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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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We have conducted a variability study of several radio/millimeter sources which are possible counterparts of high energy gamma-ray sources detected by EGRET.
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In this paper we present an interpretation of coarse resolution passive microwave data for 1989 and 1992 in the context of a simple model of ice-edge retreat to obtain the Nordbukta emayment growth and the formation and migration of an Odden polynya.
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We report on application of a combination of data mining steps guided by user-directives, and appropriate visualizations to present the results of these steps to the users.
We present a detailed spectral analysis of the prompt and afterglow emission of four nearby long-soft gamma-ray bursts (GRBs 980425,030329,031203, and 060218) that were spectroscopically found to be associated with Type IC supernovae and compare them to the general GRB population. For each event, we investigate the spectral and luminosity evolution and estimate the total energy budget based on broadband observations. The observational inventory for these events has become rich enough to allow estimates of their energy content in relativistic and subrelativistic form. The result is a global portrait of the effects of the physical processes responsible for producing long-soft GRBs. In particular, we find that the values of the energy released in mildly relativistic out8ows appears to have a sigruficantly smaller scatter than those found in highly relativistic ejecta. This is consistent with a picture in which the energy released inside the progenitor star is roughly standard, while the fracti
We explore the nature of 'hills' observed on the solar surface which had previously been attributed to Rossby waves. We investigate the sol ar hills phenomenon by analyzing the output from a synthetic model ba sed solely on the observed solar photospheric convection spectrum. We show that the characteristics of these hills can be explained by the corrugation of the surface produced by the radial flows of the conve ction. The hills in our simulations are dominated by supergranules, a well-known component of solar convection. Rossby waves have been predicted to exist within the Sun and may play an important role in the d ynamics of the solar interior, including the Sun's differential rotat ion and magnetic dynamo. Our study suggests, however, that the hills observed at the solar limb do not confirm the existence of solar Ross by waves.
We present a detailed spectral analysis of the prompt and afterglow emission of four nearby long-soft gamma-ray bursts (GRBs 980425,030329,031203, and 060218) that were spectroscopically found to be associated with Type Ic supernovae and compare them to the general GRB population. For each event, we investigate the spectral and luminosity evolution and estimate the total energy budget based on broadband observations. The observational inventory for these events has become rich enough to allow estimates of their energy content in relativistic and subrelativistic form. The result is a global portrait of the effects of the physical processes responsible for producing long-soft GRBs. In particular, we find that the values of the energy released in mildly relativistic outflows appears to have a significantly smaller scatter than those found in highly relativistic ejecta. This is consistent with a picture in which the energy released inside the progenitor star is roughly standard, while the fraction of that energy that ends up in highly relativistic ejecta outside the star can vary dramatically between different events.
A taxonomy of navigation errors (pilot deviations) during taxi operations was developed that defines 3 classes of errors: planning, decision, and execution errors. This taxonomy was applied to error data from 2 full-mission simulation studies that included trials that replicated current-day operations and trials with advanced cockpit technologies including datalink, electronic moving maps (EMM), and head-up displays (HUDs). Pilots committed navigation errors on 17% of current-day operations trials (in low-visibility and night), distributed roughly equally across the 3 error classes. Each error class was associated with a unique set of contributing factor s and mitigating solutions. Planning errors were mitigated by technologies that provided an unambiguous record of the clearance (datalink and the EMM, which possessed a text-based clearance). Decision errors were mitigated by technologies that provided both local and global awareness including information about the distance to and direction of the next turn, current township location, and a graphical depiction of the route (as provided by the EMM and HUD together). Execution errors were best mitigated by the HUD, which disambiguated the environment and depicted the clear ed taxi route. Implications for technology design and integration are provided.
A non-invasive method for analyzing the blood-brain barrier includes obtaining a Raman spectrum of a selected portion of the eye and monitoring the Raman spectrum to ascertain a change to the dynamics of the blood brain barrier. Also, non-invasive methods for determining the brain or blood level of an analyte of interest, such as glucose, drugs, alcohol, poisons, and the like, comprises: generating an excitation laser beam (e.g., at a wavelength of 600 to 900 nanometers); focusing the excitation laser beam into the anterior chamber of an eye of the subject so that aqueous humor, vitreous humor, or one or more conjunctiva vessels in the eye is illuminated; detecting (preferably confocally detecting) a Raman spectrum from the illuminated portion of the eye; and then determining the blood level or brain level (intracranial or cerebral spinal fluid level) of an analyte of interest for the subject from the Raman spectrum. In certain embodiments, the detecting step may be followed by the step of subtracting a confounding fluorescence spectrum from the Raman spectrum to produce a difference spectrum; and determining the blood level and/or brain level of the analyte of interest for the subject from that difference spectrum, preferably using linear or nonlinear multivariate analysis such as partial least squares analysis. Apparatus for carrying out the foregoing methods are also disclosed.
Dust was collected over a period of several weeks in 2007 from various HEPA filters in the U.S. Laboratory Module of the International Space Station (ISS). The dust was returned on the Space Shuttle Atlantis, mixed, sieved, and the DNA was extracted. Using a DNA-based method called mold specific quantitative PCR (MSQPCR), 39 molds were measured in the dust. Opportunistic pathogens Aspergillus flavus and A. niger and toxin producers Penicillium chrysogenum and P. brevicompactum were found at relatively high concentrations (compared to U.S. homes). No cells of the opportunistic pathogens A. fumigatus, A. terreus, Fusarium solani or Candida albicans were detected.
An apparatus, computer program product and method of analyzing structures. Intrinsic Mode Functions (IMFs) are extracted from the data and the most energetic IMF is selected. A spline is fit to the envelope for the selected IMF. The spline derivative is determined. A stability spectrum is developed by separating the positive and negative results into two different spectra representing stable (positive) and unstable (negative) damping factors. The stability spectrum and the non-linearity indicator are applied to the data to isolate unstable vibrations.
An Extended Kalman Filter is developed to estimate the linearized direct and indirect stiffness and damping force coefficients for bearings in rotor-dynamic applications from noisy measurements of the shaft displacement in response to imbalance and impact excitation. The bearing properties are modeled as stochastic random variables using a Gauss-Markov model. Noise terms are introduced into the system model to account for all of the estimation error, including modeling errors and uncertainties and the propagation of measurement errors into the parameter estimates. The system model contains two user-defined parameters that can be tuned to improve the filter s performance; these parameters correspond to the covariance of the system and measurement noise variables. The filter is also strongly influenced by the initial values of the states and the error covariance matrix. The filter is demonstrated using numerically simulated data for a rotor-bearing system with two identical bearings, which reduces the number of unknown linear dynamic coefficients to eight. The filter estimates for the direct damping coefficients and all four stiffness coefficients correlated well with actual values, whereas the estimates for the cross-coupled damping coefficients were the least accurate.
There are many aspects, which are important for maintaining environmentally clean and safe conditions for a healthy and economically self-sufficient community. This problem was somewhat of a lesser concern in earlier days because many communities were small, isolated and solely dependent upon their owners or landlords. Due to an astronomical growth in human population within the last century, extensive use of combustion technologies, and changing environmental conditions has resulted in scarcity of natural resources. In reality, the societal sustainability issues are becoming much more acute and complex. Therefore, the researchers and social scientists are joining forces to address these topics and find solutions to many contentious areas such as public health and diseases, water resources, agriculture production, survivability during and after the natural disasters, energy needs and many others. Forthrightly speaking, there is no canned solution or a methodology to go about solving these issues since the magnitude and complexity of these issues are multi-dimensional and are further inter-locked with other areas. A common sense tells us that we need data, resources and technologies to begin addressing these problems. This is where space observations have provided us with tremendous information and opportunities, which are of great assets to the science, economist, and social scientists. This paper specifically addresses what are critical areas for a successful societal sustainability and growth; and how can we take advantage of multiple sensors and models already in existence. Increasing our knowledge of the home planet, via amplified set of observations, is certainly a right step in a right direction. Furthermore, this is a pre-requisite in understanding multiple hazard phenomena's. This paper further examines various space sensors and observing architectures that can be useful specifically in addressing some of these complex issues. The ultimate goal is to serve the society by providing such valuable information so the decision makers can take full advantage in making timely societal decisions.
An Extended Kalman Filter is developed to estimate the linearized direct and indirect stiffness and damping force coefficients for bearings in rotor-dynamic applications from noisy measurements of the shaft displacement in response to imbalance and impact excitation. The bearing properties are modeled as stochastic random variables using a Gauss-Markov model. Noise terms are introduced into the system model to account for all of the estimation error, including modeling errors and uncertainties and the propagation of measurement errors into the parameter estimates. The system model contains two user-defined parameters that can be tuned to improve the filter s performance; these parameters correspond to the covariance of the system and measurement noise variables. The filter is also strongly influenced by the initial values of the states and the error covariance matrix. The filter is demonstrated using numerically simulated data for a rotor-bearing system with two identical bearings, which reduces the number of unknown linear dynamic coefficients to eight. The filter estimates for the direct damping coefficients and all four stiffness coefficients correlated well with actual values, whereas the estimates for the cross-coupled damping coefficients were the least accurate.
A non-invasive method for analyzing the blood-brain barrier includes obtaining a Raman spectrum of a selected portion of the eye and monitoring the Raman spectrum to ascertain a change to the dynamics of the blood brain barrier.Also, non-invasive methods for determining the brain or blood level of an analyte of interest, such as glucose, drugs, alcohol, poisons, and the like, comprises: generating an excitation laser beam at a selected wavelength (e.g., at a wavelength of about 400 to 900 nanometers); focusing the excitation laser beam into the anterior chamber of an eye of the subject so that aqueous humor, vitreous humor, or one or more conjunctiva vessels in the eye is illuminated; detecting (preferably confocally detecting) a Raman spectrum from the illuminated portion of the eye; and then determining the blood level or brain level (intracranial or cerebral spinal fluid level) of an analyte of interest for the subject from the Raman spectrum. In certain embodiments, the detecting step may be followed by the step of subtracting a confounding fluorescence spectrum from the Raman spectrum to produce a difference spectrum; and determining the blood level and/or brain level of the analyte of interest for the subject from that difference spectrum, preferably using linear or nonlinear multivariate analysis such as partial least squares analysis. Apparatus for carrying out the foregoing methods are also disclosed.
Aerosol optical depth (AOD), derived from satellite measurements using Moderate Resolution Imaging Spectrometer (MODIS), offers indirect estimates of particle matter. Research shows a significant positive correlation between satellite-based measurements of AOD and ground-based measurements of particulate matter with aerodynamic diameter less than or equal to 2.5 micrometers (PM2.5). In addition, satellite observations have also shown great promise in improving estimates of PM2.5 air quality surface. Research shows that correlations between AOD and ground PM2.5 are affected by a combination of many factors such as inherent characteristics of satellite observations, terrain, cloud cover, height of the mixing layer, and weather conditions, and thus might vary widely in different regions, different seasons, and even different days in a same location. Analysis of correlating AOD with ground measured PM2.5 on a day-to-day basis suggests the temporal scale, a number of immediate latest days for a given run's day, for their correlations needs to be considered to improve air quality surface estimates, especially when satellite observations are used in a real-time pollution system. The second reason is that correlation coefficients between AOD and ground PM2.5 cannot be predetermined and needs to be calculated for each day's run for a real-time system because the coefficients can vary over space and time. Few studies have been conducted to explore the optimal way to apply AOD data to improve model accuracies of PM2.5 surface estimation in a real-time air quality system. This paper discusses the best temporal scale to calculate the correlation of AOD and ground particle matter data to improve the results of pollution models in real-time system.