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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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At least 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Noise produced by turbulent flow into a rotor: Theory manual for atmospheric turbulence prediction and mean flow and turbulence contraction prediction

Prediction of helicopter main rotor noise due to ingestion of atmospheric turbulence was analyzed. The analysis combines several different models that describe the fluid mechanics of the turbulence and the ingestion process. Two models, atmospheric turbulence, and mean flow and turbulence contraction were covered. The third model, covered in a separate report, describes the rotor acoustic mode. The method incorporates the atmospheric turbulence model and a rapid distortion turbulence contraction description to determine the statistics of the anisotropic turbulence at the rotor plane. The analytical basis for a module was provided which was incorporated in NASA's ROTONET helicopter noise prediction program. The mean flow and turbulence statistics associated with the atmospheric boundary layer were modeled including effects of atmospheric stability length, wind speed, and altitude. The turbulence distortion process is modeled as a deformation of vortex filaments (which represent the turbulence field) by a mean flow field due to the rotor inflow.

Simonich, J. C.↗
NASA NTRS1972

Computers formed by the problems rather than problems deformed by the computers.

Description of an approach to computer programming which tries to minimize the time required for retranslation from the computer language into the language of the original process. A notion of a programmable network is introduced which allows the abstract machines that are a model of the processes in the user's mind to be put into a rigorous and simple form. Each process is then modeled as a particular finite-state machine, a circulating page loose system being employed as an architecture for implementing these finite-state machines. An experiment is discussed in which the use of abstract machines as a language for modeling processes, in conjunction with the use of a self-organizing computer, decreases user effort, eliminates the need for compilation, facilitates debugging, and decreases computer time.

Schaffner, M. R.↗
NASA NTRS2005

The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

Cloud microphysics are inevitable affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds, Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effect of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral-bin microphysical scheme was implemented into the the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bim microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.

Tao, Wei-Kuo↗
NASA NTRS1989

The 3D model control of image processing

Telerobotics studies remote control of distant robots by a human operator using supervisory or direct control. Even if the robot manipulators has vision or other senses, problems arise involving control, communications, and delay. The communication delays that may be expected with telerobots working in space stations while being controlled from an Earth lab have led to a number of experiments attempting to circumvent the problem. This delay in communication is a main motivating factor in moving from well understood instantaneous hands-on manual control to less well understood supervisory control; the ultimate step would be the realization of a fully autonomous robot. The 3-D model control plays a crucial role in resolving many conflicting image processing problems that are inherent in resolving in the bottom-up approach of most current machine vision processes. The 3-D model control approach is also capable of providing the necessary visual feedback information for both the control algorithms and for the human operator.

Nguyen, An H.↗
NASA NTRS1993

A model for heterogeneous chemical processes on the surfaces of ice and nitric acid trihydrate particles

The study presents a model that incorporates the physics and physical chemistry of ice surfaces relevant to polar stratospheric clouds. Surface concentrations of H2O, HCl, HOCl, ClONO2, and N2O5 on ice and nitric acid trihydrate (NAT) crystals are computed, and surface reaction rates and reaction probabilities (sticking coefficients) are determined. For gas pressures of about 10 exp -7 torr and temperatures in the range of 180-200 K, HCl completely coats ice and water-rich NAT surfaces, while HOCl, ClOHO2, and N2O5 may cover 0.01-1 percent of these surfaces. The energy parameters are used to calculate surface temperatures such as adsorption and desorption constants, surface coverages, reaction rate coefficients, surface diffusion coefficients, and reaction probabilities for various species and chemical interactions on ice and NAT surfaces. Implications for chemical processing on polar stratospheric clouds are discussed.

Tabazadeh, Azadeh↗
NASA NTRS2005

Adaptive Filtering Using Recurrent Neural Networks

A method for adaptive (or, optionally, nonadaptive) filtering has been developed for estimating the states of complex process systems (e.g., chemical plants, factories, or manufacturing processes at some level of abstraction) from time series of measurements of system inputs and outputs. The method is based partly on the fundamental principles of the Kalman filter and partly on the use of recurrent neural networks. The standard Kalman filter involves an assumption of linearity of the mathematical model used to describe a process system. The extended Kalman filter accommodates a nonlinear process model but still requires linearization about the state estimate. Both the standard and extended Kalman filters involve the often unrealistic assumption that process and measurement noise are zero-mean, Gaussian, and white. In contrast, the present method does not involve any assumptions of linearity of process models or of the nature of process noise; on the contrary, few (if any) assumptions are made about process models, noise models, or the parameters of such models. In this regard, the method can be characterized as one of nonlinear, nonparametric filtering. The method exploits the unique ability of neural networks to approximate nonlinear functions. In a given case, the process model is limited mainly by limitations of the approximation ability of the neural networks chosen for that case. Moreover, despite the lack of assumptions regarding process noise, the method yields minimum- variance filters. In that they do not require statistical models of noise, the neural- network-based state filters of this method are comparable to conventional nonlinear least-squares estimators.

Parlos, Alexander G.↗
NASA NTRS1999

A Process-based, Climate-Sensitive Model to Derive Methane Emissions from Natural Wetlands: Application to 5 Wetland Sites, Sensitivity to Model Parameters and Climate

Methane emissions from natural wetlands constitutes the largest methane source at present and depends highly on the climate. In order to investigate the response of methane emissions from natural wetlands to climate variations, a 1-dimensional process-based climate-sensitive model to derive methane emissions from natural wetlands is developed. In the model the processes leading to methane emission are simulated within a 1-dimensional soil column and the three different transport mechanisms diffusion, plant-mediated transport and ebullition are modeled explicitly. The model forcing consists of daily values of soil temperature, water table and Net Primary Productivity, and at permafrost sites the thaw depth is included. The methane model is tested using observational data obtained at 5 wetland sites located in North America, Europe and Central America, representing a large variety of environmental conditions. It can be shown that in most cases seasonal variations in methane emissions can be explained by the combined effect of changes in soil temperature and the position of the water table. Our results also show that a process-based approach is needed, because there is no simple relationship between these controlling factors and methane emissions that applies to a variety of wetland sites. The sensitivity of the model to the choice of key model parameters is tested and further sensitivity tests are performed to demonstrate how methane emissions from wetlands respond to climate variations.

Walter, Bernadette P.↗
NASA NTRS2004

Using explanatory crop models to develop simple tools for Advanced Life Support system studies

System-level analyses for Advanced Life Support require mathematical models for various processes, such as for biomass production and waste management, which would ideally be integrated into overall system models. Explanatory models (also referred to as mechanistic or process models) would provide the basis for a more robust system model, as these would be based on an understanding of specific processes. However, implementing such models at the system level may not always be practicable because of their complexity. For the area of biomass production, explanatory models were used to generate parameters and multivariable polynomial equations for basic models that are suitable for estimating the direction and magnitude of daily changes in canopy gas-exchange, harvest index, and production scheduling for both nominal and off-nominal growing conditions. c2004 COSPAR. Published by Elsevier Ltd. All rights reserved.

NASA Discipline Life Support Systems↗
NASA NTRS1993

Verification of a two-dimensional infiltration model for the resin transfer molding process

A two-dimensional finite element model for the infiltration of a dry textile preform by an injected resin was verified. The model, which is based on the finite element/control volume technique, determines the total infiltration time and the pressure increase at the mold inlet associated with the RTM process. Important input data for the model are the compaction and permeability behavior of the preform along with the kinetic and rheological behavior of the resin. The compaction behavior for several textile preforms was determined by experimental methods. A power law regression model was used to relate fiber volume fraction to the applied compaction pressure. Results showed a large increase in fiber volume fraction with the initial application of pressure. However, as the maximum fiber volume fraction was approached, the amount of compaction pressure required to decrease the porosity of the preform rapidly increased. Similarly, a power law regression model was used to relate permeability to the fiber volume fraction of the preform. Two methods were used to measure the permeability of the textile preform. The first, known as the steady state method, measures the permeability of a saturated preform under constant flow rate conditions. The second, denoted the advancing front method, determines the permeability of a dry preform to an infiltrating fluid. Water, corn oil, and an epoxy resin, Epon 815, were used to determine the effect of fluid type and viscosity on the steady state permeability behavior of the preform. Permeability values measured with the different fluids showed that fluid viscosity had no influence on the permeability behavior of 162 E-glass and TTI IM7/8HS preforms. Permeabilities measured from steady state and advancing front experiments for the warp direction of 162 E-glass fabric were similar. This behavior was noticed for tests conducted with corn oil and Epon 815. Comparable behavior was observed for the warp direction of the TTI IM7/8HS preform and corn oil. Mold filling and flow visualization experiments were performed to verify the analytical computer model. Frequency dependent electromagnetic sensors were used to monitor the resin flow front as a function of time. For the flow visualization tests, a video camera and high resolution tape recorder were used to record the experimental flow fronts. Comparisons between experimental and model predicted flow fronts agreed well for all tests. For the mold filling tests conducted at constant flow rate injection, the model was able to accurately predict the pressure increase at the mold inlet during the infiltration process. A kinetics model developed to predict the degree of cure as a function of time for the injected resin accurately calculated the increase in the degree of cure during the subsequent cure cycle.

Hammond, Vincent H.↗
NASA NTRS2018

Radiative Transfer Modeling of Phytoplankton Fluorescence Quenching Processes

We report the first radiative transfer model that is able to simulate phytoplankton fluorescence with both photo chemical and non-photo chemical quenching included. The fluorescence source term in the inelastic radiative transfer equation is proportional to both the quantum yield and scalar irradiance at excitation wavelengths. The photo chemical and non photo chemical quenching processes change the quantum yield based on the photosynthetic active radiation. A sensitivity study was performed to demonstrate the dependence of the fluorescence signal on chlorophyll a concentration, aerosol optical depths and solar zenith angles. This work enables us to better model the phytoplankton fluorescence, which can be used in the design of new space-based sensors that can provide sufficient sensitivity to detect the phytoplankton fluorescence signal. It could also lead to more accurate remote sensing algorithms for the study of phytoplankton physiology.

Inelastic scattering↗
NASA NTRS1978

Thermal control of low-pressure fractionation processes

Thermal models detailing the solidification paths for shallow basaltic magma chambers (both open and closed systems) were calculated using finite-difference techniques. The total solidification time for closed chambers are comparable to previously published calculations; however, the temperature-time paths are not. These paths are dependent on the phase relations and the crystallinity of the system, because both affect the manner in which the latent heat of crystallization is distributed. In open systems, where a chamber would be periodically replenished with additional parental liquid, calculations indicate that the possibility is strong that a steady-state temperature interval is achieved near a major phase boundary. In these cases it is straightforward to analyze fractionation models of the basaltic liquid evolution and their corresponding cumulate sequences. This steady thermal fractionating state can be invoked to explain large amounts of erupted basalts of similar composition over long time periods from the same volcanic center and some rhythmically layered basic cumulate sequences.

Usselman, T. M.↗
NASA NTRS1979

Solar potential inventory and modeling

Image processing procedures for calculating the energy that roof-mounted solar collectors can potentially supply in a metropolitan area are presented. Satellite multispectral imagery from which land cover types can be determined digitally was sampled in order to estimate the percentage of land area occupied by flat or south-facing roof tops in residential and commercial/industrial areas. Procedures were applied to the various power subdistricts of the western San Fernando valley of California, and it was found that on the average 120% of the existing power demand could be met if only half the useable rooftop area were utilized, amounting to 385 MW of peak power and indicating the applicability of solar cells to power generation in urban areas.

Angelici, G. L.↗
NASA NTRS2006

Effects of Vegetation and of Heat and Vapor Fluxes from Soil on Snowpack Evolution and Radiobrightness

The radiobrightness of a snowpack is strongly linked to the snow moisture content profile, to the point that the only operational inversion algorithms require dry snow. Forward dynamic models do not include the effects of freezing and thawing of the soil beneath the snowpack and the effect of vegetation within the snow or above the snow. To get a more realistic description of the evolution of the snowpack, we reported an addition to the Snow-Soil-Vegetation-Atmosphere- Transfer (SSVAT) model, wherein we coupled soil processes of the Land Surface Process (LSP) model with the snow model SNTHERM. In the near future we will be adding a radiobrightness prediction based on the modeled moisture, temperature and snow grain size profiles. The initial investigations with this SSVAT for a late winter and early spring snow pack indicate that soil processes warm the snowpack and the soil. Vapor diffusion needs to be considered whenever the ground is thawed. In the early spring, heat flow from the ground into a snow and a strong temperature gradient across the snow lead to thermal convection. The buried vegetation can be ignored for a late winter snow pack. The warmer surface snow temperature will affect radiobrightness since it is most sensitive to snow surface characteristics. Comparison to data shows that SSVAT provides a more realistic representation of the temperature and moisture profiles in the snowpack and its underlying soil than SNTHERM. The radiobrightness module will be optimized for the prediction of brightness when the snow is moist. The liquid water content of snow causes considerable absorption compared to dry snow, and so longer wavelengths are likely to be most revealing as to the state of a moist snowpack. For volumetric moisture contents below about 7% (the pendular regime), the water forms rings around the contact points between snow grains. Electrostatic modeling of these pendular rings shows that the absorption of these rings is significantly higher than a sphere of the same volume. The first implementation of the radiobrightness module will therefore be a simple radiative transfer model without scattering.

soil↗
NASA NTRS1974

Modeling and Analysis of Power Processing Systems

The feasibility of formulating a methodology for the modeling and analysis of aerospace electrical power processing systems is investigated. It is shown that a digital computer may be used in an interactive mode for the design, modeling, analysis, and comparison of power processing systems.

Fegley, K. A.↗
NASA NTRS1988

Determination of GPS orbits to submeter accuracy

Orbits for satellites of the Global Positioning System (GPS) were determined with submeter accuracy. Tests used to assess orbital accuracy include orbit comparisons from independent data sets, orbit prediction, ground baseline determination, and formal errors. One satellite tracked 8 hours each day shows rms error below 1 m even when predicted more than 3 days outside of a 1-week data arc. Differential tracking of the GPS satellites in high Earth orbit provides a powerful relative positioning capability, even when a relatively small continental U.S. fiducial tracking network is used with less than one-third of the full GPS constellation. To demonstrate this capability, baselines of up to 2000 km in North America were also determined with the GPS orbits. The 2000 km baselines show rms daily repeatability of 0.3 to 2 parts in 10 to the 8th power and agree with very long base interferometry (VLBI) solutions at the level of 1.5 parts in 10 to the 8th power. This GPS demonstration provides an opportunity to test different techniques for high-accuracy orbit determination for high Earth orbiters. The best GPS orbit strategies included data arcs of at least 1 week, process noise models for tropospheric fluctuations, estimation of GPS solar pressure coefficients, and combine processing of GPS carrier phase and pseudorange data. For data arc of 2 weeks, constrained process noise models for GPS dynamic parameters significantly improved the situation.

Bertiger, W. I.↗
NASA NTRS1999

Tropical Convection and Climate Processes in a Cumulus Ensemble Model

Local convective-radiative equilibrium states of the tropical atmosphere are determined by the following external forcing: 1) Insolation, 2) Surface heat and moisture exchanges (primarily radiation and evaporation), 3) Heating and moistening induced by large-scale circulation. Understanding the equilibrium states of the tropical atmosphere in different external forcing conditions is of vital importance for studying cumulus parameterization, climate feedbacks, and climate changes. We extend our previous study using the Goddard Cumulus Ensemble (GCE) Model which resolves convective-radiative processes more explicitly than global climate models do. Several experiments are carried out under fixed insolation and sea surface temperature. The prescribed SST consists of a uniform warm pool (29C) surrounded by uniform cold SST (26C). The model produces "Walker"-type circulation with the ascending branch of the model atmosphere more humid than the descending part, but the vertically integrated temperature does not show a horizontal gradient. The results are compared with satellite measured moisture by SSM/I (Special Sensor Microwave/Imager) and temperature by MSU in the ascending and descending tropical atmosphere. The vertically integrated temperature and humidity in the two model regimes are comparable to the observed values in the tropics.

Sui, Chung-Hsiung↗
NASA NTRS1986

Theory of electrophoretic separations. I - Formulation of a mathematical model

A generally applicable model of electrophoretic processes is presented. The model describes the chemical reactions, treating the chemical processes as reactions at equilibrium and accounting for convection, conservation, diffusion, and electromigration of individual species as well as the relation between charge and potential. Conservation relations are described and simplified, taking advantage of the speed of the chemical reactions as compared to the transport processes to adapt the model to the electrophoretic processes involving weak electrolytes. As an application example, isotachophoresis in a one-dimensional column is considered in detail.

Saville, D. A.↗