magnetic bearing rig at the NASA Glenn Research Center, and assisting in the development of a conical magnetic bearing for extreme temperature environments, particularly turbomachinery. It leveraged work from the ongoing Smart Efficient Components (SEC) and the Turbine-Based Combined Cycle (TBCC) program at NASA Glenn Research Center. The effort was useful in providing technology for more efficient and powerful gas turbine engines.

Keith, Theo G., Jr.↗
NASA NTRSDate not supplied

Intelligent Control & Autonomy Branch Research Overview Research

The purpose of the subject presentation is to expose engineering students at Ohio University to ongoing work being performed by the Intelligent Control and Autonomy Branch (ICAB) at the NASA Glenn Research Center in Cleveland, Ohio. The presentation will start with some introductory material about the organization. This will be followed by an overview of Electrified Aircraft Propulsion (EAP) controls research and the ICAB’s support for the Space Launch System (SLS). One aspect of EAP is the integration of electrical motor/generators and other power systems components with turbine engine technology to create propulsion & power systems for single-aisle aircraft that are more fuel efficient and have lower emissions. The presentation will introduce some of the controls, systems health management, and modeling technologies developed by the ICAB to help realize EAP. NASA’s SLS is a super-heavy-lift launch vehicle that provides the foundation for human exploration beyond Earth’s orbit. The presentation will introduce capabilities developed by the ICAB to support the SLS Mission and Fault Management function which includes capabilities for abort, caution and warning, redundancy management, and safing. The presentation will conclude with information about internships with the NASA and the ICAB.

propulsion↗
NASA NTRS1985

Development of an Expert System for Representing Procedural Knowledge

A high level of automation is of paramount importance in most space operations. It is critical for unmanned missions and greatly increases the effectiveness of manned missions. However, although many functions can be automated by using advanced engineering techniques, others require complex reasoning, sensing, and manipulatory capabilities that go beyond this technology. Automation of fault diagnosis and malfunction handling is a case in point. The military have long been interested in this problem, and have developed automatic test equipment to aid in the maintenance of complex military hardware. These systems are all based on conventional software and engineering techniques. However, the effectiveness of such test equipment is severely limited. The equipment is inflexible and unresponsive to the skill level of the technicians using it. The diagnostic procedures cannot be matched to the exigencies of the current situation nor can they cope with reconfiguration or modification of the items under test. The diagnosis cannot be guided by useful advice from technicians and, when a fault cannot be isolated, no explanation is given as to the cause of failure. Because these systems perform a prescribed sequence of tests, they cannot utilize knowledge of a particular situation to focus attention on more likely trouble spots. Consequently, real-time performance is highly unsatisfactory. Furthermore, the cost of developing test software is substantial and time to maturation is excessive. Significant advances in artificial intelligence (AI) have recently led to the development of powerful and flexible reasoning systems, known as expert or knowledge-based systems. We have devised a powerful and theoretically sound scheme for representing and reasoning about procedural knowledge.

Georgeff, Michael P.↗
NASA NTRS2003

NASA Tech Briefs, March 2003

Topics covered include: Tool for Bending a Metal Tube Precisely in a Confined Space; Multiple-Use Mechanisms for Attachment to Seat Tracks; Force-Measuring Clamps; Cellular Pressure-Actuated Joint; Block QCA Fault-Tolerant Logic Gates; Hybrid VLSI/QCA Architecture for Computing FFTs; Arrays of Carbon Nanotubes as RF Filters in Waveguides; Carbon Nanotubes as Resonators for RF Spectrum Analyzers; Software for Viewing Landsat Mosaic Images; Updated Integrated Mission Program; Software for Sharing and Management of Information; Update on Integrated Optical Design Analyzer; Optical-Quality Thin Polymer Membranes; Rollable Thin Shell Composite-Material Paraboloidal Mirrors; Folded Resonant Horns for Power Ultrasonic Applications; Touchdown Ball-Bearing System for Magnetic Bearings; Flux-Based Deadbeat Control of Induction-Motor Torque; Block Copolymers as Templates for Arrays of Carbon Nanotubes; Throttling Cryogen Boiloff To Control Cryostat Temperature; Collaborative Software Development Approach Used to Deliver the New Shuttle Telemetry Ground Station; Turbulence in Supercritical O2/H2 and C7H16/N2 Mixing Layers; and Time-Resolved Measurements in Optoelectronic Microbioanal.

Source record↗
NASA NTRS1995

DRS: Derivational Reasoning System

The high reliability requirements for airborne systems requires fault-tolerant architectures to address failures in the presence of physical faults, and the elimination of design flaws during the specification and validation phase of the design cycle. Although much progress has been made in developing methods to address physical faults, design flaws remain a serious problem. Formal methods provides a mathematical basis for removing design flaws from digital systems. DRS (Derivational Reasoning System) is a formal design tool based on advanced research in mathematical modeling and formal synthesis. The system implements a basic design algebra for synthesizing digital circuit descriptions from high level functional specifications. DRS incorporates an executable specification language, a set of correctness preserving transformations, verification interface, and a logic synthesis interface, making it a powerful tool for realizing hardware from abstract specifications. DRS integrates recent advances in transformational reasoning, automated theorem proving and high-level CAD synthesis systems in order to provide enhanced reliability in designs with reduced time and cost.

Bose, Bhaskar↗
NASA NTRS2008

Benchmarking Gas Path Diagnostic Methods: A Public Approach

Recent technology reviews have identified the need for objective assessments of engine health management (EHM) technology. The need is two-fold: technology developers require relevant data and problems to design and validate new algorithms and techniques while engine system integrators and operators need practical tools to direct development and then evaluate the effectiveness of proposed solutions. This paper presents a publicly available gas path diagnostic benchmark problem that has been developed by the Propulsion and Power Systems Panel of The Technical Cooperation Program (TTCP) to help address these needs. The problem is coded in MATLAB (The MathWorks, Inc.) and coupled with a non-linear turbofan engine simulation to produce "snap-shot" measurements, with relevant noise levels, as if collected from a fleet of engines over their lifetime of use. Each engine within the fleet will experience unique operating and deterioration profiles, and may encounter randomly occurring relevant gas path faults including sensor, actuator and component faults. The challenge to the EHM community is to develop gas path diagnostic algorithms to reliably perform fault detection and isolation. An example solution to the benchmark problem is provided along with associated evaluation metrics. A plan is presented to disseminate this benchmark problem to the engine health management technical community and invite technology solutions.

Simon, Donald L.↗
NASA NTRSDate not supplied

A Case Study on the Challenges and Opportunities for the Deployment of PHM Capabilities in Existing Engineering Systems

The field of Prognostics and Health Management (PHM) of engineering systems has experienced considerable growth over the last decade. From benefits associated with faster and more powerful hardware in the form of wireless sensors, edge devices, and general computing capabilities (GPU’s and cloud computing), to development of powerful algorithms for anomaly detection and remaining useful life (RUL) estimation, the number of engineering systems featuring advanced diagnostics and prognostics capabilities continues to grow at an increasingly faster pace. However, the deployment of PHM capabilities as part of the upgrade of existing engineering systems presents multiple challenges to the PHM practitioner charged with retrofitting such systems. Issues include a lack of specific instrumentation needed to capture the signals of interest; insufficient data and sampling rates required for fault detection and diagnosis, and for detection of failure/degradation indicators; and difficulties in the identification of a system’s nominal behavior as a result of age induced degradation. Today’s PHM practitioner must be able to quickly identify and assess these types of issues to effectively evaluate and select the optimal PHM strategies required to achieve the desired results. This paper presents results from the preliminary evaluation of the High-Pressure Gas Facility (HPGF) infrastructure at NASA’s Stennis Space Center in Hancock County, Mississippi. This evaluation is part of a feasibility study conducted prior to the deployment of prognostics and diagnostics capabilities in the pumps skids of the liquid nitrogen (LN2) system of the HPGF.

Condition Based Maintenance↗
NASA NTRS2015

Architecture, Voltage, and Components for a Turboelectric Distributed Propulsion Electric Grid (AVC-TeDP)

The purpose of this effort was to advance the selection, characterization, and modeling of a propulsion electric grid for a Turboelectric Distributed Propulsion (TeDP) system for transport aircraft. The TeDP aircraft would constitute a miniature electric grid with 50 MW or more of total power, two or more generators, redundant transmission lines, and multiple electric motors driving propulsion fans. The study proposed power system architectures, investigated electromechanical and solid state circuit breakers, estimated the impact of the system voltage on system mass, and recommended DC bus voltage range. The study assumed an all cryogenic power system. Detailed assumptions within the study include hybrid circuit breakers, a two cryogen system, and supercritical cyrogens. A dynamic model was developed to investigate control and parameter selection.

power↗
NASA NTRS1974

Standardized strapdown inertial component modularity study, volume 2

To obtain cost effective strapdown navigation, guidance and stabilization systems to meet anticipated future needs a standardized modularized strapdown system concept is proposed. Three performance classes, high, medium and low, are suggested to meet the range of applications. Candidate inertial instruments are selected and analyzed for interface compatibility. Electronic packaging and processing, materials and thermal considerations applying to the three classes are discussed and recommendations advanced. Opportunities for automatic fault detection and redundancy are presented. The smallest gyro and accelerometer modules are projected as requiring a volume of 26 cubic inches and 23.6 cubic inches, respectively. Corresponding power dissipation is projected as 5 watts, and 2.6 watts respectively.

Feldman, J.↗
NASA NTRS2005

Non-Intrusive Techniques of Inspections During the Pre-Launch Phase of Space Vehicle

This paper addresses a method of non-intrusive local inspection of surface and sub-surface conditions, interfaces, laminations and seals in both space vehicle and ground operations with an integrated suite of imaging sensors during pre-launch operations. It employs an advanced Raman spectrophotometer with additional spectrophotometers and lidar mounted on a flying robot to constantly monitor the space hardware as well as inner surface of the vehicle and ground operations hardware. This paper addresses a team of micro flying robots with necessary sensors and photometers to monitor the entire space vehicle internally and externally. The micro flying robots can reach altitude with least amount of energy, where astronauts have difficulty in reaching and monitoring the materials and subsurface faults. The micro flying robot has an embedded fault detection system which acts as an advisory system and in many cases micro flying robots act as a Supervisor to fix the problems. As missions expand to a sustainable presence in the Moon, and extend for durations longer than one year in lunar outpost, the effectiveness of the instrumentation and hardware has to be revolutionized if NASA is to meet high levels of mission safety, reliability, and overall success. The micro flying robot uses contra-rotating propellers powered by an ultra-thin, ultrasonic motor with currently the world's highest power weight ratio, and is balanced in mid-air by means of the world's first stabilizing mechanism using a linear actuator. The essence of micromechatronics has been brought together in high-density mounting technology to minimize the size and weight. The robot can take suitable payloads of photometers, embedded chips for image analysis and micro pumps for sealing cracks or fixing other material problems. This paper also highlights advantages that this type of non-intrusive techniques offer over costly and monolithic traditional techniques.

Thirumalainambi, Rejkumar↗
NASA NTRS1994

Neural networks: Alternatives to conventional techniques for automatic docking

Automatic docking of orbiting spacecraft is a crucial operation involving the identification of vehicle orientation as well as complex approach dynamics. The chaser spacecraft must be able to recognize the target spacecraft within a scene and achieve accurate closing maneuvers. In a video-based system, a target scene must be captured and transformed into a pattern of pixels. Successful recognition lies in the interpretation of this pattern. Due to their powerful pattern recognition capabilities, artificial neural networks offer a potential role in interpretation and automatic docking processes. Neural networks can reduce the computational time required by existing image processing and control software. In addition, neural networks are capable of recognizing and adapting to changes in their dynamic environment, enabling enhanced performance, redundancy, and fault tolerance. Most neural networks are robust to failure, capable of continued operation with a slight degradation in performance after minor failures. This paper discusses the particular automatic docking tasks neural networks can perform as viable alternatives to conventional techniques.

Vinz, Bradley L.↗
NASA NTRS1997

Mars Surveyor '98 Landers MVACS Robotic Arm Control System Design Concepts

This paper describes the control system design concepts for the Mars Volatiles and Climate Surveyor (MVACS) Robotic Arm which supports the scientific investigations to be conducted as part of the Mars Surveyor '98 Lander project. Solutions are presented to some of the problems encountered in this demanding space application with its tight constraints on mass, power, volume, and computing resources. Problems addressed include 4-DOF forward and inverse kinematics, trajectory planning to minimize potential impact damage, joint drive train protection, Lander tilt prevention, hardware fault monitoring, and collision avoidance.

Bonitz, Robert G.↗
NASA NTRS2021

SEE Test Results for SAMA5D3

ARM processors power a class of high-performance, lower power system on a chip devices. In the absence of radiation effects, these devices are highly desirable for space use. The processor core architecture for ARM devices is licensed to provide computing on multiple hardware platforms. The A5 processor is in a unique pioneering space for providing detailed radiation response data to explore the baseline performance of these devices. These data can help set options for ARM processors and possibly impact design choices for the next generation of ARM fault tolerance capabilities. The SAMA5D3 was tested to establish general SEE performance for a relatively simple implementation of the ARM A5 core. This testing observed SRAM sensitivity starting at an LET of about 3 MeV-cm2/mg, with a saturated cross section of about 2x10-8cm2/bit, and this was determined by both active write and read of the caches, in addition to the use of a debugger to provide test results. Crash/SEFI data was collected using both Linux and bare metal C-code. The onset LET for crashes was about LET 1.5 MeV-cm2/mg, with saturated cross sections of about 2x10-5 cm2 for bare metal (low utilization), and 2x10-4cm2 for Linux (high utilization) tests.

Daniel, Andrew C.↗
NASA NTRS1980

Conductive surge testing of circuits and systems

Techniques are given for conductive surge testing of powered electronic equipment. The correct definitions of common and normal mode are presented. Testing requires not only spike-surge generators with a suitable range of open-circuit voltage and short-circuit current waveshapes, but also appropriate means, termed couplers, for connecting test surges to the equipment under test. Key among coupler design considerations is minimization of fail positives resulting from reduction in delivered surge energy due to the coupler. Back-filters and the lines on which they are necessary, are considered as well as ground-fault and ground potential rise. A method for monitoring delivered and resulting surge waves is mentioned.

Richman, P.↗
NASA NTRS2019

Artificial Intelligence: Powering Human Exploration of the Moon and Mars

Artificial Intelligence (AI) is a growing field of computa- tional science techniques designed to mimic functions per- formed by people. Advancements in autonomy will depend on a portfolio of AI technologies. Automated planning and scheduling is a venerable field of study in AI, and is needed for a variety of mission planning functions. Plan execution technology is less well studied, but important for auton- omy and robotics. Specialized forms of automated reason- ing and machine learning are key technologies to enable fault management. Over the past decade, the NASA Au- tonomous Systems and Operations (ASO) project has devel- oped and demonstrated numerous autonomy enabling tech- nologies employing AI techniques. Our work has employed AI in three distinct ways to enable autonomous mission op- erations capabilities. Crew Autonomy gives astronauts tools to assist in the performance of each of these mission oper-ations functions. Vehicle System Management uses AI tech- niques to turn the astronaut's spacecraft into a robot, allow- ing it to operate when astronauts are not present, or to reduce astronaut workload. AI technology also enables Autonomous Robots as crew assistants or proxies when the crew are not present. When these capabilities are used to enable astro- nauts to operate autonomously, they must be integrated with user interfaces, introducing numerous human factors con- siderations; when these capabilities are used to enable vehi- cle system management, they must be integrated with flight software, and run on embedded processors under the control of real-time operating systems.We first describe human spaceflight mission operations capabilities. The remainder of the paper will describe the ASO project, and the development and demonstration per- formed by ASO since 2011. We will describe the AI tech- niques behind each of these demonstrations, which include a variety of symbolic automated reasoning and machine learn- ing based approaches. Finally, we conclude with an assess- ment of future development needs for AI to enable NASA's future Exploration missions.

Mission Operations↗
NASA NTRS1989

Properties of earthquakes generated by fault dynamics

A model for fault dynamics consisting of a uniform chain of blocks and springs pulled slowly across a rough surface is presented. The only nonlinear element of the model is a slip-stick friction force between the blocks and the surface. It is found that this model gives rise to events of all sizes. The numerical evaluation of the distribution of earthquake magnitudes results in a power-law spectrum similar to what is observed in nature. Like certain other dissipative dynamical systems, the observed large fluctuations in earthquake magnitude persist because the system is in a state of marginal stability.

Carlson, J. M.↗