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At least 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Case studies using GOES infrared data and a planetary boundary layer model to infer regional scale variations in soil moisture

Modeled temperature data from a one-dimensional, time-dependent, initial value, planetary boundary layer model for 16 separate model runs with varying initial values of moisture availability are applied, by the use of a regression equation, to longwave infrared GOES satellite data to infer moisture availability over a regional area in the central U.S. This was done for several days during the summers of 1978 and 1980 where a large gradient in the antecedent precipitation index (API) represented the boundary between a drought area and a region of near normal precipitation. Correlations between satellite derived moisture availability and API were found to exist. Errors from the presence of clouds, water vapor and other spatial inhomogeneities made the use of the measurement for anything except the relative degree of moisture availability dubious.

Rose, F. G.↗
NASA NTRS2004

Full Scale Rotor Aeroacoustic Predictions and the Link to Model Scale Rotor Data

The NASA Aeroacoustic Prediction System (NAPS) is used to establish a link between model-scale and full-scale rotor predictions and is partially validated against measured wind tunnel and flight aeroacoustic data. The prediction approach of NAPS couples a comprehensive rotorcraft analysis with acoustic source noise and propagation codes. The comprehensive analysis selected for this study is CAMRAD-II, which provides the performance/trim/wake solution for a given rotor or flight condition. The post-trim capabilities of CAMRAD-II are used to compute high-resolution sectional airloads for the acoustic tone noise analysis, WOPMOD. The tone noise is propagated to observers on the ground with the propagation code, RNM (Rotor Noise Model). Aeroacoustic predictions are made with NAPS for an isolated rotor and compared to results of the second Harmonic Aeroacoustic Rotor Test (HART-II) program, which tested a 40% dynamically and Mach-scaled BO-105 main rotor at the DNW. The NAPS is validated with comparisons for three rotor conditions: a baseline condition and two Higher Harmonic Control (HHC) conditions. To establish a link between model and full-scale rotor predictions, a full-scale BO-105 main rotor input deck for NAPS is created from the 40% scale rotor input deck. The full-scale isolated rotor predictions are then compared to the model predictions. The comparisons include aerodynamic loading, acoustic levels, and acoustic pressure time histories for each of the three conditions. With this link established, full-scale predictions are made for a range of descent flight conditions and compared with measured trends from the recent Rotorcraft Operational Noise Abatement Procedures (RONAP) flight test conducted by DLR and ONERA. Additionally, the effectiveness of two HHC conditions from the HART-II program is demonstrated for the full-scale rotor in flight.

Boyd, D. Douglas, Jr.↗
NASA NTRS2023

Reports From EXPORTS Modeling and Data-Mining Activities

EXPORTS -EXport Processes in the Ocean from RemoTe Sensing is NASA’s large field campaign focusing on development of a predictive understanding of the export, fate and carbon cycle impacts of the global net primary production. This co-funded program (NSF, private funding1, and international participation) was conceived in 2013, with EXPORTS Science plan published in 2016 (Siegel et al 2016, EXPORTS Writing Team 2015) and its implementation plan finalized in 2016 (EXPORTS Science Definition Team 2016). More details are presented in Siegel et al (2021). EXPORTS campaign is structured as a multiyear effort (Figure 1). It started with “Pre-EXPORTS” modeling and data-mining activity followed by a first phase with two major field programs and a second synthesis and modeling phase. The “Pre-EXPORTS” projects, total of 6 of them (Table 1), funded under A.3 Ocean Biology and Biogeochemistry 2015 call, helped to plan the field campaign (Resplandy et al 2019, Rousseaux & Gregg 2017), and supporting further global synthesis with datasets mined from the literature (e.g. Bisson et al (2020), Bisson et al (2018), Kramer and Siegel (2019)), directly responding to objectives outlined in Science Plan (see section 6 in Team (2015)) and Implementation team (see Figure 1 in Team (2016)). This document presents a compilation of the final reports of the Pre-EXPORTS funded projects, in hope of synthesizing the outcomes, and insuring the legacy of this program. Each of these reports contains a list of published papers, and reader should refer to them to see results in details.

Brandi J. McCarty↗
NASA NTRS1991

A model of regional primary production for use with coarse resolution satellite data

A model of crop primary production, which was originally developed to relate the amount of absorbed photosynthetically active radiation (APAR) to net production in field studies, is discussed in the context of coarse resolution regional remote sensing of primary production. The model depends on an approximately linear relationship between APAR and the normalized difference vegetation index. A more comprehensive form of the conventional model is shown to be necessary when different physiological types of plants or heterogeneous vegetation types occur within the study area. The predicted variable in the new model is total assimilation (net production plus respiration) rather than net production alone or harvest yield.

Prince, S. D.↗
NASA NTRS1995

Assimilation of Altimeter Data into a Quasigeostrophic Model of the Gulf Stream System: Dynamical Considerations - Part 1

The dynamical consequences of constraining a numerical model with sea surface height data have been investigated. The model used for this study is a quasigeostrophic model of the Gulf Stream region. The data that have been assimilated are maps of sea surface height obtained as the superposition of sea surface height variability deduced from the Geosat altimeter measurements and a mean field constructed from historical hydrographic data. The method used for assimilating the data is the nudging technique. Nudging has been implemented in such a way as to achieve a high degree of convergence of the surface model fields toward the observations. The assimilation of the surface data is thus equivalent to the prescription of a surface pressure boundary condition. The authors analyzed the mechanisms of the model adjustment and the characteristics of the resultant equilibrium state when the surface data are assimilated. Since the surface data are the superposition of a mean component and an eddy component, in order to understand the relative role of these two components in determining the characteristics of the final equilibrium state, two different experiments have been considered: in the first experiment only the climatological mean field is assimilated, while in the second experiment the total surface streamfunction field (mean plus eddies) has been used. It is shown that the model behavior in the presence of the surface data constraint can be conveniently described in terms of baroclinic Fofonoff modes. The prescribed mean component of the surface data acts as a 'surface topography' in this problem. Its presence determines a distortion of the geostrophic contours in the subsurface layers, thus constraining the mean circulation in those layers. The intensity of the mean flow is determined by the inflow/outflow conditions at the open boundaries, as well as by eddy forcing and dissipation.

Capotondi, Antonietta↗
NASA NTRS1997

Data-based magnetic field models: Present status and future prospects

Empirical magnetic field models are discussed in terms of using models in multi-instrument data analysis. The variety of previous applications of field models are demonstrated. The problems found by using data based models are addressed and the prospects of their future development are outlined. Some issues related to time-dependency of the field configuration are presented.

T. I. Pulkkinen↗
NASA NTRS2022

A Method for Incorporating Quartz Crystal Microbalance Thermo-Gravimetric Assessment Data in Contamination Modeling

The science objectives of increasingly ambitious space missions require meeting stringent contamination requirements. Contamination transport models are based on established principles such as Fick’s law for contamination diffusion within the source material, Arrhenius factors to account for temperature variations and free molecular transport for spacecraft operating in vacuum. In addition to the science principles, empirical data obtained from ASTM E1559 testing is used for engineering contamination modeling. The ASTM E1559 test provides outgassing rate data for materials at expected spacecraft temperatures during a mission. Multiple quartz crystal microbalances (QCMs) can be operated at different temperatures to measure the amount of contamination condensation that can occur on various spacecraft surfaces. At the conclusion of the ASTM E1559 test a thermo-gravimetric assessment (TGA) can be performed by heating the QCMs at a linear rate to obtain contamination desorption data. This TGA data provides a wealth of information that can be incorporated into contamination models. A method for applying this data is presented.

Anderson, John R↗
NASA NTRS1982

Improving a NASTRAN dynamic model with test data using LINWOOD

The concept of expressing test modes as a linear combination of analytical modes was applied to the prediction of corrective terms in math model mass and stiffness. Test data for the Space Shuttle quarter scale solid rocket booster were analyzed by this method and significant improvements in frequency and mode shap correlation are noted. The applicability of the method is demonstrated.

Ujihara, B. H.↗
NASA NTRS1982

Thematic mapper flight model preshipment review data package. Volume 3, part B: System data

Procedures and results are presented for performance and systems integration tests of flight model-1 thematic mapper. Aspects considered cover electronic module integration, radiometric calibration, spectral matching, spatial coverage, radiometric calibration of the calibrator, coherent noise, dynamic square wave response, band to band registration, geometric accuracy, and self induced vibration. Thermal vacuum tests, EMI/EMS, and mass properties are included. Liens are summarized.

Source record↗
NASA NTRS1985

The MSFC/J70 orbital atmosphere model and the data bases for the MSFC solar activity prediction technique

The MSFC/J70 Orbital Atmospheric Density Model, a modified version of the Smithsonian Astrophysical Observatory Jacchia 1970 model is explained. The algorithms describing the MSFC/J70 model are included as well as listing of the computer program. The 13-month smoothed values of solar flux (F sub 10.7) and geomagnetic index (S sub p), which are required as inputs for the MSFC/J70 model, are also included and discussed.

Johnson, D. L.↗
NASA NTRS1988

Modeling and estimation of a low degree geopotential model from terrestrial gravity data

The development of appropriate modeling and adjustment procedures for the estimation of harmonic coefficients of the geopotential, from surface gravity data was studied, in order to provide an optimum way of utilizing the terrestrial gravity information in combination solutions currently developed at NASA/Goddard Space Flight Center, for use in the TOPEX/POSEIDON mission. The mathematical modeling was based on the fundamental boundary condition of the linearized Molodensky boundary value problem. Atmospheric and ellipsoidal corrections were applied to the surface anomalies. Terrestrial gravity solutions were found to be in good agreement with the satellite ones over areas which are well surveyed (gravimetrically), such as North America or Australia. However, systematic differences between the terrestrial only models and GEMT1, over extended regions in Africa, the Soviet Union, and China were found. In Africa, gravity anomaly differences on the order of 20 mgals and undulation differences on the order of 15 meters, over regions extending 2000 km in diameter, occur. Comparisons of the GEMT1 implied undulations with 32 well distributed Doppler derived undulations gave an RMS difference of 2.6 m, while corresponding comparison with undulations implied by the terrestrial solution gave RMS difference on the order of 15 m, which implies that the terrestrial data in that region are substantially in error.

Pavlis, Nikolaos K.↗
NASA NTRSDate not supplied

Development of Carbon Flux Model Using ABI Data Over the Conterminous US

The satellite-driven carbon flux estimation has been playing important role to estimate continental-scale carbon budget. One of the biggest recent advances in the satellite-driven carbon flux modeling is utilization of high-frequent geostationary satellites to estimate diurnal cycle in carbon fluxes. The satellite based carbon flux estimation used the polar orbiting satellite sensors (e.g., Moderate Resolution Imaging Spectroradiometer (MODIS)), which allow us to observe target regions only once during the day. The new generation of geostationary satellite sensors provide frequent observations, often less than every 10 minutes. Here, we use GOES Advanced Baseline Imager (ABI) data to estimate hourly NEE over the conterminous US. We used the Terrestrial Observation Prediction System (TOPS) model for estimating hourly NEE. TOPS is a diagnostic ecosystem process model that simulates the fluxes of carbon and water through vegetation in response to climate variability. For the climate input, we developed hourly climate data using the same algorithm with NASA Earth Exchange Gridded Daily Meteorology (NEX-GDM) datasets based on machine learning techniques. The hourly climate data includes precipitation, maximum temperature, minimum temperature, dew point temperature, and solar radiation were derived from the Geostationary observations. The spatial patterns of ecosystem parameters used in TOPS are optimized using satellite Solar Induced Fluorescence (SIF) data. The high frequency GPP estimations from geostationary satellite sensors make it comparable to the instantaneous SIF data than daily GPP. We also used Ameriflux data for optimization of model parameters and the validation of the output. The derived data addresses the diurnal dynamics of carbon cycling at large scales and should help in reducing the uncertainties in carbon budget studies.

geostationary satellite↗
NASA NTRS1979

A maximum likelihood convolutional decoder model vs experimental data comparison

This article describes the comparison of a maximum likelihood convolutional decoder (MCD) prediction model and the actual performance of the MCD at the Madrid Deep Space Station. The MCD prediction model is used to develop a subroutine that has been utilized by the Telemetry Analysis Program (TAP) to compute the MCD bit error rate for a given signal-to-noise ratio. The results indicate that that the TAP can predict quite well compared to the experimental measurements. An optimal modulation index also can be found through TAP.

Chen, R. Y.↗
NASA NTRS2010

Validation of the Integrated Medical Model Using Historical Space Flight Data

The Integrated Medical Model (IMM) utilizes Monte Carlo methodologies to predict the occurrence of medical events, utilization of resources, and clinical outcomes during space flight. Real-world data may be used to demonstrate the accuracy of the model. For this analysis, IMM predictions were compared to data from historical shuttle missions, not yet included as model source input. Initial goodness of fit test-ing on International Space Station data suggests that the IMM may overestimate the number of occurrences for three of the 83 medical conditions in the model. The IMM did not underestimate the occurrence of any medical condition. Initial comparisons with shuttle data demonstrate the importance of understanding crew preference (i.e., preferred analgesic) for accurately predicting the utilization of re-sources. The initial analysis demonstrates the validity of the IMM for its intended use and highlights areas for improvement.

Kerstman, Eric L.↗
NASA NTRS2006

Data Needs for Stellar Atmosphere and Spectrum Modeling

The main data need for stellar atmosphere and spectrum modeling remains atomic and molecular transition data, particularly energy levels and transition cross-sections. We emphasize that data is needed for bound-free (b - f) as well as bound-bound (b - b), and collisional as well as radiative transitions. Data is now needed for polyatomic molecules as well as atoms, ions, and diatomic molecules. In addition, data for the formation of, and extinction due to, liquid and solid phase dust grains is needed. A prioritization of species and data types is presented, and gives emphasis to Fe group elements, and elements important for the investigation of nucleosynthesis and Galactic chemical evolution, such as the -elements and n-capture elements. Special data needs for topical problems in the modeling of cool stars and brown dwarfs are described.

Short, C. I.↗
NASA NTRS2003

Aeroservoelastic Model Validation and Test Data Analysis of the F/A-18 Active Aeroelastic Wing

Model validation and flight test data analysis require careful consideration of the effects of uncertainty, noise, and nonlinearity. Uncertainty prevails in the data analysis techniques and results in a composite model uncertainty from unmodeled dynamics, assumptions and mechanics of the estimation procedures, noise, and nonlinearity. A fundamental requirement for reliable and robust model development is an attempt to account for each of these sources of error, in particular, for model validation, robust stability prediction, and flight control system development. This paper is concerned with data processing procedures for uncertainty reduction in model validation for stability estimation and nonlinear identification. F/A-18 Active Aeroelastic Wing (AAW) aircraft data is used to demonstrate signal representation effects on uncertain model development, stability estimation, and nonlinear identification. Data is decomposed using adaptive orthonormal best-basis and wavelet-basis signal decompositions for signal denoising into linear and nonlinear identification algorithms. Nonlinear identification from a wavelet-based Volterra kernel procedure is used to extract nonlinear dynamics from aeroelastic responses, and to assist model development and uncertainty reduction for model validation and stability prediction by removing a class of nonlinearity from the uncertainty.

Brenner, Martin J.↗
NASA NTRS1979

Subjective evaluation of the combined influence of satellite temperature sounding data and increased model resolution on numerical weather forecasting

The present evaluation is concerned with (1) the significance of prognostic differences resulting from the inclusion of satellite-derived temperature soundings, (2) how specific differences between the SAT and NOSAT prognoses evolve, and (3) comparison of two experiments using the Goddard Laboratory for Atmospheric Sciences general circulation model. The subjective evaluation indicates that the beneficial impact of sounding data is enhanced with increased resolution. It is suggested that satellite sounding data posses valuable information content which at times can correct gross analysis errors in data sparse regions.

Atlas, R.↗