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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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Topics covered include extraterrestrial physics, high energy astrophysics, astronomy, solar physics, atmospheres, oceans, terrestrial physics, space technology, sensors, techniques, user space data systems, space communications and navigation, and system and software engineering.
An expert system, called LEADER, has been designed and implemented for automatic learning, detection, identification, verification, and correction of anomalous propulsion system operations in real time. LEADER employs a set of sensors to monitor engine component performance and to detect, identify, and validate abnormalities with respect to varying engine dynamics and behavior. Two diagnostic approaches are adopted in the architecture of LEADER. In the first approach fault diagnosis is performed through learning and identifying engine behavior patterns. LEADER, utilizing this approach, generates few hypotheses about the possible abnormalities. These hypotheses are then validated based on the SSME design and functional knowledge. The second approach directs the processing of engine sensory data and performs reasoning based on the SSME design, functional knowledge, and the deep-level knowledge, i.e., the first principles (physics and mechanics) of SSME subsystems and components. This paper describes LEADER's architecture which integrates a design based reasoning approach with neural network-based fault pattern matching techniques. The fault diagnosis results obtained through the analyses of SSME ground test data are presented and discussed.
Prototype logic gates made of n-channel junction field-effect transistors (JFETs) and epitaxial resistors have been demonstrated, with a view toward eventual implementation of digital logic devices and systems in silicon carbide (SiC) integrated circuits (ICs). This development is intended to exploit the inherent ability of SiC electronic devices to function at temperatures from 300 to somewhat above 500 C and withstand large doses of ionizing radiation. SiC-based digital logic devices and systems could enable operation of sensors and robots in nuclear reactors, in jet engines, near hydrothermal vents, and in other environments that are so hot or radioactive as to cause conventional silicon electronic devices to fail. At present, current needs for digital processing at high temperatures exceed SiC integrated circuit production capabilities, which do not allow for highly integrated circuits. Only single to small number component production of depletion mode n-channel JFETs and epitaxial resistors on a single substrate is possible. As a consequence, the fine matching of components is impossible, resulting in rather large direct-current parameter distributions within a group of transistors typically spanning multiples of 5 to 10. Add to this the lack of p-channel devices to complement the n-channel FETs, the lack of precise dropping diodes, and the lack of enhancement mode devices at these elevated temperatures and the use of conventional direct coupled and buffered direct coupled logic gate design techniques is impossible. The presented logic gate design is tolerant of device parameter distributions and is not hampered by the lack of complementary devices or dropping diodes. In addition to n-channel JFETs, these gates include level-shifting and load resistors (see figure). Instead of relying on precise matching of parameters among individual JFETS, these designs rely on choosing the values of these resistors and of supply potentials so as to make the circuits perform the desired functions throughout the ranges over which the parameters of the JFETs are distributed. The supply rails V(sub dd) and V(sub ss) and the resistors R are chosen as functions of the distribution of direct-current operating parameters of the group of transistors used.
NASA space and aeronautical missions for probing the inner solar planets as well as for in situ monitoring and control of next-generation aeronautical engines require high-temperature environment operable sensors and electronics. A 96% aluminum oxide and Au thick-film metallization based packaging system including chip-level packages, printed circuit board, and edge-connector is in development for high temperature SiC electronics. An electronic packaging system based on this material system was successfully tested and demonstrated with SiC electronics at 500 C for over 10,000 hours in laboratory conditions previously. In addition to the tests in laboratory environments, this packaging system has more recently been tested with a SiC junction field effect transistor (JFET) on low earth orbit through the NASA Materials on the International Space Station Experiment 7 (MISSE7). A SiC JFET with a packaging system composed of a 96% alumina chip-level package and an alumina printed circuit board mounted on a data acquisition circuit board was launched as a part of the MISSE7 suite to International Space Station via a Shuttle mission and tested on the orbit for eighteen months. A summary of results of tests in both laboratory and space environments will be presented. The future development of alumina based high temperature packaging using co-fired material systems for improved performance at high temperature and more feasible mass production will also be discussed.
The inductive monitoring system (IMS) is a system of computer hardware and software for automated monitoring of the performance, operational condition, physical integrity, and other aspects of the health of a complex engineering system (e.g., an industrial process line or a spacecraft). The input to the IMS consists of streams of digitized readings from sensors in the monitored system. The IMS determines the type and amount of any deviation of the monitored system from a nominal or normal ( healthy ) condition on the basis of a comparison between (1) vectors constructed from the incoming sensor data and (2) corresponding vectors in a database of nominal or normal behavior. The term inductive reflects the use of a process reminiscent of traditional mathematical induction to learn about normal operation and build the nominal-condition database. The IMS offers two major advantages over prior computational monitoring systems: The computational burden of the IMS is significantly smaller, and there is no need for abnormal-condition sensor data for training the IMS to recognize abnormal conditions. The figure schematically depicts the relationships among the computational processes effected by the IMS. Training sensor data are gathered during normal operation of the monitored system, detailed computational simulation of operation of the monitored system, or both. The training data are formed into vectors that are used to generate the database. The vectors in the database are clustered into regions that represent normal or nominal operation. Once the database has been generated, the IMS compares the vectors of incoming sensor data with vectors representative of the clusters. The monitored system is deemed to be operating normally or abnormally, depending on whether the vector of incoming sensor data is or is not, respectively, sufficiently close to one of the clusters. For this purpose, a distance between two vectors is calculated by a suitable metric (e.g., Euclidean distance) and "sufficiently close" signifies lying at a distance less than a specified threshold value. It must be emphasized that although the IMS is intended to detect off-nominal or abnormal performance or health, it is not necessarily capable of performing a thorough or detailed diagnosis. Limited diagnostic information may be available under some circumstances. For example, the distance of a vector of incoming sensor data from the nearest cluster could serve as an indication of the severity of a malfunction. The identity of the nearest cluster may be a clue as to the identity of the malfunctioning component or subsystem. It is possible to decrease the IMS computation time by use of a combination of cluster-indexing and -retrieval methods. For example, in one method, the distances between each cluster and two or more reference vectors can be used for the purpose of indexing and retrieval. The clusters are sorted into a list according to these distance values, typically in ascending order of distance. When a set of input data arrives and is to be tested, the data are first arranged as an ordered set (that is, a vector). The distances from the input vector to the reference points are computed. The search of clusters from the list can then be limited to those clusters lying within a certain distance range from the input vector; the computation time is reduced by not searching the clusters at a greater distance.
This software user manual describes the implementation and use the Extended Testability Analysis (ETA) Tool. The ETA Tool is a software program that augments the analysis and reporting capabilities of a commercial-off-the-shelf (COTS) testability analysis software package called the Testability Engineering And Maintenance System (TEAMS) Designer. An initial diagnostic assessment is performed by the TEAMS Designer software using a qualitative, directed-graph model of the system being analyzed. The ETA Tool utilizes system design information captured within the diagnostic model and testability analysis output from the TEAMS Designer software to create a series of six reports for various system engineering needs. The ETA Tool allows the user to perform additional studies on the testability analysis results by determining the detection sensitivity to the loss of certain sensors or tests. The ETA Tool was developed to support design and development of the NASA Ares I Crew Launch Vehicle. The diagnostic analysis provided by the ETA Tool was proven to be valuable system engineering output that provided consistency in the verification of system engineering requirements. This software user manual provides a description of each output report generated by the ETA Tool. The manual also describes the example diagnostic model and supporting documentation - also provided with the ETA Tool software release package - that were used to generate the reports presented in the manual
To meet the unique challenges of crewed Lunar and Mars precision landings, NASA’s Safe and Precise Landing Integrated Capabilities Evolution project has worked to advance autonomous spacecraft navigation by increasing the technology readiness level of key deorbit, entry, descent, and landing systems, including navigation sensors. Different sensors and their effects on overall system performance are evaluated using six-degree-of-freedom simulations with physics-based engineering models that capture the relevant vehicle systems and environmental effects. Building on an existing simulation framework, this work demonstrates how improved modeling fidelity enables rapid and detailed assessment of various navigation sensors on human-scale Lunar and Mars landing vehicles using NASA reference architectures.
This report describes the Active Noise Cancellation System designed by General Electric and tested in the NASA Lewis Research Center's 48 inch Active Noise Control Fan. The goal of this study was to assess the feasibility of using wall mounted secondary acoustic sources and sensors within the duct of a high bypass turbofan aircraft engine for active noise cancellation of fan tones. The control system is based on a modal control approach. A known acoustic mode propagating in the fan duct is cancelled using an array of flush-mounted compact sound sources. Controller inputs are signals from a shaft encoder and a microphone array which senses the residual acoustic mode in the duct. The canceling modal signal is generated by a modal controller. The key results are that the (6,0) mode was completely eliminated at 920 Hz and substantially reduced elsewhere. The total tone power was reduced 9.4 dB. Farfield 2BPF SPL reductions of 13 dB were obtained. The (4,0) and (4,1) modes were reduced simultaneously yielding a 15 dB modal PWL decrease. Global attenuation of PWL was obtained using an actuator and sensor system totally contained within the duct.
This report documents the performance characteristics of a Targeting Reflective Alignment Concept (TRAC) sensor. The performance will be documented for both short and long ranges. For long ranges, the sensor is used without the flat mirror attached to the target. To better understand the capabilities of the TRAC based sensors, an engineering model is required. The model can be used to better design the system for a particular application. This is necessary because there are many interrelated design variables in application. These include lense parameters, camera, and target configuration. The report presents first an analytical development of the performance, and second an experimental verification of the equations. In the analytical presentation it is assumed that the best vision resolution is a single pixel element. The experimental results suggest however that the resolution is better than 1 pixel. Hence the analytical results should be considered worst case conditions. The report also discusses advantages and limitations of the TRAC sensor in light of the performance estimates. Finally the report discusses potential improvements.
The ability to measure emissions from aeronautic engines and in commercial applications such as automotive emission control and chemical process monitoring is a necessary first step if one is going to actively control those emissions. One single sensor will not give all the information necessary to determine the chemical composition of a high-temperature, harsh environment. Rather, an array of gas sensor arrays--in effect, a high-temperature electronic "nose"--is necessary to characterize the chemical constituents of a diverse, high-temperature environment, such as an emissions stream. The signals produced by this nose could be analyzed to determine the constituents of the emission stream. Although commercial electronic noses for near-room temperature applications exist, they often depend significantly on lower temperature materials or only one sensor type. A separate development effort necessary for a high-temperature electronic nose is being undertaken by the NASA Glenn Research Center, Case Western Reserve University, Ohio State University, and Makel Engineering, Inc. The sensors are specially designed for hightemperature environments. A first-generation high-temperature electronic nose has been demonstrated on a modified automotive engine. This nose sensor array was composed of sensors designed for hightemperature environments fabricated using microelectromechanical-systems- (MEMS-) based technology. The array included a tin-oxide-based sensor doped for nitrogen oxide (NOx) sensitivity, a SiC-based hydrocarbon (CxHy) sensor, and an oxygen sensor (O2). These sensors operate on different principles--resistor, diode, and electrochemical cell, respectively--and each sensor has very different responses to the individual gases in the environment. A picture showing the sensor head for the array is shown in the photograph on the left and the sensors installed in the engine are shown in the photograph on the right. Electronics are interfaced with the sensors for temperature control and signal conditioning, and packaging designed for high temperatures is necessary for the array to survive the engine environment.
This case study format is intended to simulate the experience of facing the same difficult challenges and making the same critical decisions as managers, engineers, and scientists in the Space Shuttle Program. It has been designed for use in the classroom setting to help students develop skills related to decision-making. Students will read about the engine cut-off sensor anomaly which created challenges during the STS-114 mission and have the opportunity to make decisions as lead NASA engineers and Mission Management Team members. Included within this document are three case study presentation options - class discussion, group activity, and open-ended research. Please read the full case prior to in-class presentation to allow ample time for students' analysis and reflection, as well as to prepare additional questions. activities or exercises, material selection, etc. Depending upon the setting of your presentation and the number of participants, please choose at least one presentation format beforehand and plan accordingly. You may expect the following learning objectives by using the proposed formats. Learning Objectives: To enable students to experience the responsibilities of NASA management, engineers, and analysis; to discover possible procedures for investigating system anomalies; to become familiar with the liquid hydrogen low level engine cut-off sensor, including its function, connecting components, and location within the Space Shuttle; and to encourage critical analysis and stimulating discussion of Space Shuttle mission challenges.
Real-Time Failure Control (RTFC) algorithm part of automated monitoring-and-shutdown system being developed to ensure safety and prevent major damage to equipment during ground tests of main engine of space shuttle. Includes redundant sensors, controller voting logic circuits, automatic safe-limit logic circuits, and conditional-decision logic circuits, all monitored by human technicians. Basic principles of system also applicable to stationary powerplants and other complex machinery systems.
During phase 2 research on the application of active noise control to jet engines, the development of multiple-input/multiple-output (MIMO) active adaptive noise control algorithms and acoustic/controls models for turbofan engines were considered. Specific goals for this research phase included: (1) implementation of a MIMO adaptive minimum variance active noise controller; and (2) turbofan engine model development. A minimum variance control law for adaptive active noise control has been developed, simulated, and implemented for single-input/single-output (SISO) systems. Since acoustic systems tend to be distributed, multiple sensors, and actuators are more appropriate. As such, the SISO minimum variance controller was extended to the MIMO case. Simulation and experimental results are presented. A state-space model of a simplified gas turbine engine is developed using the bond graph technique. The model retains important system behavior, yet is of low enough order to be useful for controller design. Expansion of the model to include multiple stages and spools is also discussed.
High-temperature environment operable sensors and electronics are required for exploring the inner solar planets and distributed control of next generation aeronautical engines. Various silicon carbide (SiC) high temperature sensors, actuators, and electronics have been demonstrated at and above 500C. A compatible packaging system is essential for long-term testing and application of high temperature electronics and sensors. High temperature passive components are also necessary for high temperature electronic systems. This talk will discuss ceramic packaging systems developed for high temperature electronics, and related testing results of SiC circuits at 500C and silicon-on-insulator (SOI) integrated circuits at temperatures beyond commercial limit facilitated by these high temperature packaging technologies. Dielectric materials for high temperature multilayers capacitors will also be discussed. High-temperature environment operable sensors and electronics are required for probing the inner solar planets and distributed control of next generation aeronautical engines. Various silicon carbide (SiC) high temperature sensors, actuators, and electronics have been demonstrated at and above 500C. A compatible packaging system is essential for long-term testing and eventual applications of high temperature electronics and sensors. High temperature passive components are also necessary for high temperature electronic systems. This talk will discuss ceramic packaging systems developed for high electronics and related testing results of SiC circuits at 500C and silicon-on-insulator (SOI) integrated circuits at temperatures beyond commercial limit facilitated by high temperature packaging technologies. Dielectric materials for high temperature multilayers capacitors will also be discussed.
The visualization front-end of a Decision Support System (DSS) also includes an analysis engine linked to vehicle telemetry, and a database of learned models for known behaviors. Because the display is graphical rather than text-based, the summarization it provides has a greater information density on one screen for evaluation by a flight controller.This tool provides a system-level visualization of the state of a vehicle, and drill-down capability for more details and interfaces to separate analysis algorithms and sensor data streams. The system-level view is a 3D rendering of the vehicle, with sensors represented as icons, tied to appropriate positions within the vehicle body and colored to indicate sensor state (e.g., normal, warning, anomalous state, etc.). The sensor data is received via an Information Sharing Protocol (ISP) client that connects to an external server for real-time telemetry. Users can interactively pan, zoom, and rotate this 3D view, as well as select sensors for a detail plot of the associated time series data. Subsets of the plotted data can be selected and sent to an external analysis engine to either search for a similar time series in an historical database, or to detect anomalous events. The system overview and plotting capabilities are completely general in that they can be applied to any vehicle instrumented with a collection of sensors. This visualization component can interface with the ISP for data streams used by NASA s Mission Control Center at Johnson Space Center. In addition, it can connect to, and display results from, separate analysis engine components that identify anomalies or that search for past instances of similar behavior. This software supports NASA's Software, Intelligent Systems, and Modeling element in the Exploration Systems Research and Technology Program by augmenting the capability of human flight controllers to make correct decisions, thus increasing safety and reliability. It was designed specifically as a tool for NASA's flight controllers to monitor the International Space Station and a future Crew Exploration Vehicle.
The NASA Glenn Research Center at Lewis Field, in cooperation with Rocketdyne, has designed, developed, and implemented an automated Post-Test Diagnostic System (PTDS) for the X-33 linear aerospike engine. The PTDS was developed to reduce analysis time and to increase the accuracy and repeatability of rocket engine ground test fire and flight data analysis. This diagnostic system provides a fast, consistent, first-pass data analysis, thereby aiding engineers who are responsible for detecting and diagnosing engine anomalies from sensor data. It uses analytical methods modeled after the analysis strategies used by engineers. Glenn delivered the first version of PTDS in September of 1998 to support testing of the engine s power pack assembly. The system was used to analyze all 17 power pack tests and assisted Rocketdyne engineers in troubleshooting both data acquisition and test article anomalies. The engine version of PTDS, which was delivered in June of 1999, will support all single-engine, dual-engine, and flight firings of the aerospike engine.
The design of a Ride Quality Augmentation System (RQAS) for commuter aircraft is documented. The RQAS is designed for a Cessna 402B, an 8 passenger prop twin representative to this class of aircraft. The purpose of the RQAS is the reduction of vertical and lateral accelerations of the aircraft due to atmospheric turbulence by the application of active control. The detailed design of the hardware (the aircraft modifications, the Ride Quality Instrumentation System (RQIS), and the required computer software) is examined. The aircraft modifications, consisting of the dedicated control surfaces and the hydraulic actuation system, were designed at Cessna Aircraft by Kansas University-Flight Research Laboratory. The instrumentation system, which consist of the sensor package, the flight computer, a Data Acquisition System, and the pilot and test engineer control panels, was designed by NASA-Langley. The overall system design and the design of the software, both for flight control algorithms and ground system checkout are detailed. The system performance is predicted from linear simulation results and from power spectral densities of the aircraft response to a Dryden gust. The results indicate that both accelerations are possible.
Topics covered include: Semiautonomous Avionics-and-Sensors System for a UAV; Biomimetic/Optical Sensors for Detecting Bacterial Species; System Would Detect Foreign-Object Damage in Turbofan Engine; Detection of Water Hazards for Autonomous Robotic Vehicles; Fuel Cells Utilizing Oxygen From Air at Low Pressures; Hybrid Ion-Detector/Data-Acquisition System for a TOF-MS; Spontaneous-Desorption Ionizer for a TOF-MS; Equipment for On-Wafer Testing From 220 to 325 GHz; Computing Isentropic Flow Properties of Air/R-134a Mixtures; Java Mission Evaluation Workstation System; Using a Quadtree Algorithm To Assess Line of Sight; Software for Automated Generation of Cartesian Meshes; Optics Program Modified for Multithreaded Parallel Computing; Programs for Testing Processor-in-Memory Computing Systems; PVM Enhancement for Beowulf Multiple-Processor Nodes; Ion-Exclusion Chromatography for Analyzing Organics in Water; Selective Plasma Deposition of Fluorocarbon Films on SAMs; Water-Based Pressure-Sensitive Paints; System Finds Horizontal Location of Center of Gravity; Predicting Tail Buffet Loads of a Fighter Airplane; Water Containment Systems for Testing High-Speed Flywheels; Vapor-Compression Heat Pumps for Operation Aboard Spacecraft; Multistage Electrophoretic Separators; Recovering Residual Xenon Propellant for an Ion Propulsion System; Automated Solvent Seaming of Large Polyimide Membranes; Manufacturing Precise, Lightweight Paraboloidal Mirrors; Analysis of Membrane Lipids of Airborne Micro-Organisms; Noninvasive Diagnosis of Coronary Artery Disease Using 12-Lead High-Frequency Electrocardiograms; Dual-Laser-Pulse Ignition; Enhanced-Contrast Viewing of White-Hot Objects in Furnaces; Electrically Tunable Terahertz Quantum-Cascade Lasers; Few-Mode Whispering-Gallery-Mode Resonators; Conflict-Aware Scheduling Algorithm; and Real-Time Diagnosis of Faults Using a Bank of Kalman Filters.