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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6

Sensors Provide Early Warning of Biological Threats

Early Warning Inc. of Troy, New York, licensed powerful biosensor technology from Ames Research Center. Incorporating carbon nanotubes tipped with single strands of nucleic acid from waterborne pathogens, the sensor can detect even minute amounts of targeted, disease causing bacteria, viruses, and parasites. Early Warning features the NASA biosensor in its water analyzer, which can provide advance alert of potential biological hazards in water used for agriculture, food and beverages, showers, and at beaches and lakes -- within hours instead of the days required by conventional laboratory methods.

Source record↗

Computer vision techniques for rotorcraft low altitude flight

Rotorcraft operating in high-threat environments fly close to the earth's surface to utilize surrounding terrain, vegetation, or manmade objects to minimize the risk of being detected by an enemy. Increasing levels of concealment are achieved by adopting different tactics during low-altitude flight. Rotorcraft employ three tactics during low-altitude flight: low-level, contour, and nap-of-the-earth (NOE). The key feature distinguishing the NOE mode from the other two modes is that the whole rotorcraft, including the main rotor, is below tree-top whenever possible. This leads to the use of lateral maneuvers for avoiding obstacles, which in fact constitutes the means for concealment. The piloting of the rotorcraft is at best a very demanding task and the pilot will need help from onboard automation tools in order to devote more time to mission-related activities. The development of an automation tool which has the potential to detect obstacles in the rotorcraft flight path, warn the crew, and interact with the guidance system to avoid detected obstacles, presents challenging problems. Research is described which applies techniques from computer vision to automation of rotorcraft navigtion. The effort emphasizes the development of a methodology for detecting the ranges to obstacles in the region of interest based on the maximum utilization of passive sensors. The range map derived from the obstacle-detection approach can be used as obstacle data for the obstacle avoidance in an automatic guidance system and as advisory display to the pilot. The lack of suitable flight imagery data presents a problem in the verification of concepts for obstacle detection. This problem is being addressed by the development of an adequate flight database and by preprocessing of currently available flight imagery. The presentation concludes with some comments on future work and how research in this area relates to the guidance of other autonomous vehicles.

Sridhar, Banavar↗

Microbial Surveillance of Potable Water Sources of the International Space Station

To mitigate risk to the crew, the microbial surveillance of the quality of potable water sources of the International Space Station (ISS) has been ongoing since before the arrival of the first permanent crew. These water sources have included stored ground-supplied water, water produced by the shuttle fuel cells during flight, and ISS humidity condensate that is reclaimed and processed. Monitoring was accomplished using a self-contained filter designed to allow bacterial growth and enumeration during flight. Upon return to earth, microbial isolates were identified using 16S ribosomal gene sequencing. While the predominant isolates were common Gramnegative bacteria including Ralstonia eutropha, Methylobacterium fujisawaense, and Spingomonas paucimobilis, opportunistic pathogens such as Stenotrophomonas maltophilia and Pseudomonas aeruginosa were also isolated. Results of in-flight enumeration have indicated a fluctuation of bacterial counts above system design specifications. Additional in-flight monitoring capability for the specific detection of coliforms was added in 2004; no coliforms have been detected from any potable water source. Neither the bacterial concentrations nor the identification of the isolates recovered from these samples has suggested a threat to crew health.

Bruce, Rebekah J.↗

Upgrade Summer Severe Weather Tool in MIDDS

The goal of this task was to upgrade the severe weather database from the previous phase by adding weather observations from the years 2004 - 2009, re-analyze the data to determine the important parameters, make adjustments to the index weights depending on the analysis results, and update the MIDDS GUI. The added data increased the period of record from 15 to 21 years. Data sources included local forecast rules, archived sounding data, surface and upper air maps, and two severe weather event databases covering east-central Florida. Four of the stability indices showed increased severe weather predication. The Total Threat Score (TTS) of the previous work was verified for the warm season of 2009 with very good skill. The TTS Probability of Detection (POD) was 88% and the False alarm rate (FAR) of 8%. Based on the results of the analyses, the MIDDS Severe Weather Worksheet GUI was updated to assist the duty forecaster by providing a level of objective guidance based on the analysis of the stability parameters and synoptic-scale dynamics.

Wheeler, Mark M.↗

Potential of VIIRS Time Series Data for Aiding the USDA Forest Service Early Warning System for Forest Health Threats: A Gypsy Moth Defoliation Case Study

The Healthy Forest Restoration Act of 2003 mandated that a national forest threat Early Warning System (EWS) be developed. The USFS (USDA Forest Service) is currently building this EWS. NASA is helping the USFS to integrate remotely sensed data into the EWS, including MODIS data for monitoring forest disturbance at broad regional scales. This RPC experiment assesses the potential of VIIRS (Visible/Infrared Imager/Radiometer Suite) and MODIS (Moderate Resolution Imaging Spectroradiometer) data for contribution to the EWS. In doing so, the RPC project employed multitemporal simulated VIIRS and MODIS data for detecting and monitoring forest defoliation from the non-native Eurasian gypsy moth (Lymantria despar). Gypsy moth is an invasive species threatening eastern U.S. hardwood forests. It is one of eight major forest insect threats listed in the Healthy Forest Restoration Act of 2003. This RPC experiment is relevant to several nationally important mapping applications, including carbon management, ecological forecasting, coastal management, and disaster management

Spruce, Joseph P.↗

The Spaceguard Survey: Report of the NASA International Near-Earth-Object Detection Workshop

Impacts by Earth-approaching asteroids and comets pose a significant hazard to life and property. Although the annual probability of the Earth being struck by a large asteroid or comet is extremely small, the consequences of such a collision are so catastrophic that it is prudent to assess the nature of the threat and to prepare to deal with it. The first step in any program for the prevention or mitigation of impact catastrophes must involve a comprehensive search for Earth-crossing asteroids and comets and a detailed analysis of their orbits. At the request of the U.S. Congress, NASA has carried out a preliminary study to define a program for dramatically increasing the detection rate of Earth-crossing objects, as documented in this workshop report.

Morrison, David↗

Status of automatic guidance systems for rotorcraft in low altitude flight

Rotorcraft operating in high-threat environments fly close to the earth's surface to utilize surrounding terrain, vegetation, or man-made objects to minimize the risk of being detected by an enemy. The piloting of the rotorcraft is at best a very demanding task and the pilots need help from on-board automation tools in order to devote more time to mission-related activities. The Automated Nap-of-the-Earth (NOE) Flight Program is a cooperative NASA/Army program aimed at the development of technologies for enhancing piloted low-altitude/NOE flight path management and control through computer and sensor aiding. The long-term objective is to work towards achieving automation for aiding the pilot in NOE flight with a flight demonstration of resulting computer/sensor aiding concepts at an established course. The technology for pilot-centered NOE automation is not currently available. Success in automating NOE functions will depend on major breakthroughs in real-time flight path planning algorithms, effective methods for the pilot to interface to the automatic modes, understanding of visual images, sensor data processing/fusion, and sensor development. Our approach to developing the technologies required to solve this problem consist of the following phases: (1) algorithm development, (2) laboratory evaluation, (3) piloted ground simulation, and (4) evaluation in flight. An overview of the research in this area at NASA Ames Research Center is given.

Sridhar, Banavar↗

Remote Sensing of Hail from Space: Retrievals, Climatologies, and Challenges Going Forward

In addition to the myriad threats that severe hailstorms pose to society, infrastructure and agriculture, severe hail is difficult to measure in situ, and surface-based hail reporting and detection methods are inconsistent and subject to geographical or societal biases. This motivates the use of spaceborne remote-sensing platforms to retrieve hail and construct climatologies in the most globally consistent way. Passive-microwave algorithms leverage the sensitivity of spaceborne passive-microwave radiometers to scattering by hail, particularly in the channels from 10 to 89 GHz. These retrievals are used to construct global climatologies of severe hail. The Bang and Cecil (2019) retrievals has been applied to several different spaceborne sensors: the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Global Precipitation Measurement Mission (GPM) Microwave Imager, Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors and used to construct [near] global climatologies of severe hail. This retrieval, and others, have been tested using Global Precipitation Measurement (GPM) Ku-band precipitation radar, to assess their effectiveness and regional variability. A successful retrieval and climatology are those that correspond tightly to radar reflectivity and give minimal appearance of regional biases, especially with latitude. Satellite platforms offer consistent observations, even in remote, data-sparse, and oceanic regions that ground-based networks exclude. There are, however, potential disconnects between the processes identified aloft by the satellite and the resultant weather at the ground, leading to uncertainties in the retrievals that may propagate into satellite-based climatologies, particularly in the Tropics, where there are abundant strong - but not necessarily hailing - storms that are strongly represented in the current satellite climatologies. There are ongoing efforts to assess and mitigate the contributing factors to these uncertainties, chiefly among them the effects of non-uniform beam filling in the passive-microwave footprint, and the relationships between the size distributions of hailstones aloft and the dynamic processes and environments with which they interact throughout their trajectories.

Sarah D Bang↗

Spaceborne Remote Sensing of Hail: Retrievals, Climatologies, and Challenges Going Forward

In addition to the myriad threats that severe hailstorms pose to society, infrastructure and agriculture, severe hail is difficult to measure in situ, and surface-based hail reporting and detection methods are inconsistent and subject to geographical or societal biases. This motivates the use of spaceborne remote-sensing platforms to retrieve hail and construct climatologies in the most globally consistent way. Passive-microwave algorithms leverage the sensitivity of spaceborne passive-microwave radiometers to scattering by hail, particularly in the channels from 10 to 89 GHz. These retrievals are used to construct global climatologies of severe hail. The Bang and Cecil (2019) retrievals has been applied to several different spaceborne sensors: the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Global Precipitation Measurement Mission (GPM) Microwave Imager, Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors and used to construct [near] global climatologies of severe hail. This retrieval, and others, have been tested using Global Precipitation Measurement (GPM) Ku-band precipitation radar, to assess their effectiveness and regional variability. A successful retrieval and climatology are those that correspond tightly to radar reflectivity and give minimal appearance of regional biases, especially with latitude. Satellite platforms offer consistent observations, even in remote, data-sparse, and oceanic regions that ground-based networks exclude. There are, however, potential disconnects between the processes identified aloft by the satellite and the resultant weather at the ground, leading to uncertainties in the retrievals that may propagate into satellite-based climatologies, particularly in the Tropics, where there are abundant strong - but not necessarily hailing - storms that are strongly represented in the current satellite climatologies. There are ongoing efforts to assess and mitigate the contributing factors to these uncertainties, chiefly among them the effects of non-uniform beam filling in the passive-microwave footprint, and the relationships between the size distributions of hailstones aloft and the dynamic processes and environments with which they interact throughout their trajectories.

Sarah D Bang↗

Impact of flying qualities on mission effectiveness for helicopter air combat, volume 1

A computer simulation to investigate the impact of flying qualities on mission effectiveness is described. The objective of the study was to relate the effects of flying qualities, such as precision of flight path control and pilot workload, to the ability of a single Scout helicopter, or helicopter team, to accomplish a specified anti-armor mission successfully. The model of the actual engagement is a Monte Carlo simulation that has the capability to assess the effects of helicopter characteristics, numbers, tactics and weaponization on the force's ability to accomplish a specific mission against a specified threat as a function of realistic tactical factors. A key feature of this program is a simulation of micro-terrain features and their effects on detection, exposure, and masking for nap-of-the-earth (NOE) flight.

Harris, T. M.↗

Kalman filter based range estimation for autonomous navigation using imaging sensors

Rotorcraft operating in high-threat environments fly close to the surface of the earth to utilize surrounding terrain, vegetation, or man-made objects to minimize the risk of being detected by the enemy. Two basic requirements for obstacle avoidance are detection and range estimation of the object from the current rotorcraft position. There are many approaches to the estimation of range using a sequence of images. The approach used in this analysis differes from previous methods in two significant ways: an attempt is not made to estimate the rotorcraft's motion from the images; and the interest lies in recursive algorithms. The rotorcraft parameters are assumed to be computed using an onboard inertial navigation system. Given a sequence of images, using image-object differential equations, a Kalman filter (Sridhar and Phatak, 1988) can be used to estimate both the relative coordinates and the earth coordinates of the objects on the ground. The Kalman filter can also be used in a predictive mode to track features in the images, leading to a significant reduction of search effort in the feature extraction step of the algorithm. The purpose is to summarize early results obtained in extending the Kalman filter for use with actual image sequences. The experience gained from the application of this algorithm to real images is very valuable and is a necessary step before proceeding to the estimation of range during low-altitude curvilinear flight. A simple recursive method is presented to estimate range to objects using a sequence of images. The method produces good range estimates using real images in a laboratory set up and needs to be evaluated further using several different image sequences to test its robustness. The feature generation part of the algorithm requires further refinement on the strategies to limit the number of features (Sridhar and Phatak, 1989). The extension of the work reported here to curvilinear flight may require the use of the extended Kalman filter.

Sridhar, Banavar↗

Robust IR Remote Sensing Technique of the Total Column of Trace Gases Including Carbon Dioxide and Methane

Progress on the development of a differential radiometer based upon the Fabry-Perot interferometer (FPI) for methane (CH4) and carbon dioxide (C02) detection in the atmosphere is presented. Methane measurements are becoming increasingly important as a component of NASA's programs to understand the global carbon cycle and quantifY the threat of global warming. Methane is the third most important greenhouse gas in the Earth's radiation budget (after water vapor and carbon dioxide) and the second most important anthropogenic contributor to global warming. The importance of global warming and air quality to society caused the National Research Council to recommend that NASA develop the following missions [1]: ASCENDS (Active Sensing of C02 Emissions over Nights, Days, and Seasons), GEOCAPE (Geostationary Coastal and Air Pollution Events), and GACM (Global Atmosphere Composition Mission). Though methane measurements are not specifically called out in these missions, ongoing environmental changes have raised the importance of understanding the methane budget. In the decadal survey is stated that "to close the carbon budget, we would also address methane, but the required technology is not obvious at this time. If appropriate and cost-effective methane technology becomes available, we strongly recommend adding a methane capability". In its 2007 report the International Panel on Climate Change identified methane as a key uncertainty in our understanding saying that the causes of recent changes in the growth rate of atmospheric CH4 are not well understood. What we do know is that methane arises from a number of natural sources including wet lands and the oceans plus man made sources from agriculture, as well as coal and petroleum production and distribution. It has recently been pointed out that large amount of methane are frozen in the permafrost of Canada and Siberia. There is a fear that melting of this permafrost driven by global warming may release large amounts of methane very suddenly further exacerbating climate change [2]. Last year our group began a joint effort with Johns Hopkins Applied Physics Laboratory to investigate the possibility of developing a small unmanned aerial vehicle (UAV) equipped to measure greenhouse gases-particularly methane. Although we are targeting our system for smaller UAV's the instrument will be directly applicable to missions involving larger NASA UAV's such as Global Hawk or even on missions utilizing manned aircraft. Because of its small size, inherent ruggedness and simplicity some version of our proposed instrument may find a role as a satellite instrument for NASA or NOAA.

Georgieva, E. M.↗

Real-Time Integrity Monitoring of Stored Geo-Spatial Data Using Forward-Looking Remote Sensing Technology

Terrain Awareness and Warning Systems (TAWS) and Synthetic Vision Systems (SVS) provide pilots with displays of stored geo-spatial data (e.g. terrain, obstacles, and/or features). As comprehensive validation is impractical, these databases typically have no quantifiable level of integrity. This lack of a quantifiable integrity level is one of the constraints that has limited certification and operational approval of TAWS/SVS to "advisory-only" systems for civil aviation. Previous work demonstrated the feasibility of using a real-time monitor to bound database integrity by using downward-looking remote sensing technology (i.e. radar altimeters). This paper describes an extension of the integrity monitor concept to include a forward-looking sensor to cover additional classes of terrain database faults and to reduce the exposure time associated with integrity threats. An operational concept is presented that combines established feature extraction techniques with a statistical assessment of similarity measures between the sensed and stored features using principles from classical detection theory. Finally, an implementation is presented that uses existing commercial-off-the-shelf weather radar sensor technology.

Young, Steven D.↗

Cooperative Collision Avoidance Step 1 - Technology Demonstration Flight Test Report. Revision 1

The National Aeronautics and Space Administration (NASA) Access 5 Project Office sponsored a cooperative collision avoidance flight demonstration program for unmanned aircraft systems (UAS). This flight test was accomplished between September 21st and September 27th 2005 from the Mojave Airport, Mojave, California. The objective of these flights was to collect data for the Access 5 Cooperative Collision Avoidance (CCA) Work Package simulation effort, i.e., to gather data under select conditions to allow validation of the CCA simulation. Subsequent simulation to be verified were: Demonstrate the ability to detect cooperative traffic and provide situational awareness to the ROA pilot; Demonstrate the ability to track the detected cooperative traffic and provide position information to the ROA pilot; Demonstrate the ability to determine collision potential with detected cooperative traffic and provide notification to the ROA pilot; Demonstrate that the CCA subsystem provides information in sufficient time for the ROA pilot to initiate an evasive maneuver to avoid collision; Demonstrate an evasive maneuver that avoids collision with the threat aircraft; and lastly, Demonstrate the ability to assess the adequacy of the maneuver and determine that the collision potential has been avoided. The Scaled Composites, LLC Proteus Optionally Piloted Vehicle (OPV) was chosen as the test platform. Proteus was manned by two on-board pilots but was also capable of being controlled from an Air Vehicle Control Station (AVCS) located on the ground. For this demonstration, Proteus was equipped with cooperative collision sensors and the required hardware and software to place the data on the downlink. Prior to the flight phase, a detailed set of flight test scenarios were developed to address the flight test objectives. Two cooperative collision avoidance sensors were utilized for detecting aircraft in the evaluation: Traffic Alert and Collision Avoidance System-II (TCAS-II) and Automatic Dependent Surveillance Broadcast (ADS-B). A single intruder aircraft was used during all the flight testing, a NASA Gulfstream III (G-III). During the course of the testing, six geometrically different near-collision scenarios were evaluated. These six scenarios were each tested using various combinations of sensors and collision avoidance software. Of the 54 planned test points 49 were accomplished successfully. Proteus flew a total of 21.5 hours during the testing and the G-III flew 19.8 hours. The testing fully achieved all flight test objectives. The Flight IPT performed an analysis to determine the accuracy of the simulation model used to predict the location of the host aircraft downstream during an avoidance maneuver. The data collected by this flight program was delivered to the Access 5 Cooperative Collision Avoidance (CCA) Work Package Team who was responsible for reporting on their analysis of this flight data.

Trongale, Nicholas A.↗

Utility of Visual and Auditory Warning Alerting for Traffic Avoidance During UAS Operations

This presentation covers the results of a human-in-the-loop simulation that examined the effect of caution versus warning-level alerting in the context of Unmanned Aircraft System (UAS) operations in civil airspace. Minimum Operational Performance Standards (MOPS) are currently being developed by RTCA Special Committee 228 for UAS Detect-and-Avoid (DAA) systems. Input from subject matter experts and multiple research studies have informed display requirements for DAA systems aimed at supporting timely and appropriate pilot responses to collision hazards. DAA alerting is designed to inform pilots of potential threats to DAA "well clear"; the two highest alert levels - caution and warning - indicate how soon pilot action is required and whether there is adequate time to coordinate with the air traffic controller (ATC). Additional empirical support is needed to clarify the extent to which warning-level alerting impacts DAA task performance. The present study explores the differential effects of the auditory and visual cues provided by the DAA Warning alert, and performance implications compared to caution-only alerting are discussed.

detect and avoid↗

Thunderstorm Hypothesis Reasoner

THOR is a knowledge-based system which incorporates techniques from signal processing, pattern recognition, and artificial intelligence (AI) in order to determine the boundary of small thunderstorms which develop and dissipate over the area encompassed by KSC and the Cape Canaveral Air Force Station. THOR interprets electric field mill data (derived from a network of electric field mills) by using heuristics and algorithms about thunderstorms that have been obtained from several domain specialists. THOR generates two forms of output: contour plots which visually describe the electric field activity over the network and a verbal interpretation of the activity. THOR uses signal processing and pattern recognition to detect signatures associated with noise or thunderstorm behavior in a near real time fashion from over 31 electrical field mills. THOR's AI component generates hypotheses identifying areas which are under a threat from storm activity, such as lightning. THOR runs on a VAX/VMS at the Kennedy Space Center. Its software is a coupling of C and FORTRAN programs, several signal processing packages, and an expert system development shell.

Mulvehill, Alice M.↗

Structural Integrity Evaluation of the Lear Fan 2100 Aircraft

An in-situ nondestructive inspection was conducted to detect manufacturing and assembly induced defects in the upper two wing surfaces (skin s) and upper fuselage skin of the Lear Fan 2100 aircraft E009. The effects of the defects, detected during the inspection, on the integrity of the structure was analytically evaluated. A systematic evaluation was also conducted to determine the damage tolerance capability of the upper wing skin against impact threats and assembly induced damage. The upper wing skin was divided into small regions for damage tolerance evaluations. Structural reliability, margin of safety, allowable strains, and allowable damage size were computed. The results indicated that the impact damage threat imposed on composite military aircraft structures is too severe for the Lear Fan 2100 upper wing skin. However, the structural integrity is not significantly degraded by the assembly induced damage for properly assembled structures, such as the E009 aircraft.

Composites↗