THE EFFECTS OF NOISE THROUGH AN ANALOG INTEGRATOR WHICH INTEGRATES WITH RESPECT TO AN ARBITRARY VARIABLE
Effects of noise through analog integrator which integrates with respect to arbitrary variable
RANDOM NOISE↗
SEARCH · Engineering Papers
Results for “Random variables”
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.
The state-variable approach to continuous estimation with applications to analog communication theory
Monograph on state variable approach to continuous estimation of random processes with applications to analog communication theory
Snyder, D. L.↗
A guidance and navigation system for continuous low-thrust vehicles
A midcourse guidance and navigation system for continuous low thrust vehicles was developed. The equinoctial elements are the state variables. Uncertainties are modelled statistically by random vector and stochastic processes. The motion of the vehicle and the measurements are described by nonlinear stochastic differential and difference equations respectively. A minimum time trajectory is defined; equations of motion and measurements are linearized about this trajectory. An exponential cost criterion is constructed and a linear feedback quidance law is derived. An extended Kalman filter is used for state estimation. A short mission using this system is simulated. It is indicated that this system is efficient for short missions, but longer missions require accurate trajectory and ground based measurements.
Jack-Chingtse, C.↗
Studies of coastal mesoscale winds using SIR-B
The variability of the mesoscale wind fields near coastlines which can be caused by mountains that shadow offshore wind and by valleys that enhance them. These wind, provide relatively fixed patterns that must be considered in the development of algorithms for future spaceborne scatterometer systems; mesoscale variability over the offshore regions is random and must be averaged out for forecasting yet nearshore fixed patterns are treated differently. Before the patterns of interest can be defined quantitatively, the scattering response of the ocean to winds at the L-band frequency and SIR-B angles of incidence must be developed from the SIR-B data. Patterns can be analyzed on the images both in regions selected for high probability of the occurrence of suitable patterns, and in other regions where the patterns are observed. The patterns are analyzed for topographic effects and the distance to sea over which these effects cause variations in the oceanic wind patterns. The results are interpreted in terms of quantitative description of the processes involved and in for need of modifications of future scatterometer algorithms.
Moore, R. K.↗
Computations of turbulent evaporating sprays
A computational study of turbulent evaporating sprays is reported. The major focus is to examine the sensitivity of the vaporization behavior of turbulent sprays to the transient liquid-phase processes. Three models considered to represent these processes are the thin skin, infinite diffusion, and diffusion limit models. Favre-averaged equations with k-epsilon-g turbulence model are employed for the gas phase. The Lagrangian approach with a stochastic separated flow method is used for the liquid phase where the effects of gas turbulence on droplet trajectories and interphase transport rates are considered using random-walk computations. Also the variable-property effects are considered in detail. Results indicate that, depending upon the boiling temperature and heat of vaporization of the fuel considered, the vaporization behavior of turbulent sprays may be quite sensitive to the modeling of transient liquid-phase processes. Thus, it is important that for most hydrocarbon fuels these processes be adequately represented in any comprehensive spray computations. The present results also provide further support to the conclusions of earlier studies which have been based on simplified spray configurations.
Aggarwal, S. K.↗
Volatile/mobile trace elements in Bholghati howardite
Ag, Au, Bi, Cd, Co, Cs, Ga, In, Rb, Sb, Se, Te, Tl, U, and Zn by RNAA are determined in two kinds of material from the Bholghati howardite: a carbonaceous chondrite clast (BH-4) that originated by primary nebular condensation/accretion processes; whole-rock samples and clasts resulting from parent-body processes, especially igneous differentiation. Trace element contents in Bholghati whole-rock (matrix) samples and/or white eucritic clasts in it are high for an achondrite, and variable. These characteristics are indicative of random condensation of volcanic emanations admixed with preexisting eucrite, diogenite, and howardite layers in the HED parent body. Other HED samples show similar patterns, and the conclusion that these reflect extensive volcanism in an asteroidal-sized object is supported by other Consortium noble gas and cosmochronologic measurements.
Wang, Ming-Sheng↗
Employing Sensitivity Derivatives for Robust Optimization under Uncertainty in CFD
A robust optimization is demonstrated on a two-dimensional inviscid airfoil problem in subsonic flow. Given uncertainties in statistically independent, random, normally distributed flow parameters (input variables), an approximate first-order statistical moment method is employed to represent the Computational Fluid Dynamics (CFD) code outputs as expected values with variances. These output quantities are used to form the objective function and constraints. The constraints are cast in probabilistic terms; that is, the probability that a constraint is satisfied is greater than or equal to some desired target probability. Gradient-based robust optimization of this stochastic problem is accomplished through use of both first and second-order sensitivity derivatives. For each robust optimization, the effect of increasing both input standard deviations and target probability of constraint satisfaction are demonstrated. This method provides a means for incorporating uncertainty when considering small deviations from input mean values.
Newman, Perry A.↗
Employing Sensitivity Derivatives to Estimate Uncertainty Propagation in CFD
Two methods that exploit the availability of sensitivity derivatives are successfully employed to predict uncertainty propagation through Computational Fluid Dynamics (CFD) code for an inviscid airfoil problem. An approximate statistical second-moment method and a Sensitivity Derivative Enhanced Monte Carlo (SDEMC) method are successfully demonstrated on a two-dimensional problem. First- and second-order sensitivity derivatives of code output with respect to code input are obtained through an efficient incremental iterative approach. Given uncertainties in statistically independent, random, normally distributed flow parameters (input variables); these sensitivity derivatives enable one to formulate first- and second-order Taylor Series approximations for the mean and variance of CFD output quantities. Additionally, incorporation of the first-order sensitivity derivatives into the data reduction phase of a conventional Monte Carlo (MC) simulation allows for improved accuracy in determining the first moment of the CFD output. Both methods are compared to results generated using a conventional MC method. The methods that exploit the availability of sensitivity derivatives are found to be valid when considering small deviations from input mean values.
Putko, Michele M.↗
Method for Measuring Collimator-Pointing Sensitivity to Temperature Changes
For a variety of applications, it is important to measure the sensitivity of the pointing of a beam emerging from a collimator, as a function of temperature changes. A straightforward method for carrying out this measurement is based on using interferometry for monitoring the changes in beam pointing, which presents its own problems. The added temperature dependence and complexity issues relating to using an interferometer are addressed by not using an interferometer in the first place. Instead, the collimator is made part of an arrangement that uses a minimum number of low-cost, off-the-shelf materials and by using a quad diode to measure changes in beam pointing. In order to minimize the influence of the test arrangement on the outcome of the measurement, several steps are taken. The collimator assembly is placed on top of a vertical, 1-m-long, fused silica tube. The quad diode is bonded to a fused silica bar, which, in turn, is bonded to the lower end of the fused silica tube. The lower end of the tube rests on a self-aligning support piece, while the upper end of the tube is kept against two rounded setscrew tips, using a soft rubber string. This ensures that very little stress is applied to the tube as the support structure changes dimensions due to thermal expansion. Light is delivered to the collimator through a bare fiber in order to minimize variable bending torque caused by a randomly relaxing, rigid fiber jacket. In order to separate the effect of temperature on the collimator assembly from the effect temperature has on the rest of the setup, multiple measurements are taken with the collimator assembly rotated from measurement to measurement. Laboratory testing, with 1-m spacing between the collimator and the quad diode, has shown that the sensitivity of the arrangement is better than 100 nm rms, over time spans of at least one hour, if the beam path is protected from atmospheric turbulence by a tube. The equivalent sensitivity to detecting changes in pointing angle is 100 nanoradians.
Abramovici, Alex↗
Predicting Antarctic Net Snow Accumulation at the Kilometer Scale and Its Impact on Observed Height Changes
Sub-grid-scale processes occurring at or near the surface of an ice sheet have a potentially large impact on local and integrated net accumulation of snow via redistribution and sublimation. Given observational complexity, they are either ignored or parameterized over large-length scales. Here, we train random forest (RF) models to predict variability in net accumulation over the Antarctic Ice Sheet using atmospheric variables and topographic characteristics as predictors at 1 km resolution. Observations of net snow accumulation from both in situ and airborne radar data provide the input observable targets needed to train the RF models. We find that local net accumulation deviates by as much as 172% of the atmospheric model mean. The correlation in space between the predicted net accumulation variability and satellite-derived surface-height change indicates that surface processes operate differently through time, driven largely by the seasonal anomalies in snow accumulation.
Antarctic↗
Statistical error analysis in CCD time-resolved photometry with applications to variable stars and quasars
Differential photometric time series obtained from CCD frames are tested for intrinsic variability using a newly developed analysis of variance technique. In general, the objects used for differential photometry will not all be of equal magnitude, so the techniques derived here explicitly correct for differences in the measured variances due to photon statistics. Other random-noise terms are also considered. The technique tests for the presence of intrinsic variability without regard to its random or periodic nature. It is then applied to observations of the variable stars ZZ Ceti and US 943 and the active extragalactic objects OQ 530, US 211, US 844, LB 9743, and OJ 287.
Howell, Steve B.↗
Powder River Basin Water Resources: Mapping Russian Olive in the Powder River Basin to Inform Invasive Species Management
Since its introduction in the late 1800s, Elaeagnus augustifolia (Russian olive) has become a widespread invasive shrub that poses a threat to native riparian species in the United States by competing with native riparian plants for space and resources. To date, limited information on the distribution of Russian olive in the Powder River Basin of Montana and Wyoming have hampered management efforts and decision making. Here, we detect and model the distribution of Russian Olive using field surveys, ocular sampling, and variables from Landsat 8 Operational Land Imager (OLI), Sentinel-2 MultiSpectral Instrument (MSI), and Shuttle Radar Topography Mission (SRTM) using the Random Forest algorithm. We derived topographic, spectral, and hydrological variables from Landsat 8 OLI, Sentinel-2 MSI, and SRTM to utilize as model inputs. The team was able to successfully create a spectral Russian olive detection map for the Powder River Basin (RMSE =15.44%, R2 = 0.6482). The team also examined change in stream channel geomorphology from 1984-2020 in a time-series analysis using Landsat visible imagery and the RivMap MATLAB package and found little change. Our results will help our partners at the Powder River County Weed Board, Gay Ranch, United States Geological Survey, and University of Northern Colorado to locate and prioritize areas for riparian habitat restoration and to understand the region’s hydrology and geomorphology.
Catherine Buczek↗
Computational simulation of coupled material degradation processes for probabilistic lifetime strength of aerospace materials
The research included ongoing development of methodology that provides probabilistic lifetime strength of aerospace materials via computational simulation. A probabilistic material strength degradation model, in the form of a randomized multifactor interaction equation, is postulated for strength degradation of structural components of aerospace propulsion systems subjected to a number of effects or primative variables. These primative variable may include high temperature, fatigue or creep. In most cases, strength is reduced as a result of the action of a variable. This multifactor interaction strength degradation equation has been randomized and is included in the computer program, PROMISS. Also included in the research is the development of methodology to calibrate the above described constitutive equation using actual experimental materials data together with linear regression of that data, thereby predicting values for the empirical material constraints for each effect or primative variable. This regression methodology is included in the computer program, PROMISC. Actual experimental materials data were obtained from the open literature for materials typically of interest to those studying aerospace propulsion system components. Material data for Inconel 718 was analyzed using the developed methodology.
Boyce, Lola↗
Computational simulation of probabilistic lifetime strength for aerospace materials subjected to high temperature, mechanical fatigue, creep and thermal fatigue
This report presents the results of a fourth year effort of a research program, conducted for NASA-LeRC by the University of Texas at San Antonio (UTSA). The research included on-going development of methodology that provides probabilistic lifetime strength of aerospace materials via computational simulation. A probabilistic material strength degradation model, in the form of a randomized multifactor interaction equation, is postulated for strength degradation of structural components of aerospace propulsion systems subject to a number of effects or primitive variables. These primitive variables may include high temperature, fatigue or creep. In most cases, strength is reduced as a result of the action of a variable. This multifactor interaction strength degradation equation has been randomized and is included in the computer program, PROMISS. Also included in the research is the development of methodology to calibrate the above-described constitutive equation using actual experimental materials data together with regression analysis of that data, thereby predicting values for the empirical material constants for each effect or primitive variable. This regression methodology is included in the computer program, PROMISC. Actual experimental materials data were obtained from industry and the open literature for materials typically for applications in aerospace propulsion system components. Material data for Inconel 718 has been analyzed using the developed methodology.
Boyce, Lola↗
Image discrimination models predict detection in fixed but not random noise
By means of a two-interval forced-choice procedure, contrast detection thresholds for an aircraft positioned on a simulated airport runway scene were measured with fixed and random white-noise masks. The term fixed noise refers to a constant, or unchanging, noise pattern for each stimulus presentation. The random noise was either the same or different in the two intervals. Contrary to simple image discrimination model predictions, the same random noise condition produced greater masking than the fixed noise. This suggests that observers seem unable to hold a new noisy image for comparison. Also, performance appeared limited by internal process variability rather than by external noise variability, since similar masking was obtained for both random noise types.
NASA Center ARC↗
Quantifying Effects of Voids in Woven Ceramic Matrix Composites
Randomness in woven ceramic matrix composite architecture has been found to cause large variability in stiffness and strength. The inherent voids are an aspect of the architecture that may cause a significant portion of the variability. A study is undertaken to investigate the effects of many voids of random sizes and distributions. Response surface approximations were formulated based on void parameters such as area and length fractions to provide an estimate of the effective stiffness. Obtaining quantitative relationships between the properties of the voids and their effects on stiffness of ceramic matrix composites are of ultimate interest, but the exploratory study presented here starts by first modeling the effects of voids on an isotropic material. Several cases with varying void parameters were modeled which resulted in a large amount of variability of the transverse stiffness and out-of-plane shear stiffness. An investigation into a physical explanation for the stiffness degradation led to the observation that the voids need to be treated as an entity that reduces load bearing capabilities in a space larger than what the void directly occupies through a corrected length fraction or area fraction. This provides explanation as to why void volume fraction is not the only important factor to consider when computing loss of stiffness.
Goldsmith, Marlana B.↗
Computation of Variability in the Average Thermal and Mechanical Properties of a Melt-infiltrated Sic/sic Composite
Thermal conductivity and tensile properties (elastic modulus, proportional limit strength, inplane tensile strength, and strain to failure) of a SiC/SiC composite were experimentally determined at 816 and 1204 C. Tests were performed at room temperature on the same material to obtain interlaminar shear and tensile strength. For each thermal and mechanical property 24 tests were conducted to capture the variation. A random sampling method was used to quantify the variability exhibited by the mean values of the thermal and mechanical properties. The minimum number of tests required to characterize the mean value of each thermal or mechanical property for the composite was determined by varying the group size of the random sample.
Kalluri, Sreeramesh↗
On-line methods for rotorcraft aeroelastic mode identification
The requirements for the on-line identification of rotorcraft aeroelastic blade modes from random response test data are presented. A recursive maximum likelihood (RML) technique is used in conjunction with a bandpass filter to identify isolated blade mode damping and frequency. The RML technique is demonstrated to have excellent convergence characteristics in random measurement noise and random process noise excitation. The RML identification technique uses an ARMA representation for the aeroelastic stochastic system and requires virtually no user interaction while providing accurate confidence bands on the parameter estimates. Comparisons are made with an off-line Newton type maximum likelihood algorithm which uses a state variable model representation. Results are presented from simulation random response data which quantify the identifed parameter convergence behavior for various levels of random excitation which is typical of wind tunnel turbulence levels. The RML technique is applied to hingless rotor test data from the NASA Langley Research Center Helicopter Hover Facility.
Molusis, J. A.↗