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Results for “Parameter Dimensionality Reduction”

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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

GIXSGUI : a MATLAB toolbox for grazing-incidence X-ray scattering data visualization and reduction, and indexing of buried three-dimensional periodic nanostructured films

GIXSGUI is a MATLAB toolbox that offers both a graphical user interface and script-based access to visualize and process grazing-incidence X-ray scattering data from nanostructures on surfaces and in thin films. It provides routine surface scattering data reduction methods such as geometric correction, one-dimensional intensity linecut, two-dimensional intensity reshaping etc . Three-dimensional indexing is also implemented to determine the space group and lattice parameters of buried organized nanoscopic structures in supported thin films.

Jiang, Zhang↗
DOE OSTI2018

Cylindrical Damped Solitary Propagation in Superthermal Plasmas

Wave properties of damped solitons in a collisional unmagnetized four-components dusty fluid plasma system contains superthermal distributed electrons, mobile ions, and negative-positive dusty grains have been examined. To study dissipative DIA mode properties, a reductive perturbation (RP) analysis is used under convenient geometrical coordinate transformation, three-dimensional damped Kadomtsev–Petviashvili (3D-CDKP) equation in cylindrical coordinates is obtained. Effects of collisional parameters on damped soliton pulse structures are studied. More specifically, the impact of axial, radial, and polar coordinates with the time on solitary propagation are examined. This investigation may be viable in plasma of the Earth’s mesosphere.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Extending Parsimonious Bayesian Inference

Parsimonious Bayesian inference is a theoretical framework for efficient data assimilation that seeks to balance increased consistency between predictions and training data against corresponding increases in model complexity. Within this framework, over-training is understood as optimization that encodes excessive information within model parameters while only achieving small improvements between predictions and training data. This project aims to develop practical methods of limiting excess model information during optimization. One key observation is that practical heuristics for parsimonious learning in high-dimensions must balance expressivity, i.e. the ability of the model to capture diverse predictions with only a few non-zero parameters, against discoverability, i.e. the ability to train the model with gradient-based optimization and drive parameters to low information states. As such, we developed logical activation functions that are able to adaptively approximate arbitrary truth tables that define Boolean logic operations within a probabilistic framework. These functions have demonstrated the ability to learn exclusive disjunction (XOR) and conditioned disjunction (if [condition] then [result_if_true] else [result_if_false]) within a single layer of a neural network. To efficiently exploit these activation functions to drive parsimonious learning required several other advances within the domain of variational inference. The most efficient form of complexity suppression is structured sparsification, driving most model parameters to zero while achieving the structural coherence among nonzeros needed for bandwidth reduction. Such models are not only far more efficient at suppressing information-theoretic complexity, they also reduce the other forms of complexity (computations, communication, storage, and the number of dependencies needed to evaluate predictions). Aiming to support enhanced sparsification, this project examined new approaches to high-dimensional variational inference that allow us to calibrate and control parameter uncertainty during optimization. By identifying which parameters can sustain sparsifying perturbations with little impact on prediction quality, we can develop better pruning strategies by framing them as approximate Bayesian inference. These advances also open paths to mitigate concerns with deploying advanced learning methods in resource-constrained environments, such as running models on power-limited or communication-limited devices.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Reactive burn model calibration using high-throughput initiation experiments at sub-millimeter length scales

We report a first-of-its-kind model calibration was performed using Sandia National Laboratories’ high-throughput initiation (HTI) experiment for two types of vapor-deposited explosive films consisting of hexanitrostilbene (HNS) or pentaerythritol tetranitrate (PETN). These films exhibit prompt initiation, and they reach steady detonation at sub-millimeter length scales. Following prior work on HNS, we test the hypothesis of approximating these explosive films as fine-grained homogeneous solids with simple Arrhenius kinetics burn models. The model calibration process is described herein using a single-step as well as a two-step Arrhenius rate law, and it consists of systematic parameter sampling leading to a reduction in the model degrees of freedom. Multiple local minima are observed; results are given for seven different optimized parameter sets. Each model set is further evaluated in a two-dimensional simulation of the critical failure thickness for a sustained detonation. Overall, the two-step Arrhenius kinetics model captures the observed behavior for HNS; however, neither model produces a good fit to the PETN data. We hypothesize that the HTI results for PETN correspond to a heterogeneous response, owing to the smaller reaction zone of PETN compared to HNS (i.e., it does not homogenize the fine-grained hot spots as well). Future work should consider using the ignition and growth model for PETN, as well as other reactive burn models such as xHVRB, AWSD, PiSURF, and CREST.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1988

Finite-dimensional approximation for optimal fixed-order compensation of distributed parameter systems

In controlling distributed parameter systems it is often desirable to obtain low-order, finite-dimensional controllers in order to minimize real-time computational requirements. Standard approaches to this problem employ model/controller reduction techniques in conjunction with LQG theory. In this paper we consider the finite-dimensional approximation of the infinite-dimensional Bernstein/Hyland optimal projection theory. This approach yields fixed-finite-order controllers which are optimal with respect to high-order, approximating, finite-dimensional plant models. The technique is illustrated by computing a sequence of first-order controllers for one-dimensional, single-input/single-output, parabolic (heat/diffusion) and hereditary systems using spline-based, Ritz-Galerkin, finite element approximation. Numerical studies indicate convergence of the feedback gains with less than 2 percent performance degradation over full-order LQG controllers for the parabolic system and 10 percent degradation for the hereditary system.

Bernstein, Dennis S.↗
NASA NTRS1991

A parametric study of transonic blade-vortex interaction noise

Several parameters of transonic blade-vortex interactions (BVI) are being studied and some ideas for noise reduction are introduced and tested using numerical simulation. The model used is the two-dimensional high frequency transonic small disturbance equation with regions of distributed vorticity (VTRAN2 code). The far-field noise signals are obtained by using the Kirchhoff method with extends the numerical 2-D near-field aerodynamic results to the linear acoustic 3-D far-field. The BVI noise mechanisms are explained and the effects of vortex type and strength, and angle of attack are studied. Particularly, airfoil shape modifications which lead to noise reduction are investigated. The results presented are expected to be helpful for better understanding of the nature of the BVI noise and better blade design.

Lyrintzis, A. S.↗
NASA NTRS1995

Advances in reduction techniques for tire contact problems

Some recent developments in reduction techniques, as applied to predicting the tire contact response and evaluating the sensitivity coefficients of the different response quantities, are reviewed. The sensitivity coefficients measure the sensitivity of the contact response to variations in the geometric and material parameters of the tire. The tire is modeled using a two-dimensional laminated anisotropic shell theory with the effects of variation in geometric and material parameters, transverse shear deformation, and geometric nonlinearities included. The contact conditions are incorporated into the formulation by using a perturbed Lagrangian approach with the fundamental unknowns consisting of the stress resultants, the generalized displacements, and the Lagrange multipliers associated with the contact conditions. The elemental arrays are obtained by using a modified two-field, mixed variational principle. For the application of reduction techniques, the tire finite element model is partitioned into two regions. The first region consists of the nodes that are likely to come in contact with the pavement, and the second region includes all the remaining nodes. The reduction technique is used to significantly reduce the degrees of freedom in the second region. The effectiveness of the computational procedure is demonstrated by a numerical example of the frictionless contact response of the space shuttle nose-gear tire, inflated and pressed against a rigid flat surface. Also, the research topics which have high potential for enhancing the effectiveness of reduction techniques are outlined.

Noor, Ahmed K.↗
DOE OSTI2012

Science Goals for the ARM Recovery Act Radars

Science Goals for the ARM Recovery Act Radars. In October 2008, an ARM workshop brought together approximately 30 climate research scientists to discuss the Atmospheric Radiation Measurement (ARM) Climate Research Facility's role in solving outstanding climate science issues. Through this discussion it was noted that one of ARM's primary contributions is to provide detailed information about cloud profiles and their impact on radiative fluxes. This work supports cloud parameterization development and improved understanding of cloud processes necessary for that development. A critical part of this work is measuring microphysical properties (cloud ice and liquid water content, cloud particle sizes, shapes, and distribution). ARM measurements and research have long included an emphasis on obtaining the best possible microphysical parameters with the available instrumentation. At the time of the workshop, this research was reaching the point where additional reduction in uncertainties in these critical parameters required new instrumentation for applications such as specifying radiative heating profiles, measuring vertical velocities, and studying the convective triggering and evolution of three-dimensional (3D) cloud fields. ARM was already operating a subset of the necessary instrumentation to make some progress on these problems; each of the ARM sites included (and still includes) a cloud radar (operating at 35 or 94 GHz), a cloud lidar, and balloon-borne temperature and humidity sensors. However, these measurements were inadequate for determining detailed microphysical properties in most cases. Additional instrumentation needed to improve retrievals of microphysical processes includes radars at two additional frequencies for a total of three at a single site (35 GHz, 94 GHz, and a precipitation radar) and a Doppler lidar. Evolving to a multi-frequency scanning radar is a medium-term goal to bridge our understanding of two-dimensional (2D) retrievals to the 3D cloud field. These additional microphysical measurements would allow detailed cloud properties to be derived even in the presence of light precipitation. It is important to couple these detailed measurements of cloud microphysics to vertical motion on the cloud scale to couple microphysics with meteorological processes. Vertically pointing Doppler radars provide the vertical motion of cloud particles but, to separate particle motion from air motion, a wind profiler is required. The American Recovery and Reinvestment Act provided the means to address these needs and implement a multi-frequency suite of radars, including scanning radars, at each of the ARM sites. In addition, Doppler lidars have been deployed at several sites. With these new measurement capabilities, ARM has the measurement capabilities to tackle the problems of improving microphysical profile descriptions and evaluating the relationship between our current narrow-field-of view, zenith perspective on clouds to a description of the full 3D cloud field and its temporal evolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Online data-driven changepoint detection for high-dimensional dynamical systems

In this study, the detection of anomalies or transitions in complex dynamical systems is of critical importance to various applications. In this study, we propose the use of machine learning to detect changepoints for high-dimensional dynamical systems. Here, changepoints indicate instances in time when the underlying dynamical system has a fundamentally different characteristic—which may be due to a change in the model parameters or due to intermittent phenomena arising from the same model. We propose two complementary approaches to achieve this, with the first devised using arguments from probabilistic unsupervised learning and the latter devised using supervised deep learning. To accelerate the deployment of transition detection algorithms in high-dimensional dynamical systems, we introduce dimensionality reduction techniques. Our experiments demonstrate that transitions can be detected efficiently, in real-time, for the two-dimensional forced Kolmogorov flow and the Rössler dynamical system, which are characterized by anomalous regimes in phase space where dynamics are perturbed off the attractor at potentially uneven intervals. Finally, we also demonstrate how variations in the frequency of detected changepoints may be utilized to detect a significant modification to the underlying model parameters by utilizing the Lorenz-63 dynamical system.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1995

Reduction technique for tire contact problems

A reduction technique and a computational procedure are presented for predicting the tire contact response and evaluating the sensitivity coefficients of the different response quantities. The sensitivity coefficients measure the sensitivity of the contact response to variations in the geometric and material parameters of the tire. The tire is modeled using a two-dimensional laminated anisotropic shell theory with the effects of variation in geometric and material parameters, transverse shear deformation, and geometric nonlinearities included. The contact conditions are incorporated into the formulation by using a perturbed Lagrangian approach with the fundamental unknowns consisting of the stress resultants, the generalized displacements, and the Lagrange multipliers associated with the contact conditions. The elemental arrays are obtained by using a modified two-field, mixed variational principle. For the application of the reduction technique, the tire finite element model is partitioned into two regions. The first region consists of the nodes that are likely to come in contact with the pavement, and the second region includes all the remaining nodes. The reduction technique is used to significantly reduce the degrees of freedom in the second region. The effectiveness of the computational procedure is demonstrated by a numerical example of the frictionless contact response of the space shuttle nose-gear tire, inflated and pressed against a rigid flat surface.

Noor, Ahmed K.↗
NASA NTRS1990

Riblets

In addition to characterizing the various concepts reported in the literature on longitudinally-ribbed surface for aerodynamic surface drag reduction, the present development status evaluation of this technology correlates all available experimental data. An analysis of these data is then conducted to ascertain the parameters most directly involved in drag reduction, and to evaluate the effects which have thus far been exerted on turbulent boundary layer structures. Such advanced riblet techniques as compound and three-dimensional riblets, riblets in combination with large-eddy breakup devices, and riblets with suction/blowing, are also discussed.

Walsh, Michael J.↗
DOE OSTI2016

Spectrally-broadened multimode lasing based on structurally graded InGaN nanocolumn photonic crystals suitable for reduction of speckle contrast

Bottom-up grown structurally graded InGaN-based nanocolumn photonic crystals, in which nanocolumns were arranged in triangular lattice and the nanocolumn diameter changed one-dimensionally from 93 to 213 nm with a fixed lattice constant of 250 nm, were fabricated. The spatial distribution of the diameter resulted in random-laser-like operation under optical excitation. A broad multi-wavelength lasing spectrum with more than 10 peaks was obtained with a full width at half maximum of 27 nm at 505 nm wavelength as well as lowering of the polarization degree, which is expected to be suitable for speckle contrast reduction in laser projection display applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

A Discrete Nonlinear Schrödinger-Type Hierarchy, Its Finite-Dimensional Reduction Analysis, and the Numerical Integration Scheme

We investigate the procedures of discretization of the integrable nonlinear Schrödinger dynamical system, well known as the Ablowitz–Ladik equation, the corresponding symplectic structures, and the finite-dimensional invariant reductions. We develop an efficient scheme of invariant reduction of the corresponding infinite system of ordinary differential equations to an equivalent finite system of ordinary differential equations with respect to the evolution parameter. We construct a finite set of recurrence algebraic regular relations that allows one to generate solutions of the discrete nonlinear Schrödinger dynamical system and discuss the related functional spaces of solutions. Finally, we analyze the Fourier-transform approach to the study of the set of solutions of the discrete nonlinear Schrödinger dynamical system and its functional-analytic aspects.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Estimating parameters from rotating ring disc electrode measurements

Rotating ring disc electrode (RRDE) experiments are a classic tool for investigating kinetics of electrochemical reactions. Several standardized methods exist for extracting transport parameters and reaction rate constants using RRDE measurements. Here in this work, we compare some approximate solutions to the convective diffusion used popularly in the literature to a rigorous numerical solution of the Nernst-Planck equations coupled to the three dimensional flow problem. In light of these computational advancements, we explore design aspects of the RRDE that will help improve sensitivity of our parameter estimation procedure to experimental data. We use the oxygen reduction in acidic media involving three charge transfer reactions and a chemical reaction as an example, and identify ways to isolate reaction currents for the individual processes in order to accurately estimate the exchange current densities.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

Dimensionality Reduction of SDSS Spectra with Variational Autoencoders

High-resolution galaxy spectra contain much information about galactic physics, but the high dimensionality of these spectra makes it difficult to fully utilize the information they contain. We apply variational autoencoders (VAEs), a nonlinear dimensionality reduction technique, to a sample of spectra from the Sloan Digital Sky Survey (SDSS). In contrast to principal component analysis (PCA), a widely used technique, VAEs can capture nonlinear relationships between latent parameters and the data. We find that a VAE can reconstruct the SDSS spectra well with only six latent parameters, outperforming PCA with the same number of components. Different galaxy classes are naturally separated in this latent space, without class labels having been given to the VAE. The VAE latent space is interpretable because the VAE can be used to make synthetic spectra at any point in latent space. For example, making synthetic spectra along tracks in latent space yields sequences of realistic spectra that interpolate between two different types of galaxies. Using the latent space to find outliers may yield interesting spectra: in our small sample, we immediately find unusual data artifacts and stars misclassified as galaxies. In this exploratory work, we show that VAEs create compact, interpretable latent spaces that capture nonlinear features of the data. While a VAE takes substantial time to train (≈1 day for 48,000 spectra), once trained, VAEs can enable the fast exploration of large astronomical data sets.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1989

Solution of the incompressible Navier-Stokes equations using artificial compressibility methods

A modified artificial compressibility formulation is derived from a preconditioned low Mach number compressible formulation, and these two methods are compared on a two-dimensional laminar leading edge flow using a LBI/ADI solution algorithm. The two methods are essentially equivalent with appropriate preconditioning parameters and have the same convergence rates and efficiency, giving 4 orders of residual reduction in about 75 iterations with a vectorized CRAY-XMP run time of 20 seconds for 3000 grid points.

Briley, W. R.↗
DOE OSTI2019

Gradient-Free Construction of Active Subspaces for Dimension Reduction

Recent developments in the field of reduced order modeling - and in particular, active subspace construction - have made it possible to efficiently approximate complex models by constructing low-order response surfaces based upon a small subspace of the original high dimensional parameter space. These methods rely upon the fact that the response tends to vary more prominently in a few dominant directions defined by linear combinations of the original inputs, allowing for a rotation of the coordinate axis and a consequent transformation of the parameters. In this talk, we discuss a gradient free active subspace algorithm that is feasible for high dimensional parameter spaces where finite-difference techniques are impractical. We illustrate an initialized gradient-free active subspace algorithm for a neutronics example implemented with SCALE6.1, for input dimensions up to 7700.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1990

Acoustic Reduction Of Separation Of Flow

Report discusses experiments in use of acoustic excitation to reduce separation of two-dimensional laminar flow about airfoils at low angles of attack. Purpose of investigation to gain better understanding of effect of excitation, scaling of parameters of excitation, and ranges of frequencies in which excitation reduces separation effectively.

Zaman, K. B. M. Q.↗