Search NASA⌕ Search

SEARCH · Search NASA

Results for “physical parameters”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Environmental parameters of the Tennessee River in Alabama. 2: Physical, chemical, and biological parameters

Physical, chemical and biological water quality data from five sites in the Tennessee River, two in Guntersville Reservoir and three in Wheeler Reservoir were correlated with climatological data for three annual cycles. Two of the annual cycles are for the years prior to the Browns Ferry Nuclear Power Plant operations and one is for the first 14 months of Plant operations. A comparison of the results of the annual cycles indicates that two distinct physical conditions in the reservoirs occur, one during the warm months when the reservoirs are at capacity and one during the colder winter months when the reservoirs have been drawn-down for water storage during the rainy months and for weed control. The wide variations of physical and chemical parameters to which the biological organisms are subjected on an annual basis control the biological organisms and their population levels. A comparison of the parameters of the site below the Power plant indicates that the heated effluent from the plant operating with two of the three reactors has not had any effect on the organisms at this site. Recommendations given include the development of prediction mathematical models (statistical analysis) for the physical and chemical parameters under specific climatological conditions which affect biological organisms. Tabulated data of chemical analysis of water and organism populations studied is given.

Rosing, L. M.↗
NASA NTRS2008

Black Hole Mergers as Probes of Structure Formation

Observations of gravitational waves from massive black hole (MBH) mergers can provide us with important clues about the era of structure formation in the early universe. Previous research in this field has been limited to calculating merger rates of MBHs using different models where many assumptions are made about the specific values of physical parameters of the mergers, resulting in merger rate estimates that span 5 to 6 orders of magnitude. We develop a semi-analytical, phenomenological model that includes plausible combinations of several physical parameters involved in the mergers. which we then turn around to determine how well LISA observations will be able to enhance our understanding of the universe during the critical z approximately equal to 5-30 structure formation era. We do this by generating synthetic LISA observable data (masses, redshifts, merger rates), which are then analyzed using a Markov Chain Monte Carlo (MCMC) method. This allows us to constrain the physical parameters of the mergers.

Alicea-Munoz, Emily↗
NASA NTRS2008

Black Hole Mergers as Probes of Structure Formation

Intense structure formation and reionization occur at high redshift, yet there is currently little observational information about this very important epoch. Observations of gravitational waves from massive black hole (MBH) mergers can provide us with important clues about the formation of structures in the early universe. Past efforts have been limited to calculating merger rates using different models in which many assumptions are made about the specific values of physical parameters of the mergers, resulting in merger rate estimates that span a very wide range (0.1 - 104 mergers/year). Here we develop a semi-analytical, phenomenological model of MBH mergers that includes plausible combinations of several physical parameters, which we then turn around to determine how well observations with the Laser Interferometer Space Antenna (LISA) will be able to enhance our understanding of the universe during the critical z 5 - 30 structure formation era. We do this by generating synthetic LISA observable data (total BH mass, BH mass ratio, redshift, merger rates), which are then analyzed using a Markov Chain Monte Carlo method. This allows us to constrain the physical parameters of the mergers. We find that our methodology works well at estimating merger parameters, consistently giving results within 1- of the input parameter values. We also discover that the number of merger events is a key discriminant among models. This helps our method be robust against observational uncertainties. Our approach, which at this stage constitutes a proof of principle, can be readily extended to physical models and to more general problems in cosmology and gravitational wave astrophysics.

Alicea-Munoz, E.↗
NASA NTRS2018

Flux-Pinned Dynamics Model Parameterization and Sensitivity Study

Flux-pinned interfaces for spacecraft are an action-at-a-distance technology that can maintain a passively stable equilibrium between two spacecraft in close-proximity using the physics of magnetic flux pinning. Although flux pinning dynamics have been studied from a material-science perspective and at an interface level, there is a need to better understand the sensitivities and implications of system-level designs on the flux-pinned interface dynamics, especially in designs with multiple magnets and superconductors. These interfaces have highly nonlinear, coupled dynamics that are influenced by physical parameters including but not limited to strength of magnetic field sources, field-cooled position, and superconductor geometry. This paper addresses that gap by codifying parametric terms into an improved dynamics model, which can then be used to simulate the interaction of a multiple-superconductor-multiple-magnet interface. A standard starting point for modeling flux pinning dynamics is Kordyuk’s frozen image model, which defines a geometric mapping between magnetic field sources and their corresponding magnetic point source “images inside the volume of the superconductor.” The frozen image model successfully approximates the characteristics of flux pinning dynamics, but could provide more precise position and orientation predictions with the addition of various physical parameter refinements. The sensitivity of the general flux-pinned dynamics model is studied by varying the physical parameters and simulating the systems level dynamics. A predictive dynamics model is crucial to the maturation of this technology so it can be utilized in spacecraft systems, and this work represents a critical step in the development of that model.

Peck, Mason↗
NASA NTRS1984

Remote Sensing of Earth Terrain

Theoretical models that are useful and practical in relating remote sensing data to the important physical parameters characterizing Earth terrain are developed. The development of models that are useful in data analysis and interpretation, scene simulation, and developing new remote sensing approaches and techniques is discussed. Numerous theoretical models that are applicable to the active and passive remote sensing of plowed fields, atmospheric precipitation, vegetation, and snow fields were developed. The radiative transfer theory is used to interpret the active and passive data as a function of rain rate. Both the random medium model and the discrete scatterer model is used to study the remote sensing of vegetation fields. Due to the non-spherical geometry of the scatterers there is strong azimuthal dependence in the observed data. Thus, the anisotropic random medium model and the discrete scatterer model with nonspherical particles was developed. In order to relate the remote sensing data to the actual physical parameters, the scattering of electromagnetic waves from randomly distributed dielectric scatterers was studied. Both the rigorous random discrete scatterer theory and the strong fluctuation theory are used to derive the backscattering cross section in terms of the actual physical parameters and the results agree well with the data obtained from the snow fields.

Kong, J. A.↗
NASA NTRS1993

Application of the target decomposition theorem to a polarimetric random media model

With advances in polarimetric radar measurements of land surfaces, the need for understanding the underlying scattering mechanisms and dominant target features has become the focus of many studies. In particular, the maximum use of the polarimetric information to identify and/or separate parameters related to the surface features such as vegetation thickness, structure, water content, and soil surface characteristics will enhance the possibility of using polarimetric radars for monitoring the earth's surface from space. In this paper, Cloude's decomposition theorem is applied to a polarimetric random media model to simulate the radar measurements of vegetated canopies. The vegetated canopies are modeled as a three layer discrete random medium with leaves and branches in the first layer, tree trunks in the second layer, and a half space of homogeneous ground with rough interface as the bottom layer. The distorted born approximation (DBA) has been used to compute full Mueller matrix of the canopy, using canonical dielectric objects such as thin discs and cylinders as leaves, branches, and trunks, respectively. The Mueller matrix and the derived covariance matrix contain information on the second order statistics of radar signals at various polarizations from the canopy. To decompose the covariance matrix to its constituent targets, the eigenvalues and eigenvectors of the covariance matrix are computed in terms of the physical parameters of the canopy. In addition, each eigenvector explicitly shows the scattering mechanisms such as odd and even reflections in the canopy. Cloude's decomposition theorem is applied using the Pauli spin matrices as a basis and an expression for the degree of disorder or the entropy for the vegetated surface is found. Then, the physical parameters estimated from in situ measurements are used in the random media to obtain realistic covariance matrices. As a result, the sensitivity of the eigenvalue spectrums and the coefficients resulting from the target decomposition theorem to the physical parameters of the canopy are examined and the possible use of Cloude's theorem to estimate vegetation and soil parameters is discussed.

Saatchi, Sasan S.↗
NASA NTRS1991

Use of system identification techniques for improving airframe finite element models using test data

A method for using system identification techniques to improve airframe finite element models was developed and demonstrated. The method uses linear sensitivity matrices to relate changes in selected physical parameters to changes in total system matrices. The values for these physical parameters were determined using constrained optimization with singular value decomposition. The method was confirmed using both simple and complex finite element models for which pseudo-experimental data was synthesized directly from the finite element model. The method was then applied to a real airframe model which incorporated all the complexities and details of a large finite element model and for which extensive test data was available. The method was shown to work, and the differences between the identified model and the measured results were considered satisfactory.

Hanagud, Sathya V.↗
NASA NTRS1991

Use of system identification techniques for improving airframe finite element models using test data

A method for using system identification techniques to improve airframe finite element models using test data has been developed and demonstrated. The method uses linear sensitivity matrices to relate changes in selected physical parameters to changes in the total system matrices. The values for these physical parameters were determined using constrained optimization with singular value decomposition. The method was confirmed using both simple and complex finite element models for which pseudo-experimental data was synthesized directly from the finite element model. The method was then applied to a real airframe model which incorporated all of the complexities and details of a large finite element model and for which extensive test data was available. The method was shown to work, and the differences between the identified model and the measured results were considered satisfactory.

Hanagud, Sathya V.↗
NASA NTRS1993

Use of system identification techniques for improving airframe finite element models using test data

A method for using system identification techniques to improve airframe finite element models using test data was developed and demonstrated. The method uses linear sensitivity matrices to relate changes in selected physical parameters to changes in the total system matrices. The values for these physical parameters were determined using constrained optimization with singular value decomposition. The method was confirmed using both simple and complex finite element models for which pseudo-experimental data was synthesized directly from the finite element model. The method was then applied to a real airframe model which incorporated all of the complexities and details of a large finite element model and for which extensive test data was available. The method was shown to work, and the differences between the identified model and the measured results were considered satisfactory.

Hanagud, Sathya V.↗
NASA NTRS1975

Use of LIDAR systems in measuring certain physical oceanographic parameters

Remote sensing techniques, such as LIDAR, are the only observation methods which are capable of fast scanning over a vast area to produce synoptic views which are necessary for time and space study of the ocean. However, due to the very nature of the way data are collected, all the information thus obtained is confined, to or in the immediate neighborhood of the surface. Nevertheless, all the physical processes in the ocean are controlled mainly by both surface and subsurface parameters; they act and interact among themselves and produce the phenomena we actually observe in time and space. Remote sensing techniques are very effective for those phenomena controlled by surface parameters which account for most of the crucial problems in physical oceanography.

Chen, D. T.↗
NASA NTRS1984

Thermal evolution of Venus

A modification of the Boussinesq fluid assumption is the basis of the present theory of three-dimensional and finite amplitude convection in a viscous spherical shell with temperature- and pressure-dependent physical parameters. The theory is applied to the definition of thermal evolution models for Venus which emphasize the effects of certain physical parameters on thermal evolution, rather than the specific thermal history of the planet. It is suggested that a significant portion of the present temperature in the mantle and surface heat flux of Venus is due to the decay of a high temperature that was established in the planet at the completion of its core formation, and that Venus has been highly convective over the course of its history, until about 0.5 Ga ago.

Arkani-Hamed, J.↗
NASA NTRS1974

A Simulation Model for Studying Effects of Pollution and Freshwater Inflow on Secondary Productivity in an Ecosystem

A mathematical model of an ecosystem is developed. Secondary productivity is evaluated in terms of man related and controllable factors. Information from an existing physical parameters model is used as well as pertinent biological measurements. Predictive information of value to estuarine management is presented. Biological, chemical, and physical parameters measured in order to develop models of ecosystems are identified.

Johnson, R. W.↗
NASA NTRS2022

Using Desis and EO-1 Hyperion Reflectance Time Series for the Assessment of Vegetation Traits and Gross Primary Production (GPP)

This study evaluates the potential of the DLR Earth Sensing Imaging Spectrometer (DESIS) visible through near-infrared (VNIR) surface reflectance to augment the EO-1 Hyperion full spectrum (400-2400 nm) reflectance collection over vegetated flux sites to extend the reflectance time series up to the present. We compared DESIS and Hyperion surface reflectance magnitude and variability at a pseudo-invariant site (PICS) and a vegetated flux site (VFS). VNIR reflectance magnitudes between the two sensors did not significantly differ at the PICS. However, DESIS variability was higher, likely due to differences in the data acquisition time and observation geometry. Using empirical and biophysical models, both DESIS and Hyperion datasets captured the seasonal variations in gross primary production (GPP) and canopy bio-physical parameters such as chlorophyll content, leaf area index (LAI), and senescent material at the VFS. Differences in the magnitudes of the bio-physical parameters were observed, likely due to the differences in the sensors spectral range and resolution. Using VNIR reflectance from EO-1 Hyperion with DESIS convolved to Hyperion spectral resolution to estimate canopy chlorophyll and GPP, we demonstrate that combining historic and current space-based reflectance data in a common multi-sensor approach is feasible. This is of importance for extending the reflectance record established with EO-1 Hyperion to provide continuity with the current orbital instruments (e.g., DESIS/ISS, PRISMA/ASI) and the forthcoming NASA Surface Biology and Geology (SBG), ESA CHIME and DLR EnMAP satellite missions, which is of key importance for comparisons of current and past trends in the seasonal dynamics of vegetation traits and photosynthetic function.

DESIS↗
NASA NTRS2016

Multi-Parameter Scattering Sensor and Methods

Methods, detectors and systems detect particles and/or measure particle properties. According to one embodiment, a detector for detecting particles comprises: a sensor for receiving radiation scattered by an ensemble of particles; and a processor for determining a physical parameter for the detector, or an optimal detection angle or a bound for an optimal detection angle, for measuring at least one moment or integrated moment of the ensemble of particles, the physical parameter, or detection angle, or detection angle bound being determined based on one or more of properties (a) and/or (b) and/or (c) and/or (d) or ranges for one or more of properties (a) and/or (b) and/or (c) and/or (d), wherein (a)-(d) are the following: (a) is a wavelength of light incident on the particles, (b) is a count median diameter or other characteristic size parameter of the particle size distribution, (c) is a standard deviation or other characteristic width parameter of the particle size distribution, and (d) is a refractive index of particles.

Greenberg, Paul S.↗
NASA NTRS1990

The saturation of the electron-cyclotron maser instability and the interpretation of solar millisecond spikes

A self-consistent numeric two-dimensional code of the kinetic wave-particle equations developed to investigate the maser dynamics in the solar context is applied to solar millisecond-spike observations in order to improve the diagnostic capabilities of the theory of the electron-cyclotron maser instablitity. Attention is given to the inhomogeneity of the magnetic field selecting magneto-ionic modes with relatively short saturation lengths and suppressing mechanisms such as collisional deflection, free-free absorption, and gyroresonance absorption. The time scales of maser saturation in respect to time scales of global particle changes in a magnetic loop are covered, relevant observations of solar millisecond spikes are described, and the interpretation in terms of physical parameters deduced from the quasi-linear maser simulations are presented. It is demonstrated that the quasi-linear simulations make it possible to constrain the physical parameters from the observed time scale and frequency.

Aschwanden, M. J.↗
NASA NTRS1995

Investigation of microwave backscatter from the air-sea interface

Monitoring the ocean surface winds and mean ocean surface level is essential for improving our knowledge of the climate. Two instruments that may provide us with this information are satellite-based scatterometers and altimeters. However, these instruments measure the backscatter characteristics of the ocean surface from which other physical parameters, such as the wind speed or ocean surface height, are derived. To improve the algorithms or models that relate the electromagnetic backscatter to the desired physical parameters, the University of Massachusetts (UMass) Microwave Remote Sensing Laboratory (MIRSL) designed and fabricated three airborne scatterometers: a C-band scatterometer (CSCAT), Ku-band scatterometer (KUSCAT) and C/Ku-band scatterometer (EMBR). One or more of these instruments participated in the Electromagnetic Bias experiment (EM Bias), Shelf Edge Exchange Processes experiment (SEEP), Surface Wave Dynamics Experiment (SWADE), Southern Ocean Wave Experiment (SOWEX), Hurricane Tina research flights, Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE), and Ladir In-space Technology Experiment (LITE). This document describes the three scatterometers, summarizes our measurement campaigns and major contributions to the scientific and engineering communities, lists the publications that resulted, and presents the degrees earned under the support of this NASA grant.

Mcintosh, Robert E.↗
NASA NTRS1993

Model updating based on sensitivities of system matrices

A new approach, which allows the physical parameters to be adjusted and preserves the structural connectivity condition, is developed in this paper. This approach is based on the sensitivities of the mass and stiffness matrices with respect to physical parameters in an attempt to use test data to correct the analytical model. The analytical mass and stiffness matrices can be corrected simultaneously. The modal data of the updated model dramatically converges to that of the test model. A numerical example is presented to illustrate the feasibility of this approach. Comparisons with the other methods are also given.

Huang, Hsin-Hsen↗
NASA NTRS2011

GRB 091127: The Cooling Break Race on Magnetic Fuel

Using high-quality, broad-band afterglow data for GRB 091127, we investigate the validity of the synchrotron fireball model for gamma-ray bursts, and infer physical parameters of the ultra-relativistic outflow. Methods. We used multi-wavelength (NIR to X-ray) follow-up observations obtained with GROND simultaneously in the g' r' t' i' z' JH filters and the XRT onboard the Swift satellite in the 0.3 to 10 keY energy range. The resulting afterglow light curve is of excellent accuracy with relative photometric errors as low as 1 %, and the spectral energy distribution (SED) is well-sampled over 5 decades in energy. These data present one of the most comprehensive observing campaigns for a single GRB afterglow and allow us to test several proposed emission models and outflow characteristics in unprecedented detail. Results. Both the multi-color light curve and the broad-band SED of the afterglow of GRB 091127 show evidence of a cooling break moving from high to lower energies. The early light curve is well described by a broken power-law, where the initial decay in the optical/NlR wavelength range is considerably flatter than at X-rays. Detailed fitting of the time-resolved SED shows that the break is very smooth with a sharpness index of 2.2 +/- 0.2, and evolves towards lower frequencies as a power-law with index -1.23 +/- 0.06. These are the first accurate and contemporaneous measurements of both the sharpness of the spectral break and its time evolution. Conclusions. The measured evolution of the cooling break (V(sub c) varies as t(sup -1.2) is not consistent with the predictions of the standard model, wherein V(sub c) varies as t(sup -05) is expected. A possible explanation for the observed behavior is a time dependence of the microphysical parameters, in particular the fraction of the total energy in the magnetic field epsilon(sub Beta). This conclusion provides further evidence that the standard fireball model is too simplistic, and time-dependent micro-physical parameters may be required to model the growing number of well-sampled afterglow light curves.

Filgas, R.↗