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Results for “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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

On the stabilization of three-dimensional boundary layers by suction and cooling

A significant reduction in the drag of transonic aircraft can be achieved by using an active method of boundary-layer control to maintain laminar flow on the aerodynamic surfaces. The stabilizing influence of suction for both favorable and adverse pressure gradients is demonstrated by means of the self-similar incompressible three-dimensional boundary layers on yawed wedges. Profile instability is measured by the maximum amplification rate of fixed-frequency disturbances computed according to linearized, locally parallel, spatial stability theory. Suction is found to be more effective in controlling Tollmien-Schlichting instability than stationary cross-flow disturbances. The effectiveness of surface cooling as a method of stabilization is compared with suction for the boundary layers on a transonic 35 deg swept wing of infinite span. It is found from compressible stability theory that when the surface is cooled to a uniform temperature such that the maximum cross-flow velocity is reduced by the same amount as with a uniform suction distribution, the stabilizing effect of cooling on cross-flow disturbances is less than with suction.

Mack, L. M.↗
NASA NTRS1981

Application of a Laser Interferometer Skin-Friction Meter in Complex Flows

A nonintrusive skin-friction meter has been found useful for a variety of complex wind-tunnel flows. This meter measures skin friction with a remotely located laser interferometer that monitors the thickness change of a thin oil film. Its accuracy has been proven in a low-speed flat-plate flow. The wind-tunnel flows described here include sub-sonic separated and reattached flow over a rearward-facing step, supersonic flow over a flat plate at high Reynolds numbers, and supersonic three - dimensional vortical flow over the lee of a delta wing at angle of attack. The data-reduction analysis was extended to apply to three-dimensional flows with unknown flow direction, large pressure and shear gradients, and large oil viscosity changes with time. The skin friction measurements were verified, where possible, with results from more conventional techniques and also from theoretical computations.

Monson, D. J.↗
DOE OSTI2019

Machine-learning error models for approximate solutions to parameterized systems of nonlinear equations

Here, this work proposes a machine-learning framework for constructing statistical models of errors incurred by approximate solutions to parameterized systems of nonlinear equations. These approximate solutions may arise from early termination of an iterative method, a lower-fidelity model, or a projection-based reduced-order model, for example. The proposed statistical model comprises the sum of a deterministic regression-function model and a stochastic noise model. The method constructs the regression-function model by applying regression techniques from machine learning (e.g., support vector regression, artificial neural networks) to map features (i.e., error indicators such as sampled elements of the residual) to a prediction of the approximate-solution error. The method constructs the noise model as a mean-zero Gaussian random variable whose variance is computed as the sample variance of the approximate-solution error on a test set; this variance can be interpreted as the epistemic uncertainty introduced by the approximate solution. This work considers a wide range of feature-engineering methods, data-set-construction techniques, and regression techniques that aim to ensure that (1) the features are cheaply computable, (2) the noise model exhibits low variance (i.e., low epistemic uncertainty introduced), and (3) the regression model generalizes to independent test data. Finally, numerical experiments performed on several computational-mechanics problems and types of approximate solutions demonstrate the ability of the method to generate statistical models of the error that satisfy these criteria and significantly outperform more commonly adopted approaches for error modeling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Facile Synthesis of Boron-Doped rGO as Cathode Material for High Energy Li–O 2 Batteries

To improve the electrochemical performance of the high energy Li–O2 batteries, it is important to design and construct a suitable and effective oxygen-breathing cathode. Herein, a three-dimensional (3D) porous boron-doped reduction graphite oxide (B-rGO) material with a hierarchical structure has been prepared by a facile freeze-drying method. In this design, boric acid as the boron source helps to form the 3D porous structure, owing to its cross-linking and pore-forming function. This architecture facilitates the rapid oxygen diffusion and electrolyte penetration in the electrode. Meanwhile, the boron–oxygen functional groups linking to the carbon surface or edge serve as additional reaction sites to activate the ORR process. It is vital that boron atoms have been doped into the carbon lattices to greatly activate the electrons in the carbon π system, which is beneficial for fast charge under large current densities. Density functional theory calculation demonstrates that B-rGO exhibits much stronger interactions with Li5O6 clusters, so that B-rGO more effectively activates Li–O bonds to decompose Li2O2 during charge than rGO does. With B-rGO as a catalytic substrate, the Li–O2 battery achieves a high discharge capacity and excellent rate capability. Moreover, catalysts could be added into the B-rGO substrate to further lower the overpotential and enhance the cycling performance in future.

Wu, Feng↗
DOE OSTI2021

Probabilistic error estimation for non-intrusive reduced models learned from data of systems governed by linear parabolic partial differential equations

This work derives a residual-based a posteriori error estimator for reduced models learned with non-intrusive model reduction from data of high-dimensional systems governed by linear parabolic partial differential equations with control inputs. It is shown that quantities that are necessary for the error estimator can be either obtained exactly as the solutions of least-squares problems in a non-intrusive way from data such as initial conditions, control inputs, and high-dimensional solution trajectories or bounded in a probabilistic sense. Here, the computational procedure follows an offline/online decomposition. In the offline (training) phase, the high-dimensional system is judiciously solved in a black-box fashion to generate data and to set up the error estimator. In the online phase, the estimator is used to bound the error of the reduced-model predictions for new initial conditions and new control inputs without recourse to the high-dimensional system. Numerical results demonstrate the workflow of the proposed approach from data to reduced models to certified predictions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Cylindrical ion-acoustic solitary waves in electronegative plasmas with superthermal electrons

By using the standard reductive perturbation technique, a three-dimensional cylindrical Kadomtsev-Petviashvili equation (CKPE), which governs the dynamics of ion acoustic solitary waves (IASWs), is derived for small but finite amplitude ion-acoustic waves in cylindrical geometry in a collisionless unmagnetized plasma with kappa distributed electrons, thermal positrons, and cold ions. The generalized expansion method is used to solve analytically the CKPE. The existence regions of localized pulses are investigated. It is found that the solution of the CKPE supports only compressive solitary waves. Furthermore, the effects of superthermal electrons, the ratio of the electron temperature to positron temperature, the ratio of the positron density to electron density and direction cosine of the wave propagation on the profiles of the amplitudes, and widths of the solitary structures are examined numerically. It is shown these parameters play a vital role in the formation of ion acoustic solitary waves.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Over 50% reduction in the formation energy of Co-based Heusler alloy films by two-dimensional crystallisation

Crystalline formation of high magnetic-moment thin films through low-temperature annealing processes compatible with current semiconductor technologies is crucial for the development of next generation devices, which can utilise the spin degree of freedom. Utilising in-situ aberration corrected electron microscopy, we report a 235 °C crystallisation process for a Co-based ternary Heusler-alloy film whose initial nucleation is initiated by as few as 27 unit cells. The crystallisation occurs preferentially in the 〈111〉 crystalline directions via a two-dimensional (2D) layer-by-layer growth mode; resulting in grains with [110] surface normal and [111] plane facets. This growth process was found to reduce the crystallisation energy by more than 50% when compared to bulk samples whilst still leading to the growth of highly ordered grains expected to give a high degree of spin-polarisation. Our findings suggest that the 2D layer-by-layer growth minimises the crystallisation energy allowing for the possible implementation of highly spin-polarised alloy films into current chip and memory technologies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Beyond Solanaceae: incorporation of feruloyltyramine and feruloyloctopamine into Cannabaceae lignins

The ferulic acid amides, feruloyltyramine and feruloyloctopamine, have been widely reported as integral constituents in the lignins in several species of Solanaceae in which they function as authentic lignin monomers. In the present study, we demonstrate that these ferulic acid amides are likewise incorporated into the lignins of species within Cannabaceae, including hemp (Cannabis sativa), hops (Humulus lupulus), and European nettle tree (Celtis australis). Structural analyses using derivatization followed by reductive cleavage (DFRC) and two-dimensional nuclear magnetic resonance (2D-NMR) spectroscopy revealed that these ferulic acid amides are incorporated via 4−O- and 8−O-ether linkages, as well as through 8−5′ linkages forming phenylcoumaran structures. Examination of a broad phylogenetic range of plant families demonstrated the absence of these ferulic acid amides from the lignins of all families studied except Solanaceae and Cannabaceae. Given the distant phylogenetic relationship between Solanaceae and Cannabaceae, the recruitment of these ferulic acid amides as lignin monomers in both lineages likely constitutes a case for convergent evolution at the level of lignin biosynthetic pathways. The significance of these ferulic acid amides lies in their unique role as the sole nitrogen-containing phenolic compounds known to participate in lignin formation.

Cannabaceae↗
DOE OSTI2020

Gravitational-wave signal of a core-collapse supernova explosion of a 15M ⊙ star

In this paper we report on the gravitational-wave signal computed in the context of a three-dimensional simulation of a core-collapse supernova explosion of a 15 M ⊙ star. The simulation was performed with our neutrino hydrodynamics code chimera . We detail the gravitational wave strains as a function of time, for both polarizations, and discuss their physical origins. We also present the corresponding spectral signatures. Gravitational wave emission in our model has two key features: low-frequency emission (less than 200 Hz) emanates from the gain layer as a result of neutrino-driven convection and the standing accretion shock instability (SASI), and high-frequency emission (greater than 600 Hz) emanates from the proto–neutron star due to Ledoux convection within it. The high-frequency emission dominates the gravitational wave emission in our model and emanates largely from the convective layer itself, not from the convectively stable layer above it, due to convective overshoot. Moreover, the low-frequency emission emanates from the gain layer itself, not from the proto–neutron star, due to accretion onto it. We provide evidence of the SASI in our model and demonstrate that the peak of our low-frequency gravitational wave emission spectrum corresponds to it. Given its origin in the gain layer, we classify the SASI emission in our model as p-mode emission and assign a purely acoustic origin, not a vortical–acoustic origin, to it. We compare the results of our three-dimensional model analysis with those obtained from the model’s two-dimensional counterpart and find a significant reduction in the strain amplitudes in the former case, as well as significant reductions in all related quantities. Our dominant proto–neutron star gravitational wave emission is not well characterized by emission from surface g modes, complicating the relationship between peak frequencies observed and the mass and radius of the proto–neutron star expressed by analytic estimates under the assumption of surface g-mode emission. We present our frequency normalized characteristic strain along with the sensitivity curves of current- and next-generation gravitational wave detectors. This simple analysis indicates that the spectrum of gravitational wave emission between approximately 20 Hz and approximately 1 kHz, stemming from neutrino-driven convection, the SASI, accretion onto the proto–neutron star, and proto–neutron star convection, will be accessible for a Galactic event.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Two-Level Switches for Advanced Time-Division Multiplexing

Superconducting quantum interference device (SQUID)-based time-division multiplexing (TDM) is a mature and widely implemented technology used to read out transition-edge sensor arrays. As the number of pixels in modern arrays continues to increase, a higher multiplexing factor is required to reduce the number of wires and amplifier channels. Yet, as the multiplexing factor is increased, the number of row-select wires (used to turn on a row of TDM SQUIDs in a two-dimensional configuration) also increases, limiting the reduction in array wires. We introduce a more advanced TDM architecture that enforces multi-level switching between subgroups of pixels. We show that this technique can dramatically reduce the number of required row-select lines. We also present the design, fabrication, and testing of a TDM multiplexer incorporating a two-level switch, which implements a second switch for each group of ten TDM pixels. In this application, a multiplexing factor of 100 can be addressed using ten group-select wiring pairs and ten row-select wiring pairs. We demonstrate multiplexer functionality and present measured operating margins of this new TDM multiplexer.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Research and Development of Multiphysics Models in Support of the Conversion of the High Flux Isotope Reactor to Low Enriched Uranium Fuel

The findings presented in this report are results of a five year effort led by the RRD Division of the ORNL, which is focused on research and development toward the conversion of the High Flux Isotope Reactor (HFIR) fuel from high-enriched uranium (HEU) to low-enriched uranium (LEU). This report focuses on the tasks accomplished by the University of Tennessee Knoxville (UTK) team from the Department of Mechanical, Aerospace, and Biomedical Engineering (MABE) that provided expert support in multiphysics modeling of complex problems associated with the LEU conversion of the HFIR reactor. The COMSOL software was used as the main computational modeling tool, whereas Solidworks was also used in support of computer-aided-design (CAD) modeling of the proposed LEU fuel design. The UTK research has been governed by a statement of work (SOW), which was updated annually to clearly define the specific tasks reported herein. Ph.D. student Isaac T. Bodey has focused on heat transfer and fluid flow modeling issues and has been aided by his major professor Dr. Rao V. Arimilli. Ph.D. student Franklin G. Curtis has been focusing on modeling the fluid-structure interaction (FSI) phenomena caused by the mechanical forces acting on the fuel plates, which in turn affect the fluid flow in between the fuel plates, and ultimately the heat transfer, is also affected by the FSI changes. Franklin Curtis has been aided by his major professor Dr. Kivanc Ekici. M.Sc. student Adam R. Travis has focused two major areas of research: (1) on accurate CAD modeling of the proposed LEU plate design, and (2) reduction of the model complexity and dimensionality through interdimensional coupling of the fluid flow and heat transfer for the HFIR plate geometry. Adam Travis is also aided by his major professor, Dr. Kivanc Ekici. We must note that the UTK team, and particularly the graduate students, have been in very close collaboration with Dr. James D. Freels (ORNL technical monitor and mentor) and have benefited greatly from his leadership and expertise in COMSOL modeling of complex physical phenomena. Both UTK and ORNL teams have used COMSOL releases 3.4 through 5.0 inclusive (with particular emphasis on 3.5a, 4.3a, 4.3b, and 4.4) for most of the work described in this report, except where stated otherwise. Just as in the performance of the research, each of the respective sections has been originally authored by respective authors. Therefore, the reader will observe a contrast in writing style throughout this document.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1992

High performance polymers and polymer matrix composites for spacecraft structural applications

A program implemented by NASA Langley Research Center to develop and evaluate new polymers and polymer matrix composites for spacecraft structural applications is examined. Various polymeric films, moldings, and adhesives are evaluated for resistance to atomic oxygen and high energy electron and UV radiation. Thin films from the poly(arylene ether)s containing phenylphosphine oxide groups and the siloxane-epoxies exhibited minor weight loss compared to Kapton polyimide after exposure. Large doses (greater than 10 exp 9 rads) of electron radiation, simulating 30 yr of exposure in GEO, are found to alter the chemical structure of epoxies by both chain scission and cross-linking. The thermal cycling representative of both LEO and GEO environments can cause microcracking in composites which can in turn affect the dimensional stability and produce mechanical property reductions. The processing and fabrication issues associated with precision composite spacecraft components are also addressed.

Bowles, D. E.↗
DOE OSTI2014

Simulation of Thermal Stratification in BWR Suppression Pools with One Dimensional Modeling Method

The suppression pool in a boiling water reactor (BWR) plant not only is the major heat sink within the containment system, but also provides the major emergency cooling water for the reactor core. In several accident scenarios, such as a loss-of-coolant accident and extended station blackout, thermal stratification tends to form in the pool after the initial rapid venting stage. Accurately predicting the pool stratification phenomenon is important because it affects the peak containment pressure; the pool temperature distribution also affects the NPSHa (available net positive suction head) and therefore the performance of the Emergency Core Cooling System and Reactor Core Isolation Cooling System pumps that draw cooling water back to the core. Current safety analysis codes use zero dimensional (0-D) lumped parameter models to calculate the energy and mass balance in the pool; therefore, they have large uncertainties in the prediction of scenarios in which stratification and mixing are important. While three-dimensional (3-D) computational fluid dynamics (CFD) methods can be used to analyze realistic 3-D configurations, these methods normally require very fine grid resolution to resolve thin substructures such as jets and wall boundaries, resulting in a long simulation time. For mixing in stably stratified large enclosures, the BMIX++ code (Berkeley mechanistic MIXing code in C++) has been developed to implement a highly efficient analysis method for stratification where the ambient fluid volume is represented by one-dimensional (1-D) transient partial differential equations and substructures (such as free or wall jets) are modeled with 1-D integral models. This allows very large reductions in computational effort compared to multi-dimensional CFD modeling. One heat-up experiment performed at the Finland POOLEX facility, which was designed to study phenomena relevant to Nordic design BWR suppression pool including thermal stratification and mixing, is used for validation. Comparisons between the BMIX++, GOTHIC, and CFD calculations against the POOLEX experimental data are discussed in detail.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Manifold Learning-Based Polynomial Chaos Expansions for High-Dimensional Surrogate Models

In this work we introduce a manifold learning-based method for uncertainty quantification (UQ) in systems describing complex spatiotemporal processes. Our first objective is to identify the embedding of a set of high-dimensional data representing quantities of interest of the computational or analytical model. For this purpose, we employ Grassmannian diffusion maps, a two-step nonlinear dimension reduction technique which allows us to reduce the dimensionality of the data and identify meaningful geometric descriptions in a parsimonious and inexpensive manner. Polynomial chaos expansion is then used to construct a mapping between the stochastic input parameters and the diffusion coordinates of the reduced space. An adaptive clustering technique is proposed to identify an optimal number of clusters of points in the latent space. The similarity of points allows us to construct a number of geometric harmonic emulators which are finally utilized as a set of inexpensive pretrained models to perform an inverse map of realizations of latent features to the ambient space and thus perform accurate out-of-sample predictions. Thus, the proposed method acts as an encoder-decoder system which is able to automatically handle very high-dimensional data while simultaneously operating successfully in the small-data regime. The method is demonstrated on two benchmark problems and on a system of advection-diffusion-reaction equations which model a first-order chemical reaction between two species. In all test cases, the proposed method is able to achieve highly accurate approximations which ultimately lead to the significant acceleration of UQ tasks.

42 ENGINEERING↗
NASA NTRS2003

A Wavelet based Suboptimal Kalman Filter for Assimilation of Stratospheric Chemical Tracer Observations

A suboptimal Kalman filter system which evolves error covariances in terms of a truncated set of wavelet coefficients has been developed for the assimilation of chemical tracer observations of CH4. This scheme projects the discretized covariance propagation equations and covariance matrix onto an orthogonal set of compactly supported wavelets. Wavelet representation is localized in both location and scale, which allows for efficient representation of the inherently anisotropic structure of the error covariances. The truncation is carried out in such a way that the resolution of the error covariance is reduced only in the zonal direction, where gradients are smaller. Assimilation experiments which last 24 days, and used different degrees of truncation were carried out. These reduced the covariance size by 90, 97 and 99 % and the computational cost of covariance propagation by 80, 93 and 96 % respectively. The difference in both error covariance and the tracer field between the truncated and full systems over this period were found to be not growing in the first case, and growing relatively slowly in the later two cases. The largest errors in the tracer fields were found to occur in regions of largest zonal gradients in the constituent field. This results indicate that propagation of error covariances for a global two-dimensional data assimilation system are currently feasible. Recommendations for further reduction in computational cost are made with the goal of extending this technique to three-dimensional global assimilation systems.

Tangborn, Andrew↗
NASA NTRS2013

Vectorized Rebinning Algorithm for Fast Data Down-Sampling

A vectorized rebinning (down-sampling) algorithm, applicable to N-dimensional data sets, has been developed that offers a significant reduction in computer run time when compared to conventional rebinning algorithms. For clarity, a two-dimensional version of the algorithm is discussed to illustrate some specific details of the algorithm content, and using the language of image processing, 2D data will be referred to as "images," and each value in an image as a "pixel." The new approach is fully vectorized, i.e., the down-sampling procedure is done as a single step over all image rows, and then as a single step over all image columns. Data rebinning (or down-sampling) is a procedure that uses a discretely sampled N-dimensional data set to create a representation of the same data, but with fewer discrete samples. Such data down-sampling is fundamental to digital signal processing, e.g., for data compression applications.

Dean, Bruce↗