Search NASA⌕ Search

SEARCH · Search NASA

Results for “random 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 235 records · Page 13

Direct Simulation of Multiple Scattering by Discrete Random Media Illuminated by Gaussian Beams

The conventional orientation-averaging procedure developed in the framework of the superposition T-matrix approach is generalized to include the case of illumination by a Gaussian beam (GB). The resulting computer code is parallelized and used to perform extensive numerically exact calculations of electromagnetic scattering by volumes of discrete random medium consisting of monodisperse spherical particles. The size parameters of the scattering volumes are 40, 50, and 60, while their packing density is fixed at 5%. We demonstrate that all scattering patterns observed in the far-field zone of a random multisphere target and their evolution with decreasing width of the incident GB can be interpreted in terms of idealized theoretical concepts such as forward-scattering interference, coherent backscattering (CB), and diffuse multiple scattering. It is shown that the increasing violation of electromagnetic reciprocity with decreasing GB width suppresses and eventually eradicates all observable manifestations of CB. This result supplements the previous demonstration of the effects of broken reciprocity in the case of magneto-optically active particles subjected to an external magnetic field.

Mackowski, Daniel W.↗

Assessment of Bulk Absorber Properties for Multi-Layer Perforates in Porous Honeycomb Liners

CONTINUING progress in materials technology provides potential for improved acoustic liners for attenuating broadband fan noise emissions from aircraft engine nacelles. Conventional liners (local-reacting perforate-over-honeycomb structures) provide significant narrow-band attenuation, but limited attenuation over wide bandwidths. Two approaches for increasing attenuation bandwidth are to (1) replace the honeycomb structure with bulk material, or (2) cascade multiple layers of perforate/honeycomb structures. Usage of the first approach is limited because of mechanical and maintenance reasons, while multi-layer liners are limited to about three layers because of their additional mechanical complexity, depth and weight. The current research concerns a novel approach reported by the University of Cincinnati, in which a single-layer conventional liner is converted into an extended-reaction, broadband absorber by making the honeycomb core structure porous. This modified single-layer liner requires no increase in depth and weight, and minimal increase in mechanical complexity. Langley has initiated research to identify potential benefits of liner structures with porous cell walls. This research has two complementary goals: (1) develop and validate experimental techniques for treating multi-layer perforates (representative of the internal cells of a liner with porous cell walls) as 1-D bulk materials, and (2) develop analytical approaches to validate this bulk material assumption. If successful, the resultant model can then be used to design optimized porous honeycomb liners. The feasibility of treating an N-layer perforate system (N porous plates separated by uniform air gaps) as a one-dimensional bulk absorber is assessed using the Two-Thickness Method (TTM), which is commonly used to educe bulk material intrinsic acoustic parameters. Tests are conducted with discrete tone and random noise sources, over an SPL range sufficient to determine the nonlinearity of the test specimens, for test specimens consisting of 5, 10 and 15% porous plates. Measured impedances for two liner thicknesses (e.g., 12 and 24 layers) are used as input to the TTM to determine the characteristic impedance and propagation constant that characterize these liners as bulk absorbers. These parameters are then used to calculate the predicted impedance of liners with different thicknesses (e.g., 36 layers), and a comparison of predicted and measured impedances for these other thicknesses is used to determine the efficacy of this approach. Finally, an independent method is used to educe the propagation constant for a single representative sample, and excellent comparison between the results for this method and those for the TTM provides increased confidence in the results achieved with the TTM. In general, the results demonstrate these multi-layer perforates can be acceptably treated as bulk absorbers.

Jones, Michael G.↗

Numerically Exact Computer Simulations of Light Scattering by Densely Packed, Random Particulate Media

Direct computer simulations of electromagnetic scattering by discrete random media have become an active area of research. In this progress review, we summarize and analyze our main results obtained by means of numerically exact computer solutions of the macroscopic Maxwell equations. We consider finite scattering volumes with size parameters in the range, composed of varying numbers of randomly distributed particles with different refractive indices. The main objective of our analysis is to examine whether all backscattering effects predicted by the low-density theory of coherent backscattering (CB) also take place in the case of densely packed media. Based on our extensive numerical data we arrive at the following conclusions: (i) all backscattering effects predicted by the asymptotic theory of CB can also take place in the case of densely packed media; (ii) in the case of very large particle packing density, scattering characteristics of discrete random media can exhibit behavior not predicted by the low-density theories of CB and radiative transfer; (iii) increasing the absorptivity of the constituent particles can either enhance or suppress typical manifestations of CB depending on the particle packing density and the real part of the refractive index. Our numerical data strongly suggest that spectacular backscattering effects identified in laboratory experiments and observed for a class of high-albedo Solar System objects are caused by CB.

Dlugach, Janna M.↗

Information theory optimization of signals from small-angle scattering measurements

Small-angle X-ray scattering (SAXS) of particles in solution informs on the conformational states and assemblies of biological macromolecules (bioSAXS) outside of cryo- and solid-state conditions. In bioSAXS, the SAXS measurement under dilute conditions is resolution limited, and through an inverse Fourier transform, the measured SAXS intensities directly relate to the physical space occupied by the particles via the P (r)-distribution. Yet, this inverse transform of SAXS data has been historically cast as an ill-posed, ill-conditioned problem requiring an indirect approach. Here, we show that through the applications of matrix and information theories, the inverse transform of SAXS intensity data is a well-conditioned problem. The so-called ill-conditioning of the inverse problem is directly related to the Shannon number. By exploiting the oversampling enabled by modern detectors, a direct inverse Fourier transform of the SAXS data is possible, provided the recovered information does not exceed the Shannon number. The Shannon limit corresponds to the maximum number of significant singular values that can be recovered in a SAXS experiment, suggesting this relationship is a fundamental property of band-limited inverse integral transform problems. This correspondence reduces the complexity of the inverse problem to the Shannon limit and maximum dimension. We propose a hybrid scoring function using an information theory framework that assesses both the quality of the model-data fit as well as the quality of the recovered P (r)-distribution. The hybrid score utilizes the Akaike information criteria and Durbin-Watson statistic that considers parameter-model complexity, i.e., degrees of freedom, and the randomness of the model-data residuals. The described tests and findings extend the boundaries for bioSAXS by completing the information theory formalism initiated by Peter B. Moore to enable a quantitative measure of resolution in SAXS, robustly determine maximum dimension, and more precisely define the best parameter model appropriately representing the observed scattering data.

Rambo, Robert P. [Science and Technology Facilitie↗

Radar optimization for sea surface and geodetic measurements

The efficient estimation of geoid and sea state parameters is discussed, and the optimum processing structures, including maximum likelihood estimators, and their accuracy limits are given for a model. The model accounts for random surface reflectivity, sea height, and additive noise, and allows for arbitrary radar system parameters, based on the assumption the received signal is a sample function of a normal random process. The integral equation associated with the Gaussian signal in Gaussian noise inference problem was solved. It is shown that the optimum processing is generally a mixture of coherent and incoherent integrations which may be viewed as a weighted summation of received power of the match-filtered received data. When estimates are correlated, the strongest correlation appears between geoid and asymmetry estimates, and between wave height standard deviation and reflectivity estimates.

Harger, R. O.↗

Reference clock parameters for digital communications systems applications

The basic parameters relevant to the design of network timing systems describe the random and systematic time departures of the system elements, i.e., master (or reference) clocks, transmission links, and other clocks controlled over the links. The quantitative relations between these parameters were established and illustrated by means of numerical examples based on available measured data. The examples were limited to a simple PLL control system but the analysis can eventually be applied to more sophisticated systems at the cost of increased computational effort.

Kartaschoff, P.↗

Fluid Physics Under a Stochastic Acceleration Field

The research summarized in this report has involved a combined theoretical and computational study of fluid flow that results from the random acceleration environment present onboard space orbiters, also known as g-jitter. We have focused on a statistical description of the observed g-jitter, on the flows that such an acceleration field can induce in a number of experimental configurations of interest, and on extending previously developed methodology to boundary layer flows. Narrow band noise has been shown to describe many of the features of acceleration data collected during space missions. The scale of baroclinically induced flows when the driving acceleration is random is not given by the Rayleigh number. Spatially uniform g-jitter induces additional hydrodynamic forces among suspended particles in incompressible fluids. Stochastic modulation of the control parameter shifts the location of the onset of an oscillatory instability. Random vibration of solid boundaries leads to separation of boundary layers. Steady streaming ahead of a modulated solid-melt interface enhances solute transport, and modifies the stability boundaries of a planar front.

Vinals, Jorge↗

Artificial intelligence driven laser parameter search: Inverse design of photonic surfaces using greedy surrogate-based optimization

Photonic surfaces designed with specific optical characteristics are becoming increasingly crucial for novel energy harvesting and storage systems. The design of these surfaces can be achieved by texturing materials using lasers. The optimal adjustment of laser fabrication parameters to achieve target surface optical properties is an open challenge. Thus, we develop a surrogate-based optimization approach. Our framework employs the Random Forest algorithm to model the forward relationship between the laser fabrication parameters and the resulting optical characteristics. During the optimization process, we use a greedy, prediction-based exploration strategy that iteratively selects batches of laser parameters to be used in experimentation by minimizing the predicted discrepancy between the surrogate model’s outputs and the user-defined target optical characteristics. This strategy allows for efficient identification of optimal fabrication parameters without the need to model the error landscape directly. We demonstrate the efficiency and effectiveness of our approach on two synthetic benchmarks and two specific experimental applications of photonic surface inverse design targets. By calculating the average performance of our algorithm compared to other state of the art optimization methods, we show that our algorithm performs, on average, twice as well across all benchmarks. Additionally, a warm starting inverse design technique for changed target optical characteristics enhances the performance of the introduced approach.

97 MATHEMATICS AND COMPUTING↗

Calibration of Predictor Models Using Multiple Validation Experiments

This paper presents a framework for calibrating computational models using data from several and possibly dissimilar validation experiments. The offset between model predictions and observations, which might be caused by measurement noise, model-form uncertainty, and numerical error, drives the process by which uncertainty in the models parameters is characterized. The resulting description of uncertainty along with the computational model constitute a predictor model. Two types of predictor models are studied: Interval Predictor Models (IPMs) and Random Predictor Models (RPMs). IPMs use sets to characterize uncertainty, whereas RPMs use random vectors. The propagation of a set through a model makes the response an interval valued function of the state, whereas the propagation of a random vector yields a random process. Optimization-based strategies for calculating both types of predictor models are proposed. Whereas the formulations used to calculate IPMs target solutions leading to the interval value function of minimal spread containing all observations, those for RPMs seek to maximize the models' ability to reproduce the distribution of observations. Regarding RPMs, we choose a structure for the random vector (i.e., the assignment of probability to points in the parameter space) solely dependent on the prediction error. As such, the probabilistic description of uncertainty is not a subjective assignment of belief, nor is it expected to asymptotically converge to a fixed value, but instead it casts the model's ability to reproduce the experimental data. This framework enables evaluating the spread and distribution of the predicted response of target applications depending on the same parameters beyond the validation domain.

Crespo, Luis G.↗

Probabilistic flux limiters

The stable numerical integration of shocks in compressible flow simulations relies on the reduction or elimination of Gibbs phenomena (unstable, spurious oscillations). A popular method to virtually eliminate Gibbs oscillations caused by numerical discretization in under-resolved simulations is to use a flux limiter. A wide range of flux limiters have been studied in the literature, with recent interest in their optimization via machine learning methods trained on high-resolution datasets. The common use of flux limiters in numerical codes as plug-and-play blackbox components makes them key targets for design improvement. Even for deterministic dynamical models, numerical uncertainty is introduced via coarse-graining required by insufficient computational power to solve all scales of motion. Conventional flux limiters are deterministic and lack the capacity to address uncertainties, both aleatoric (inherent randomness) and epistemic (modeling uncertainty due to limited knowledge), which arise in coarse-grained numerical simulations. Here, we introduce a conceptually distinct type of flux limiter that is designed to handle the effects of randomness in the model and uncertainty in model parameters. Unlike traditional single-function flux limiters, these new probabilistic flux limiters incorporate multiple flux limiting functions, each applied with a learned probability drawn from high-resolution data to mitigate the effects of uncertainty in numerical simulations. This approach departs from traditional single-function limiters by explicitly modeling and incorporating uncertainty into the shock capturing process. Using the example of Burgers' equation as a testbed, we show that a machine learned, probabilistic flux limiter may be used in a shock capturing code to more accurately capture shock profiles. In particular, we show that our probabilistic flux limiter outperforms standard limiters and can be successively improved upon (up to a point) by expanding the set of probabilistically chosen flux limiting functions.

97 MATHEMATICS AND COMPUTING↗

A relation between cosmic-ray fluctuations, gradient, and diffusion coefficient

The motion of charged particles in a stochastic magnetic field is considered via a generalized quasi-linear expansion of Liouville's equation. The result is an equation relating cosmic-ray scintillations to particle gradients and to magnetic-field fluctuations (or diffusion coefficient). The resulting theory may be regarded as an example of a fluctuation-dissipation phenomenon, in which the diffusion coefficient plays the role of the dissipative parameter. The resonant interaction between particles and the random interplanetary magnetic field is considered explicitly, and it is shown that observed scintillations of high-energy (about 1 GeV) cosmic rays may be reasonably explained by the model.

Owens, A. J.↗

A model based technique for the design of flight directors

A new technique for designing flight directors is discussed. This technique uses the optimal-control pilot/vehicle model to determine the appropriate control strategy. The dynamics of this control strategy are then incorporated into the director control laws, thereby enabling the pilot to operate at a significantly lower workload. A preliminary design of a control director for maintaining a STOL vehicle on the approach path in the presence of random air turbulence is evaluated. By selecting model parameters in terms of allowable path deviations and pilot workload levels, a set of director laws is achieved which allows improved system performance at reduced workload levels. The pilot acts essentially as a proportional controller with regard to the director signals, and control motions are compatible with those appropriate to status-only displays.

Levison, W. H.↗

On estimating the phase of a periodic waveform in additive Gaussian noise, part 1

Motivated by recent advances in technology, a new look is taken at the problem of estimating the phase of a periodic waveform in additive Gaussian noise. The maximum a posteriori probability criterion with signal space interpretation is used to obtain the structures of optimum and some suboptimum phase estimators for the following cases: (1) known constant frequency and unknown constant phase with an a priori distribution; (2) unknown constant frequency and phase with a joint a priori distribution; (3) frequency a parameterized function of time with a joint a priori distribution on parameters and phase and (4) frequency a Gaussian random process.

Rauch, L. L.↗

A simple parameterization of ozone infrared absorption for atmospheric heating rate calculations

A simple parameterization of ozone absorption in the 9.6-micron region which is suitable for two- and three-dimensional stratospheric and tropospheric models is presented. The band is divided into two parts, a brand center region and a band wing region, grouping together regions for which the temperature dependence of absorption is similar. Each of the two regions is modeled with a function having the form of the Goody random model, with pressure and temperature dependent band parameters chosen by empirically fitting line-by-line equivalent widths for pressures between 0.25 and 1000 mbar and ozone absorber amounts between 1.0 x 10 to the -7th and 1.0 cm atm. The model has been applied to calculations of atmospheric heating rates using an absorber amount weighted mean pressure and temperature along the inhomogeneous paths necessary for flux computations. In the stratosphere, maximum errors in the heating rates relative to line-by-line calculations are 0.1 K/d, or 5 percent of the peak cooling at the stratopause. In the troposphere the errors are at most 0.005 K/d.

Rosenfield, Joan E.↗

The application of structural reliability techniques to plume impingement loading of the Space Station Freedom Photovoltaic Array

A new aerospace application of structural reliability techniques is presented, where the applied forces depend on many probabilistic variables. This application is the plume impingement loading of the Space Station Freedom Photovoltaic Arrays. When the space shuttle berths with Space Station Freedom it must brake and maneuver towards the berthing point using its primary jets. The jet exhaust, or plume, may cause high loads on the photovoltaic arrays. The many parameters governing this problem are highly uncertain and random. An approach, using techniques from structural reliability, as opposed to the accepted deterministic methods, is presented which assesses the probability of failure of the array mast due to plume impingement loading. A Monte Carlo simulation of the berthing approach is used to determine the probability distribution of the loading. A probability distribution is also determined for the strength of the array. Structural reliability techniques are then used to assess the array mast design. These techniques are found to be superior to the standard deterministic dynamic transient analysis, for this class of problem. The results show that the probability of failure of the current array mast design, during its 15 year life, is minute.

Yunis, Isam S.↗

Interactive Reliability Model for Whisker-toughened Ceramics

Wider use of ceramic matrix composites (CMC) will require the development of advanced structural analysis technologies. The use of an interactive model to predict the time-independent reliability of a component subjected to multiaxial loads is discussed. The deterministic, three-parameter Willam-Warnke failure criterion serves as the theoretical basis for the reliability model. The strength parameters defining the model are assumed to be random variables, thereby transforming the deterministic failure criterion into a probabilistic criterion. The ability of the model to account for multiaxial stress states with the same unified theory is an improvement over existing models. The new model was coupled with a public-domain finite element program through an integrated design program. This allows a design engineer to predict the probability of failure of a component. A simple structural problem is analyzed using the new model, and the results are compared to existing models.

Palko, Joseph L.↗

The Application of Structural Reliability Techniques to Plume Impingement Loading of the Space Station Freedom Photovoltaic Array

A new aerospace application of structural reliability techniques is presented, where the applied forces depend on many probabilistic variables. This application is the plume impingement loading of the Space Station Freedom Photovoltaic Arrays. When the space shuttle berths with Space Station Freedom it must brake and maneuver towards the berthing point using its primary jets. The jet exhaust, or plume, may cause high loads on the photovoltaic arrays. The many parameters governing this problem are highly uncertain and random. An approach, using techniques from structural reliability, as opposed to the accepted deterministic methods, is presented which assesses the probability of failure of the array mast due to plume impingement loading. A Monte Carlo simulation of the berthing approach is used to determine the probability distribution of the loading. A probability distribution is also determined for the strength of the array. Structural reliability techniques are then used to assess the array mast design. These techniques are found to be superior to the standard deterministic dynamic transient analysis, for this class of problem. The results show that the probability of failure of the current array mast design, during its 15 year life, is minute.

Yunis, Isam S.↗

HRDI Observations of Inertia-Gravity Waves in the Mesosphere and Lower Thermosphere

Vertical profiles of High-resolution Doppler imager (HRDI) mesospheric winds have small-scale structure (vertical wavelengths between 10 and 20 km) that is virtually always present. Fourier analysis of HRDI zonal and meridional wind profiles have been carried out, and the spectral characteristics are sorted by latitude, month and local time. Power spectral density (PSD) exhibits a universal exp(-km) structure in the 10-20km wavelength regime, with K lying between 2 and 3. The observed PSD for wavelengths between 10 and 20 km is a factor of 3 higher than a null spectrum constructed from HRDI reported error bars multiplied by randomly varying numbers between -1 and +1. Stokes parameters were consolidated by month into Northern and Southern hemisphere middle and high latitudes belts (40-72 degrees), tidal belts (32-16 degrees) and a tropical belt (8S-8N). Vertical waves between 10 and 15 km in wavelength are about 10-15% polarized everywhere. The inferred propagation direction in the middle and high latitude Southern hemisphere is predominantly meridional during solstice, and significantly more zonal during equinoxes. In the tropical belt, the wave orientations are nearly North-South during solstices, with a slightly higher east-west component during equinox. In the tidal belts where the background wind includes a strong meridional tidal wind, the preferred wave orientation has a significant zonal component during equinox. These findings are consistent with the interpretation of wave filtering by the background wind.

Lieberman, Ruth S.↗