- API data.nasa.gov | Last Updated 2018-07-19T17:40:50.000Z
EDI Redaction letter
- API data.nasa.gov | Last Updated 2018-07-19T09:01:29.000Z
High-temperature passive wireless surface acoustic wave (SAW) sensors are highly desirable for improving safety and efficiency in aviation and space vehicles. This proposal addresses the growth and processing of a new class of high temperature material into acceptable SAW wafers, the production of SAW temperature sensors, and the integration of the SAW and thin film antenna (SAWtenna). The project will provide a new, unique material grown in the US (no other US manufacturer is known, produce high temperature, radiation hard, solid state, passive wireless sensors for use in harsh environments. In this project, we will: 1) Develop a crystal material for SAW wafers suitable for high-temperature SAW fabrication. 2) Design orthogonally frequency coded OFC (up to 1000 degrees C) SAW temperature sensors . 3) Integrate the SAW and antenna onto the wafer such that there are no external connections. In Phase I the capability for the production of LGT crystals was established and 2in diameter boules were grown. The crystals were processed into SAW wafers and confirmed to be of excellent quality, as evidenced from SAW parameters extraction. A thin film process using simple metallization demonstrated extended device operation at 700 oC and short-term operation at 800 oC. Phase I demonstrated the feasibility of high-temperature SAW devices, and a clear path in the Phase II effort for 1000 oC device operation. During Phase II, we will explore variations of the metallization and encapsulation, which will extend device life. SAW OFC high temperature sensors, operating in the 915 ISM band, will operate simultaneously over temperature and will be delivered to NASA. Phase II will develop a fully integrated sensor antenna and upscale the crystal growth for 3-4in SAW wafers. Probability for Phase III commercialization of both the wireless SAW sensors and SAW wafers is very high.
- API data.nasa.gov | Last Updated 2018-07-19T17:56:25.000Z
Regression problems on massive data sets are ubiquitous in many application domains including the Internet, earth and space sciences, and finances. In many cases, regression algorithms such as linear regression or neural networks attempt to fit the target variable as a function of the input variables without regard to the underlying joint distribution of the variables. As a result, these global models are not sensitive to variations in the local structure of the input space. Several algorithms, including the mixture of experts model, classification and regression trees (CART), and others have been developed, motivated by the fact that a variability in the local distribution of inputs may be reflective of a significant change in the target variable. While these methods can handle the non-stationarity in the relationships to varying degrees, they are often not scalable and, therefore, not used in large scale data mining applications. In this paper we develop Block-GP, a Gaussian Process regression framework for multimodal data, that can be an order of magnitude more scalable than existing state-of-the-art nonlinear regression algorithms. The framework builds local Gaussian Processes on semantically meaningful partitions of the data and provides higher prediction accuracy than a single global model with very high confidence. The method relies on approximating the covariance matrix of the entire input space by smaller covariance matrices that can be modeled independently, and can therefore be parallelized for faster execution. Theoretical analysis and empirical studies on various synthetic and real data sets show high accuracy and scalability of Block-GP compared to existing nonlinear regression techniques.
- API data.nasa.gov | Last Updated 2018-07-19T17:47:39.000Z
UNDERSTANDING SEVERE WEATHER PROCESSES THROUGH SPATIOTEMPORAL RELATIONAL RANDOM FORESTS AMY MCGOVERN, TIMOTHY SUPINIE, DAVID JOHN GAGNE II, NATHANIEL TROUTMAN, MATTHEW COLLIER, RODGER A. BROWN, JEFFREY BASARA, AND JOHN K. WILLIAMS Abstract. Major severe weather events can cause a significant loss of life and property. We seek to revolutionize our understanding of and ability to predict such events through the mining of severe weather data. Because weather is inherently a spatiotemporal phenomenon, mining such data requires a model capable of representing and reasoning about complex spatiotemporal dynamics, including temporally and spatially varying attributes and relationships. We introduce an augmented version of the Spatiotemporal Relational Random Forest, which is a Random Forest that learns with spatiotemporally varying relational data. Our algorithm maintains the strength and performance of Random Forests but extends their applicability, including the estimation of variable importance, to complex spatiotemporal relational domains. We apply the augmented Spatiotemporal Relational Random Forest to three severe weather data sets. These are: predicting atmospheric turbulence across the continental United States, examining the formation of tornadoes near strong frontal boundaries, and understanding the translation of drought across the southern plains of the United States. The results on such a wide variety of real-world domains demonstrate the extensive applicability of the Spatiotemporal Relational Random Forest. Our long-term goal is to significantly improve the ability to predict and warn about severe weather events.
- API data.nasa.gov | Last Updated 2018-07-19T08:28:00.000Z
Robots need to know their location to map of their surroundings but without global positioning data they need a map to identify their surroundings and estimate their location. Simultaneous localization and mapping (SLAM) solves these dual problems at once. SLAM does not depend on any kind of infrastructure and is thus a promising localization technology for NASA planetary missions and for many terrestrial applications as well. However, state-of-the-art SLAM depends on easily-recognizable landmarks in the robot's environment, which are lacking in barren planetary surfaces. Our work will develop a technology we call MeshSLAM, which constructs robust landmarks from associations of weak features extracted from terrain. Our test results will also show that MeshSLAM applies to all environments in which NASA's rovers could someday operate: dunes, rocky plains, overhangs, cliff faces, and underground structures such as lava tubes. Another limitation of SLAM for planetary missions is its significant data-association problems. As a robot travels it must infer its motion from the sensor data it collects, which invariably suffers from drift due to random error. To correct drift, SLAM recognize when the robot has returned to a previously-visited place, which requires searching over a great deal of previously-sensed data. Computation on such a large amount of memory may be infeasible on space-relevant hardware. MeshSLAM eases these requirements. It employs topology-based map segmentation, which limits the scope of a search. Furthermore, a faster, multi-resolution search is performed over the topological graph of observations. Mesh Robotics LLC and Carnegie Mellon University have formed a partnership to commercially develop MeshSLAM. MeshSLAM technology will be available via open source, to ease its adoption by NASA. In Phase 1 of our project we will show the feasibility of MeshSLAM for NASA and commercial applications through a series of focused technical demonstrations.
- API data.nasa.gov | Last Updated 2018-07-19T08:31:24.000Z
Extravehicular Activity (EVA) systems are critical to every foreseeable human exploration mission for in-space microgravity EVA and for planetary surface exploration. Innoflight proposes developing a Compact Wireless EVA Communications System (CWECS) as a replacement and advancement of the Space-to-Space EVA Mobility Unit (EMU) Radio (SSER). The CWECS goals are to: (a) provide backward-compatibility with the existing SSCS network and SSER; (b) provide enhanced communication between the EMU and space vehicle (or ISS or future space habitat) via 802.11n, including high-speed telemetry from the EMU to the spacecraft; and (c) provide body area network (BAN) coverage for wireless biomedical devices and sensors within the EMU. The Phase II will leverage Innoflight's DeSCReeT IF-SDR architecture, which uses cutting edge radiation-tolerant components as the foundation of a software-defined radio (SDR), and transform it into an integrated unit supporting SSCS, 802.11n and BAN. The end result of the Phase II will be a brass-board CWECS that demonstrates compatibility with the selected waveforms.
- API data.nasa.gov | Last Updated 2018-07-19T15:57:23.000Z
JEM Engineering proved the technical feasibility of the FlexScan array?a very low-cost, highly-efficient, wideband phased array antenna?in Phase I, and stands ready to develop it into a fully-functional, flight-qualifiable prototype in Phase II. JEM developed an S-Band (2.0-2.3 GHz) antenna array design appropriate for the stratospheric balloon application through requirements definition, modeling, and performance predictions. The critical technology for this array is an electrically-controlled Variable Delay Line (VDL), used to provide true time-delay for beamsteering. VDLs were designed, built and tested, and shown to have excellent performance. The VDLs were tested over 2.4 million cycles without degradation, indicating good life, especially for the balloon application. A 4-port linear beamformer was built, and used to validate the beamformer concept. The objective of the proposed 24-month Phase II effort is to develop, prototype, and demonstrate a flight-qualifiable FlexScan phased array that achieves the bandwidth, antenna gain, and scan range required for a balloon-borne TDRSS data link in S-band, while meeting environmental requirements. Upon completion of Phase II, the FlexScan array will be ready to commercialize for the balloon-borne application, with other NASA and non-NASA commercial applications soon to follow.
Development of In-situ Nondestructive Evaluation Techniques and Physical Standards for Inspection of Welded Tubing used in Spacecraftdata.nasa.gov | Last Updated 2018-07-19T08:52:34.000Z
<p>Although orbital welding processes are widely used in the manufacture of pressurized tubing assemblies found in spacecraft environmental control and propulsion systems, in many instances the complexity of the tubing assembly restricts access to the orbital welds making full inspection problematic, especially in the case of radiography. For these situations, the inspection requirements are often modified to permit partial inspection or to eliminate one or more inspection methods in their entirety. As a result, confidence in the integrity of the inaccessible weld and, by extension, the entire tubing assembly is reduced. Hence an alternative inspection technique is needed that can substitute for the traditional dye penetrant and radiographic inspections in cases where access to the weld is limited. Recognizing that the inaccessible weld locations must be accessible for welding, this project develops and validates an eddy current inspection device based on a commercially-available orbital tube welding head. Tubing samples containing electrical discharge machining (EDM) notches, fatigue cracks and natural weld defects will be produced to assess and down select eddy current probe and scanner options as well as conduct a probability of detection (POD) assessment of the final inspection device.</p><p> </p> <p><strong>Objective</strong></p><p>Develop and validate an eddy current inspection technique for orbital tubing welds that cannot be inspected using the normally applied methods due to access restrictions.</p><p> </p><p><strong>Background</strong></p><p>Orbital welding processes are widely used in the manufacture of pressurized tubing assemblies found in spacecraft environmental control and propulsion systems. The structural integrity of tubing assemblies is ensured through proof testing, leak testing and pre and post proof nondestructive inspection of the orbital welds. Weld inspections typically consist of visual, dye penetrant and radiographic inspections designed to detect a variety of anomalies such as porosity, cracks, incomplete penetration and incomplete fusion.</p><p>In many instances, the complexity of the tubing assembly restricts access to the orbital welds making full inspection problematic, especially in the case of radiography. In these situations, the inspection requirements are often modified to permit partial inspection or to eliminate one or more inspection methods in their entirety. As a result, confidence in the integrity of the inaccessible weld and, by extension, the entire tubing assembly is reduced. Therefore, an alternative inspection technique is needed that can substitute for the traditional dye penetrant and radiographic inspections in cases where access to the weld is limited. Recognizing that the inaccessible weld locations must be accessible for welding, this project aims to develop and validate an eddy current inspection scanning device based on a commercially available orbital tube welding head. Tubing samples containing electrical discharge machining (EDM) notches, fatigue cracks and natural weld defects will be produced to assess and down select eddy current probe and scanner options as well as conduct a probability of detection (POD) assessment of the final inspection device.</p><p> </p><p><strong>Benefits/Payoffs</strong></p><p>The in-situ eddy current technique developed by this project will increase safety and mission assurance by making it possible to inspect previously uninspectable welds for flaws which could potentially lead to the failure of pressurized systems. The inspection technique will benefit programs with tubing assemblies containing welds with limited access such as the Orion Multipurpose Crew Vehicle.</p><p> </p><p><strong>Recent Accomplishments</strong></p><p>Commercially available and custom wound eddy current probes have been successfully tested on tubing samples containin
Slow Light Based On-Chip High Resolution Fourier Transform Spectrometer For Geostationary Imaging of Atmospheric Greenhouse Gases, Phase Idata.nasa.gov | Last Updated 2018-07-19T07:44:33.000Z
Fourier transform spectroscopy (FTS) in infrared wavelength range is an effective measure for global greenhouse gas monitoring. However, conventional FTS instruments are bulky, heavy, and frail to environmental vibration, making them not suitable for satellite platforms. In this proposal, Omega Optics, Inc., together with the University of Texas at Austin, proposes a slow light enhanced on-chip FTS array covering compound spectral wavelength range (1.1 ~ 6.2 m) for geostationary imaging of greenhouse gases. Each array pixel is made of a Mach-Zehnder interferometer, one arm of which is conventional waveguide and the other is 'fishbone' slow light waveguide. Harnessing the nonlinear phase enhancement generated by the slow light effect of the 'fishbone' waveguide, a resolution better than 0.2 cm-2 can be readily achieved within a limited chip surface. An N x M array can be formed by integrating N pixels on one silicon-on-sapphire chip and stacking M chips. Leveraging the CMOS compatible fabrication process, the imaging unit can be ~$10 per pixel and the whole imaging array weights ~ 30g. In addition, the whole module does not have moving parts, making it an ideal candidate for airborne and spaceborne applications.
- API data.nasa.gov | Last Updated 2018-07-19T08:46:11.000Z
<p>Current water quality monitors aboard the International Space Station (ISS) are specialized and provide limited data. As water and air samples are often analyzed using similar ground-based techniques, it seems logical to use a combined instrument in flight. Of the instruments that measure air and water quality, air monitors provide more detailed information. We therefore propose to construct an ion mobility spectrometer with the ability to measure both air and water samples. We have recently prepared an electrospray ionization (ESI) source that will allow analytes to be liberated from the water matrix. This source will be interfaced with the constructed ion mobility spectrometer and used to analyze different water samples. Upon the successful completion of this work, it will have been demonstrated that the volatile organic composition of water samples can be measured using an air analyzer and more detailed information can be obtained than is currently available in real-time monitors.<p/><p>The Colorimetric Water Quality Monitor Kit (CWQMK) and the Total Organic Carbon Analyzer (TOCA) are used to measure biocide concentrations and the total organic carbon load, respectively. While each of these instruments provides important analytical information, they lack the ability to fully characterize the organic and inorganic compounds present in the ISS water systems. Identification of individual compounds requires the return of ISS archival samples that are analyzed in ground laboratories. A survey of the other environmental monitoring hardware used on the ISS reveals that air quality monitors have advanced further toward the end goal of providing real-time, compound-specific information that can be used by the crew. As many of the organic compounds on the target lists for air and water quality monitoring are identical, evaluating the current air quality monitoring technologies is a logical first step toward development of a water quality platform that can characterize the organic load in spacecraft water systems. The initial phase of this effort is focused on ion mobility spectrometry (IMS). IMS technology was previously used in the ISS Volatile Organic Analyzer (VOA), and it is employed for numerous terrestrial applications, such as the detection of a variety of large analytes in aqueous solution. It also is widely field-deployed by the Department of Homeland Security for explosives detection. Our approach couples IMS with electrospray ionization (ESI) to ionize and detect target analytes in water samples. The successful completion of this work could potentially allow for the analysis of both air and water samples using a single instrument.</p>