SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Light scattering off particles flowing through a two-slit interference pattern can be used to measure the shear stress of the fluid. We have designed and fabricated a miniature diffractive optic sensor based on this principle.
The objectives of this program are to develop heat flux sensors suitable for installation in hot section airfoils of advanced aircraft turbine engines and to experimentally verify the operation of these heat flux sensors in a cylinder in a cross flow experiment. Embedded thermocouple and Gardon gauge sensors were developed and fabricated into both blades and vanes. These were then calibrated using a quartz lamp bank heat source and finally subjected to thermal cycle and thermal soak testing. These sensors were also fabricated into cylindrical test pieces and tested in a burner exhaust to verify heat flux measurements produced by these sensors. The results of the cylinder in cross flow tests are given.
An experimental and numerical investigation of the thermochemical state of arcjet flows is currently being conducted at NASA Ames Research Center. The experimental approach relies on the use of laser- and emission-spectroscopic diagnostic techniques in three regions of the flow. A fiber optic sensor is used to record spectrally resolved emission signals from the electrode package region, where the flow is most likely to be in thermochemical equilibrium. A second emission diagnostic measurement is made in the shock layer formed over a blunt-body test article placed in the stream, and a CCD camera is used to simultaneously record spectral emission from several measurement locations along the stagnation streamline. Downstream of the nozzle exit, but upstream of the test article, Laser-Induced Fluorescence (LIF) of atomic nitrogen is used to assess the nonequilibrium distribution of flow enthalpy in the free stream. Results from the measurements are compared with predictions from a two-temperature, axisymmetric flow model that solves the nozzle and shock-layer flows.
Design features and characteristics of a means for measuring total temperature and total pressure at a single point in a gas stream are presented. A rake that provides five such combination measurements is described. Experimental data are included for the aerodynamic recovery and time response of the temperature sensor and for the flow-angle sensitivity of both the temperature and pressure sensors. Data were obtained over a subsonic Mach number range of 0.3 to 0.9 as well as at a Mach number of 1.4.
Wake vortex monitoring systems, especially those using laser Doppler sensors, were investigated. The initial phases of the effort involved talking with potential users (air traffic controllers, pilots, etc.) of a wake vortex monitoring system to determine system requirements from the user's viewpoint. These discussions involved the volumes of airspace to be monitored for vortices, and potential methods of using the monitored vortex data once the data are available. A subsequent task led to determining a suitable mathematical model of the vortex phenomena and developing a mathematical model of the laser Doppler sensor for monitoring the vortex flow field. The mathematical models were used in combination to help evaluate the capability of laser Doppler instrumentation in monitoring vortex flow fields both in the near vicinity of the sensor (within 1 kilometer and at long ranges(10 kilometers).
Cross flow and parallel flow concepts of fluidic wind speed sensors
An analysis of the flow state on a trapezoidal wing model from the NASA 3-D High Lift Flow Physics Experiment is presented. The objective of the experiment was to characterize the flow over a non-proprietary semi-span three-element high-lift configuration to aid in assessing the state of the art in the computation of three-dimensional high-lift flows. Surface pressures and hot-film sensors are used to determine the flow conditions on the slat, main, and flap. The locations of the attachments lines and the values of the attachment line Reynolds number are estimated based on the model surface pressures. Data from the hot-films are used to determine if the flow is laminar, transitional, or turbulent by examining the hot-film time histories, statistics, and frequency spectra.
Topics include: Computational Ghost Imaging for Remote Sensing; Digital Architecture for a Trace Gas Sensor Platform; Dispersed Fringe Sensing Analysis - DFSA; Indium Tin Oxide Resistor-Based Nitric Oxide Microsensors; Gas Composition Sensing Using Carbon Nanotube Arrays; Sensor for Boundary Shear Stress in Fluid Flow; Model-Based Method for Sensor Validation; Qualification of Engineering Camera for Long-Duration Deep Space Missions; Remotely Powered Reconfigurable Receiver for Extreme Environment Sensing Platforms; Bump Bonding Using Metal-Coated Carbon Nanotubes; In Situ Mosaic Brightness Correction; Simplex GPS and InSAR Inversion Software; Virtual Machine Language 2.1; Multi-Scale Three-Dimensional Variational Data Assimilation System for Coastal Ocean Prediction; Pandora Operation and Analysis Software; Fabrication of a Cryogenic Bias Filter for Ultrasensitive Focal Plane; Processing of Nanosensors Using a Sacrificial Template Approach; High-Temperature Shape Memory Polymers; Modular Flooring System; Non-Toxic, Low-Freezing, Drop-In Replacement Heat Transfer Fluids; Materials That Enhance Efficiency and Radiation Resistance of Solar Cells; Low-Cost, Rugged High-Vacuum System; Static Gas-Charging Plug; Floating Oil-Spill Containment Device; Stemless Ball Valve; Improving Balance Function Using Low Levels of Electrical Stimulation of the Balance Organs; Oxygen-Methane Thruster; Lunar Navigation Determination System - LaNDS; Launch Method for Kites in Low-Wind or No-Wind Conditions; Supercritical CO2 Cleaning System for Planetary Protection and Contamination Control Applications; Design and Performance of a Wideband Radio Telescope; Finite Element Models for Electron Beam Freeform Fabrication Process Autonomous Information Unit for Fine-Grain Data Access Control and Information Protection in a Net-Centric System; Vehicle Detection for RCTA/ANS (Autonomous Navigation System); Image Mapping and Visual Attention on the Sensory Ego-Sphere; HyDE Framework for Stochastic and Hybrid Model-Based Diagnosis; and IMAGESEER - IMAGEs for Education and Research.
The measurement of shear stress developed as a fluid moves around a solid body is difficult to measure. Stresses at the fluid-solid interface are very small and the nature of the fluid flow is easily disturbed by introducing sensor components to the interface. To address these challenges, an array of direct and indirect techniques have been investigated with various advantages and challenges. Hot wire sensors and other indirect sensors all protrude significantly into the fluid flow. Microelectromechanical systems (MEMS) devices, although facilitating very accurate measurements, are not durable, are prone to contamination, and are difficult to implement into existing model geometries. One promising approach is the use of engineered surfaces that interact with fluid flow in a detectable manner. To this end, standard lithographic techniques have been utilized to generate elastomeric micropillar arrays of various lengths and diameters. Micropillars of controlled length and width were generated in polydimethylsiloxane (PDMS) elastomer using a soft-lithography technique. The 3D mold for micropillar replication was fabricated using laser ablative micromachining and contact lithography. Micropillar dimensions and mechanical properties were characterized and compared to shear sensing requirements. The results of this characterization as well as shear stress detection techniques will be discussed.
Arrays of actuators are affixed to structural elements to impede the transmission of vibrational energy. A single pair is used to provide control of bending and extensional waves and two pairs are used to control torsional motion. The arrays are applied to a wide variety of structural elements such as a beam structure that is part of a larger framework that may or may not support a rigid or non-rigid skin. Electrical excitation is applied to the actuators that generate forces on the structure. These electrical inputs may be adjusted in their amplitude and phase by a controller in communication with appropriate vibrational wave sensors to impede the flow of vibrational power in all of the above mentioned wave forms beyond the actuator location. Additional sensor elements can be used to monitor the performance and adjust the electrical inputs to maximize the attenuation of vibrational energy.
The responses of a hot film sensor and a pressure probe to acoustic excitation in steady flow up to a Mach number of 0.5 were measured and compared with the responses of a microphone, flush mounted in the wall of the flow duct. When compared in terms of fluctuating pressure, the response of the pressure probe was less than that of the wall microphone by about 2.1 dB or less at the 0.5 Mach number, while the response of the ho film probe was as much as 6.0 dB above that of the wall sensor, at the Mach numbers 0.3 and 0.5. In terms of fluctuating Reynolds number, the response of the hot film probe was greater than that of the wall-mounted sensor by at most 5.0 dB at the same Mach numbers. Removing the response contribution from fluctuating temperature in the hot film mathematical model improved the agreement between the two transducer responses for both comparisons.
Proposed acoustic sensor measures density of flowing gas or mixture of gases. Constructed in variety of configurations for use in monitoring industrial processes. Basic configuration, sensor comprises narrow tube closed at one end and open at other, sound transmitter located in closed end, and microphone located part way along tube. Entire sensor, or at least open end of tube, placed inside pipe or vessel containing gas, density of which measured. Transducer produces constant-velocity-amplitude sound waves at frequency lower than fundamental resonant frequency of tube.
The Solar, Anomalous, and Magnetospheric Particle Explorer (SAMPEX) science pointing mode is presented with the additional constraint of velocity avoidance. This constraint has been added in light of the orbital debris and micrometeoroid fluxes that have been revealed by the Long Duration Exposure Facility (LDEF) recovered in January 1990. These fluxes are 50-100 times higher than the flux tables that were used in the September 1988 proposal to NASA for the SAMPEX mission. The SAMPEX Heavey Ion Large Telescope (HILT) sensor includes a flow-through isobutane proportional counter that is susceptible to penetration by orbital debris and micrometeoroids. Thus, keeping the HILT sensor pointed away from the velocity vector, the direction of maximum flux, will compensate for the higher than expected fluxes. Using an orbital debris model and a micrometeoroid model developed at the Johnson Space Center (JSC), and a SAMPEX dynamic simulator developed by the Guidance and Control Branch at the Goddard Space Flight Center (GSFC), an 'optimal' minimum ram angle (the angle between the HILT boresight and the velocity vector) of 90 degrees has been determined. It is optimal in the sense of minimizing the science pointing performance degradation while providing approximately an 89 percent chance of survival for the HILT sensor over a three year period.
A system that incorporates inertial sensor information into optical flow computations to detect obstacles and to provide alternative navigational paths free from obstacles. The system is a maximally passive obstacle detection system that makes selective use of an active sensor. The active detection typically utilizes a laser. Passive sensor suite includes binocular stereo, motion stereo and variable fields-of-view. Optical flow computations involve extraction, derotation and matching of interest points from sequential frames of imagery, for range interpolation of the sensed scene, which in turn provides obstacle information for purposes of safe navigation.
Safe and effective generation of terrestrial nuclear power greatly benefits from the actionable data provided by the array of sensors located throughout a plant to provide a holistic online indication of reactor operation. This array includes sensors for monitoring coolant flow and pressure, temperature and heat transfer, radiation levels, structure health monitoring, and other critical parameters for reactor operation. While sensors capable of measuring these parameters have been developed, the electronics used in the pre-amplification and analog-to-digital conversion of the small signals they produce are extremely sensitive and susceptible to damage by high-temperatures and radiation environments nuclear reactors encounter while generating power. The small signals from sensors in nuclear power plants (NPPs) are transmitted over long cable runs which introduce dispersion artifacts into the signals of interest as well as electromagnetic interference (EMI) from lighting fixtures, pumps, mains electricity, and other equipment. To overcome these challenges, a front-end digitization (FREND) platform has been developed to use radiation-tolerant electronics to multiplex, amplify, and optically encode signals from an array of sensors for transmission over an optical fiber to mitigate dispersion and EMI artifacts from long runs of electrical cabling. To recover the optically transmitted data, a signal processing scheme based on 1-dimensional template matching to an indexing channel is described herein and demonstrated to have an effective bit-depth of 9.2 bits (1%). This scheme has been validated in proof-of-concept, non-nuclear testing and preliminary experimental results show good agreement between the measured optical output and and sensor input signals. The FREND system represents a low-loss data link between sensors in nuclear environments and data acquisition hardware which is aimed at improving the signal-to-noise ratio of the data acquired from these sensors to provide better information to operators and researchers.
Efficacy of existing on-board propulsion systems health management systems (HMS) are severely impacted by computational limitations (e.g., low sampling rates); paradigmatic limitations (e.g., low-fidelity logic/parameter redlining only, false alarms due to noisy/corrupted sensor signatures, preprogrammed diagnostics only); and telemetry bandwidth limitations on space/ground interactions. Ultra-compact/light, adaptive neural networks with massively parallel, asynchronous, fast reconfigurable and fault-tolerant information processing properties have already demonstrated significant potential for inflight diagnostic analyses and resource allocation with reduced ground dependence. In particular, they can automatically exploit correlation effects across multiple sensor streams (plume analyzer, flow meters, vibration detectors, etc.) so as to detect anomaly signatures that cannot be determined from the exploitation of single sensor. Furthermore, neural networks have already demonstrated the potential for impacting real-time fault recovery in vehicle subsystems by adaptively regulating combustion mixture/power subsystems and optimizing resource utilization under degraded conditions. A class of high-performance neuroprocessors, developed at JPL, that have demonstrated potential for next-generation HMS for a family of space transportation vehicles envisioned for the next few decades, including HLLV, NLS, and space shuttle is presented. Of fundamental interest are intelligent neuroprocessors for real-time plume analysis, optimizing combustion mixture-ratio, and feedback to hydraulic, pneumatic control systems. This class includes concurrently asynchronous reprogrammable, nonvolatile, analog neural processors with high speed, high bandwidth electronic/optical I/O interfaced, with special emphasis on NASA's unique requirements in terms of performance, reliability, ultra-high density ultra-compactness, ultra-light weight devices, radiation hardened devices, power stringency, and long life terms.
Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate expected sensor values for targeted fault scenarios. Taken together, this information provides an efficient condensation of the engineering experience and engine flow physics needed for sensor selection. The systematic sensor selection strategy is composed of three primary algorithms. The core of the selection process is a genetic algorithm that iteratively improves a defined quality measure of selected sensor suites. A merit algorithm is employed to compute the quality measure for each test sensor suite presented by the selection process. The quality measure is based on the fidelity of fault detection and the level of fault source discrimination provided by the test sensor suite. An inverse engine model, whose function is to derive hardware performance parameters from sensor data, is an integral part of the merit algorithm. The final component is a statistical evaluation algorithm that characterizes the impact of interference effects, such as control-induced sensor variation and sensor noise, on the probability of fault detection and isolation for optimal and near-optimal sensor suites.
Heat flux sensors were used to characterize the performance of insulation on the Structural Heat Intercept, Insulation, and Vibration Evaluation Rig (SHIIVER), a large-scale test article designed to simulate upper stage cryogenic propellant tank thermal performance in simulated space environments. Usually, the insulation heat loads are derived from calculations removing all other heat sources and attributing the residual heat load to the insulation system. Testing for SHIIVER included the tank being just insulated with spray-on-foam insulation as well as covering the domes with multilayer insulation while leaving the barrel section insulated with spray-on-foam. Heat flux sensors were located at multiple locations on both domes as well as on the barrel section of the tank. Results from the SHIIVER testing using the heat flux sensors are compared to other calculated heat inputs for both liquid nitrogen and liquid hydrogen testing as a function of tank fill level. Further investigation into the transient nature of the SHIIVER testing including the heat flux sensors provided insight into heat flow patterns that may not have been otherwise seen using temperature sensors and calculated insulation heat loads. While the demonstrated uncertainties in the absolute values in the heat flux sensors are high, the values and the trends match well with other calculation methods. The results of SHIIVER allow for the use of heat flux sensors for measurements of insulation performance and dynamic system thermal response for future applications.