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At least 559 records · Page 31

Pulse Detonation Engine Test Bed Developed

A detonation is a supersonic combustion wave. A Pulse Detonation Engine (PDE) repetitively creates a series of detonation waves to take advantage of rapid burning and high peak pressures to efficiently produce thrust. NASA Glenn Research Center's Combustion Branch has developed a PDE test bed that can reproduce the operating conditions that might be encountered in an actual engine. It allows the rapid and cost-efficient evaluation of the technical issues and technologies associated with these engines. The test bed is modular in design. It consists of various length sections of both 2- and 2.6- in. internal-diameter combustor tubes. These tubes can be bolted together to create a variety of combustor configurations. A series of bosses allow instrumentation to be inserted on the tubes. Dynamic pressure sensors and heat flux gauges have been used to characterize the performance of the test bed. The PDE test bed is designed to utilize an existing calorimeter (for heat load measurement) and windowed (for optical access) combustor sections. It uses hydrogen as the fuel, and oxygen and nitrogen are mixed to simulate air. An electronic controller is used to open the hydrogen and air valves (or a continuous flow of air is used) and to fire the spark at the appropriate times. Scheduled tests on the test bed include an evaluation of the pumping ability of the train of detonation waves for use in an ejector and an evaluation of the pollutants formed in a PDE combustor. Glenn's Combustion Branch uses the National Combustor Code (NCC) to perform numerical analyses of PDE's as well as to evaluate alternative detonative combustion devices. Pulse Detonation Engine testbed.

Breisacher, Kevin J.↗

The Earth Science Afternoon Constellation: Preparing for Autonomous but Coordinated Operations

This paper describes how the challenges of coordinating the autonomous operations of geographically dispersed mission control centers for several small and large satellites are being overcome. The Earth Science Afternoon Constellation, also referred to as the "A-Train", is an international grouping of five NASA satellites (two major NASA EOS missions and three NASA/Earth System Science Pathfinder missions) and one French satellite orbiting in close proximity. This grouping of satellites provides scientists with the opportunity to perform coincident observations using data from two or more instruments on various satellites with measurements taken at approximately the same time. Three of the six missions are currently on-orbit, with the two missions expected to join the constellation later this year and one mission in 2007. The operational challenges are daunting for several reasons. There are several Mission Control Centers (widely separated on two continents), operating autonomously under tight budget constraints. All of the Mission Control Centers have reasons to be concerned about safety while flying in close proximity to other satellites, but most Centers did not have the resources or the desire to address this concern alone - the interfaces are too numerous and anticipated operations too costly. Clearly, an efficient approach was needed. This paper describes the steps taken to make this Earth science constellation a reality. Agreements were forged to allow the Mission Control Centers to maintain their autonomy, while ensuring their satellite's safety. Each member mission in the constellation operates independently in accordance with its own mission requirements, but the member missions have agreed to coordinate their operations, i.e., orbital positions and control to ensure the safety of the entire constellation. A centralized system was developed at NASA Goddard Space Flight Center to collect, analyze, and distribute ephemeris data used by each of the mission teams to determine the positions of the satellites in the constellation. The system issues warnings regarding possible dangerous configurations, eliminating the need for redundant capabilities at each Mission Control Center. On-orbit contingency situations were identified and analyzed; agreements were reached in advance of contingency operations to ensure that coordination between the Mission Control Centers can be handled expeditiously and fairly. In this manner, recovery from anomalous situations can be more quickly realized, thereby increasing the science return and reducing costs. The process used to develop these contingency procedures and the systems used to facilitate the contingency resolution are described as well.

Case, Warren↗

Geocam Space: Enhancing Handheld Digital Camera Imagery from the International Space Station for Research and Applications

Handheld astronaut photography of the Earth has been collected from the International Space Station (ISS) since 2000, making it the most temporally extensive remotely sensed dataset from this unique Low Earth orbital platform. Exclusive use of digital handheld cameras to perform Earth observations from the ISS began in 2004. Nadir viewing imagery is constrained by the inclined equatorial orbit of the ISS to between 51.6 degrees North and South latitude, however numerous oblique images of land surfaces above these latitudes are included in the dataset. While unmodified commercial off-the-shelf digital cameras provide only visible wavelength, three-band spectral information of limited quality current cameras used with long (400+ mm) lenses can obtain high quality spatial information approaching 2 meters/ground pixel resolution. The dataset is freely available online at the Gateway to Astronaut Photography of Earth site (http://eol.jsc.nasa.gov), and now comprises over 2 million images. Despite this extensive image catalog, use of the data for scientific research, disaster response, commercial applications and visualizations is minimal in comparison to other data collected from free-flying satellite platforms such as Landsat, Worldview, etc. This is due primarily to the lack of fully-georeferenced data products - while current digital cameras typically have integrated GPS, this does not function in the Low Earth Orbit environment. The Earth Science and Remote Sensing (ESRS) Unit at NASA Johnson Space Center provides training in Earth Science topics to ISS crews, performs daily operations and Earth observation target delivery to crews through the Crew Earth Observations (CEO) Facility on board ISS, and also catalogs digital handheld imagery acquired from orbit by manually adding descriptive metadata and determining an image geographic centerpoint using visual feature matching with other georeferenced data, e.g. Landsat, Google Earth, etc. The lack of full geolocation information native to the data makes it difficult to integrate astronaut photographs with other georeferenced data to facilitate quantitative analysis such as urban land cover/land use classification, change detection, or geologic mapping. The manual determination of image centerpoints is both time and labor-intensive, leading to delays in releasing geolocated and cataloged data to the public, such as the timely use of data for disaster response. The GeoCam Space project was funded by the ISS Program in 2015 to develop an on-orbit hardware and ground-based software system for increasing the efficiency of geolocating astronaut photographs from the ISS (Fig. 1). The Intelligent Robotics Group at NASA Ames Research Center leads the development of both the ground and on-orbit systems in collaboration with the ESRS Unit. The hardware component consists of modified smartphone elements including cameras, central processing unit, wireless Ethernet, and an inertial measurement unit (gyroscopes/accelerometers/magnetometers) reconfigured into a compact unit that attaches to the base of the current Nikon D4 camera - and its replacement, the Nikon D5 - and connects using the standard Nikon peripheral connector or USB port. This provides secondary, side and downward facing cameras perpendicular to the primary camera pointing direction. The secondary cameras observe calibration targets with known internal X, Y, and Z position affixed to the interior of the ISS to determine the camera pose corresponding to each image frame. This information is recorded by the GeoCam Space unit and indexed for correlation to the camera time recorded for each image frame. Data - image, EXIF header, and camera pose information - is transmitted to the ground software system (GeoRef) using the established Ku-band USOS downlink system. Following integration on the ground, the camera pose information provides an initial geolocation estimate for the individual film frame. This new capability represents a significant advance in geolocation from the manual feature-matching approach for both nadir and off-nadir viewing imagery. With the initial geolocation estimate, full georeferencing of an image is completed using the rapid tie-pointing interface in GeoRef, and the resulting data is added to the Gateway to Astronaut Photography of Earth online database in both Geotiff and Keyhole Markup Language (kml) formats. The integration of the GeoRef software component of Geocam Space into the CEO image cataloging workflow is complete, and disaster response imagery acquired by the ISS crew is now fully georeferenced as a standard data product. The on-orbit hardware component (GeoSens) is in final prototyping phase, and is on-schedule for launch to the ISS in late 2016. Installation and routine use of the Geocam Space system for handheld digital camera photography from the ISS is expected to significantly improve the usefulness of this unique dataset for a variety of public- and private-sector applications.

Stefanov, William L.↗

The automated Army ROTC Questionnaire (ARQ)

The Reserve Officer Training Corps Cadet Command (ROTCCC) takes applications for its officer training program from college students and Army enlisted personnel worldwide. Each applicant is required to complete a set of application forms prior to acceptance into the ROTC program. These forms are covered by several regulations that govern the eligibility of potential applicants and guide the applicant through the application process. Eligibility criteria changes as Army regulations are periodically revised. Outdated information results in a loss of applications attributable to frustration and error. ROTCCC asked for an inexpensive and reliable way of automating their application process. After reviewing the process, it was determined that an expert system with good end user interface capabilities could be used to solve a large part of the problem. The system captures the knowledge contained within the regulations, enables the quick distribution and implementation of eligibility criteria changes, and distributes the expertise of the admissions personnel to the education centers and colleges. The expert system uses a modified version of CLIPS that was streamlined to make the most efficient use of its capabilities. A user interface with windowing capabilities provides the applicant with a simple and effective way to input his/her personal data.

Young, David L. H.↗

TRMM Re-Entry Planning: Attitude Determination and Control During Thruster Modes

The Tropical Rainfall Measuring Mission (TRMM) spacecraft has been undergoing design for a controlled re-entry to Earth. During simulation of the re-entry plan, there was evidence of errors in the attitude determination algorithms during thruster modes. These errors affected the bum efficiency, and thus planning, during re-entry. During thruster modes, the spacecraft attitude is controlled off of integrated Gyro Error Angles that were designed to closely follow the nominal spacecraft pointing frame (Tip Frame). These angles, however, were not exactly mapped to the Tip Frame from the Body Frame. Additionally, in the initial formulation of the thruster mode attitude determination algorithms, several assumptions and approximations were made to conserve processor speed. These errors became noticeable and significant when simulating bums of much longer duration (-10 times) than had been produced in flight. A solution is proposed that uses attitude determination information from a propagated extended Kalman filter that already exists in the TRMM thruster modes. This attitude information is then used to rotate the Gyro Error Angles into the Tip Frame. An error analysis is presented that compares the two formulations. The new algorithm is tested using the TRMM High-Fidelity Simulator and verified with the TRMM Software Testing and Training Facility. Simulation results for both configurations are also presented.

DeWeese, Keith↗

Psychophysiological Monitoring of Aerospace Crew State

As next-generation space exploration missions necessitate increasingly autonomous systems, there is a critical need to better detect and anticipate crewmember interactions with these systems. The success of present and future autonomous technology in exploration spaceflight is ultimately dependent upon safe and efficient interaction with the human operator. Optimal interaction is particularly important for surface missions during highly coordinated extravehicular activity (EVA), which consists of high physical and cognitive demands with limited ground support. Crew functional state may be affected by a number of variables including workload, stress, and motivation. Real-time assessments of crew state that do not require a crewmember’s time and attention to complete will be especially important to assess operational performance and behavioral health during flight. In response to the need for objective, passive assessment of crew state, the aim of this work is to develop an accurate and precise prediction model of human functional state for surface EVA using multi-modal psychophysiological sensing. The psychophysiological monitoring approach relies on extracting a set of features from physiological signals and using these features to classify an operator’s cognitive state. This work aims to compile a non-invasive sensor suite to collect physiological data in real-time. Training data during cognitive and more complex functional tasks will be used to develop a classifier to discriminate high and low cognitive workload crew states. The classifier will then be tested in an operationally relevant EVA simulation to predict cognitive workload over time. Once a crew state is determined, further research into specific countermeasures, such as decision support systems, would be necessary to optimize the automation and improve crew state and operational performance.

Wusk, Grace C.↗

Controller evaluations of the descent advisor automation aid

An automation aid to assist air traffic controllers in efficiently spacing traffic and meeting arrival times at a fix has been developed at NASA Ames Research Center. The automation aid, referred to as the descent advisor (DA), is based on accurate models of aircraft performance and weather conditions. The DA generates suggested clearances, including both top-of-descent point and speed profile data, for one or more aircraft in order to achieve specific time or distance separation objectives. The DA algorithm is interfaced with a mouse-based, menu-driven controller display that allows the air traffic controller to interactively use its accurate predictive capability to resolve conflicts and issue advisories to arrival aircraft. This paper focuses on operational issues concerning the utilization of the DA, specifically, how the DA can be used for prediction, intrail spacing, and metering. In order to evaluate the DA, a real time simulation was conducted using both current and retired controller subjects. Controllers operated in teams of two, as they do in the present environment; issues of training and team interaction will be discussed. Evaluations by controllers indicated considerable enthusiasm for the DA aid, and provided specific recommendations for using the tool effectively.

Tobias, Leonard↗

Controller evaluations of the descent advisor automation aid

An automation aid to assist air traffic controllers in efficiently spacing traffic and meeting arrival times at a fix has been developed at NASA Ames Research Center. The automation aid, referred to as the descent advisor (DA), is based on accurate models of aircraft performance and weather conditions. The DA generates suggested clearances, including both top-of-descent point and speed profile data, for one or more aircraft in order to achieve specific time or distance separation objectives. The DA algorithm is interfaced with a mouse-based, menu-driven controller display that allows the air traffic controller to interactively use its accurate predictive capability to resolve conflicts and issue advisories to arrival aircraft. This paper focuses on operational issues concerning the utilization of the DA, specifically, how the DA can be used for prediction, intrail spacing, and metering. In order to evaluate the DA, a real time simulation was conducted using both current and retired controller subjects. Controllers operated in teams of two, as they do in the present environment; issues of training and team interaction will be discussed. Evaluations by controllers indicated considerable enthusiasm for the DA aid, and provided specific recommendations for using the tool effectively.

Tobias, Leonard↗

Urban Air Mobility (UAM) Market Study

The Booz Allen Team explored market size and potential barriers to Urban Air Mobility (UAM) by focusing on three potential markets – Airport Shuttle, Air Taxi, and Air Ambulance. We found that the Airport Shuttle and Air Taxi markets are viable, with a significant total available market value in the U.S. of $500 billion, for a fully unconstrained scenario. In this unconstrained best-case scenario, passengers would have the ability to access and fly a UAM at any time, from any location to any destination, without being hindered by constraints such as weather, infrastructure, or traffic volume. Significant legal and regulatory, weather, certification, public perception, and infrastructure constraints exist, which reduce the market potential for these applications to only about 0.5% of the total available market, or $2.5 billion, in the near term. However, we determined that these constraints can be addressed through ongoing intra-governmental partnerships, government and industry collaboration, strong industry commitment, and existing legal and regulatory enablers. We found that the Air Ambulance market is not a viable market if served by electric vertical takeoff and landing (eVTOL) vehicles due to technology constraints but may potentially be viable if a hybrid VTOL aircraft are utilized. The barriers and challenges we characterized in this study can be stratified according to their applicability or potential mitigation through technology as well as market maturity (Figure 1). In the near term, high cost of service will be a key economic challenge. We found potential for significant reduction in service cost through increased vehicle and component efficiency, and automation in a more mature market scenario. Weather conditions also pose a challenge to the UAM market, though there is potential for mitigation of some of these impacts through technology such as sensors enabling operations in low visibility. However, even in a mature market with advanced technology, disruptions are still likely to occur due to weather events such as thunderstorms and strong winds. High density operations will likely stress the current Air Traffic Management (ATM) system in the near term, but technology and new initiatives such as the Air Traffic Management -eXploration project (ATM-X) will enable safe and efficient integration of UAM into the National Airspace System (NAS). Current battery technology creates a barrier in the near term, especially for the Air Ambulance market, as battery weight and extensive recharging times would be needed for these operations. Advancements in battery technology, as well as use of hybrid VTOLs, could significantly reduce this barrier in the longer term. As UAM emerges as a viable mode of transportation in the near term, adverse energy and environmental impacts, particularly noise, may impact community acceptance and potentially persist as the market matures into larger-scale operations. For non-technology related challenges, we found that infrastructure constraints will create a significant barrier to UAM in the near term but could be addressed in the longer term through development and expansion of vertiports. Competition from existing modes of transportation such as ride-sharing (e.g., Lyft, Uber) and ground taxi’s pose a key barrier to UAM in the short term, which will likely evolve into competition from other emerging technologies such as autonomous cars and electric trains in the longer term. Weather events will influence other components of the operation such as passenger comfort (e.g., extreme temperatures, turbulence) and infrastructure (e.g., winter weather causing cracks and degradation in vertiports). There is also potential for these impacts to be heightened in the longer term from the increased frequency of adverse weather such as thunderstorms due to changing climatic conditions. We also found that the public has strong concerns about safety as a passenger in a piloted UAM, including “lasing” of pilots, unruly passengers, and sabotage. They would prefer that all passengers pass through a security screening process before boarding a vehicle. They would also prefer to use UAM for longer regional trips, such as flying from Washington, DC to Baltimore, MD or San Diego, CA to Los Angeles, CA. A longer term automated UAM vehicle market will face challenges due to public apprehension about automation and unmanned operations, and a preference to fly with passengers they know in an autonomous (unmanned) operational scenario.

Rohit Goyal↗

Collaborative Systems Engineering in the Ascent Abort-2 Crew Module/Separation Ring Project

Generally speaking, systems engineering (SE) tool-sets face a dilemma balancing power and accessibility. High-powered SE tools (MagicDraw, Cradle, Core, etc.) tend to be specialized and are available only to highly trained Systems Engineers, and/or through the use of a 'back room' developer team making the output products available to the broader team. On the other hand, highly accessible tools (MS Word, Excel, etc.) do not have the power to implement SE in a rigorous manner. NASA has to test all aspects of the new human-rated Orion Multi-Purpose Crew Vehicle spacecraft prior to its first crewed mission. The test program includes uncrewed launch abort flight tests to demonstrate the capability to save the crew in the event that a launch failure occurs. Orion's second abort flight test will be a low-altitude flight test known as "Ascent Abort 2 (AA-2)." This test is currently scheduled to be carried out at Cape Canaveral Air Force Station's Space Launch Complex 46 (SLC-46) in Florida in 2019. NASA's in-house AA-2 Crew Module and Separation Ring (CSR) Team is producing the crew module and separation ring. Operating jointly as both an Advanced Exploration Systems (AES) Project and an Orion Project, the CSR project charter includes development of innovative, streamlined and generally more efficient practices for creation of flight hardware and software. One result of this tasking has been development of a collaborative and data-centric systems engineering environment within the team's shared web environment (Microsoft SharePoint). Through the use of built-in, 'out of the box capabilities' present in MS SharePoint, the CSR Systems Engineering team has created (with some limited developer support) a data-centric architecture for the project's SE implementation, including functional and interface analysis, requirements development and management, risk management, verification planning and management, test results, and end item management. Data elements are linked between data structures so as to define and control relationships between item types, link requirements to parents and children, and link tests to the requirements that they verify. The overall project team integration is increased by also linking SE content to project management content over the project life cycle, including team communication, action items, configuration management, decisional and meeting materials, and life cycle reviews. This presentation will provide an overview of the collaborative SE environment, showing how it provides the power for a number of SE tasks while still providing the accessibility and transparency to allow the full project team to collaborate and succeed. Given the project phase, we'll be able to present a nearly full lifecycle discussion, from concept through verification and approaching delivery.

Systems Engineering environments↗

NASA Tech Briefs, October 2013

Topics include: A Short-Range Distance Sensor with Exceptional Linearity; Miniature Trace Gas Detector Based on Microfabricated Optical Resonators; Commercial Non-Dispersive Infrared Spectroscopy Sensors for Sub-Ambient Carbon Dioxide Detection; Fast, Large-Area, Wide-Bandgap UV Photodetector for Cherenkov Light Detection; Mission Data System Java Edition Version 7; Adaptive Distributed Environment for Procedure Training (ADEPT); LEGEND, a LEO-to-GEO Environment Debris Model; Electronics/Computers; Millimeter-Wave Localizers for Aircraft-to-Aircraft Approach Navigation; Impedance Discontinuity Reduction Between High-Speed Differential Connectors and PCB Interfaces; SpaceCube Version 1.5; High-Pressure Lightweight Thrusters; Non-Magnetic, Tough, Corrosion- and Wear-Resistant Knives From Bulk Metallic Glasses and Composites; Ambient Dried Aerogels; Applications for Gradient Metal Alloys Fabricated Using Additive Manufacturing; Passivation of Flexible YBCO Superconducting Current Lead With Amorphous SiO2 Layer; Propellant-Flow-Actuated Rocket Engine Igniter; Lightweight Liquid Helium Dewar for High-Altitude Balloon Payloads; Method to Increase Performance of Foil Bearings Through Passive Thermal Management; Unibody Composite Pressurized Structure; JWST Integrated Science Instrument Module Alignment Optimization Tool; Radar Range Sidelobe Reduction Using Adaptive Pulse Compression Technique; Digitally Calibrated TR Modules Enabling Real-Time Beamforming SweepSAR Architectures; Electro-Optic Time-to-Space Converter for Optical Detector Jitter Mitigation; Partially Transparent Petaled Mask/Occulter for Visible-Range Spectrum; Educational NASA Computational and Scientific Studies (enCOMPASS); Coarse-Grain Bandwidth Estimation Scheme for Large-Scale Network; Detection of Moving Targets Using Soliton Resonance Effect; High-Efficiency Nested Hall Thrusters for Robotic Solar System Exploration; High-Voltage Clock Driver for Photon-Counting CCD Characterization; Development of the Code RITRACKS; and Enabling Microliquid Chromatography by Microbead Packing of Microchannels.

Source record↗

Elevating the Quality of Space Omics Sequencing Data: Innovations and Methodologies from NASA GeneLab Sample Processing Laboratory

NASA’s GeneLab, part of the NASA Open Science Data Repository, is a space-related database that hosts a diverse range of transcriptomics, proteomics, epigenomics and genomics data. The NASA GeneLab Sample Processing Laboratory (SPL) generates omics data from biological experiments conducted aboard the International Space Station, Space Shuttle and space related ground experiments, this omics data then hosted on the GeneLab repository. Samples generated such experiments pose numerous technical challenges such as small experimental sample size, variance in dissection times, limited tissue preservation methods, prolonged storage time, and more. GeneLab SPL team had developed specialized expertise in nucleic acid extraction, library preparation and sequencing of such biological samples via extensive training and years of experience. In order to ensure data accuracy and consistency across experiments, SPL has developed standardized protocols for each species and tissue type. These protocols in conjunction with quality control metrics and data standards are crucial in generating of high-quality data. SPL protocols and standards have been developed in collaboration with the scientific community and had been made publicly available on the GeneLab portal, guaranteeing comparability of datasets across spaceflight experiments. To ensure reliability of data generation, SPL leverages cutting-edge innovations in laboratory automation for sample processing. By leveraging these state-of-the-art platforms, SPL achieves high levels of data reproducibility while significantly minimizing sources of bias and variability, especially across experiments with large numbers of samples. Over the past few years, the space biology investigator community has accessed SPL-generated data from the Open Science Data Repository for a myriad of data re-analysis and re-use studies. We observe a trend that in-house SPL-generated data consistently outperforms outsourced sequencing data in terms of technical standards, quality control metrics, timeliness of data delivery, and sequencing and reagent efficiency. Superior data generation has and will continue to enable discoveries in disease, diagnostic tools, and the biological effects of long duration spaceflight.

GeneLab↗

Elevating the Quality of Space Omics Sequencing Data: Innovations and Methodologies from NASA GeneLab Sample Processing Laboratory

NASA’s GeneLab, part of the NASA Open Science Data Repository, is a space-related database that hosts a diverse range of transcriptomics, proteomics, epigenomics and genomics data. The NASA GeneLab Sample Processing Laboratory (SPL) generates omics data from biological experiments conducted aboard the International Space Station, Space Shuttle and space related ground experiments, this omics data then hosted on the GeneLab repository. Samples generated such experiments pose numerous technical challenges such as small experimental sample size, variance in dissection times, limited tissue preservation methods, prolonged storage time, and more. GeneLab SPL team had developed specialized expertise in nucleic acid extraction, library preparation and sequencing of such biological samples via extensive training and years of experience. In order to ensure data accuracy and consistency across experiments, SPL has developed standardized protocols for each species and tissue type. These protocols in conjunction with quality control metrics and data standards are crucial in generating of high-quality data. SPL protocols and standards have been developed in collaboration with the scientific community and had been made publicly available on the GeneLab portal, guaranteeing comparability of datasets across spaceflight experiments. To ensure reliability of data generation, SPL leverages cutting-edge innovations in laboratory automation for sample processing. By leveraging these state-of-the-art platforms, SPL achieves high levels of data reproducibility while significantly minimizing sources of bias and variability, especially across experiments with large numbers of samples. Over the past few years, the space biology investigator community has accessed SPL-generated data from the Open Science Data Repository for a myriad of data re-analysis and re-use studies. We observe a trend that in-house SPL-generated data consistently outperforms outsourced sequencing data in terms of technical standards, quality control metrics, timeliness of data delivery, and sequencing and reagent efficiency. Superior data generation has and will continue to enable discoveries in disease, diagnostic tools, and the biological effects of long duration spaceflight.

GeneLab↗

Intelligent Control for the BEES Flyer

This paper describes the effort to provide a preliminary capability analysis and a neural network based adaptive flight control system for the JPL-led BEES aircraft project. The BEES flyer was envisioned to be a small, autonomous platform with sensing and control systems mimicking those of biological systems for the purpose of scientific exploration on the surface of Mars. The platform is physically tightly constrained by the necessity of efficient packing within rockets for the trip to Mars. Given the physical constraints, the system is not an ideal configuration for aerodynamics or stability and control. The objectives of this effort are to evaluate the aerodynamics characteristics of the existing design, to make recommendaaons as to potential improvements and to provide a control system that stabilizes the existing aircraft for nominal flight and damaged conditions. Towards this several questions are raised and analyses are presented to arrive at answers to some of the questions raised. CART3D, a high-fidelity inviscid analysis package for conceptual and preliminary aerodynamic design, was used to compute a parametric set of solutions over the expected flight domain. Stability and control derivatives were extracted from the database and integrated with the neural flight control system. The Integrated Vehicle Modeling Environment (IVME) was also used for estimating aircraft geometric, inertial, and aerodynamic characteristics. A generic neural flight control system is used to provide adaptive control without the requirement for extensive gain scheduling or explicit system identification. The neural flight control system uses reference models to specify desired handling qualities in the roll, pitch, and yaw axes, and incorporates both pre-trained and on-line learning neural networks in the inverse model portion of the controller. Results are presented for the BEES aircraft in the subsonic regime for terrestrial and Martian environments.

Krishnakumar, K.↗

NASA Tech Briefs, December 2009

Topics include: A Deep Space Network Portable Radio Science Receiver; Detecting Phase Boundaries in Hard-Sphere Suspensions; Low-Complexity Lossless and Near-Lossless Data Compression Technique for Multispectral Imagery; Very-Long-Distance Remote Hearing and Vibrometry; Using GPS to Detect Imminent Tsunamis; Stream Flow Prediction by Remote Sensing and Genetic Programming; Pilotless Frame Synchronization Using LDPC Code Constraints; Radiometer on a Chip; Measuring Luminescence Lifetime With Help of a DSP; Modulation Based on Probability Density Functions; Ku Telemetry Modulator for Suborbital Vehicles; Photonic Links for High-Performance Arraying of Antennas; Reconfigurable, Bi-Directional Flexfet Level Shifter for Low-Power, Rad-Hard Integration; Hardware-Efficient Monitoring of I/O Signals; Video System for Viewing From a Remote or Windowless Cockpit; Spacesuit Data Display and Management System; IEEE 1394 Hub With Fault Containment; Compact, Miniature MMIC Receiver Modules for an MMIC Array Spectrograph; Waveguide Transition for Submillimeter-Wave MMICs; Magnetic-Field-Tunable Superconducting Rectifier; Bonded Invar Clip Removal Using Foil Heaters; Fabricating Radial Groove Gratings Using Projection Photolithography; Gratings Fabricated on Flat Surfaces and Reproduced on Non-Flat Substrates; Method for Measuring the Volume-Scattering Function of Water; Method of Heating a Foam-Based Catalyst Bed; Small Deflection Energy Analyzer for Energy and Angular Distributions; Polymeric Bladder for Storing Liquid Oxygen; Pyrotechnic Simulator/Stray-Voltage Detector; Inventions Utilizing Microfluidics and Colloidal Particles; RuO2 Thermometer for Ultra-Low Temperatures; Ultra-Compact, High-Resolution LADAR System for 3D Imaging; Dual-Channel Multi-Purpose Telescope; Objective Lens Optimized for Wavefront Delivery, Pupil Imaging, and Pupil Ghosting; CMOS Camera Array With Onboard Memory; Quickly Approximating the Distance Between Two Objects; Processing Images of Craters for Spacecraft Navigation; Adaptive Morphological Feature-Based Object Classifier for a Color Imaging System; Rover Slip Validation and Prediction Algorithm; Safety and Quality Training Simulator; Supply-Chain Optimization Template; Algorithm for Computing Particle/Surface Interactions; Cryogenic Pupil Alignment Test Architecture for Aberrated Pupil Images; and Thermal Transport Model for Heat Sink Design.

Source record↗

Neural Network Reflectance Prediction Model for Both Open Ocean and Coastal Waters

Remote sensing of global ocean color is a valuable tool for understanding the ecology and biogeochemistry of the worlds oceans, and provides critical input to our knowledge of the global carbon cycle and the impacts of climate change. Ocean polarized reflectance contains information about the constituents of the upper ocean euphotic zone, such as colored dissolved organic matter (CDOM), sediments, phytoplankton, and pollutants. In order to retrieve the information on these constituents, remote sensing algorithms typically rely on radiative transfer models to interpret water color or remote-sensing reflectance; however, this can be resource-prohibitive for operational use due to the extensive CPU time involved in radiative transfer solutions. In this work, we report a fast model based on machine learning techniques, called Neural Network Reflectance Prediction Model (NNRPM), which can be used to predict ocean bidirectional polarized reflectance given inherent optical properties of ocean waters. This supervised model is trained using a large volume of data derived from radiative transfer simulations for coupled atmosphere and ocean systems using the successive order of scattering technique (SOS-CAOS). The performance of the model is validated against another large independent test dataset generated from SOS-CAOS. The model is able to predict both polarized and unpolarized reflectances with an absolute error (AE) less than 0.004 for 99% of test cases. We have also shown that the degree of linear polarization (DoLP) for unpolarized incident light can be predicted with an AE less than 0.002 for 99% of test cases. In general, the simulation time of SOS-CAOS depends on optical depth, and required accuracy. When comparing the average speeds of the NNRPM against the SOS-CAOS model for the same parameters, we see that the NNRPM is able to predict the Ocean BRDF 6000 times faster than SOS-CAOS. Both ultraviolet and visible wavelengths are included in the model to help differentiate between dissolved organic material and chlorophyll in the study of the open ocean and the coastal zone. The incorporation of this model into the retrieval algorithm will make the retrieval process more efficient, and thus applicable for operational use with global satellite observations.

radiative transfer↗

Evaluation of Hands-Free Devices for the Display of Maintenance Procedures

Over the past year, NASA's focus has turned to crewed long duration and exploration missions. On these journeys, crewmembers will be required to execute thousands of procedures to maintain life support systems, check out space suits, conduct science experiments, and perform medical exams. To support the many complex tasks crewmembers undertake in microgravity, NASA is interested in providing crewmembers a hands-free work environment to promote more efficient operations. The overarching objective is to allow crewmembers to use both of their hands for tasks related to their mission, versus holding a paper manual or interacting with a display. The use of advanced, hands-free tools will undoubtedly make the crewmembers task easier, but they can also add to overall task complexity if not properly designed. A leading candidate technology for supporting a hands-free environment is the Head-Mounted Display (HMD). A more recent technology (e-book reader) that could be easily temp-stowed near the work area is also a potential hands-free solution. Previous work at NASA involved the evaluation of several commercially available HMDs for visual quality, comfort, and fit, as well as suitability for use in microgravity. Based on results from this work, three HMDs were selected for further evaluation (along with an e-book reader), using International Space Station (ISS)-like maintenance procedures. Two evaluations were conducted in the Space Station Mockup and Trainer Facility (SSMTF) located at the NASA Johnson Space Center (building 9). The SSMTF is a full scale, medium fidelity replica of the pressurized portions of the ISS. It supports crew training such as ingress and egress, habitability, and emergency procedures. In each of the two evaluations, the participants performed two maintenance procedures. One maintenance procedure involved inspecting air filters in a life support system and replacing them with a clean filter if one were found to be contaminated. The second maintenance procedure focused on working in a confined space; specifically, pulling down a rack to inspect wiring configurations, and rewiring in a different pattern. The maintenance procedures were selected to assess mobility, tool use, and access to multiple document sources during task performance. That is, the participant had to move from rack to rack, use a wrench, a camera, etc., replace components, and refer to diagrams to complete tasks. A constraint was imposed that the ISS-like format of the procedures was to be retained, and not modified or optimized for the electronic device ("plug and play" approach). This was based on future plans to test with real procedures on ISS.

Ronald B Hoffman↗

Fatigue Analysis of Notched Laminates: A Time-Efficient Macro-Mechanical Approach

A coupled transversely isotropic deformation and damage fatigue model is implemented within the finite element method and was utilized along with a static progressive damage model to predict the fatigue life, stiffness degradation as a function of number of cycles, and post-fatigue tension and compression response of notched, multidirectional laminates. Initially, the material parameters for the fatigue model were obtained utilizing micromechanics simulations and the provided [0], [90] and [plus or minus 45] experimental composite laminate S-N (stress-cycle) data. Within the fatigue damage model, the transverse and shear properties of the plies were degraded with an isotropic scalar damage variable. The damage in the longitudinal (fiber) ply direction was suppressed, and only the strength of the fiber was degraded as a function of fatigue cycles. A maximum strain criterion was used to capture the failure in each element, and once this criterion was satisfied, the longitudinal stiffness of the element was decreased by a factor of 10 (sup 4). The resulting, degraded properties were then used to calculate the new stress state. This procedure was repeated until final failure of the composite laminate was achieved or a specified number of cycles reached. For post-fatigue tension and compression behavior, four internal state variables were used to control the damage and failure. The predictive capability of the above-mentioned approach was assessed by performing blind predictions of the notched multidirectional IM7/977-3 composite laminates response under fatigue and post-fatigue tensile and compressive loading, followed by a recalibration phase. Although three different multidirectional laminates were analyzed in the course of this study, only detailed results (i.e., stiffness degradation and post-fatigue stress-train curves as well as damage evolution states for a single laminate ([30/60/90/minus 30/minus 60] (sub 2s)) are discussed in detail here.

Composite Fatigue analysis↗