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At least 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Creep fatigue life prediction for engine hot section materials (isotropic)

The first two years of a two-phase program aimed at improving the high temperature crack initiation life prediction technology for gas turbine hot section components are discussed. In Phase 1 (baseline) effort, low cycle fatigue (LCF) models, using a data base generated for a cast nickel base gas turbine hot section alloy (B1900+Hf), were evaluated for their ability to predict the crack initiation life for relevant creep-fatigue loading conditions and to define data required for determination of model constants. The variables included strain range and rate, mean strain, strain hold times and temperature. None of the models predicted all of the life trends within reasonable data requirements. A Cycle Damage Accumulation (CDA) was therefore developed which follows an exhaustion of material ductility approach. Material ductility is estimated based on observed similarities of deformation structure between fatigue, tensile and creep tests. The cycle damage function is based on total strain range, maximum stress and stress amplitude and includes both time independent and time dependent components. The CDA model accurately predicts all of the trends in creep-fatigue life with loading conditions. In addition, all of the CDA model constants are determinable from rapid cycle, fully reversed fatigue tests and monotonic tensile and/or creep data.

Moreno, Vito↗
NASA NTRS2005

Data Assimilation Technology Transfer from Planetary Exploration to Terrestrial Applications

Data assimilation can be a valuable tool for discovery and exploration. Planetary missions--principally polar orbiting spacecraft--are now capable of returning enough information to constrain global dynamical models. However, such missions operate under a number of severe constraints: there is no ground truth to calibrate and validate either the models or the data: and there are limited computational resources available, particularly onboard the spacecraft, for the near real-time processing that is required for aerobraking and other semi-autonomous maneuvers. A modified data assimilation approach, in which the prime analysis variable is the observed quantity (i.e., infrared radiances), has been found to be effective in deriving global meteorology from Mars Global Surveyor Thermal Emission Spectrometer data. It may also be useful in a number of terrestrial applications (e.g. aerosol assimilation).

Houben, Howard↗
NASA NTRS2015

Finding Atmospheric Composition (AC) Metadata

The Atmospheric Composition Portal (ACP) is an aggregator and curator of information related to remotely sensed atmospheric composition data and analysis. It uses existing tools and technologies and, where needed, enhances those capabilities to provide interoperable access, tools, and contextual guidance for scientists and value-adding organizations using remotely sensed atmospheric composition data. The initial focus is on Essential Climate Variables identified by the Global Climate Observing System CH4, CO, CO2, NO2, O3, SO2 and aerosols. This poster addresses our efforts in building the ACP Data Table, an interface to help discover and understand remotely sensed data that are related to atmospheric composition science and applications. We harvested GCMD, CWIC, GEOSS metadata catalogs using machine to machine technologies - OpenSearch, Web Services. We also manually investigated the plethora of CEOS data providers portals and other catalogs where that data might be aggregated. This poster is our experience of the excellence, variety, and challenges we encountered.Conclusions:1.The significant benefits that the major catalogs provide are their machine to machine tools like OpenSearch and Web Services rather than any GUI usability improvements due to the large amount of data in their catalog.2.There is a trend at the large catalogs towards simulating small data provider portals through advanced services. 3.Populating metadata catalogs using ISO19115 is too complex for users to do in a consistent way, difficult to parse visually or with XML libraries, and too complex for Java XML binders like CASTOR.4.The ability to search for Ids first and then for data (GCMD and ECHO) is better for machine to machine operations rather than the timeouts experienced when returning the entire metadata entry at once. 5.Metadata harvest and export activities between the major catalogs has led to a significant amount of duplication. (This is currently being addressed) 6.Most (if not all) Earth science atmospheric composition data providers store a reference to their data at GCMD.

metadata search↗
NASA NTRSDate not supplied

CFD Validation Study of a Hypersonic Cone-Slice-Flap Variable Geometry Configuration

Model validation is the process of determining the degree of accuracy between physical reality and the model. The result of model validation can either be used to improve the model through calibration or quantify the model-form uncertainty. This work focuses on providing the model-form uncertainty through an area metric for a hypersonic cone-slice-flap variable geometry configuration given uncertainty in both the simulation and experimental data. The research here compares two different turbulence models for the simulations. For a variable geometry, performing uncertainty quantification to capture the model-form uncertainty on every configuration is computationally challenging. This work lays out a procedure that can give an accurate representation of the model-form uncertainty using a small number of high-fidelity runs and many low-fidelity runs on multiple configurations. Running this comparison provides a quantifiable measurement for the accuracy of each turbulence model for this type of design. The high-fidelity CFD solver used was VULCAN-CFD and the low-fidelity results came from Cart3D. The experimental data came from the 20-Inch Mach 6 Tunnel located at NASA Langley Research Center. The present work showed that the using both the Spalart and Allamaras and Menter Shear-Stress Transport turbulence models overpredicted the drag and lift coefficient, while underpredicting the pitching moment coefficient. The model-form uncertainty estimate resulted in up to a 13.6% change in the total uncertainty for the drag coefficient, up to a 57.4% change in total uncertainty for the lift coefficient, and up to a 100% change in total uncertainty for the pitching moment coefficient.

Laura M. White↗
NASA NTRS2005

The contribution of CEOP data to the understanding and modeling of monsoon systems

CEOP has contributed and will continue to provide integrated data sets from diverse platforms for better understanding of the water and energy cycles, and for validating models. In this talk, I will show examples of how CEOP has contributed to the formulation of a strategy for the study of the monsoon as a system. The CEOP data concept has led to the development of the CEOP Inter-Monsoon Studies (CIMS), which focuses on the identification of model bias, and improvement of model physics such as the diurnal and annual cycles. A multi-model validation project focusing on diurnal variability of the East Asian monsoon, and using CEOP reference site data, as well as CEOP integrated satellite data is now ongoing. Similar validation projects in other monsoon regions are being started. Preliminary studies show that climate models have difficulties in simulating the diurnal signals of total rainfall, rainfall intensity and frequency of occurrence, which have different peak hours, depending on locations. Further more model diurnal cycle of rainfall in monsoon regions tend to lead the observed by about 2-3 hours. These model bias offer insight into lack of, or poor representation of key components of the convective,and stratiform rainfall. The CEOP data also stimulated studies to compare and contrasts monsoon variability in different parts of the world. It was found that seasonal wind reversal, orographic effects, monsoon depressions, meso-scale convective complexes, SST and land surface land influences are common features in all monsoon regions. Strong intraseasonal variability is present in all monsoon regions. While there is a clear demarcation of onset, breaks and withdrawal in the Asian and Australian monsoon region associated with climatological intraseasonal variability, it is less clear in the American and Africa monsoon regions. The examination of satellite and reference site data in monsoon has led to preliminary model experiments to study the impact of aerosol on monsoon variability. I will show examples of how the study of the dynamics of aerosol-water cycle interactions in the monsoon region, can be best achieved using the CEOP data and modeling strategy.

Lau, William K. M.↗
NASA NTRS1997

Biogeochemistry of DMS in Surface Waters

Dimethylsulfide (DMS) is important in influencing the formation of aerosols in the troposphere over large areas of the world's oceans. Understanding the dynamics of aerosols is important to understanding the earth's radiation balance. In evaluating the factors controlling DMS in the troposphere it is vital to understand the dynamics of DMS in the surface ocean. The biogeochemical processes controlling DMS concentration in seawater are myriad; modeling and theoretical estimation are problematic. At the beginning of this project we believed that we were on the verge of simplifying the ship-track measurement of DMS, and we proposed to deploy such a system to develop a database relating high frequency DMS measurements to biological and physicochemical and optical properties of surface water that can be quantified by remote sensing techniques. We designed a system to measure DMS concomitantly with other basic chemical and biological data in a flow-through system. The project was collaborative between Woods Hole Oceanographic Institution (WHOI) and Bermuda Biological Station for Research (BBSR). The project on which we are reporting was budgeted for only one year with a one year no-cost extension. At WHOI our effort was directed towards designing traps which would be used to concentrate DMS from seawater and allow storage for subsequent analysis. At that time, GC systems were too large for easy long-term deployment on a research vessel like R/V Weatherbird, so we focused on simplifying the shipboard sampling procedure. Initial studies of sample recovery with high levels of DMS suggested that Carboxen 1000, a relatively new carbon molecular sieve, could be used as a stable storage medium. The affinity of Carboxen for DMS is several orders of magnitude higher than gold wool (another adsorbent used for DMS collection) on a weight or volume basis. Furthermore, Carboxen's affinity for DMS is also far less susceptible to humidity than gold wool. Unfortunately, further experiments with low level DMS indicated that recovery of DMS after storage was not quantitative. The material has proven to be completely acceptable for short term storage and has been incorporated into a micro-GC system. Since working on this project, we have collaborated with RVM Scientific in Santa Barbara in the design and construction of small portable micro-GC's that will make feasible at-sea measurement in moving ships, making rapid gas analysis and quantification feasible in a ship-track mode. Throughout this period at both WHOI and BBSR, we continued to analyze field data to understand that patterns of time and space variability in DMS and the processes that govern it. These insights will be crucial to determining the specifications for our automated sampling program. The data from this, the longest continuous sampling program for ocean DMS, provided insights into year to year and short-term variability.

Dacey, J. W. H.↗
NASA NTRS1998

Bi-Level Integrated System Synthesis (BLISS)

BLISS is a method for optimization of engineering systems by decomposition. It separates the system level optimization, having a relatively small number of design variables, from the potentially numerous subsystem optimizations that may each have a large number of local design variables. The subsystem optimizations are autonomous and may be conducted concurrently. Subsystem and system optimizations alternate, linked by sensitivity data, producing a design improvement in each iteration. Starting from a best guess initial design, the method improves that design in iterative cycles, each cycle comprised of two steps. In step one, the system level variables are frozen and the improvement is achieved by separate, concurrent, and autonomous optimizations in the local variable subdomains. In step two, further improvement is sought in the space of the system level variables. Optimum sensitivity data link the second step to the first. The method prototype was implemented using MATLAB and iSIGHT programming software and tested on a simplified, conceptual level supersonic business jet design, and a detailed design of an electronic device. Satisfactory convergence and favorable agreement with the benchmark results were observed. Modularity of the method is intended to fit the human organization and map well on the computing technology of concurrent processing.

Sobieszczanski-Sobieski, Jaroslaw↗
NASA NTRS1998

Bi-Level Integrated System Synthesis (BLISS)

BLISS is a method for optimization of engineering systems by decomposition. It separates the system level optimization, having a relatively small number of design variables, from the potentially numerous sub-system optimizations that may each have a large number of local design variables. The subsystem optimizations are autonomous and may be conducted concurrently. Subsystem and system optimizations alternate, linked by sensitivity data, producing a design improvement in each iteration. Starting from a best guess initial design, the method improves that design in iterative cycles, each cycle comprised of two steps. In step one, the system level variables are frozen and the improvement is achieved by separate, concurrent, and autonomous optimizations in the local variable subdomains. In step two, further improvement is sought in the space of the system level variables. Optimum sensitivity data link the second step to the first. The method prototype was implemented using MATLAB and iSIGHT programming software and tested on a simplified, conceptual level supersonic business jet design, and a detailed design of an electronic device.

Sobieszczanski-Sobieski, Jaroslaw↗
NASA NTRS2021

Probabilistic Machine Learning Estimation of Ocean Mixed Layer Depth from Dense Satellite and Sparse In-Situ Observations

The ocean mixed layer plays an important role in the coupling between the upper ocean and atmosphere across a wide range of time scales. Estimation of the variability of the ocean mixed layer is therefore important for atmosphere-ocean prediction and analysis. The increasing coverage of in situ Argo profile data allows for an increasingly accurate analysis of the mixed layer depth (MLD) variability associated with deviations from the seasonal climatology. However, sampling rates are not sufficient to fully resolve subseasonal (<90 day) MLD variability. Yet, many multivariate observations-based analyses include implicit modeled subseasonal MLD variability. One analysis method is optimal interpolation of in situ data, but the interior analysis can be improved by leveraging surface data with regression or variational approaches. Here, we demonstrate how machine learning methods and satellite sea surface temperature, salinity, and height facilitate MLD estimation in a pilot study of two regions: the mid-latitude southern Indian and the eastern equatorial Pacific Oceans. We construct multiple machine learning architectures to produce weekly 1/2° gridded MLD anomaly fields (relative to a monthly climatology) with uncertainty estimates. We test multiple traditional and probabilistic machine learning techniques to compare both accuracy and probabilistic calibration. We validate our methodology by applying it to ocean model simulations. We find that incorporating sea surface data through a machine learning model improves the performance of spatiotemporal MLD variability estimation compared to optimal interpolation of Argo observations alone. These preliminary results are a promising first step for the application of machine learning to MLD prediction.

Machine Learning↗
NASA NTRS1976

Determination of particle size using measurement of scatter

Scatter from glass beads placed on a mirror was measured using a quartz lamp and laser. Data were obtained in the plane containing the normal to the surface and the incident beam. For the quartz lamp the best correlation can be obtained for data measured at a zenith of 55 deg and 180 deg from the incident beam. The best correlation when the laser is used is obtained at about the same position. However, the correlation variables are angular spacing of the minimums of the data versus the size. Whereas, with the quartz lamp the correlation variables are the amount of scattered energy versus size.

Scott, R. L., Jr.↗
NASA NTRSDate not supplied

Deep Neural Network Based Unsteady Flamelet Progress Variable Approach in a Supersonic Combustor

Higher dimensional flamelet manifolds are essential in capturing the coupled effects of pressure gradients and unsteady chemical kinetics observed in supersonic combustion applications. Previous studies have validated the feasibility of using deep neural networks as an alternative to computation-ally intensive multidimensional flamelet table storage and lookup. This approach has demonstrated a significant reduction in memory footprint and enabled the use of larger dimensional tabulated manifolds for supersonic combustion in canonical problems. In this study, the Unsteady Flamelet Progress Variable (UFPV)-ANN model implemented in the VULCAN-CFD code is validated by the Burrows-Kurkov supersonic mixing/combustion configuration. The well characterized experimental problem consists of hydrogen injection into a supersonic vitiated crossflow that results in a lifted flame structure. The initial model consists of a 4-dimensional table where the independent variables Z, C, Xst, P are tabulated using an unsteady flamelet code with boundary conditions corresponding to the vitiated air conditions. The results show the development of a lifted flame structure and over-all acceptable agreement with finite-rate chemistry (FRC) simulation and the experimental data. Moreover, direct mapping between the independent variables and the flamelet table is replaced by a deep neural network for significant memory reduction. The results indicate that the UFPV-ANN approach can retrieve the same solution as the memory intensive lookup table approach.

Flamelet↗
NASA NTRS2003

The Updated Umkehr Ozone Retrieval Algorithm and its Validation against Satellite Data

Improvements to the Umkehr ozone profile retrieval algorithm have been developed and are now being evaluated. The updated algorithm is able to simulate observations more accurately and provides data output that is easier to analyze. Among the new diagnostic capabilities that the updated algorithm provides is the averaging kernel (AK) method. The AK approach allows studying how the algorithm responds when a small perturbation is made in a particular layer of the atmosphere [Rodgers 1976, 1990]. We will use the AK method to define precisely what Umkehr should measure given a set of profiles measured by other platforms. This method allows us to compare trends and offsets in data more accurately than it has been done in the past. The updated Umkehr retrievals will be validated against SAGE II ozone profiles as well as SSBUV ozone profile data. We will discuss possible reasons for offset between data and differences in derived ozone profile trends. Considerable variability of the ozone profile within the 10-degree latitude envelope creates noise in the SAGE matching dataset and makes comparisons difficult. To eliminate this problem, the SAGE and Umkehr data had been previously de-seasonalized by subtracting the latitude/season dependent ozone climatology. However, the remaining noise in the ozone residuals was still considerably high for trend analysis and was attributed to longitude variability of SAGE sampling. The new ozone climatology (Labow, NASA) that has longitude dependent ozone variability will be used to minimize contribution of sampling noise in comparisons of satellite and ground station. The comparison of zenith-sky radiances (Umkehr N-value measurements) synthesized for a given set of SAGE profiles will be used to determine whether SAGE-derived N-values agree with the Umkehr-measured N-values. The instrumental effects will be discussed. Both the Umkehr data and SAGE II measurements will be analyzed for their information about ozone variability and loss and recovery rates at the mid- and upper (40 km) levels. The updated long-term Umkehr dataset can be used to provide high quality information for identifying signs of ozone recovery. The long Umkehr historical record can provide additional information for separating the dynamic and chemical mechanisms of depletion, and can help the community better understand climate change effects.

Petropavlovskikh, I.↗
NASA NTRS1981

Top-mounted inlet system feasibility for transonic-supersonic fighter aircraft

The more salient findings are presented of recent top inlet performance evaluations aimed at assessing the feasibility of top-mounted inlet systems for transonic-supersonic fighter aircraft applications. Top inlet flow field and engine-inlet performance test data show the influence of key aircraft configuration variables-inlet longitudinal position, wing leading-edge extension planform area, canopy-dorsal integration, and variable incidence canards-on top inlet performance over the Mach range of 0.6 to 2.0. Top inlet performance data are compared with those or more conventional inlet/airframe integrations in an effort to assess the viability of top-mounted inlet systems relative to conventional inlet installations.

Williams, T. L.↗
NASA NTRS1984

Preliminary Evaluation of Thematic Mapper Image Data Quality

Thematic Mapper (TM) data from Mississippi County, Arkansas, and Webster County, Iowa, were examined for the purpose of evaluating the image data quality of the TM which was launched on board the LANDSAT-4 spacecraft. Preliminary clustering and principal component analysis indicates that the middle infrared and thermal infrared data of TM appear to add significant information over that of the near IR and visible bands of the multispectral scanner data. Moreover, the higher spatial resolution of TM appears to provide better definition of the edges and the within variability of agricultural fields. The geometric performance of TM data, without ground control correction, was found to exceed expectations. The modulation transfer function for the 1.65 m band was found to agree with prelaunch specifications when the effects of the GSFC cubic convolution and the atmosphere were removed. The band to band registration for the bands within the noncooled focal plane was found to be better than specified. However, the middle infrared and thermal infrared, which are on a separate cooled focal plane were found to be misregistered and were significantly worse than prelaunch specifications.

Macdonald, R. B.↗
NASA NTRS1995

Solar cycle dependence of the sun's radius at lambda = 525.0 nm

The Mount Wilson (California) synoptic program of solar magnetic observations scans the solar disk between 1 and 20 times per day. As part of this program, the radius is determined as an average distance between the image center and the point where the intensity in the FeI line at lambda = 525.0 nm drops to 25 percent of its value at the disk's center. The data base of information was analyzed and corrected for effects such as scattered light and atmospheric reflection. The solar variability and the measurement techniques are described. The observation data sets, the corrections made to the data, and the observed variations, are discussed. It is stated that similar spectral lines at lambda = 525.0 nm, which are common in the solar spectrum, probably exhibit similar radius changes. All portions of the sun are weighted equally so that it is concluded that, within spectral lines, the radiating area of the sun is increased at the solar maximum.

Ulrich, Roger K.↗
NASA NTRS2001

Correlation Studies of Sea Ice Concentration with Surface Temperature and Meltponding

The spatial and temporal variability of sea ice concentrations derived from passive microwave data is studied in conjunction with co-registered high resolution infrared and visible satellite data. Cloud free infrared and visible data provide surface temperature and large scale surface characteristics, respectively, that can be used to better understand regional and seasonal fluctuations in ice concentrations. Results from correlation analysis of ice concentration versus surface temperature data show the intuitively expected negative relationship but the strength in the relationship is unexpectedly very strong. In the Antarctic, the correlation is consistently very high spatially when yearly anomalies are used, and not so high in some areas when seasonal anomalies are used, especially during spring and summer. In the monthly anomalies, the correlation is also good, especially in dynamically active regions. The expanse in the anomalies in surface temperature are shown to go way beyond the sea ice regions into the open ocean and continental areas, suggesting strong atmospheric forcing. Weak correlations are normally found in highly consolidated areas, where large changes in temperature do not cause large changes in ice concentration on a short term, and in open ocean polynya areas, where the change in ice concentration may be cause by melt from the underside of the ice. In the Arctic, strong correlations between surface temperature and ice concentration are evident for all seasons except during the summer. In the summer, factors such as meltponding, surface wetness, and ice breakup, as detected by high resolution visible data, contributes to larger uncertainties in the determination of ice concentration and the lack of good correlation of the variables.

Comiso, J. C.↗
NASA NTRS1971

Individual variation in circadian rhythms of sleep, EEG, temperature, and activity among monkeys - Implications for regulatory mechanisms.

Investigation of circadian rhythms in a number of variables related to sleep, EEG, temperature, and motor activity in rhesus monkeys on an LD 12:12 schedule. Circadian rhythms were found to appear in each of 15 variables investigated. Statistical procedures assessed the variables for evidence of common regulation in these aspects of their circadian rhythms: acrophase (timing), amplitude (extent of change), and level (24-hr mean value). Patterns appearing in the data suggested that the circadian rhythms of certain variables are regulated in common. The circadian modulation of activity in the beta and sigma frequency bands of the EEG was correlated with statistical significance in acrophase, level, and amplitude. The delta frequency band appeared to be under circadian rhythm regulation distinct from that of the other bands. The circadian rhythm of REM stage sleep was like that of beta activity in level and amplitude. The data indicate that REM stage may share some common regulation of circadian timing with both stage 3-4 sleep and with temperature. Generally, however, the circadian rhythm of temperature appeared to bear little relation to the circadian rhythms of motor activity, EEG, or sleep.

Crowley, T. J.↗
NASA NTRS2015

The Global Structure of UTLS Ozone in GEOS-5: A Multi-Year Assimilation of EOS Aura Data

Eight years of ozone measurements retrieved from the Ozone Monitoring Instrument (OMI) and the Microwave Limb Sounder, both on the EOS Aura satellite, have been assimilated into the Goddard Earth Observing System version 5 (GEOS-5) data assimilation system. This study thoroughly evaluates this assimilated product, highlighting its potential for science. The impact of observations on the GEOS-5 system is explored by examining the spatial distribution of the observation-minus-forecast statistics. Independent data are used for product validation. The correlation coefficient of the lower-stratospheric ozone column with ozonesondes is 0.99 and the bias is 0.5%, indicating the success of the assimilation in reproducing the ozone variability in that layer. The upper-tropospheric assimilated ozone column is about 10% lower than the ozonesonde column but the correlation is still high (0.87). The assimilation is shown to realistically capture the sharp cross-tropopause gradient in ozone mixing ratio. Occurrence of transport-driven low ozone laminae in the assimilation system is similar to that obtained from the High Resolution Dynamics Limb Sounder (HIRDLS) above the 400 K potential temperature surface but the assimilation produces fewer laminae than seen by HIRDLS below that surface. Although the assimilation produces 5 - 8 fewer occurrences per day (up to approximately 20%) during the three years of HIRDLS data, the interannual variability is captured correctly. This data-driven assimilated product is complementary to ozone fields generated from chemistry and transport models. Applications include study of the radiative forcing by ozone and tracer transport near the tropopause.

GEOS-5↗