SEARCH · Engineering Papers

Results for “Average model”

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.

SourceResearch connectionFrom yearThrough year

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

At least 199 records · Page 11

All sources NASA NTRS DOE OSTI

NASA NTRS2001

Optimal firing rate estimation

We define a measure for evaluating the quality of a predictive model of the behavior of a spiking neuron. This measure, information gain per spike (Is), indicates how much more information is provided by the model than if the prediction were made by specifying the neuron's average firing rate over the same time period. We apply a maximum Is criterion to optimize the performance of Gaussian smoothing filters for estimating neural firing rates. With data from bullfrog vestibular semicircular canal neurons and data from simulated integrate-and-fire neurons, the optimal bandwidth for firing rate estimation is typically similar to the average firing rate. Precise timing and average rate models are limiting cases that perform poorly. We estimate that bullfrog semicircular canal sensory neurons transmit in the order of 1 bit of stimulus-related information per spike.

NASA Discipline Neuroscience↗

NASA NTRS1982

Regionally applicable angular reflectance models

Determination of the angular variation of the reflected radiance field in order to infer the reflected component of the Earth radiation budget from medium or narrow field of view radiometer measurements is discussed. An average angular model applicable at 250 to 1000 km is presented and evaluated. The nature of the convergence of the radiance patterns to the regional means is also discussed. Radiances measured during summer Monex 1979, from Hudson Bay to Saudi Arabia, were averaged and then normalized by multiplying by pi and dividing by the scene-averaged reflected flux density. This casts the model into the inverse of the bidirectional reflectance normalization coefficient, which has the value of unity for an isotropic surface. The reflected component of the Earth's radiation budget is inferred to an accuracy of about 2.5%.

Davis, J. M.↗

NASA NTRS1979

A semi-analytic theory for the motion of a close-earth artificial satellite with drag

A semi-analytic method is used to estimate the decay history/lifetime and to generate orbital ephemeris for close-earth satellites perturbed by the atmospheric drag and earth oblateness due to the spherical harmonics J2, J3, and J4. The theory maintains efficiency through the application of the theory of a method of averaging and employs sufficient numerical emphasis to include a rather sophisticated atmospheric density model. The averaged drag effects with respect to mean anomaly are evaluated by a Gauss-Legendre quadrature while the averaged variational equations of motion are integrated numerically with automatic step size and error control.

Liu, J. J. F.↗

NASA NTRS1992

Issues related to waveform computations for radar altimeter applications

An algorithm has been developed to model the average return power waveforms available from general radar altimeter systems, such as the Multimode Airborne Radar Altimeter (MARA) system operated at NASA Goddard Space Flight Center - Wallops Flight Facility. The algorithm is based on a convolutional model comprised of three functions: the average flat surface impulse response (FSIR), the radar system point target response (PTR), and the height pdf of the specular points on the sea surface. The FSIR is modified to account for the asymmetric antenna beam used by the MARA system, and then certain properties of this modified SIR are exploited to obtain closed-form expressions that can be rapidly evaluated. An FFT convolution routine is used to further speed up the computations. The result is an algorithm that can be used to study the effects of pointing errors in surface measurements.

Newkirk, Michael H.↗

NASA NTRS1994

Three dimensional model calculations of the global dispersion of high speed aircraft exhaust and implications for stratospheric ozone loss

Two-dimensional (zonally averaged) photochemical models are commonly used for calculations of ozone changes due to various perturbations. These include calculating the ozone change expected as a result of change in the lower stratospheric composition due to the exhaust of a fleet of supersonic aircraft flying in the lower stratosphere. However, zonal asymmetries are anticipated to be important to this sort of calculation. The aircraft are expected to be restricted from flying over land at supersonic speed due to sonic booms, thus the pollutant source will not be zonally symmetric. There is loss of pollutant through stratosphere/troposphere exchange, but these processes are spatially and temporally inhomogeneous. Asymmetry in the pollutant distribution contributes to the uncertainty in the ozone changes calculated with two dimensional models. Pollutant distributions for integrations of at least 1 year of continuous pollutant emissions along flight corridors are calculated using a three dimensional chemistry and transport model. These distributions indicate the importance of asymmetry in the pollutant distributions to evaluation of the impact of stratospheric aircraft on ozone. The implications of such pollutant asymmetries to assessment calculations are discussed, considering both homogeneous and heterogeneous reactions.

Douglass, Anne R.↗

NASA NTRS1985

A model for closing the inviscid form of the average-passage equation system

A mathematical model is proposed for closing or mathematically completing the system of equations which describes the time average flow field through the blade passages of multistage turbomachinery. These equations referred to as the average passage equation system govern a conceptual model which has proven useful in turbomachinery aerodynamic design and analysis. The closure model is developed so as to insure a consistency between these equations and the axisymmetric through flow equations. The closure model was incorporated into a computer code for use in simulating the flow field about a high speed counter rotating propeller and a high speed fan stage. Results from these simulations are presented.

Adamczyk, J. J.↗

NASA NTRS1986

A model for closing the inviscid form of the average-passage equation system

Adamczyk, J. J.↗

NASA NTRS1997

Linear and nonlinear ARMA model parameter estimation using an artificial neural network

This paper addresses parametric system identification of linear and nonlinear dynamic systems by analysis of the input and output signals. Specifically, we investigate the relationship between estimation of the system using a feedforward neural network model and estimation of the system by use of linear and nonlinear autoregressive moving-average (ARMA) models. By utilizing a neural network model incorporating a polynomial activation function, we show the equivalence of the artificial neural network to the linear and nonlinear ARMA models. We compare the parameterization of the estimated system using the neural network and ARMA approaches by utilizing data generated by means of computer simulations. Specifically, we show that the parameters of a simulated ARMA system can be obtained from the neural network analysis of the simulated data or by conventional least squares ARMA analysis. The feasibility of applying neural networks with polynomial activation functions to the analysis of experimental data is explored by application to measurements of heart rate (HR) and instantaneous lung volume (ILV) fluctuations.

NASA Discipline Regulatory Physiology↗

NASA NTRS1989

Research in LMSS propagation

The Virginia Tech Satellite Communications Group has participated in the Land Mobile Satellite System (LMSS) program through JPL sponsorship since 1985. Involvement has mainly been in modeling and simulation of propagation characteristics and effects. Models developed to predict cummulative fade distributions for fading LMSS signals include LMSSMOD and the Simple Models which approximate LMSSMOD. Models to predict the mean and standard deviation of signal attenuation through roadside vegetation, namely the Average Path Model, were developed. In the area of simulation, efforts have centered around the development of a software simulator that uses data bases derived from experimental data to generate simulated data with arbitrary statistical behavior. This work has progressed to the development of an integrated analysis and simulation package, LIPS. The basic theory and results for the models and simulator have been previously documented in reports and papers. All LMSS activities are summarized and details of this year's efforts are given.

Barts, R. M.↗

NASA NTRS2017

Quantifying the Causes of Differences in Tropospheric OH Within Global Models

The hydroxyl radical (OH) is the primary daytime oxidant in the troposphere and provides the main loss mechanism for many pollutants and greenhouse gases, including methane (CH4). Global mean tropospheric OH differs by as much as 80% among various global models, for reasons that are not well understood. We use neural networks (NNs), trained using archived output from eight chemical transport models (CTMs) that participated in the Polar Study using Aircraft, Remote Sensing, Surface Measurements and Models, of Climate, Chemistry, Aerosols and Transport Model Intercomparison Project (POLMIP), to quantify the factors responsible for differences in tropospheric OH and resulting CH4 lifetime (Tau CH4) between these models. Annual average Tau CH4, for loss by OH only, ranges from 8.0 to 11.6 years for the eight POLMIP CTMs. The factors driving these differences were quantified by inputting 3-D chemical fields from one CTM into the trained NN of another CTM. Across all CTMs, the largest mean differences in Tau CH4 (Delta Tau CH4) result from variations in chemical mechanisms (Delta Tau CH4 = 0.46 years), the photolysis frequency (J) of O3 yields O(D-1) (0.31 years), local O3 (0.30 years), and CO (0.23 years). The Delta Tau CH4 due to CTM differences in NO(x) (NO + NO2) is relatively low (0.17 years), although large regional variation in OH between the CTMs is attributed to NO(x). Differences in isoprene and J(NO2) have negligible overall effect on globally averaged tropospheric OH, although the extent of OH variations due to each factor depends on the model being examined. This study demonstrates that NNs can serve as a useful tool for quantifying why tropospheric OH varies between global models, provided that essential chemical fields are archived.

Surface Measurements and Models↗

NASA NTRSDate not supplied

Medium-Range River Flood Forecasts Using a Long Short-Term Memory Network

River flooding and the impacts are a concern for decision makers throughout the United States. Accurate medium-range forecasts (~3-7 days) are critical for providing advanced outlooks to emergency management officials. Unfortunately, accurately forecasting rainfall-runoff and the subsequent rise and fall within rivers remain a challenge in hydrological modeling. While complex physical modeling systems are the standard for representing the hydrological processes, they are computationally demanding and can require extensive calibration. Further, uncertainties remain in the model parameters and input data. The use of machine learning can reduce some of the computational demand while maintaining high accuracy. Therefore, this project makes use of a Long Short-Term Memory (LSTM) network which explicitly accounts for the time-dependent nature of rainfall-runoff modeling. The developed LSTM was trained to predict river gauge height, or stage height, based on time-lagged input features which include: gauge height to initialize the model, the NASA Short-term Prediction Research and Transition Center’s instance of the Land Information System (SPoRT-LIS) relative soil moisture to describe the rainfall infiltration rate, and 6-hr Multi-Radar Multi-Sensor quantitative precipitation estimate (MRMS QPE). The developed LSTM based system is then used to produce 7-day forecasts with a 6-hr temporal resolution using three different quantitative precipitation forecasts (QPF) from the NWS’s Weather Prediction Center (WPC), the NCEP Global Forecast System (GFS) model and the National Blend of Models (NBM). This trained modeling system has been implemented as an experimental product at over 100 different rivers in collaboration with at multiple National Weather Service (NWS) Forecast Offices and River Forecast Centers (RFC) across the eastern half of the United States. The developed LSTM model achieved average Nash-Sutcliffe efficiency (NSE) 0.89 higher than the equivalent medium-range National Water Model ensemble member forecast over a 7-day forecast. In addition to the initial development and evaluation, this project has continued to expand. While the initial model was developed for precipitation dominated basins, expansion of the project has taken it to basins effected by snow melt. This presentation will provide an overview of the project with focus on recent developments on incorporating snow melt processes into the model.

Andrew T. White↗

NASA NTRS2009

Exploring Modeling Options and Conversion of Average Response to Appropriate Vibration Envelopes for a Typical Cylindrical Vehicle Panel with Rib-stiffened Design

Although applications for Statistical Energy Analysis (SEA) techniques are more widely used in the aerospace industry today, opportunities to anchor the response predictions using measured data from a flight-like launch vehicle structure are still quite valuable. Response and excitation data from a ground acoustic test at the Marshall Space Flight Center permitted the authors to compare and evaluate several modeling techniques available in the SEA module of the commercial code VA One. This paper provides an example of vibration response estimates developed using different modeling approaches to both approximate and bound the response of a flight-like vehicle panel. Since both vibration response and acoustic levels near the panel were available from the ground test, the evaluation provided an opportunity to learn how well the different modeling options can match band-averaged spectra developed from the test data. Additional work was performed to understand the spatial averaging of the measurements across the panel from measured data. Finally an evaluation/comparison of two conversion approaches from the statistical average response results that are output from an SEA analysis to a more useful envelope of response spectra appropriate to specify design and test vibration levels for a new vehicle.

Harrison, Phil↗

NASA NTRS2007

Parametric Study of Flow Control Over a Hump Model Using an Unsteady Reynolds- Averaged Navier-Stokes Code

This is an expanded version of a limited-length paper that appeared at the 5th International Symposium on Turbulence and Shear Flow Phenomena by the same authors. A computational study was performed for steady and oscillatory flow control over a hump model with flow separation to assess how well the steady and unsteady Reynolds-averaged Navier-Stokes equations predict trends due to Reynolds number, control magnitude, and control frequency. As demonstrated in earlier studies, the hump model case is useful because it clearly demonstrates a failing in all known turbulence models: they under-predict the turbulent shear stress in the separated region and consequently reattachment occurs too far downstream. In spite of this known failing, three different turbulence models were employed to determine if trends can be captured even though absolute levels are not. Overall the three turbulence models showed very similar trends as experiment for steady suction, but only agreed qualitatively with some of the trends for oscillatory control.

Rumsey, Christopher L.↗

NASA NTRS1984

Postprocessing for the UCLA climate model

Postprocessing programs written to analyze the results of a general circulation model are described. The model history data is interpolated to pressure surfaces, converted from 64-bit Cyber words to 32 bit IBM words, and transferred to tape for further analysis. The time average program reads the interpolation output tape and produces 15-day time averages. The model outputs a very detailed record for selected grid points. This data is sent to a tape in Cyber full words. The conversion program changes the format of the tape from 64 bit Cyber words to 32 bit IBM words, processing a month of data at a time. The grid-point history sorting program inputs the converted grid point history tape and sorts it by time. The end product is a tape with a time history of each field for every point. After the PBP data has been stored, it can be plotted. The plotting package is flexible, and allows the choice of fields and grid points. The one-dimensional fields are plotted as functions of time, and a daily summary is also produced. For the two-dimensional fields, time-height cross sections and daily summaries are produced. The model plotting package produces plots for all fields on the time average and pressure tapes. These plots include world maps, polar projections, zonal means, vectors, streamlines, and latitude-height plots.

Abeles, J.↗

NASA NTRS1991

Simulation of the present-day atmospheric ozone, odd nitrogen, chlorine and other species using a coupled 2-D model in isentropic coordinates

A zonally averaged two-dimensional model for chemical species in the atmosphere (Olaguer et al., 1990), with coupled dynamics, radiation transfer, and chemistry, is used to study the present-day atmospheric ozone, odd nitrogen, chlorine, other species. The model utilizes all zonally averaged physical equations of momentum, energy, and mass and determines self-consistently the advective and diffusive tranasport parameters from the temperature specific to the period of observation. A comparison of the model results with observations showed good agreement.

Yang, H.↗

NASA NTRS1999

Applications of amorphous track models in radiation biology

The average or amorphous track model uses the response of a system to gamma-rays and the radial distribution of dose about an ion's path to describe survival and other cellular endpoints from proton, heavy ion, and neutron irradiation. This model has been used for over 30 years to successfully fit many radiobiology data sets. We review several extensions of this approach that address objections to the original model, and consider applications of interest in radiobiology and space radiation risk assessment. In the light of present views of important cellular targets, the role of target size as manifested through the relative contributions from ion-kill (intra-track) and gamma-kill (inter-track) remains a critical question in understanding the success of the amorphous track model. Several variations of the amorphous model are discussed, including ones that consider the radial distribution of event-sizes rather than average electron dose, damage clusters rather than multiple targets, and a role for repair or damage processing.

NASA Discipline Radiation Health↗

NASA NTRS1995

Error modeling for differential GPS

Differential Global Positioning System (DGPS) positioning is used to accurately locate a GPS receiver based upon the well-known position of a reference site. In utilizing this technique, several error sources contribute to position inaccuracy. This thesis investigates the error in DGPS operation and attempts to develop a statistical model for the behavior of this error. The model for DGPS error is developed using GPS data collected by Draper Laboratory. The Marquardt method for nonlinear curve-fitting is used to find the parameters of a first order Markov process that models the average errors from the collected data. The results show that a first order Markov process can be used to model the DGPS error as a function of baseline distance and time delay. The model's time correlation constant is 3847.1 seconds (1.07 hours) for the mean square error. The distance correlation constant is 122.8 kilometers. The total process variance for the DGPS model is 3.73 sq meters.

Blerman, Gregory S.↗

NASA NTRS2013

Stratospheric Ozone Response in Experiments G3 and G4 of the Geoengineering Model Intercomparison Project (GeoMIP)

Geoengineering with stratospheric sulfate aerosols has been proposed as a means of temporarily cooling the planet, alleviating some of the side effects of anthropogenic CO2 emissions. However, one of the known side effects of stratospheric injections of sulfate aerosols is a decrease in stratospheric ozone. Here we show results from two general circulation models and two coupled chemistry climate models that have simulated stratospheric sulfate aerosol geoengineering as part of the Geoengineering Model Intercomparison Project (GeoMIP). Changes in photolysis rates and upwelling of ozone-poor air in the tropics reduce stratospheric ozone, suppression of the NOx cycle increases stratospheric ozone, and an increase in available surfaces for heterogeneous chemistry modulates reductions in ozone. On average, the models show a factor 20-40 increase of the sulfate aerosol surface area density (SAD) at 50 hPa in the tropics with respect to unperturbed background conditions and a factor 3-10 increase at mid-high latitudes. The net effect for a tropical injection rate of 5 Tg SO2 per year is a decrease in globally averaged ozone by 1.1-2.1 DU in the years 2040-2050 for three models which include heterogeneous chemistry on the sulfate aerosol surfaces. GISS-E2-R, a fully coupled general circulation model, performed simulations with no heterogeneous chemistry and a smaller aerosol size; it showed a decrease in ozone by 9.7 DU. After the year 2050, suppression of the NOx cycle becomes more important than destruction of ozone by ClOx, causing an increase in total stratospheric ozone. Contribution of ozone changes in this experiment to radiative forcing is 0.23 W m-2 in GISS-E2-R and less than 0.1 W m-2 in the other three models. Polar ozone depletion, due to enhanced formation of both sulfate aerosol SAD and polar stratospheric clouds, results in an average 5 percent increase in calculated surface UV-B.

aerosol↗