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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Urban Landscape Characterization Using Remote Sensing Data For Input into Air Quality Modeling

The urban landscape is inherently complex and this complexity is not adequately captured in air quality models that are used to assess whether urban areas are in attainment of EPA air quality standards, particularly for ground level ozone. This inadequacy of air quality models to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well these models predict ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban growth projections as improved inputs to meteorological and air quality models focusing on the Atlanta, Georgia metropolitan area as a case study. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the Community Multiscale Air Quality (CMAQ) modeling schemes. Use of these data have been found to better characterize low density/suburban development as compared with USGS 1 km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission. This allows the State Environmental Protection agency to evaluate how these transportation plans will affect future air quality.

Quattrochi, Dale A.↗
NASA NTRS1988

Kinetics of low pressure CVD growth of SiO2 on InP and Si

The kinetics of low pressure CVD growth of SiO2 from SiH4 and O2 has been investigated for the case of an indirect (remote) plasma process. Homogeneous (gas phase) and heterogeneous operating ranges have been experimentally identified. The process was shown to be consistent within the heterogeneous surface-reaction dominated range of operation. A kinetic rate equation is given for growth at 14 W RF power input and 400 mtorr total pressure on both InP and Si substrates. The process exhibits an activation energy of 8.4 + or - 0.6 kcal/mol.

Iyer, R.↗
NASA NTRS1994

Effects of the Mount Pinatubo eruption on the radiative and chemical processes in the troposphere and stratosphere

The Lawrence Livermore National Laboratory two-dimensional zonally-averaged chemical-radiative-transport model of the global atmosphere was used to study the effects of the 15 June 1991 eruption of the Mt. Pinatubo volcano on stratospheric processes. SAGE 2 time-dependent aerosol surface area density and optical extinction data were used as input into the model. By 22 December 1991, a maximum equatorial change of -1.8 percent in column ozone was derived from heterogeneous chemical processes that convert NO(x) into HNO3 on sulfuric acid aerosols. Radiative feedbacks from increased aerosol optical thickness independently changes column ozone by approximately -3.5 percent for the same period. This occurs from increasing the net heating of the lower stratosphere, which indirectly increases chemical reaction rates via their temperature dependence and from changes in actinic fluxes, which directly modify photodissociation rates. Including both heterogeneous and radiative effects changes column ozone by -5.5 percent. The model-derived change overestimates the decrease in column ozone relative to the TOMS instrument on the Nimbus 7 satellite. Maximum local ozone decreases of 12 percent were derived in the equatorial region, at 25 km. Model-derived column NO2 peaked (-14 percent) at 30 deg S in October 1991. The timing of the NO2 peak is consistent with observation, but the model underestimates the magnitude of the decrease. Local concentrations of NO(x) (NO + NO2), ClO(x) (Cl + ClO), and HO(x) (OH + HO2), in the lower stratosphere between 30 deg S and 30 deg N, were calculated to have changed by -40 percent, +100 to +160 percent, and +120 to +140 percent respectively.

Kinnison, Douglas E.↗
NASA NTRS2011

Space-Time Data Fusion

Space-time Data Fusion (STDF) is a methodology for combing heterogeneous remote sensing data to optimally estimate the true values of a geophysical field of interest, and obtain uncertainties for those estimates. The input data sets may have different observing characteristics including different footprints, spatial resolutions and fields of view, orbit cycles, biases, and noise characteristics. Despite these differences all observed data can be linked to the underlying field, and therefore the each other, by a statistical model. Differences in footprints and other geometric characteristics are accounted for by parameterizing pixel-level remote sensing observations as spatial integrals of true field values lying within pixel boundaries, plus measurement error. Both spatial and temporal correlations in the true field and in the observations are estimated and incorporated through the use of a space-time random effects (STRE) model. Once the models parameters are estimated, we use it to derive expressions for optimal (minimum mean squared error and unbiased) estimates of the true field at any arbitrary location of interest, computed from the observations. Standard errors of these estimates are also produced, allowing confidence intervals to be constructed. The procedure is carried out on a fine spatial grid to approximate a continuous field. We demonstrate STDF by applying it to the problem of estimating CO2 concentration in the lower-atmosphere using data from the Atmospheric Infrared Sounder (AIRS) and the Japanese Greenhouse Gasses Observing Satellite (GOSAT) over one year for the continental US.

Greenhouse Gases Observing Satellite (GOSAT)↗
NASA NTRS1996

Optimization of Residual Stresses in MMC's through Process Parameter Control and the use of Heterogeneous Compensating/Compliant Interfacial Layers. OPTCOMP2 User's Guide

A user's guide for the computer program OPTCOMP2 is presented in this report. This program provides a capability to optimize the fabrication or service-induced residual stresses in unidirectional metal matrix composites subjected to combined thermomechanical axisymmetric loading by altering the processing history, as well as through the microstructural design of interfacial fiber coatings. The user specifies the initial architecture of the composite and the load history, with the constituent materials being elastic, plastic, viscoplastic, or as defined by the 'user-defined' constitutive model, in addition to the objective function and constraints, through a user-friendly data input interface. The optimization procedure is based on an efficient solution methodology for the inelastic response of a fiber/interface layer(s)/matrix concentric cylinder model where the interface layers can be either homogeneous or heterogeneous. The response of heterogeneous layers is modeled using Aboudi's three-dimensional method of cells micromechanics model. The commercial optimization package DOT is used for the nonlinear optimization problem. The solution methodology for the arbitrarily layered cylinder is based on the local-global stiffness matrix formulation and Mendelson's iterative technique of successive elastic solutions developed for elastoplastic boundary-value problems. The optimization algorithm employed in DOT is based on the method of feasible directions.

Pindera, Marek-Jerzy↗
NASA NTRS2004

Automated Classification of ROSAT Sources Using Heterogeneous Multiwavelength Source Catalogs

We describe an on-line system for automated classification of X-ray sources, ClassX, and present preliminary results of classification of the three major catalogs of ROSAT sources, RASS BSC, RASS FSC, and WGACAT, into six class categories: stars, white dwarfs, X-ray binaries, galaxies, AGNs, and clusters of galaxies. ClassX is based on a machine learning technology. It represents a system of classifiers, each classifier consisting of a considerable number of oblique decision trees. These trees are built as the classifier is 'trained' to recognize various classes of objects using a training sample of sources of known object types. Each source is characterized by a preselected set of parameters, or attributes; the same set is then used as the classifier conducts classification of sources of unknown identity. The ClassX pipeline features an automatic search for X-ray source counterparts among heterogeneous data sets in on-line data archives using Virtual Observatory protocols; it retrieves from those archives all the attributes required by the selected classifier and inputs them to the classifier. The user input to ClassX is typically a file with target coordinates, optionally complemented with target IDs. The output contains the class name, attributes, and class probabilities for all classified targets. We discuss ways to characterize and assess the classifier quality and performance and present the respective validation procedures. Based on both internal and external validation, we conclude that the ClassX classifiers yield reasonable and reliable classifications for ROSAT sources and have the potential to broaden class representation significantly for rare object types.

McGlynn, Thomas↗
NASA NTRS2007

Observations on Cost Modeling and Performance Measurement of Long Term Archives

This paper describes a prototype suite of Excel-based tools that could be used for estimating lifecycle costs for newly planned or modified long-term archival facilities. These tools may also prove valuable for monitoring the long-term performance of such facilities once operational. Cost estimation is by analogy, using statistical curve-fitting techniques across a database of comparable data activities. The database currently includes 29 operational data centers ranging from small (2 FTEs) to large (66 FTEs), and is readily expandable to include additional activities specifically involving data preservation and added value. Each comparable data center is described in terms of its staffing, throughput workload, archival and distribution requirements, levels of user service, overall complexity, degree of automation, and other data, comprising 94 distinct descriptors in all. The descriptors were developed by normalizing heterogeneous data from the various centers and mapping them into an Excel framework consistent with the OAIS reference model. A user-friendly tool is provided for generating input to and updating the comparables database. This tool can also be used to benchmark the performance (in terms of cost versus throughput) of an operational data center, and to update the staffing, cost and workload data on a periodic basis. The comparables database could thus provide a history of staffing and throughput over time, as a means of performance monitoring and providing feedback for continuous improvement. Ancillary tools are also provided for performing "what-if' cost exercises for planning purposes, and for graphical display of data and results. We provide a high-level description of the tools; present our experiences and observations on gathering the information and maintaining the database; and discuss how this tool set might be applied to long term archives.

Fontaine, Kathy↗
NASA NTRS2016

Understanding Cirrus Ice Crystal Number Variability for Different Heterogeneous Ice Nucleation Spectra

Along with minimizing parameter uncertainty, understanding the cause of temporal and spatial variability of the nucleated ice crystal number, Ni, is key to improving the representation of cirrus clouds in climate models. To this end, sensitivities of Ni to input variables like aerosol number and diameter provide valuable information about nucleation regime and efficiency for a given model formulation. Here we use the adjoint model of the adjoint of a cirrus formation parameterization (Barahona and Nenes, 2009b) to understand Ni variability for various ice-nucleating particle (INP) spectra. Inputs are generated with the Community Atmosphere Model version 5, and simulations are done with a theoretically derived spectrum, an empirical lab-based spectrum and two field-based empirical spectra that differ in the nucleation threshold for black carbon particles and in the active site density for dust. The magnitude and sign of Ni sensitivity to insoluble aerosol number can be directly linked to nucleation regime and efficiency of various INP. The lab-based spectrum calculates much higher INP efficiencies than field-based ones, which reveals a disparity in aerosol surface properties. Ni sensitivity to temperature tends to be low, due to the compensating effects of temperature on INP spectrum parameters; this low temperature sensitivity regime has been experimentally reported before but never deconstructed as done here.

Cirrus↗
NASA NTRS1994

A Monte Carlo study of photochemical model uncertainties affecting the calculation of subsonic perturbations in the upper troposphere

Monte Carlo methods are frequently applied to the evaluation of uncertainties in models with multiple inputs that themselves have associated imprecisions. In the case of photochemical models used to evaluate changes in O3 or OH, inputs analyzed include rate coefficients measured in the laboratory, and chemical and physical constituents measured in the atmosphere. The Monte Carlo method was used with the 1-dimensional GSFC tropospheric photochemical model to examine uncertainty propagation to calculation of NO(x) and the major oxidants (O3, OH) in the upper troposphere. In all cases chemical kinetics inputs are varied and the NO(x) perturbation of a subsonic fleet is simulated. A series of model runs is used to explore sensitivities of model-computed parameters to other parameters: heterogeneous processes, the uncertainty in upper tropospheric H2O vapor measurements, aircraft emissions at different latitudes.

Thompson, Anne M.↗
NASA NTRS1993

Heterogeneity and scaling land-atmospheric water and energy fluxes in climate systems

The effects of small-scale heterogeneity in land surface characteristics on the large-scale fluxes of water and energy in land-atmosphere system has become a central focus of many of the climatology research experiments. The acquisition of high resolution land surface data through remote sensing and intensive land-climatology field experiments (like HAPEX and FIFE) has provided data to investigate the interactions between microscale land-atmosphere interactions and macroscale models. One essential research question is how to account for the small scale heterogeneities and whether 'effective' parameters can be used in the macroscale models. To address this question of scaling, three modeling experiments were performed and are reviewed in the paper. The first is concerned with the aggregation of parameters and inputs for a terrestrial water and energy balance model. The second experiment analyzed the scaling behavior of hydrologic responses during rain events and between rain events. The third experiment compared the hydrologic responses from distributed models with a lumped model that uses spatially constant inputs and parameters. The results show that the patterns of small scale variations can be represented statistically if the scale is larger than a representative elementary area scale, which appears to be about 2 - 3 times the correlation length of the process. For natural catchments this appears to be about 1 - 2 sq km. The results concerning distributed versus lumped representations are more complicated. For conditions when the processes are nonlinear, then lumping results in biases; otherwise a one-dimensional model based on 'equivalent' parameters provides quite good results. Further research is needed to fully understand these conditions.

Wood, Eric F.↗
NASA NTRS2007

Advanced Transport Delay Compensation Algorithms: Results of Delay Measurement and Piloted Performance Tests

This report summarizes the results of delay measurement and piloted performance tests that were conducted to assess the effectiveness of the adaptive compensator and the state space compensator for alleviating the phase distortion of transport delay in the visual system in the VMS at the NASA Langley Research Center. Piloted simulation tests were conducted to assess the effectiveness of two novel compensators in comparison to the McFarland predictor and the baseline system with no compensation. Thirteen pilots with heterogeneous flight experience executed straight-in and offset approaches, at various delay configurations, on a flight simulator where different predictors were applied to compensate for transport delay. The glideslope and touchdown errors, power spectral density of the pilot control inputs, NASA Task Load Index, and Cooper-Harper rating of the handling qualities were employed for the analyses. The overall analyses show that the adaptive predictor results in slightly poorer compensation for short added delay (up to 48 ms) and better compensation for long added delay (up to 192 ms) than the McFarland compensator. The analyses also show that the state space predictor is fairly superior for short delay and significantly superior for long delay than the McFarland compensator.

Guo, Liwen↗
NASA NTRS2017

Using Information from Rendezvous Missions for Best-Case Appraisals of Impact Damage to Planet Earth Caused by Natural Objects

The Asteroid Threat Assessment Project (ATAP), a part of NASAs Planetary Defense Coordination Office (PDCO) has the responsibility to appraise the range of surface damage by potential asteroid impacts on land or water. If a threat is realized, the project will provide appraisals to officials empowered to make decisions about potential mitigation actions. This paper describes a scenario for assessment of surface damage when characterization of an asteroid had been accomplished by a rendezvous mission that would be conducted by the international planetary defense community. It is shown that the combination of data from ground and in-situ measurements on an asteroid provides knowledge that can be used to pin-point its impact location and predict the level of devastation it would cause. The hypothetical asteroid 2017 PDC with a size range of 160 to 290 m in diameter to be discussed at the PDC 2017 is used as an example. In order of importance for appraising potential damage, information required is: (1) where will the surface impact occur? (2) what is the mass, shape and size of the asteroid and what is its entry state (speed and entry angle) at the 100 km atmospheric pierce point? And (3) is the asteroid a monolith or a rubble pile? If it is a rubble pile, what is its structure and heterogeneity from the surface and throughout its interior? Item (1) is of first order importance to determine levels of devastation (loss of life and infrastructure damage) because it varies strongly on the impact location. Items (2) and (3) are used as inputs for ATAPs simulations to define the level of surface hazards: winds, overpressure, thermal exposure; all created by the deposition of energy during the objects atmospheric flight, andor cratering. Topics presented in this paper include: (i) the devastation predicted by 2017 PDCs impact on land based on initial observations using ATAPs risk assessment capability, (ii) how information corresponding to items (1) to (3) could be obtained from a rendezvous mission, and (iii) how information from a rendezvous mission could be used, along with that from ground observations and data from the literature to provide input for a new risk analysis capability that is emerging from ATAPs research. It is concluded that this approach would result in the creation of an appraisal of the threat from 2017 PDC with the least uncertainty possible, herein called the best-case.

Asteroid Impact Appraisals↗
NASA NTRS1996

Optimization of residual stresses in MMC's through the variation of interfacial layer architectures and processing parameters

The objective of this work was the development of efficient, user-friendly computer codes for optimizing fabrication-induced residual stresses in metal matrix composites through the use of homogeneous and heterogeneous interfacial layer architectures and processing parameter variation. To satisfy this objective, three major computer codes have been developed and delivered to the NASA-Lewis Research Center, namely MCCM, OPTCOMP, and OPTCOMP2. MCCM is a general research-oriented code for investigating the effects of microstructural details, such as layered morphology of SCS-6 SiC fibers and multiple homogeneous interfacial layers, on the inelastic response of unidirectional metal matrix composites under axisymmetric thermomechanical loading. OPTCOMP and OPTCOMP2 combine the major analysis module resident in MCCM with a commercially-available optimization algorithm and are driven by user-friendly interfaces which facilitate input data construction and program execution. OPTCOMP enables the user to identify those dimensions, geometric arrangements and thermoelastoplastic properties of homogeneous interfacial layers that minimize thermal residual stresses for the specified set of constraints. OPTCOMP2 provides additional flexibility in the residual stress optimization through variation of the processing parameters (time, temperature, external pressure and axial load) as well as the microstructure of the interfacial region which is treated as a heterogeneous two-phase composite. Overviews of the capabilities of these codes are provided together with a summary of results that addresses the effects of various microstructural details of the fiber, interfacial layers and matrix region on the optimization of fabrication-induced residual stresses in metal matrix composites.

Pindera, Marek-Jerzy↗
NASA NTRS2010

Multiple Kernel Learning for Heterogeneous Anomaly Detection: Algorithm and Aviation Safety Case Study

The world-wide aviation system is one of the most complex dynamical systems ever developed and is generating data at an extremely rapid rate. Most modern commercial aircraft record several hundred flight parameters including information from the guidance, navigation, and control systems, the avionics and propulsion systems, and the pilot inputs into the aircraft. These parameters may be continuous measurements or binary or categorical measurements recorded in one second intervals for the duration of the flight. Currently, most approaches to aviation safety are reactive, meaning that they are designed to react to an aviation safety incident or accident. In this paper, we discuss a novel approach based on the theory of multiple kernel learning to detect potential safety anomalies in very large data bases of discrete and continuous data from world-wide operations of commercial fleets. We pose a general anomaly detection problem which includes both discrete and continuous data streams, where we assume that the discrete streams have a causal influence on the continuous streams. We also assume that atypical sequence of events in the discrete streams can lead to off-nominal system performance. We discuss the application domain, novel algorithms, and also discuss results on real-world data sets. Our algorithm uncovers operationally significant events in high dimensional data streams in the aviation industry which are not detectable using state of the art methods

Das, Santanu↗
NASA NTRS1994

The distribution of hydrogen, nitrogen, and chlorine radicals in the lower stratosphere: Implications for changes in O3 due to emission of NO(y) from supersonic aircraft

In situ measurements of hydrogen, nitrogen, and chlorine radicals obtained in the lower statosphere during SPADE are compared to results from a photochemical model that assimilates measurements of radical precursors and environmental conditions. Models allowing for heterogeneous hydrolysis of N2O5 agree well with measured concentrations of NO and ClO, but concentrations of HO2 and OH are underestimated by 10 to 25%, concentrations of NO2 are overestimated by 10 to 30%, and concentrations of HCl are overestimated by a factor of 2. Discrepancies for (OH) and (HO2) are reduced if we allow for higher yields of O((1)D) from O2 photolysis and for heterogeneous production of HNO2. The data suggest more efficent catalytic removal of O3 by hydrogen and halogen radicals relative to nitrogen oxide radicals than predicted by models using recommendend rates and cross sections. Increased in (O3) in the lower stratosphere may be larger in response to inputs of NO(y) from supersonic aircraft than estimated by current assessment models.

Salawitch, R. J.↗
NASA NTRS1994

The Distribution of Hydrogen, Nitrogen, and Chlorine Radicals in the Lower Stratosphere: Implications for Changes in O3 due to Emission of NO(y) from Supersonic Aircraft

In situ measurements of hydrogen, nitrogen, and chlorine radicals obtained in the lower stratosphere during the Stratospheric Photochemistry, Aerosols and Dynamics Expedition (SPADE) are compared to results from a photochemical model that assimilates measurements of radical precursors and environmental conditions. Models allowing for heterogeneous hydrolysis of N2O5 agree well with measured concentrations of NO and ClO, but concentrations of HO2 and OH are underestimated by 10 to 25%, concentrations of NO2 are overestimated by 10 to 30%, and concentrations of HCl are overestimated by a factor of 2. Discrepancies for [OH] and [HO2] are reduced if we allow for higher yields of O(sup 1)D) from 03 photolysis and for heterogeneous production of HNO2. The data suggest more efficient catalytic removal of O3 by hydrogen and halogen radicals relative to nitrogen oxide radicals than predicted by models using recommended rates and cross sections. Increases in [O3] in the lower stratosphere may be larger in response to inputs of NO(sub y) from supersonic aircraft than estimated by current assessment models.

Salawitch, R. J.↗
NASA NTRS2000

BOREAS RSS-8 BIOME-BGC SSA Simulation of Annual Water and Carbon Fluxes

The BOREAS RSS-8 team performed research to evaluate the effect of seasonal weather and landcover heterogeneity on boreal forest regional water and carbon fluxes using a process-level ecosystem model, BIOME-BGC, coupled with remote sensing-derived parameter maps of key state variables. This data set contains derived maps of landcover type and crown and stem biomass as model inputs to determine annual evapotranspiration, gross primary production, autotrophic respiration, and net primary productivity within the BOREAS SSA-MSA, at a 30-m spatial resolution. Model runs were conducted over a 3-year period from 1994-1996; images are provided for each of those years. The data are stored in binary image format. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗
NASA NTRS2005

Remote Sensing Characterization of the Urban Landscape for Improvement of Air Quality Modeling

The urban landscape is inherently complex and this complexity is not adequately captured in air quality models, particularly the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban growth projections as improved inputs to the meteorology component of the CMAQ model focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, in moderating ground-level ozone and air temperature, compared to "business as usual" simulations in which heat island mitigation strategies are not applied. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the (CMAQ) modeling schemes. Use of these data has been found to better characterize low densityhburban development as compared with USGS 1 km land use/land cover data that have traditionally been used in modeling. Air quality prediction for fiture scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the state Environmental Protection agency to evaluate how these transportation plans will affect fbture air quality.

Quattrochi, Dale A.↗