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NASA NTRSDate not supplied

Understanding the Durability of SiC Based Ceramic Matrix Composites (CMCs) for Gas Turbine Engine Hot Section Components

Silicon carbide fiber reinforced silicon carbide ceramic matrix composites (SiCf/SiC-CMCs) are being used in the fabrication of gas turbine engine hot section components due to their light weight and excellent thermal and chemical stabilities at high-temperature. These superior properties enable significant enhancements in engine efficiency and reduced fuel burn, emissions, and cooling requirements. In support of NASA’s Aeronautics Mission under various programs at Glenn Research Center, different types of composites have been developed and assessed for a high temperature (2700 °F) SiCf/SiC CMC system for turbine engine applications. These composites have creep-resistant SiC fibers, advanced 3D weaves, 2700 °F-capable hybrid SiC matrices, and durable environmental barrier coatings (EBCs). These efforts have resulted in improvements in the overall CMC thermomechanical and environmental durability. In order to study the role of different constituents and processing variables, a single fiber tow CVI (chemical vapor infiltration) SiC/SiC mini-composite can be considered the basic architectural feature of woven and laminate SiC/SiC CMCs. Moreover, the mini-composite mechanical and tensile creep damage behavior represents the creep behavior of 0° fiber tows in the axial loading direction of a macro-composite or component. In addition, a large number of mini-composite samples can be fabricated at relatively low cost within a short time, which makes them attractive for obtaining a robust set of experimental data and studying constituent behavior. In this presentation, the mini-composite approach to study damage mechanisms that limit CMC life in extreme environments including exposure to steam will be presented. The effects of constituent type and volume fraction on the CMC durability, which will help influence CMC design, will be discussed.

Ceramic Matrix Composites (CMCs)↗
NASA NTRS2014

How Well Do Satellite AOD Observations Represent the Spatial and Temporal Variability of PM2.5 Concentration for the United States?

Due to their extensive spatial coverage, satellite Aerosol Optical Depth (AOD) observations have been widely used to estimate and predict surface PM2.5 concentrations. While most previous studies have focused on establishing relationships between collocated, hourly or daily AOD and PM2.5 measurements, in this study, we instead focus on the comparison of the large-scale spatial and temporal variability between satellite AOD and PM2.5 using monthly mean measurements. A newly developed spectral analysis technique e Combined Maximum Covariance Analysis (CMCA) is applied to Moderate Resolution Imaging Spectroradiometer (MODIS), Multi-angle Imaging Spectroradiometer (MISR), Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Ozone Monitoring Instrument (OMI) AOD datasets and Environmental Protection Agency (EPA) PM2.5 data, in order to extract and compare the dominant modes of variability. Results indicate that AOD and PM2.5 agree well in terms of interannual variability. An overall decrease is found in both AOD and PM2.5 across the United States, with the strongest signal over the eastern US. With respect to seasonality, good agreement is found only for Eastern US, while for Central and Western US, AOD and PM2.5 seasonal cycles are largely different or even reversed. These results are verified using Aerosol Robotic Network (AERONET) AOD observations and differences between satellite and AERONET are also examined. MODIS and MISR appear to have the best agreement with AERONET. In order to explain the disagreement between AOD and PM2.5 seasonality, we further use Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) extinction profile data to investigate the effect of two possible contributing factors, namely aerosol vertical distribution and cloud-free sampling. We find that seasonal changes in aerosol vertical distribution, due to the seasonally varying mixing height, is the primary cause for the AOD and PM2.5 seasonal discrepancy, in particular, the low AOD but high PM2.5 observed during the winter season for Central and Western US. In addition, cloud-free sampling by passive sensors also induces some bias in AOD seasonality, especially for the Western US, where the largest seasonal change in cloud fraction is found. The seasonal agreement between low level (below 500 m AGL), all sky CALIOP AOD and PM2.5 is significantly better than column AOD from MODIS, MISR, SeaWiFS and OMI. In particular, the correlation between low level, all sky AOD and PM2.5 seasonal cycles increases to above 0.7 for Central and Western US, as opposed to near zero or negative correlation for column, clear sky AOD. This result highlights the importance of accounting for the seasonally varying aerosol profiles and cloud-free sampling bias when using column AOD measurements to infer surface PM2.5 concentrations.

MODIS (radiometry)↗
NASA NTRS2000

Water Vapor Tacers as Diagnostics of the Regional Atmospheric Hydrologic Cycle

Understanding of the local and remote sources of water vapor can be a valuable diagnostic in understanding the regional atmospheric hydrologic cycle, especially in North America where moisture transport and local evaporation are important sources of water for precipitation. In the present study, we have implemented passive tracers as prognostic variables to follow water vapor evaporated in predetermined regions until the water tracer precipitates. All evaporative sources of water are accounted for by tracers, and the water vapor variable provides the validation of the tracer water and the formulation of the sources and sinks. The Geostationary Operational Environmental Satellites General Circulation Model (GEOS GCM) is used to simulate several summer periods to determine the source regions of precipitation for the United States and India. Using this methodology, a detailed analysis of the recycling of water, interannual variability of the sources of water and links to the Great Plains low-level jet and North American monsoon will be presented. Potential uses in GCM sensitivity studies, predictability studies and data assimilation especially regarding the North American monsoon and GEWEX America Prediction Project (GAPP) will be discussed.

Bosilovich, Michael G.↗
NASA NTRS1992

Effect of Personal and Situational Variables on Noise Annoyance: with Special Reference to Implications for En Route Noise

Over 680 publications from 282 social surveys of residents' reactions to environmental noise have been examined to locate 495 published findings on 26 topics concerning non-noise explanations for residents' reactions to environmental noise. This report (1) tabulates the evidence on the 26 response topics, (2) identifies the 495 findings, and (3) discusses the implications for en route noise assessment. After controlling for noise level, over half of the social survey evidence indicates that noise annoyance is not strongly affected by any of the nine demographic variables examined (age, sex, social status, income, education, homeownership, type of dwelling, length of residence, or receipt of benefits from the noise source), but is positively associated with each of the five attitudinal variables examined (a fear of danger from the noise source, a sensitivity towards noise generally, the belief that the authorities can control the noise, the awareness of non-noise impacts of the source, and the belief that the noise source is not important).

Fields, James M.↗
NASA NTRS1989

The effects of window shape and reticle presence on performance in a vertical alignment task

This study was conducted to evaluate the effect of selected interior work-station orientational cuing upon the ability to align a target image with local vertical in the frontal plane. Angular error from gravitational vertical in an alignment task was measured for 20 observers viewing through two window shapes (square, round), two initial orientations of a computer-generated space shuttle image, and the presence or absence of a stabilized optical alignment reticle. In terms of overall accuracy, it was found that observer error was significantly smaller for the square window and reticle-present conditions than for the round window and reticle-absent conditions. Response bias data reflected an overall tendency to undershoot and greater variability of response in the round window/no reticle condition. These results suggest that environmental cuing information, such as that provided by square window frames and alignment reticles, may aid in subjective orientation and increase accuracy of response in a Space Station proximity operations alignment task.

Rosenberg, Erika L.↗
NASA NTRS2008

Effective Interpolation of Incomplete Satellite-Derived Leaf-Area Index Time Series for the Continental United States

Many earth science modeling applications employ continuous input data fields derived from satellite data. Environmental factors, sensor limitations and algorithmic constraints lead to data products of inherently variable quality. This necessitates interpolation of one form or another in order to produce high quality input fields free of missing data. The present research tests several interpolation techniques as applied to satellite-derived leaf area index, an important quantity in many global climate and ecological models. The study evaluates and applies a variety of interpolation techniques for the Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf-Area Index Product over the time period 2001-2006 for a region containing the conterminous United States. Results indicate that the accuracy of an individual interpolation technique depends upon the underlying land cover. Spatial interpolation provides better results in forested areas, while temporal interpolation performs more effectively over non-forest cover types. Combination of spatial and temporal approaches offers superior interpolative capabilities to any single method, and in fact, generation of continuous data fields requires a hybrid approach such as this.

Jasinski, Michael F.↗
NASA NTRS2016

Synthesis and Review: African Environmental Processes and Water-Cycle Dynamics

Africa's vast landmass harbors a variety of physical processes that affect the environment and the water cycle. This focus issue on the "African Environmental Processes and Water-Cycle Dynamics" contains eight articles that address these phenomena from different but complementary perspectives. Fires used for agricultural and related purposes play a major role in land-cover change, surface albedo modifications, and smoke emission; all of which affect the environment and the water cycle in different ways. However, emissions of aerosols and trace gases are not restricted to fires, but also emanate from other natural and human activities. The African water cycle undergoes significant perturbations that are attributable to several factors, including the aforesaid environmental processes. These changes in the water cycle have produced severe drought and flooding events in recent decades that affect societal wellbeing across sub-Saharan Africa. The combined effects of the environmental processes and water-cycle dynamics affect and are affected by climate variability and can be propagated beyond the continent. Future studies should utilize the wealth of observations and modeling tools that are constantly improving to clearly elucidate the interrelationships between all of these phenomena for the benefit of society.

Water cycle dynamics↗
NASA NTRS2020

Decadal Changes in the Interannual Variability of Heat Waves in East Asia Caused by Atmospheric Teleconnection Changes

The heat wave in East Asia is examined by using empirical orthogonal function analysis to isolate dominant heat-wave patterns in the ground-based temperature observations over the Korean Peninsula and China and related large-scale atmospheric circulations obtained from the National Centers for Environmental Prediction–National Center for Atmospheric Research Reanalysis 1 during 1973–2012. This study focuses particularly on the interannual variability of heat waves and its decadal change. The analysis identifies two major atmospheric teleconnection patterns playing an important role in developing typical heat-wave patterns in East Asia—the Scandinavian (SCAND) and the circumglobal teleconnection (CGT) patterns, which exhibit a significant decadal change in the interannual variability in the mid-1990s. Before the mid-1990s, heat-wave occurrence was closely related to the CGT pattern, whereas the SCAND pattern is more crucial to explain heat-wave variability in the recent period. The stationary wave model experiments suggest an intensification of the SCAND pattern in the recent period driven by an increase in land–atmosphere interaction over Eurasia and decadal change in the dominant heat-wave patterns in East Asia.

heat wave patterns↗
NASA NTRS1997

Technical Report Series on Global Modeling and Data Assimilation: Interannual Variability and Potential Predictability in Reanalysis Products - Volume 13

The Data Assimilation Office (DAO) at Goddard Space Flight Center and the National Center for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR) have produced multi-year global assimilations of historical data employing fixed analysis systems. These "reanalysis" products are ideally suited for studying short-term climatic variations. The availability of multiple reanalysis products also provides the opportunity to examine the uncertainty in the reanalysis data. The purpose of this document is to provide an updated estimate of seasonal and interannual variability based on the DAO and NCEP/NCAR reanalyses for the 15-year period 1980-1995. Intercomparisons of the seasonal means and their interannual variations are presented for a variety of prognostic and diagnostic fields. In addition, atmospheric potential predictability is re-examined employing selected DAO reanalysis variables.

Min, Wei↗
NASA NTRS1996

Precipitable Water Variability Using SSM/I and GOES VAS Pathfinder Data Sets

Determining moisture variability for all weather scenes is critical to understanding the earth's hydrologic cycle and global climate changes. Remote sensing from geostationary satellites provides the necessary temporal and spatial resolutions necessary for global change studies. Due to antenna size constraints imposed with the use of microwave radiometers, geostationary satellites have carried instruments passively measuring radiation at infrared wavelengths or shorter. The shortfall of using infrared instruments in moisture studies lies in its inability to sense terrestrial radiation through clouds. Microwave emissions, on the other hand, are mostly unaffected by cloudy atmospheres. Land surface emissivity at microwave frequencies exhibit both high temporal and spatial variability thus confining moisture retrievals at microwave frequencies to over marine atmospheres (a near uniform cold background). This study intercompares the total column integrated water content Precipitable Water, (PW) as derived from both the Special Sensor Microwave Imager (SSM/I) and the Geostationary Operational Environmental Satellite (GOES) VISSR Atmospheric Sounder (VAS) pathfinder data sets. PW is a bulk parameter often used to quantify moisture variability and is important to understanding the earth's hydrologic cycle and climate system. This research has been spawned in an effort to combine two different algorithms which together can lead to a more comprehensive quantification of global water vapor. The approach taken here is to intercompare two independent PW retrieval algorithms and to validate the resultant retrievals against an existing data set, namely the European Center for Medium range Weather Forecasts (ECMWF) model analysis data.

Lerner, Jeffrey A.↗
NASA NTRS1995

Aqueous cleaning design presentation

The phase-out of CFC's and other ozone depleting chemicals has prompted industries to re-evaluate their present methods of cleaning. It has become necessary to find effective substitutes for their processes as well as to meet the new cleaning challenges of improved levels of cleanliness and to satisfy concerns about environmental impact of any alternative selected. One of the most popular alternatives being selected is aqueous cleaning. This method offers an alternative for removal of flux, grease/oil, buffing compound, particulates and other soils while minimizing environmental impact. What I will show are methods that can be employed in an aqueous cleaning system that will make it environmentally friendly, relatively simple to maintain and capable of yielding an even higher quality of cleanliness than previously obtained. I will also explore several drying techniques available for these systems and other alternatives along with recent improvements made in this technology. When considering any type of cleaning system, a number of variables should be determined before selecting the basic configuration. Some of these variables are: (1) Soil or contaminants being removed from your parts; (2) The level of cleanliness required; (3) The environmental considerations of your area; (4) Maintenance requirements; and (5) Operating costs.

Maltby, Peter F.↗
NASA NTRS2002

Upper Tropospheric Ozone Between Latitudes 60S and 60N Derived from Nimbus 7 TOMS/THIR Cloud Slicing

This study evaluates the spatial distributions and seasonal cycles in upper tropospheric ozone (pressure range 200-500 hPa) from low to high latitudes (60S to 60N) derived from the satellite retrieval method called "Cloud Slicing." Cloud Slicing is a unique technique for determining ozone profile information in the troposphere by combining co-located measurements of cloud-top, pressure and above-cloud column ozone. For upper tropospheric ozone, co-located measurements of Nimbus 7 Total Ozone Mapping Spectrometer (TOMS) above-cloud column ozone, and Nimbus 7 Temperature Humidity Infrared Radiometer (THIR) cloud-top pressure during 1979-1984 were incorporated. In the tropics, upper tropospheric ozone shows year-round enhancement in the Atlantic region and evidence of a possible semiannual variability. Upper tropospheric ozone outside the tropics shows greatest abundance in winter and spring seasons in both hemispheres with largest seasonal and largest amounts in the NH. These characteristics are similar to lower stratospheric ozone. Comparisons of upper tropospheric column ozone with both stratospheric ozone and a proxy of lower stratospheric air mass (i.e., tropopause pressure) from National Centers for Environmental Prediction (NCEP) suggest that stratosphere-troposphere exchange (STE) may be a significant source for the seasonal variability of upper tropospheric ozone almost everywhere between 60S and 60N except in low latitudes around 10S to 25N where other sources (e.g., tropospheric transport, biomass burning, aerosol effects, lightning, etc.) may have a greater role.

Ziemke, Jerald R.↗
NASA NTRS2019

Global Disease Outbreaks Associated with the 2015-2016 El Niño Event

Interannual climate variability patterns associated with the El Niño-Southern Oscillation phenomenon result in climate and environmental anomaly conditions in specific regions worldwide that directly favor outbreaks and/or amplification of variety of diseases of public health concern including chikungunya, hantavirus, Rift Valley fever, cholera, plague, and Zika. We analyzed patterns of some disease outbreaks during the strong 2015–2016 El Niño event in relation to climate anomalies derived from satellite measurements. Disease outbreaks in multiple El Niño-connected regions worldwide (including Southeast Asia, Tanzania, western US, and Brazil) followed shifts in rainfall, temperature, and vegetation in which both drought and flooding occurred in excess (14–81% precipitation departures from normal). These shifts favored ecological conditions appropriate for pathogens and their vectors to emerge and propagate clusters of diseases activity in these regions. Our analysis indicates that intensity of disease activity in some ENSO-teleconnected regions were approximately 2.5–28% higher during years with El Niño events than those without. Plague in Colorado and New Mexico as well as cholera in Tanzania were significantly associated with above normal rainfall (p < 0.05); while dengue in Brazil and southeast Asia were significantly associated with above normal land surface temperature (p < 0.05). Routine and ongoing global satellite monitoring of key climate variable anomalies calibrated to specific regions could identify regions at risk for emergence and propagation of disease vectors. Such information can provide sufficient lead-time for outbreak prevention and potentially reduce the burden and spread of ecologically coupled diseases.

El Nino↗
NASA NTRS1975

Physiological system integrations with emphasis on the respiratory-cardiovascular system

The integration of two types of physiological system simulations is presented. The long term model is a circulatory system model which simulates long term blood flow variations and compartmental fluid shifts. The short term models simulate transient phenomena of the respiratory, thermoregulatory, and pulsatile cardiovascular systems as they respond to stimuli such as LBNP, exercise, and environmental gaseous variations. An overview of the interfacing approach is described. Descriptions of the variable interface for long term to short term and between the three short term models are given.

Gallagher, R. R.↗
NASA NTRS1981

Spectral-agronomic relationships of corn, soybean and wheat canopies

During the past six years several thousand reflectance spectra of corn, soybean, and wheat canopies were acquired and analyzed. The relationships of biophysical variables, including leaf area index, percent soil cover, chlorophyll and water content, to the visible and infrared reflectance of canopies are described. The effects on reflectance of cultural, environmental, and stress factors such as planting data, seeding rate, row spacing, cultivar, soil type and nitrogen fertilization are also examined. The conclusions are that several key agronomic variables including leaf area index, development stage and degree of stress are strongly related to spectral reflectance and that it should be possible to estimate these descriptions of crop condition from satellite acquired multispectral data.

Bauer, M. E.↗
NASA NTRS1998

Capacitively Stabilized Etalon Technology for Spaceborne Wind Lidar Application

Global monitoring by satellites is important for many types of environmental studies. Among these, the wind field is the single most important atmospheric state variable required for understanding atmospheric motion and predicting weather. Studies indicate that a global determination of the tropospheric wind field to an accuracy of 1-5 m/sec is critical for improved numerical weather forecasting. This measurement could be carried out with a spaceborne lidar system sensing the Doppler shift of a laser signal backscattered from the atmosphere. Over the past four years we have developed a ground-based Edge Technique lidar system and demonstrated wind measurements through the troposphere with high accuracy (1-6 m/s) and high spatial resolution. Recently, we began the design of a shuttle based wind measurement system for technology demonstration as part of the Zephyr program. In this paper, we present the characteristics of the high spectral resolution etalon filter technology for lidar wind measurement with the Edge Technique. In conclusion, a spacecraft motion compensation method has been discussed. We demonstrated experimentally that the etalon can be tuned to compensate for any satellite induced Doppler shift to an accuracy of better than 0.6 m/s over a time period of 2.5 ms.

Li, Steven X.↗
NASA NTRS2001

Uncertainty Optimization Applied to the Monte Carlo Analysis of Planetary Entry Trajectories

Recently, strong evidence of liquid water under the surface of Mars and a meteorite that might contain ancient microbes have renewed interest in Mars exploration. With this renewed interest, NASA plans to send spacecraft to Mars approx. every 26 months. These future spacecraft will return higher-resolution images, make precision landings, engage in longer-ranging surface maneuvers, and even return Martian soil and rock samples to Earth. Future robotic missions and any human missions to Mars will require precise entries to ensure safe landings near science objective and pre-employed assets. Potential sources of water and other interesting geographic features are often located near hazards, such as within craters or along canyon walls. In order for more accurate landings to be made, spacecraft entering the Martian atmosphere need to use lift to actively control the entry. This active guidance results in much smaller landing footprints. Planning for these missions will depend heavily on Monte Carlo analysis. Monte Carlo trajectory simulations have been used with a high degree of success in recent planetary exploration missions. These analyses ascertain the impact of off-nominal conditions during a flight and account for uncertainty. Uncertainties generally stem from limitations in manufacturing tolerances, measurement capabilities, analysis accuracies, and environmental unknowns. Thousands of off-nominal trajectories are simulated by randomly dispersing uncertainty variables and collecting statistics on forecast variables. The dependability of Monte Carlo forecasts, however, is limited by the accuracy and completeness of the assumed uncertainties. This is because Monte Carlo analysis is a forward driven problem; beginning with the input uncertainties and proceeding to the forecasts outputs. It lacks a mechanism to affect or alter the uncertainties based on the forecast results. If the results are unacceptable, the current practice is to use an iterative, trial-and-error approach to reconcile discrepancies. Therefore, an improvement to the Monte Carlo analysis is needed that will allow the problem to be worked in reverse. In this way, the largest allowable dispersions that achieve the required mission objectives can be determined quantitatively.

Olds, John↗
NASA NTRS2003

Mapping a Better Vintage

Vineyards such as those located in California's Napa Valley tend to be subdivided into relatively large fields or blocks that often encompass heterogeneous physical conditions. Since growers typically treat the entire block as a single minimum management unit for cultivation and harvest, mapping and monitoring the variability within a block is a concern. Over the last decade, an increasing number of vineyard managers have utilized digital remote sensing and geographic information systems (GIS) to visualize the variability within their blocks. With computer software designed to overlay remotely sensed imagery with environmental and agronomic geographic data on a map, GIS helps growers recognize and explain patterns that might not have been obvious otherwise. GIS can also serve as a valuable archiving mechanism for future reference. To further develop the use of image technology and GIS for vineyard management support, NASA's Earth Science Enterprise partnered with the U.S. wine and commercial remote sensing industries for a project known as the Viticultural Integration of NASA Technologies for Assessment of the Grapevine Environment (VINTAGE). With project investigators from NASA's Ames Research Center, the California State University at Monterey Bay, and the University of Montana, several prototype products have been developed to support agricultural decisions concerning canopy management and irrigation practice. One key VINTAGE aspect involved the evaluation of satellite and airborne multispectral imagery for delineation of sub-block management zones within a vineyard.

Source record↗