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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Sonoluminescence: A Galaxy of Nanostars Created in a Beaker

As part of basic and applied research on advanced instrumentation technologies, the NASA Glenn Research Center is examining applications for sonoluminescence: ultrasonically produced glowing bubbles that are hotter than the Sun. In the last decade, those outside of the ultrasonic community have become interested in understanding sonoluminescence and in using some of its more interesting properties. First discovered in the 1930s as a byproduct of early work on sonar, the phenomenon is defined as the generation of light energy from sound waves. This glow, which was originally thought to be a form of static electricity, was found to be generated in flashes of much less than a billionth of a second that result when microscopic bubbles of air collapse. The temperature generated in the collapsing bubbles is at least 4 times that of the surface of the Sun.

Wrbanek, John D.↗
NASA NTRS2004

Fram Strait sea ice outflow

We summarize 24 years (1978??2) of ice export estimates and examine, over a 9-year record, the associated variability in the time-varying upward-looking sonar (ULS) thickness distributions of the Fram Strait.

Fram strait ice export ice thickness↗
NASA NTRS2004

Fram Strait sea ice outflow

We summarize 24 years of ice export estimates and examine, over a 9-year record, the associated variability in the time-varying upward-looking sonar (ULS) thickness distributions of the Fram Strait. A more thorough assessment of the PMW (passive microwave) ice motion with 5 years of synthetic aperture radar (SAR)observations shows the uncertainties to be consistent with that found by Kwok and Rothrock [1999], giving greater confidence to the record of ice flux calculations.

Fram Strait ice export ice thickness↗
NASA NTRS1977

Air Safety Spinoffs

Weight saving-even a matter of a few pounds-is an important consideration in airplane design and . construction. Boeing saved 200 pounds simply by substituting a new type of compressed gas cylinder on their 747 commercial airliners. For quickly evacuating passengers in the event of a ground emergency the 747 escape chutes allow ' passengers to slide to safety from the two-story height of the cabin deck. The chutes pop out of exitways and are automatically inflated in seconds by compressed air stored in pressure vessels. Boeing's weight saving resulted from a recent changeover to a new type of pressure vessel built by Structural Composites Industries Inc. of Azusa, Cal. The company employs technology originally developed for rocket motor casings; the cylinders are constructed by winding fibers around an aluminum liner. This technique offers high strength for very low weight-in this case 60 percent less than the pressure vessels earlier used on the 747. Another contribution to improved air safety is an underwater locator device. Called the "Pinger," it uses sonar techniques to locate aircraft crashed in water-or, more specifically, to recover the flight recorder aboard the airplane. Its recovery provides clues as to what caused the accident and suggests measures to prevent similar future occurrences. Until recently, there was no way to recover flight recorders aboard aircraft lost in water crashes. The Pinger, now serving 95 percent of the airline industry, provides an answer. Key element of the Pinger system is a small, battery-powered transmitter, or homing beacon, included as part of the recorder package. For as long as 30 days, the transmitter sends out an acoustic signal from water depths up to 20,000 feet. The other element of the system is a receiver, used by search crews to home in on the transmitter's signal. Originating as a U.S. Navy project, this device was refined and further developed by NASA's Langley Research Center to retrieve submerged nose cones from research rockets. NASA's contractor for the transmitter portion of the system was Dukane Corp., St. Charles, Ill. who subsequently developed the commercial version.

Source record↗
NASA NTRS2003

Kinematic analysis of conically scanned environmental properties

A method for determining the velocity of features such as wind. The method preferably includes producing sensor signals and projecting the sensor signals sequentially along lines lying on the surface of a cone. The sensor signals may be in the form of lidar, radar or sonar for example. As the sensor signals are transmitted, the signals contact objects and are backscattered. The backscattered sensor signals are received to determine the location of objects as they pass through the transmission path. The speed and direction the object is moving may be calculated using the backscattered data. The data may be plotted in a two dimensional array with a scan angle on one axis and a scan time on the other axis. The prominent curves that appear in the plot may be analyzed to determine the speed and direction the object is traveling.

Wilkerson, Thomas D.↗
NASA NTRS2009

An Amplitude-Based Estimation Method for International Space Station (ISS) Leak Detection and Localization Using Acoustic Sensor Networks

The development of a robust and efficient leak detection and localization system within a space station environment presents a unique challenge. A plausible approach includes the implementation of an acoustic sensor network system that can successfully detect the presence of a leak and determine the location of the leak source. Traditional acoustic detection and localization schemes rely on the phase and amplitude information collected by the sensor array system. Furthermore, the acoustic source signals are assumed to be airborne and far-field. Likewise, there are similar applications in sonar. In solids, there are specialized methods for locating events that are used in geology and in acoustic emission testing that involve sensor arrays and depend on a discernable phase front to the received signal. These methods are ineffective if applied to a sensor detection system within the space station environment. In the case of acoustic signal location, there are significant baffling and structural impediments to the sound path and the source could be in the near-field of a sensor in this particular setting.

Tian, Jialin↗
NASA NTRS2010

Mud Volcanoes - Analogs to Martian Cones and Domes (by the Thousands!)

Mud volcanoes are mounds formed by low temperature slurries of gas, liquid, sediments and rock that erupt to the surface from depths of meters to kilometers. They are common on Earth, with estimates of thousands onshore and tens of thousands offshore. Mud volcanoes occur in basins with rapidly-deposited accumulations of fine-grained sediments. Such settings are ideal for concentration and preservation of organic materials, and mud volcanoes typically occur in sedimentary basins that are rich in organic biosignatures. Domes and cones, cited as possible mud volcanoes by previous authors, are common on the northern plains of Mars. Our analysis of selected regions in southern Acidalia Planitia has revealed over 18,000 such features, and we estimate that more than 40,000 occur across the area. These domes and cones strongly resemble terrestrial mud volcanoes in size, shape, morphology, associated flow structures and geologic setting. Geologic and mineralogic arguments rule out alternative formation mechanisms involving lava, ice and impacts. We are studying terrestrial mud volcanoes from onshore and submarine locations. The largest concentration of onshore features is in Azerbaijan, near the western edge of the Caspian Sea. These features are typically hundreds of meters to several kilometers in diameter, and tens to hundreds of meters in height. Satellite images show spatial densities of 20 to 40 eruptive centers per 1000 square km. Many of the features remain active, and fresh mud flows as long as several kilometers are common. A large field of submarine mud volcanoes is located in the Gulf of Cadiz, off the Atlantic coasts of Morocco and Spain. High-resolution sonar bathymetry reveals numerous km-scale mud volcanoes, hundreds of meters in height. Seismic profiles demonstrate that the mud erupts from depths of several hundred meters. These submarine mud volcanoes are the closest morphologic analogs yet found to the features in Acidalia Planitia. We are also conducting laboratory analyses of surface samples collected from mud volcanoes in Azerbaijan, Taiwan and Japan. X-ray diffraction, visible / near infrared reflectance spectroscopy and Raman spectroscopy show that the samples are dominated by mixed-layer smectite clays, along with quartz, calcite and pyrite. Thin section analysis by optical and scanning electron microscopy confirms the mineral identifications. These samples also contain chemical and morphological biosignatures, including common microfossils, with evidence of partial replacement by pyrite. The bulk samples contain approximately 1 wt% total organic carbon and 0.4 mg / gm volatile hydrocarbons. The thousands of features in Acidalia Planitia cited as analogous to terrestrial mud volcanoes clearly represent an important element in the sedimentary record of Mars. Their location, in the distal depocenter for massive Hesperian-age floods, suggests that they contain fine-grained sediments from a large catchment area in the martian highlands. We have proposed these features as a new class of exploration target that can provide access to minimally-altered material from significant depth. By analogy to terrestrial mud volcanoes, these features may also be excellent sites for the sampling martian organics and subsurface microbial life, if such exist or ever existed.

Allen, Carlton C.↗
NASA NTRS2010

Multi-Stage System for Automatic Target Recognition

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feedforward back-propagation neural network (NN) is then trained to classify each feature vector and to remove false positives. The system parameter optimizations process has been developed to adapt to various targets and datasets. The objective was to design an efficient computer vision system that can learn to detect multiple targets in large images with unknown backgrounds. Because the target size is small relative to the image size in this problem, there are many regions of the image that could potentially contain the target. A cursory analysis of every region can be computationally efficient, but may yield too many false positives. On the other hand, a detailed analysis of every region can yield better results, but may be computationally inefficient. The multi-stage ATR system was designed to achieve an optimal balance between accuracy and computational efficiency by incorporating both models. The detection stage first identifies potential ROIs where the target may be present by performing a fast Fourier domain OT-MACH filter-based correlation. Because threshold for this stage is chosen with the goal of detecting all true positives, a number of false positives are also detected as ROIs. The verification stage then transforms the regions of interest into feature space, and eliminates false positives using an artificial neural network classifier. The multi-stage system allows tuning the detection sensitivity and the identification specificity individually in each stage. It is easier to achieve optimized ATR operation based on its specific goal. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar and video image datasets.

Chao, Tien-Hsin↗
NASA NTRS2011

Pseudorandom Noise Code-Based Technique for Cloud and Aerosol Discrimination Applications

NASA Langley Research Center is working on a continuous wave (CW) laser based remote sensing scheme for the detection of CO2 and O2 from space based platforms suitable for ACTIVE SENSING OF CO2 EMISSIONS OVER NIGHTS, DAYS, AND SEASONS (ASCENDS) mission. ASCENDS is a future space-based mission to determine the global distribution of sources and sinks of atmospheric carbon dioxide (CO2). A unique, multi-frequency, intensity modulated CW (IMCW) laser absorption spectrometer (LAS) operating at 1.57 micron for CO2 sensing has been developed. Effective aerosol and cloud discrimination techniques are being investigated in order to determine concentration values with accuracies less than 0.3%. In this paper, we discuss the demonstration of a PN code based technique for cloud and aerosol discrimination applications. The possibility of using maximum length (ML)-sequences for range and absorption measurements is investigated. A simple model for accomplishing this objective is formulated, Proof-of-concept experiments carried out using SONAR based LIDAR simulator that was built using simple audio hardware provided promising results for extension into optical wavelengths. Keywords: ASCENDS, CO2 sensing, O2 sensing, PN codes, CW lidar

Campbell, Joel F.↗
NASA NTRS2005

Laser System for Precise, Unambiguous Range Measurements

The Modulation Sideband Technology for Absolute Range (MSTAR) architecture is the basis of design of a proposed laser-based heterodyne interferometer that could measure a range (distance) as great as 100 km with a precision and resolution of the order of 1 nm. Simple optical interferometers can measure changes in range with nanometer resolution, but cannot measure range itself because interference is subject to the well-known integer-multiple-of-2 -radians phase ambiguity, which amounts to a range ambiguity of the order of 1 m at typical laser wavelengths. Existing rangefinders have a resolution of the order of 10 m and are therefore unable to resolve the ambiguity. The proposed MSTAR architecture bridges the gap, enabling nanometer resolution with an ambiguity range that can be extended to arbitrarily large distances. The MSTAR architecture combines the principle of the heterodyne interferometer with the principle of extending the ambiguity range of an interferometer by using light of two wavelengths. The use of two wavelengths for this purpose is well established in optical metrology, radar, and sonar. However, unlike in traditional two-color laser interferometry, light of two wavelengths would not be generated by two lasers. Instead, multiple wavelengths would be generated as sidebands of phase modulation of the light from a single frequency- stabilized laser. The phase modulation would be effected by applying sinusoidal signals of suitable frequencies (typically tens of gigahertz) to high-speed electro-optical phase modulators. Intensity modulation can also be used

Dubovitsky, Serge↗
NASA NTRS2004

NASA Tech Briefs, January 2004

Topics covered include: Multisensor Instrument for Real-Time Biological Monitoring; Sensor for Monitoring Nanodevice-Fabrication Plasmas; Backed Bending Actuator; Compact Optoelectronic Compass; Micro Sun Sensor for Spacecraft; Passive IFF: Autonomous Nonintrusive Rapid Identification of Friendly Assets; Finned-Ladder Slow-Wave Circuit for a TWT; Directional Radio-Frequency Identification Tag Reader; Integrated Solar-Energy-Harvesting and -Storage Device; Event-Driven Random-Access-Windowing CCD Imaging System; Stroboscope Controller for Imaging Helicopter Rotors; Software for Checking State-charts; Program Predicts Broadband Noise from a Turbofan Engine; Protocol for a Delay-Tolerant Data-Communication Network; Software Implements a Space-Mission File-Transfer Protocol; Making Carbon-Nanotube Arrays Using Block Copolymers: Part 2; Modular Rake of Pitot Probes; Preloading To Accelerate Slow-Crack-Growth Testing; Miniature Blimps for Surveillance and Collection of Samples; Hybrid Automotive Engine Using Ethanol-Burning Miller Cycle; Fabricating Blazed Diffraction Gratings by X-Ray Lithography; Freeze-Tolerant Condensers; The StarLight Space Interferometer; Champagne Heat Pump; Controllable Sonar Lenses and Prisms Based on ERFs; Measuring Gravitation Using Polarization Spectroscopy; Serial-Turbo-Trellis-Coded Modulation with Rate-1 Inner Code; Enhanced Software for Scheduling Space-Shuttle Processing; Bayesian-Augmented Identification of Stars in a Narrow View; Spacecraft Orbits for Earth/Mars-Lander Radio Relay; and Self-Inflatable/Self-Rigidizable Reflectarray Antenna.

Source record↗
NASA NTRS2011

Pseudorandom Noise Code-Based Technique for Thin Cloud Discrimination with CO2 and O2 Absorption Measurements

NASA Langley Research Center is working on a continuous wave (CW) laser based remote sensing scheme for the detection of CO2 and O2 from space based platforms suitable for ACTIVE SENSING OF CO2 EMISSIONS OVER NIGHTS, DAYS, AND SEASONS (ASCENDS) mission. ASCENDS is a future space-based mission to determine the global distribution of sources and sinks of atmospheric carbon dioxide (CO2). A unique, multi-frequency, intensity modulated CW (IMCW) laser absorption spectrometer (LAS) operating at 1.57 micron for CO2 sensing has been developed. Effective aerosol and cloud discrimination techniques are being investigated in order to determine concentration values with accuracies less than 0.3%. In this paper, we discuss the demonstration of a pseudo noise (PN) code based technique for cloud and aerosol discrimination applications. The possibility of using maximum length (ML)-sequences for range and absorption measurements is investigated. A simple model for accomplishing this objective is formulated, Proof-of-concept experiments carried out using SONAR based LIDAR simulator that was built using simple audio hardware provided promising results for extension into optical wavelengths.

Campbell, Joel F.↗
NASA NTRS2012

Fully Self-Contained Vision-Aided Navigation and Landing of a Micro Air Vehicle Independent from External Sensor Inputs

Direct-lift micro air vehicles have important applications in reconnaissance. In order to conduct persistent surveillance in urban environments, it is essential that these systems can perform autonomous landing maneuvers on elevated surfaces that provide high vantage points without the help of any external sensor and with a fully contained on-board software solution. In this paper, we present a micro air vehicle that uses vision feedback from a single down looking camera to navigate autonomously and detect an elevated landing platform as a surrogate for a roof top. Our method requires no special preparation (labels or markers) of the landing location. Rather, leveraging the planar character of urban structure, the landing platform detection system uses a planar homography decomposition to detect landing targets and produce approach waypoints for autonomous landing. The vehicle control algorithm uses a Kalman filter based approach for pose estimation to fuse visual SLAM (PTAM) position estimates with IMU data to correct for high latency SLAM inputs and to increase the position estimate update rate in order to improve control stability. Scale recovery is achieved using inputs from a sonar altimeter. In experimental runs, we demonstrate a real-time implementation running on-board a micro aerial vehicle that is fully self-contained and independent from any external sensor information. With this method, the vehicle is able to search autonomously for a landing location and perform precision landing maneuvers on the detected targets.

autonomous landing↗
NASA NTRS2009

Neural Network Target Identification System for False Alarm Reduction

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feed forward back propagation neural network (NN) is then trained to classify each feature vector and remove false positives. This paper discusses the test of the system performance and parameter optimizations process which adapts the system to various targets and datasets. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar image dataset.

ATR↗
NASA NTRS2015

Titan Submarine: Exploring The Depths of Kraken Mare

The conceptual design of a submarine for Saturn's moon Titan was a funded NASA Innovative Advanced Concepts (NIAC) Phase I for 2014. The effort investigated what science a submarine for Titan's liquid hydrocarbon approximately 93 Kelvin (-180 degrees Centigrade) seas might accomplish and what that submarine might look like. Focusing on a flagship class science system (approximately100 kilograms) it was found that a submersible platform can accomplish extensive and exciting science both above and below the surface of the Kraken Mare The submerged science includes mapping using side looking sonar, imaging and spectroscopy of the sea at all depths, as well as sampling of the sea's bottom and shallow shoreline. While surfaced the submarine will not only sense weather conditions (including the interaction between the liquid and atmosphere) but also image the shoreline, as much as 2 kilometers inland. This imaging requirement pushed the landing date to Titan's next summer period (approximately 2047) to allow for continuous lighted conditions, as well as direct-to-Earth (DTE) communication, avoiding the need for a separate relay orbiter spacecraft. Submerged and surfaced investigation are key to understanding both the hydrological cycle of Titan as well as gather hints to how life may have begun on Earth using liquid/sediment/chemical interactions. An estimated 25 megabits of data per day would be generated by the various science packages. Most of the science packages (electronics at least) can be safely kept inside the submarine pressure vessel and warmed by the isotope power system. This paper discusses the results of Phase I as well as the plans for Phase II.

submarine↗
NASA NTRS2016

Feasibility of Varying Geo-Fence Around an Unmanned Aircraft Operation Based on Vehicle Performance and Wind

Managing trajectory separation is critical to ensuring accessibility, efficiency, and safety in the unmanned airspace. The notion of geo-fences is an emerging concept, where distance buffers enclose individual trajectories and areas of operation in order to manage the airspace. Currently, the Air Traffic Management system for commercial travel defines static distance buffers around the aircraft; however, commercial UASs are envisioned to operate in significantly closer proximity to other UAS requiring a geo-fence for spacing operations. The geo-fence size can be determined based on vehicle performance characteristics, state of the airspace, weather, and other unforeseen events such as emergency or disaster response. Calculation of the geo-fence size could be determined as part of pre-flight planning and during real-time operations. A largely non-homogeneous fleet of UASs will be operating in low altitude and will likely be commercially developed. Due to intellectual property concerns, the operators may not provide detailed specifications of the control system to UTM. In addition, the huge variety of UAS makes modeling each control system prohibitive and flight data for these vehicles may not exist. Therefore, a generalized, simple geo-fence sizing algorithm must be developed such that it does not rely on detailed knowledge of the vehicle control system, accounts for the presence of urban winds, and is sufficiently accurate. In this work, two simple models are investigated to determine its feasibility as an adequate means for calculating the geo-fence size. The vehicle data used in this work are provided by UAS manufactures who have partnered with NASA's UTM project and some publicly available websites. The first model utilizes wind data processed from the NOAA HRRR (Hourly Rapid Refresh) product and Sonar Annemometer data provided by San Jose State. The second model utilizes OpenFOAM which is a CFD code used to generate a wind field for flow around a single building. The key vehicle performance parameters can include UAS response time to disturbances, command to actuation latency, control system rate limits, time to recovery to desired path, and aerodynamics. It was found that the first model provides an initial understanding of geo-fence sizing, but does not provide enough accuracy to provide UTM with an efficient means of scheduling vehicles. The results of the second model reveal that modeling UAS controls systems with a linearized plant and gain scheduled PID controller does not allow capture the UAS flight dynamics within a significant envelope of the wind disturbances.

uncertainty↗
NASA NTRS2020

Analyzing the Impact of CryoSat-2 Ice Thickness Initialization on Seasonal Arctic Sea Ice Prediction

Twin 5-month seasonal forecast experiments are performed to predict the September 2018 minimum ice extent using the fully coupled Navy Earth System Prediction Capability (ESPC). In the control run, ensemble forecasts are initialized from the operational US Navy Global Ocean Forecasting System (GOFS) 3.1 for the ocean and sea ice but do not assimilate ice thickness data. Another set of forecasts are initialized from the same GOFS 3.1 fields but with sea ice thickness derived from CryoSat-2 (CS2). The Navy ESPC ensemble mean September 2018 minimum sea ice extent initialized with GOFS 3.1 ice thickness was over-predicted by 0.68 M sq.km (5.27 M sq.km) versus the ensemble set of forecasts initialized with CS2 ice thickness that had an error of 0.40 M sq.km (4.99 M sq.km), a 56% reduction in error. The September mean Integrated Ice Edge Error (IIEE) shows a 19% improvement for the entire Arctic with the CS2 data versus the control run. Comparison against Upward Looking Sonar (ULS) ice thickness in the Beaufort Sea reveals a lower bias and RMSE with the CS2 forecasts at all three moorings. Ice concentration at these locations is also improved, but neither set of experiments show ice free conditions as observed at moorings A and D.

time-lagged ensembles↗