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At least 379 records · Page 21

Reliability of void detection in structural ceramics by use of scanning laser acoustic microscopy

The reliability of scanning laser acoustic microscopy (SLAM) for detecting surface voids in structural ceramic test specimens was statistically evaluated. Specimens of sintered silicon nitride and sintered silicon carbide, seeded with surface voids, were examined by SLAM at an ultrasonic frequency of 100 MHz in the as fired condition and after surface polishing. It was observed that polishing substantially increased void detectability. Voids as small as 100 micrometers in diameter were detected in polished specimens with 0.90 probability at a 0.95 confidence level. In addition, inspection times were reduced up to a factor of 10 after polishing. The applicability of the SLAM technique for detection of naturally occurring flaws of similar dimensions to the seeded voids is discussed. A FORTRAN program listing is given for calculating and plotting flaw detection statistics.

Roth, D. J.↗

Evaluation of liquid water measuring instruments in cold clouds sampled during FIRE

Airborne liquid water content (LWC) measurements were conducted with an icing detector and a forward-scattering spectrometer probe during 10 flights into cold clouds, as part of the First ISCCP Research Experiment (FIRE). The LWC measurements thus obtained compare favorably with those from the hot-wire probes in the range where LWC is above the detection limits of the latter; the hot-wire probes have detection thresholds about one order of magnitude higher than is possible with the icing detector and spectrometer probe. FIRE experiment data indicate that LWC should be taken into consideration in cloud studies at temperatures down to at least 35 C.

Heymsfield, Andrew J.↗

ISS Destiny Laboratory Smoke Detection Model

Smoke transport and detection were modeled numerically in the ISS Destiny module using the NIST, Fire Dynamics Simulator code. The airflows in Destiny were modeled using the existing flow conditions and the module geometry included obstructions that simulate the currently installed hardware on orbit. The smoke source was modeled as a 0.152 by 0.152 m region that emitted smoke particulate ranging from 1.46 to 8.47 mg/s. In the module domain, the smoke source was placed in the center of each Destiny rack location and the model was run to determine the time required for the two smoke detectors to alarm. Overall the detection times were dominated by the circumferential flow, the axial flow from the intermodule ventilation and the smoke source strength.

Brooker, John E.↗

Role of MODIS Vegetation Phenology Products in the ForWarn System for Monitoring of Forest Disturbances in the Conterminous United States

This presentation discusses MODIS vegetation phenology products used in the ForWarn Early Warning System (EWS) tool for near real time regional forest disturbance detection and surveillance at regional to national scales. The ForWarn EWS is being developed by the USDA Forest Service NASA, ORNL, and USGS to aid federal and state forest health management activities. ForWarn employs multiple historical land surface phenology products that are derived from MODIS MOD13 Normalized Difference Vegetation Index (NDVI) data. The latter is temporally processed into phenology products with the Time Series Product Tool (TSPT) and the Phenological Parameter Estimation Tool (PPET) software produced at NASA Stennis Space Center. TSPT is used to effectively noise reduce, fuse, and void interpolate MODIS NDVI data. PPET employs TSPT-processed NDVI time series data as an input, outputting multiple vegetation phenology products at a 232 meter resolution for 2000 to 2011, including NDVI magnitude and day of year products for seven key points along the growing season (peak of growing season and the minima, 20%, and 80% of the peak NDVI for both the left and right side of growing season), cumulative NDVI integral products for the most active part of the growing season and sequentially across the growing season at 8 day intervals, and maximum value NDVI products composited at 24 day intervals in which each product date has 8 days of overlap between the previous and following product dates. MODIS NDVI phenology products are also used to compute nationwide NRT forest change products refreshed every 8 days. These include percent change in forest NDVI products that compare the current NDVI from USGS eMODIS products to historical MODIS MOD13 NDVI. For each date, three forest change products are produced using three different maximum value NDVI baselines (from the previous year, three previous years, and all previous years). All change products are output with a rainbow color table in which forests with the most severe NDVI decreases are assigned hot colors (yellow to red) and forests with prominent NDVI increases are assigned cold colors (blue tones). All mentioned products have been integrated as data layers into ForWarn s geospatial data viewer known as the U.S. Forest Change Assessment Viewer (FCAV). The latter is used to view and assess the context of the mentioned forest change products with respect to ancillary data layers, such as land cover, elevation, hydrologic features, climatic data, storm data, aerial disturbance surveys, fire data, and land ownership. The FCAV also includes a temporal NDVI profiler for viewing phenological change in multi-year NDVI associated with known or suspected regionally apparent forest disturbances (e.g., from fire and insects). ForWarn forest change products have been used to detect, track, and assess several biotic and abiotic regional forest disturbance events across the country, including ephemeral and longer lasting damage from storms, drought, and insects. Such change products are most effective for viewing severe disturbances affecting multiple MODIS pixels. MODIS vegetation phenology products contribute vital current information on forest conditions to the ForWarn system and this role is expected to grow as these products are refined and derivative products are added.

Spruce, Joseph P.↗

Analysis of Cirrus Cloud Microphysical Data

The First International Satellite Cloud Climatology Regional Experiment (FIRE) program has the goal of improving our capabilities to understand, model and detect the properties of climatically-important clouds. This is being undertaken through a three-pronged effort of modeling, long-term observations and short-term intensive field studies. Through examination of satellite and other data it is apparent that stratus and cirrus cloud types have the greatest impact on climate due to their radiative effects and ubiquitous nature. As a result, the FIRE program has developed two paths of investigation, each having its own subset of research objectives and measurement programs. The work conducted under this grant was directed toward furthering our understanding of cirrus cloud systems. While it is known that cirrus are climatically important, the magnitude and even sign of the impact is unclear. Cirrus clouds affect the transfer of radiation according to their physical depth and location in the atmosphere and their microphysical composition. However, significant uncertainties still exist in how cirrus clouds form and how they are maintained, what their physical properties are and how they can be parameterized in numerical models. Better remote sensing techniques for monitoring cirrus cloud systems and improved modeling of radiative transfer through ice particles are also needed. A critical element in resolving these issues is a better understanding of cirrus cloud microphysical properties and how they vary. The focus of the research to be conducted under this grant was th data collected in situ by the University of North Dakota Citation aircraft. The goals of this research were to add to the body of knowledge of cirrus cloud microphysics, particularly at the small end of the size spectrum; and analyze the spatial variation of cirrus clouds.

Poellot, Michael R.↗

Drone Applications for Wildfires and Other Emergency Situations

Potential Solutions to Wildfires This project is looking at multiple aspects of the use of UAV’s during wildfire season. This project identifies multiple solutions to communication problems, early action response, and innovative tactics to fight wildfires during the dark hours of the second shift. This project will identify the features and innovations needed to create a second shift that can more effectively fight wildland fires at night. In addition, this project will look to find which satellite systems work best for detection of wildfires, with a special focus on remote locations with more rural communities. There will also be a focus on ways to improve current UAVs and sensors for aerial fire surveillance as well as the understanding on how to establish a safe airspace for these UAVs during wildfires. More specifically, unmanned ariel vehicles (UAV) or drones can be used during natural disasters and other situations to help first responders be a more efficient team, ultimately saving hundreds of more lives. Depending on the situation, drones can be equipped with many different accessories, each with their own advantages. When it comes to operating a drone, communication between the first responder, dispatcher, and the person flying the drone is very important when exchanging useful information. A focus on existing systems, and what changes could be made to create more novel systems will also be shown. Moreover, wildfires not only pose a hazard to human safety and a dent on communication methods, but it also has detrimental effects on the environment. Specifically, the use of common fire retardants have dangerous health effects on human health and the environment as a whole. Therefore, this project will also explore the use of alternative eco-friendly fire retardants and recent innovations to the use of sustainable retardants.

Drones↗

Failure Control Techniques for the SSME

Since ground testing of the Space Shuttle Main Engine (SSME) began in 1975, the detection of engine anomalies and the prevention of major damage have been achieved by a multi-faceted detection/shutdown system. The system continues the monitoring task today and consists of the following: sensors, automatic redline and other limit logic, redundant sensors and controller voting logic, conditional decision logic, and human monitoring. Typically, on the order of 300 to 500 measurements are sensed and recorded for each test, while on the order of 100 are used for control and monitoring. Despite extensive monitoring by the current detection system, twenty-seven (27) major incidents have occurred. This number would appear insignificant compared with over 1200 hot-fire tests which have taken place since 1976. However, the number suggests the requirement for and future benefits of a more advanced failure detection system.

Taniguchi, M. H.↗

Studies of images of short-lived events using ERTS data

The author has identified the following significant results. Of significance are the continued detection and analysis of such short-lived events as forest fires, oil spills, vegetation damage, volcanoes, storm ridges, and earthquakes.

Deutschman, W. A.↗

The Jeffcott equations in nonlinear rotordynamics

The Jeffcott equations are a system of coupled differential equations representing the behavior of a rotating shaft. This is a simple model which allows investigation of the basic dynamic behavior of rotating machinery. Nolinearities can be introduced by taking into consideration deadband, side force, and rubbing, among others. The properties of the solutions of the Jeffcott equations with deadband are studied. In particular, it is shown how bounds for the solution of these equations can be obtained from bounds for the solutions of the linearized equations. By studying the behavior of the Fourier transforms of the solutions, we are also able to predict the onset of destructive vibrations. These conclusions are verified by means of numerical solutions of the equations, and of power spectrum density (PSD) plots. This study offers insight into a possible detection method to determine pump stability margins during flight and hot fire tests, and was motivated by the need to explain a phenomenon observed in the development phase of the cryogenic pumps of the Space Shuttle, during hot fire ground testing; namely, the appearance of vibrations at frequencies that could not be accounted for by means of linear models.

Zalik, R. A.↗

Identification of the Space Shuttle Main Engine dynamic models from firing data

A multi-input multi-output system identification technique is used to obtain linearized point models of the Space Shuttle Main Engine (SSME) at five different operating conditions (power levels) from the engine firing data. This study demonstrates that the open-loop dynamics of the SSME can be successfully modeled from the engine firing data. The identified linear models may be used for fault detection studies and control system design and development.

Saravanan, N.↗

Synergic use of TOMS and Aeronet Observations for Characterization of Aerosol Absorption

The role of aerosol absorption on the radiative transfer balance of the earth-atmosphere system is one of the largest sources of uncertainty in the analysis of global climate change. Global measurements of aerosol single scattering albedo are, therefore, necessary to properly assess the radiative forcing effect of aerosols. Remote sensing of aerosol absorption is currently carried out using both ground (Aerosol Robotic Network) and space (Total Ozone Mapping Spectrometer) based observations. The satellite technique uses measurements of backscattered near ultraviolet radiation. Carbonaceous aerosols, resulting from the combustion of biomass, are one of the most predominant absorbing aerosol types in the atmosphere. In this presentation, TOMS and AERONET retrievals of single scattering albedo of carbonaceous aerosols, are compared for different environmental conditions: agriculture related biomass burning in South America and Africa and peat fires in Eastern Europe. The AERONET and TOMS derived aerosol absorption information are in good quantitative agreement. The most absorbing smoke is detected over the African Savanna. Aerosol absorption over the Brazilian rain forest is less absorbing. Absorption by aerosol particles resulting from peat fires in Eastern Europe is weaker than the absorption measured in Africa and South America. This analysis shows that the near UV satellite method of aerosol absorption characterization has the sensitivity to distinguish different levels of aerosol absorption. The analysis of the combined AERONET-TOMS observations shows a high degree of synergy between satellite and ground based observations.

Torres, O.↗

Quantifying Black Carbon Deposition Over the Greenland Ice Sheet from Forest Fires in Canada

Black carbon (BC) concentrations observed in 22 snowpits sampled in the northwest sector of the Greenland ice sheet in April 2014 have allowed us to identify a strong and widespread BC aerosol deposition event, which was dated to have accumulated in the pits from two snow storms between 27 July and 2 August 2013. This event comprises a significant portion (57 on average across all pits) of total BC deposition over 10 months (July 2013 to April 2014). Here we link this deposition event to forest fires burning in Canada during summer 2013 using modeling and remote sensing tools. Aerosols were detected by both the Cloud-Aerosol Lidar with Orthogonal Polarization (on board CALIPSO) and Moderate Resolution Imaging Spectroradiometer (Aqua) instruments during transport between Canada and Greenland. We use high-resolution regional chemical transport modeling (WRF-Chem) combined with high-resolution fire emissions (FINNv1.5) to study aerosol emissions, transport, and deposition during this event. The model captures the timing of the BC deposition event and shows that fires in Canada were the main source of deposited BC. However, the model underpredicts BC deposition compared to measurements at all sites by a factor of 2100. Underprediction of modeled BC deposition originates from uncertainties in fire emissions and model treatment of wet removal of aerosols. Improvements in model descriptions of precipitation scavenging and emissions from wildfires are needed to correctly predict deposition, which is critical for determining the climate impacts of aerosols that originate from fires.

albedo↗

Mobile In Vivo Infrared Data Collection and Diagnoses Comparison System

Described is a mobile in vivo infrared brain scan and analysis system. The system includes a data collection subsystem and a data analysis subsystem. The data collection subsystem is a helmet with a plurality of infrared (IR) thermometer probes. Each of the IR thermometer probes includes an IR photodetector capable of detecting IR radiation generated by evoked potentials within a user's skull. The helmet is formed to collect brain data that is reflective of firing neurons in a mobile subject and transmit the brain data to the data analysis subsystem. The data analysis subsystem is configured to generate and display a three-dimensional image that depicts a location of the firing neurons. The data analysis subsystem is also configured to compare the brain data against a library of brain data to detect an anomaly in the brain data, and notify a user of any detected anomaly in the brain data.

Mintz, Frederick W.↗

Nondestructive Determination of Heat/Fire Damage to Polymer- Matrix Composites Using Obliquely Insonified Ultrasonic Waves

Heat and fire damage to composite structures cause loss of strength that cannot be detected by current NDE methods unless physical damage occurs. Further, there is a lack of fundamental understanding of the mechanism of damage from thermal exposure of organic matrix composites to elevated temperatures. Information compiled from field reports and lab experiments increasingly suggests that there is material degradation and it is not necessarily involved with the introduction of physical defects. In recent years, various researchers examined the potential to identifying thermal degradation to organic matrix composites prior to delamination. The methods that were used include: ultrasonics, backscattered X-ray, eddy current, thermography, drift and LPF spectroscopies, acousto-ultrasonics and hardness testing. None of these methods were able to correlate NDE results with loss of mechanical properties.

polymer-matrix composite fire damage NDE nondestru↗

Connecting Crop Productivity, Residue Fires, and Air Quality over Northern India

Northwestern India is known as the “breadbasket” of the country producing two-thirds of food grains, with wheat and rice as the principal crops grown under the crop rotation system. Agricultural data from India indicates a 25% increase in the post-monsoon rice crop production in Punjab during 2002–2016. NASA’s A-train satellite sensors detect a consistent increase in the vegetation index (net 21%) and post-harvest agricultural fire activity (net ~60%) leading to nearly 43% increase in aerosol loading over the populous Indo-Gangetic Plain in northern India. The ground-level particulate matter (PM2.5) downwind over New Delhi shows a concurrent uptrend of net 60%. The effectiveness of a robust satellite-based relationship between vegetation index—a proxy for crop amounts, and post-harvest fires—a precursor of extreme air pollution events, has been further demonstrated in predicting the seasonal agricultural burning. An efficient crop residue management system is critically needed towards eliminating open field burning to mitigate episodic hazardous air quality over northern India.

Hiren Jethva↗

Multispectral radiation detection of small changes in target emissivity

An investigation into the multispectral radiation detection of small changes in target emissivity has been performed by Georgia Tech. A series of ice detection measurements on the shuttle external tank (ET) were performed using an advanced instrumentation radiometer operating at 35/95 GHz. Actual shuttle ET ice detection measurements were run at NASA's National Space Technology Laboratory (NSTL) during cryogenic fueling operations prior to orbiter engine firing tests. Investigations revealed that ET icing caused an increase in surface brightness temperature and the test results further demonstrated the usefulness of millimeter wave radiometry for the detection of ice on the ET.

Gagliano, J. A.↗

Annular arc accelerator shock tube

An annular arc accelerator shock tube employs a cold gas driver to flow a stream of gas from an expansion section through a high voltage electrode section to a test section, thus driving a shock wave in front of it. A glow discharge detects the shock wave and actuates a trigger generator which in turn fires spark-gap switches to discharge a bank of capacitors across a centered cathode and an annular anode in tandem electrode sections. The initial shock wave passes through the anode section from the cathode section thereby depositing energy into the flow gas without the necessity of any diaphragm opening in the gas flow from the expansion section through the electrode sections.

Leibowitz, L. P.↗

Use of remote sensing for land use policy formulation

Progress in studies for using remotely sensed data for assessing crop stress and in crop estimation is reported. The estimation of acreage of small forested areas in the southern lower peninsula of Michigan using LANDSAT data is evaluated. Damage to small grains caused by the cereal leaf beetle was assessed through remote sensing. The remote detection of X-disease of peach and cherry trees and of fire blight of pear and apple trees was investigated. The reliability of improving on standard methods of crop production estimation was demonstrated. Areas of virus infestation in vineyards and blueberry fields in western and southwestern Michigan were identified. The installation and systems integration of a microcomputer system for processing and making available remotely sensed data are described.

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