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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 NTRS1996

The smart highway project: Smart highways, smart vehicles, smart engineering

The Smart Highway project is a six mile, limited access roadway being built between Interstate 81 and Blacksburg, Virginia. The initial construction segment will be two miles long and is designed to serve as a test bed and test track for Intelligent Transportation Systems (ITS) research. The Center for Transportation Research (CTR) at Virginia Tech is developing three evaluation tools for its ITS research including DYNAVIMTS (a software framework), and the FLASH Lab (a 1/15th scale model highway and vehicle system). The Smart Highway rounds out the Center's evaluation methodology by allowing full scale operational tests, evaluations, and research under both experimental and conventional traffic conditions. Currently under development is a concept for a fully automated highway using a 'Cooperative Infrastructure Managed System' which involves ultra wide band communication beacons installed in the infrastructure with appropriate sensors, receivers and processors on board the vehicles. The project is part of the research program funded by the National Automated Highway System Consortium. The CTR hopes to develop the automated concept to prototype status by 1997. Other smart transportation and smart engineering concepts are proposed. This presentation will address the goals and objectives of the Smart Highway project, overview its status and importance to the region, and identify some of the transportation technology now under development and planned in the future.

Pethtel, Ray D.↗

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 NTRS2002

Latest Development in Advanced Sensors at Kennedy Space Center (KSC)

Inexpensive space transportation system must be developed in order to make spaceflight more affordable. To achieve this goal, there is a need to develop inexpensive smart sensors to allow autonomous checking of the health of the vehicle and associated ground support equipment, warn technicians or operators of an impending problem and facilitate rapid vehicle pre-launch operations. The Transducers and Data Acquisition group at Kennedy Space Center has initiated an effort to study, research, develop and prototype inexpensive smart sensors to accomplish these goals. Several technological challenges are being investigated and integrated in this project multi-discipline sensors; self-calibration, health self-diagnosis capabilities embedded in sensors; advanced data acquisition systems with failure prediction algorithms and failure correction (self-healing) capabilities.

Perotti, Jose M.↗

NASA NTRS2010

Comparison of Node-Centered and Cell-Centered Unstructured Finite-Volume Discretizations: Inviscid Fluxes

Cell-centered and node-centered approaches have been compared for unstructured finite-volume discretization of inviscid fluxes. The grids range from regular grids to irregular grids, including mixed-element grids and grids with random perturbations of nodes. Accuracy, complexity, and convergence rates of defect-correction iterations are studied for eight nominally second-order accurate schemes: two node-centered schemes with weighted and unweighted least-squares (LSQ) methods for gradient reconstruction and six cell-centered schemes two node-averaging with and without clipping and four schemes that employ different stencils for LSQ gradient reconstruction. The cell-centered nearest-neighbor (CC-NN) scheme has the lowest complexity; a version of the scheme that involves smart augmentation of the LSQ stencil (CC-SA) has only marginal complexity increase. All other schemes have larger complexity; complexity of node-centered (NC) schemes are somewhat lower than complexity of cell-centered node-averaging (CC-NA) and full-augmentation (CC-FA) schemes. On highly anisotropic grids typical of those encountered in grid adaptation, discretization errors of five of the six cell-centered schemes converge with second order on all tested grids; the CC-NA scheme with clipping degrades solution accuracy to first order. The NC schemes converge with second order on regular and/or triangular grids and with first order on perturbed quadrilaterals and mixed-element grids. All schemes may produce large relative errors in gradient reconstruction on grids with perturbed nodes. Defect-correction iterations for schemes employing weighted least-square gradient reconstruction diverge on perturbed stretched grids. Overall, the CC-NN and CC-SA schemes offer the best options of the lowest complexity and secondorder discretization errors. On anisotropic grids over a curved body typical of turbulent flow simulations, the discretization errors converge with second order and are small for the CC-NN, CC-SA, and CC-FA schemes on all grids and for NC schemes on triangular grids; the discretization errors of the CC-NA scheme without clipping do not converge on irregular grids. Accurate gradient reconstruction can be achieved by introducing a local approximate mapping; without approximate mapping, only the NC scheme with weighted LSQ method provides accurate gradients. Defect correction iterations for the CC-NA scheme without clipping diverge; for the NC scheme with weighted LSQ method, the iterations either diverge or converge very slowly. The best option in curved geometries is the CC-SA scheme that offers low complexity, second-order discretization errors, and fast convergence.

Diskin, Boris↗

NASA NTRS1985

Computer architectures for computational physics work done by Computational Research and Technology Branch and Advanced Computational Concepts Group

Slides are reproduced that describe the importance of having high performance number crunching and graphics capability. They also indicate the types of research and development underway at Ames Research Center to ensure that, in the near term, Ames is a smart buyer and user, and in the long-term that Ames knows the best possible solutions for number crunching and graphics needs. The drivers for this research are real computational physics applications of interest to Ames and NASA. They are concerned with how to map the applications, and how to maximize the physics learned from the results of the calculations. The computer graphics activities are aimed at getting maximum information from the three-dimensional calculations by using the real time manipulation of three-dimensional data on the Silicon Graphics workstation. Work is underway on new algorithms that will permit the display of experimental results that are sparse and random, the same way that the dense and regular computed results are displayed.

Source record↗

NASA NTRS2008

Overview of the Smart Network Element Architecture and Recent Innovations

In industrial environments, system operators rely on the availability and accuracy of sensors to monitor processes and detect failures of components and/or processes. The sensors must be networked in such a way that their data is reported to a central human interface, where operators are tasked with making real-time decisions based on the state of the sensors and the components that are being monitored. Incorporating health management functions at this central location aids the operator by automating the decision-making process to suggest, and sometimes perform, the action required by current operating conditions. Integrated Systems Health Management (ISHM) aims to incorporate data from many sources, including real-time and historical data and user input, and extract information and knowledge from that data to diagnose failures and predict future failures of the system. By distributing health management processing to lower levels of the architecture, there is less bandwidth required for ISHM, enhanced data fusion, make systems and processes more robust, and improved resolution for the detection and isolation of failures in a system, subsystem, component, or process. The Smart Network Element (SNE) has been developed at NASA Kennedy Space Center to perform intelligent functions at sensors and actuators' level in support of ISHM.

Perotti, Jose M.↗

NASA NTRSDate not supplied

Flight Test Configuration of the Sensor Payload and the Ground Nodes in Distributed Sensing Frameworks

The realization of the Urban Air Mobility (UAM) vision, entailing the deployment of high-density autonomous flights over urban areas, necessitates methodologies transcending contemporary airborne sensing techniques. An instrumental innovation in this realm is the advent of distributed sensing. In this paradigm, environmental sensors function as active agents, engaging in the triad of sensing, processing, and communication either amongst themselves, with ground stations, or both. This concerted effort creates a dynamic and responsive "smart space," facilitating real-time autonomous control. NASA Ames Research Center is actively engaged in a series of comprehensive indoor and outdoor flight tests to garner requisite data and insights essential for the actualization of this ambitious vision. This paper delineates the holistic configuration of the flight payload and the distributed ground nodes pivotal to the NASA flight test campaign. Furthermore, it expounds upon the intricacies of the sensor node communication framework. The narrative extends to provide a detailed overview of the strategic placement of distributed sensors and a comprehensive account of the varied indoor and outdoor flight tests orchestrated in pursuit of UAM objectives.

urban air mobility↗

NASA NTRSDate not supplied

Flight Test Configuration of the Sensor Payload and the Ground Nodes in Distributed Sensing Frameworks

urban air mobility↗

NASA NTRS2005

Intelligent Sensors: An Integrated Systems Approach

The need for intelligent sensors as a critical component for Integrated System Health Management (ISHM) is fairly well recognized by now. Even the definition of what constitutes an intelligent sensor (or smart sensor) is well documented and stems from an intuitive desire to get the best quality measurement data that forms the basis of any complex health monitoring and/or management system. If the sensors, i.e. the elements closest to the measurand, are unreliable then the whole system works with a tremendous handicap. Hence, there has always been a desire to distribute intelligence down to the sensor level, and give it the ability to assess its own health thereby improving the confidence in the quality of the data at all times. This paper proposes the development of intelligent sensors as an integrated systems approach, i.e. one treats the sensors as a complete system with its own sensing hardware (the traditional sensor), A/D converters, processing and storage capabilities, software drivers, self-assessment algorithms, communication protocols and evolutionary methodologies that allow them to get better with time. Under a project being undertaken at the NASA Stennis Space Center, an integrated framework is being developed for the intelligent monitoring of smart elements. These smart elements can be sensors, actuators or other devices. The immediate application is the monitoring of the rocket test stands, but the technology should be generally applicable to the Intelligent Systems Health Monitoring (ISHM) vision. This paper outlines some fundamental issues in the development of intelligent sensors under the following two categories: Physical Intelligent Sensors (PIS) and Virtual Intelligent Sensors (VIS).

Mahajan, Ajay↗

NASA NTRS2000

Hydrogen Sensors Demonstrated on the Shuttle

Microelectromechanical-systems- (MEMS-) based hydrogen sensor technology developed by the NASA Glenn Research Center at Lewis Field and Case Western Reserve University was demonstrated on shuttle missions STS-95 (Senator Glenn s mission) and STS-96. These smart sensors, commercialized by Makel Engineering Inc., were part of an "Integrated Vehicle Health Monitoring HEDS Technology Demonstration" series conducted at the NASA Kennedy Space Center. The experiments were designed to demonstrate the effect of technological upgrades on shuttle performance. The hydrogen sensors were micro-fabricated for minimal size, weight, and power consumption. A temperature detector and heater were included on the sensor for temperature control. Two palladium chrome (PdCr) hydrogen detection devices were included in each sensor package: a Schottky diode for low concentrations and a resistor for high concentrations. These sensor designs allow operation in inert environments. "Smart" electronics developed by Makel Engineering were integrated with the sensors to control the sensor temperature and process the output of the various sensors. This complete hydrogen detection system (two sensors on a chip with smart electronics) flew on STS-95 (launched October 1998) and STS-96 (launched May 1999). It was installed in the aft compartment of the shuttle and used to monitor the hydrogen concentration in that region. Up to this time, a mass spectrometer had monitored the hydrogen concentration in the aft compartment before launch, and "grab" bottles had been used after launch. The inside of these bottles is at vacuum. During flight, the grab bottles are pyrotechnically opened for a brief period, and the gas in the aft compartment is captured in the bottle. Several of these bottles are opened at different times during takeoff, and their contents are used to determine the time profile of the gases in the aft chamber. However, this information is not available until after the flight. On the launch pad, results from the new sensor technology paralleled the responses of the mass spectrometer with, in some cases, a quicker response time. In flight, data from the new sensors agreed with those derived from analyzing the contents of the grab bottles. Moreover, this microsensor can monitor the aft compartment continuously and, in principle, could monitor the health of the vehicle in real time during flight.

Hunter, Gary W.↗

NASA NTRS1997

Novel Multidisciplinary Models Assess the Capabilities of Smart Structures to Manage Vibration, Sound, and Thermal Distortion in Aeropropulsion Components

The development of aeropropulsion components that incorporate "smart" composite laminates with embedded piezoelectric actuators and sensors is expected to ameliorate critical problems in advanced aircraft engines related to vibration, noise emission, and thermal stability. To facilitate the analytical needs of this effort, the NASA Lewis Research Center has developed mechanics and multidisciplinary computational models to analyze the complicated electromechanical behavior of realistic smart-structure configurations operating in combined mechanical, thermal, and acoustic environments. The models have been developed to accommodate the particular geometries, environments, and technical challenges encountered in advanced aircraft engines, yet their unique analytical features are expected to facilitate application of this new technology in a variety of commercial applications.

Saravanos, Dimitris A.↗

NASA NTRS1999

Contributions to Active Buffeting Alleviation Programs by the NASA Langley Research Center

Buffeting is an aeroelastic phenomenon which plagues high performance aircraft, especially those with twin vertical tails like the F/A-18, at high angles of attack. This buffeting is a concern from fatigue and inspection points of view. By means of wind-tunnel and flight tests, this phenomenon is well studied to the point that buffet loads can be estimated and fatigue life can be increased by structural enhancements to the airframe. In more recent years, buffeting alleviation through active control of smart materials has been highly researched in wind-tunnel proof-of-concept demonstrations and full-scale ground tests using the F/A-18 as a test bed. Because the F/A-18 resides in fleets outside as well as inside the United States, these tests have evolved into international collaborative research activities with Australia and Canada, coordinated by the Air Force Research Laboratory (AFRL) and conducted under the auspices of The Technical Cooperation Program (TTCP). With the recent successes and advances in smart materials, the main focus of these buffeting alleviation tests has also evolved to a new level: utilize the F/A-18 as a prototype to mature smart materials for suppressing vibrations of aerospace structures. The role of the NASA Langley Research Center (LaRC) in these programs is presented.

Moses, Robert W.↗

NASA NTRS2005

Physical Intelligent Sensors

This paper proposes the development of intelligent sensors as part of an integrated systems approach, i.e. one treats the sensors as a complete system with its own sensing hardware (the traditional sensor), A/D converters, processing and storage capabilities, software drivers, self-assessment algorithms, communication protocols and evolutionary methodologies that allow them to get better with time. Under a project being undertaken at the NASA s Stennis Space Center, an integrated framework is being developed for the intelligent monitoring of smart elements. These smart elements can be sensors, actuators or other devices. The immediate application is the monitoring of the rocket test stands, but the technology should be generally applicable to the Integrated Systems Health Monitoring (ISHM) vision. This paper outlines progress made in the development of intelligent sensors by describing the work done till date on Physical Intelligent Sensors (PIS). The PIS discussed here consists of a thermocouple used to read temperature in an analog form which is then converted into digital values. A microprocessor collects the sensor readings and runs numerous embedded event detection routines on the collected data and if any event is detected, it is reported, stored and sent to a remote system through an Ethernet connection. Hence the output of the PIS is data coupled with confidence factor in the reliability of the data which leads to information on the health of the sensor at all times. All protocols are consistent with IEEE 1451.X standards. This work lays the foundation for the next generation of smart devices that have embedded intelligence for distributed decision making capabilities.

Bandhil, Pavan↗

NASA NTRS2005

Intelligent Sensors: Strategies for an Integrated Systems Approach

This paper proposes the development of intelligent sensors as an integrated systems approach, i.e. one treats the sensors as a complete system with its own sensing hardware (the traditional sensor), A/D converters, processing and storage capabilities, software drivers, self-assessment algorithms, communication protocols and evolutionary methodologies that allow them to get better with time. Under a project being undertaken at the Stennis Space Center, an integrated framework is being developed for the intelligent monitoring of smart elements. These smart elements can be sensors, actuators or other devices. The immediate application is the monitoring of the rocket test stands, but the technology should be generally applicable to the Intelligent Systems Health Monitoring (ISHM) vision. This paper outlines progress made in the development of intelligent sensors by describing the work done till date on Physical Intelligent Sensors (PIS) and Virtual Intelligent Sensors (VIS).

Chitikeshi, Sanjeevi↗

NASA NTRS2012

Optimal Topology and Experimental Evaluation of Piezoelectric Materials for Actively Shunted General Electric Polymer Matrix Fiber Composite Blades

NASA Glenn Research Center, in collaboration with GE Aviation, has begun the development of a smart adaptive structure system with piezoelectric (PE) transducers to improve composite fan blade damping at resonances. Traditional resonant damping approaches may not be realistic for rotating frame applications such as engine blades. The limited space in which the blades reside in the engine makes it impossible to accommodate the circuit size required to implement passive resonant damping. Thus, a novel digital shunt scheme has been developed to replace the conventional electric passive shunt circuits. The digital shunt dissipates strain energy through the load resistor on a power amplifier. General Electric (GE) designed and fabricated a variety of polymer matrix fiber composite (PMFC) test specimens. Investigating the optimal topology of PE sensors and actuators for each test specimen has revealed the best PE transducer location for each target mode. Also a variety of flexible patches, which can conform to the blade surface, have been tested to identify the best performing PE patch. The active damping control achieved significant performance at target modes. This work has been highlighted by successful spin testing up to 5000 rpm of subscale GEnx composite blades in Glenn s Dynamic Spin Rig.

Choi, Benjamin B.↗

NASA NTRSDate not supplied

A Structurally-Adaptive Framework for Distributed Airborne Sensing over Real-time Collaborative Information Sharing Networks

The emergence and maturation of wireless communication technologies continue to transform the aviation industry and are enabling new solutions to challenges faced by NASA’s Advanced Air Mobility (AAM) initiative. AAM is leading towards high-density autonomous aircraft operations in areas underserved by traditional aviation, such as over densely populated urban centers. In this paper, we build on concepts from distributed sensing and smart spaces - where sensing, processing, and communication are embedded in an environment, and agents are operating within the space can exploit these capabilities in real-time through collaborative information sharing networks. Building from these concepts, we propose a framework to enable a dynamic, topologically-adaptive, and distributed estimation system for man-rated aviation to address challenges faced by autonomous AAM operations. This paper presents the initial concept of operations and system design for this framework, presents a mathematical formulation for abstraction of the problem, identifies requirements and constraints for operation, and presents algorithmic constructs to demonstrate operation. The initial framework design will focus on supporting precision navigation and independent surveillance supporting conformance monitoring of aircraft in airspace corridors and vertiport airspaces. Preliminary results from this framework shows promise in addressing gaps in current technologies needed to enable future AAM concepts, while promising greater capabilities, performance, robustness, and safety over current aviation systems and operations.

Distributed sensing↗

NASA NTRS1993

Solid Modeling Aerospace Research Tool (SMART) user's guide, version 2.0

The Solid Modeling Aerospace Research Tool (SMART) software package is used in the conceptual design of aerospace vehicles. It provides a highly interactive and dynamic capability for generating geometries with Bezier cubic patches. Features include automatic generation of commonly used aerospace constructs (e.g., wings and multilobed tanks); cross-section skinning; wireframe and shaded presentation; area, volume, inertia, and center-of-gravity calculations; and interfaces to various aerodynamic and structural analysis programs. A comprehensive description of SMART and how to use it is provided.

Mcmillin, Mark L.↗

NASA NTRS2005

All-Terrain Intelligent Robot Braves Battlefront to Save Lives

As NASA s lead center for creating robotic spacecraft and rovers, the Jet Propulsion Laboratory (JPL) builds smart machines that can perform very complicated tasks, far, far away from the homeland. JPL s robotic proficiency is making an impact millions of miles away on Mars, where two rovers are presently unlocking the secrets of the Red Planet s rugged terrain, and thousands of miles away in the embattled regions of Iraq and Afghanistan, where robots sown from the seeds of JPL machines have been deployed to be the "eyes and ears" of humans on the front line. This commercial offspring, known as the PackBot Tactical Mobile Robot, is manufactured by iRobot, Inc., of Burlington, Massachusetts.

Source record↗