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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Deep Interacting Multiple Model Filtering

In this paper, a deep learning-based multiple model estimation framework is presented for the state estimation of hybrid dynamical systems from high dimensional observations such as camera images. A low dimensional vector which represents the measurement of the latent dynamical system and its corresponding variance are learned using a deep encoder neural network. An Interacting Multiple Model (IMM) filter is used to generate the latent state estimates and covariances using multiple dynamical models, which can be learned using backpropagation through time. The state estimates of the dynamical system and the corresponding covariance matrix are generated from the latent state estimates and covariance using a deep decoder neural network. The whole network is trained in an end-to-end manner using a loss function which minimizes the negative log-likelihood of the neural network parameters. Simulation results are presented using a 2D bouncing ball example and estimation error statistics are computed which demonstrates the accuracy and consistency of the estimation.

Ghananeel Rotithor↗
NASA NTRS1996

Two Reduced Resolution Filter Approaches to Data Assimilation

In this paper we evaluate the performance of two reduced resolution filter approaches to data assimilation. The main distinction between these approaches is in the manner they propagate error covariances. Both account for error covariances in a space with dimension m smaller than the model's state vector dimension n. In the first approach the m dimensional error covariance matrix is interpolated to the n-dimensional space and propagated with the n-dimensional dynamics. In the second approach the low-dimensional error covariance matrix is propagated by a dynamical operator generated in the m-dimensional space. Our experiments indicate that the first approach provides a more reliable simplified scheme for error covariance propagation than the second approach.

Todling, Ricardo↗
NASA NTRS1994

Modelling the low-latitude boundary layer with reconnection entry

We develop a one-dimensional Low Latitude Boundary Layer (LLBL) model for northward interplanetary magnetic field (IMF). The boundary layer in this model is uniform in the direction normal to the magnetopause, a 'plateau-type' boundary layer. The boundary layer motion is decoupled from the magnetosheath motion and driven by the plasma pressure associated with the incoming solar wind plasma near local noon, which has become entrained on closed field lines as a result of reconnection in the cusp region. Dissipation in the ionosphere at the feet of the boundary layer field lines opposes this motion. There are two physical solutions for the model. In one, the boundary layer reaches a terminal velocity in the tail as the boundary layer plasma effectively joins the solar wind flow. In the other solution, the flow is nearly stopped in the far tail. In combination with other mechanisms, this latter solution may correspond to the case in which the boundary layer plasma participates in magnetospheric convection and returns sunward. The density, velocity, and thickness as functions of distance from local noon are studied, assuming that the magnetopause hasa elliptical shape and the magnetospheric field is dipolar.

Song, P.↗
NASA NTRS2018

A Deterministic Self-Organizing Map Approach and its Application on Satellite Data based Cloud Type Classification

A self-organizing map (SOM) is a type of competitive artificial neural network, which projects the high dimensional input space of the training samples into a low dimensional space with the topology relations preserved. This makes SOMs supportive of organizing and visualizing complex data sets and have been pervasively used among numerous disciplines with different applications. Notwithstanding its wide applications, the self-organizing map is perplexed by its inherent randomness, which produces dissimilar SOM patterns even when being trained on identical training samples with the same parameters every time, and thus causes usability concerns for other domain practitioners and precludes more potential users from exploring SOM based applications in a broader spectrum. Motivated by this practical concern, we propose a deterministic approach as a supplement to the standard self-organizing map. In accordance with the theoretical design, the experimental results with satellite cloud data demonstrate the effective and efficient organization as well as simplification capabilities of the proposed approach.

Initialization method↗
NASA NTRSDate not supplied

High dimensional similarity search with quantum assisted variational autoencoder

Recent progress in quantum algorithms and hardware is indicator of the potential importance of quantum computing in the next future. However, finding suitable application areas remains an active area of research. Quantum machine learning [1] is touted as a potential approach to demonstrate quantum advantage within both the gate-model [2,3] and the adiabatic [4,5] schemes. For instance, the Quantum-assisted Variational Autoencoder (QVAE) [6] has been proposed as a quantum enhancement to the discrete VAE [7]. We extend on previous work and study the real-world applicability of a QVAE, specifically, for similarity search in large-scale high dimensional datasets. While similarity search algorithms are available for low dimensional datasets, scaling to billion-scale datasets with thousands of dimensions is non-trivial. We show how the latent-space representation of a QVAE can be used to construct a space-efficient search index. We back up our claims by experimental results which show a correlation between the Hamming distance in the embedded space and the Euclidean distance in the original space on the Moderate Resolution Imaging Spectroradiometer (MODIS) dataset. Further, we show real-world speedups compared to linear search and demonstrate memory efficient scaling to large-scale datasets.

Nicholas D Gao↗
NASA NTRS1987

EA-6B high-lift wing modifications

NASA-Langley has accomplished the computational design and experimental verification of EA-6B aircraft wing modifications for improved high lift capability. The modifications are comparatively simple, and attempt to improve low speed high lift performance while maintaining high speed cruise efficiency. Several two- and three-dimensional low speed and transonic computational techniques were employed, together with extensive wind tunnel tests. The modified inboard and outboard edge slat/flap system sections yielded efficiency improvements that were verified by three-dimensional wind tunnel experiments to amount to an 11-percent wing-body lift coefficient enhancement at low speed.

Waggoner, E. G.↗
NASA NTRSDate not supplied

High-Dimensional Similarity Search with Quantum-Assisted Variational Autoencoder

Recent progress in quantum algorithms and hardware indicates the potential importance of quantum computing in the near future. However, finding suitable application areas remains an active area of research. Quantum machine learning is touted as a potential approach to demonstrate quantum advantage within both the gate-model and the adiabatic schemes. For instance, the QVAE has been proposed as a quantum enhancement to the discrete VAE. We extend on previous work and study the real-world applicability of a QVAE by presenting a proof-of-concept for similarity search in large-scale high-dimensional datasets. While exact and fast similarity search algorithms are available for low dimensional datasets, scaling to high-dimensional data is non-trivial. We show how to construct a space-efficient search index based on the latent space representation of a QVAE. Our experiments show a correlation between the Hamming distance in the embedded space and the Euclidean distance in the original space on the MODIS dataset. Further, we find real-world speedups compared to linear search and demonstrate memory-efficient scaling to half a billion data points.

Data mining, similarity search, quantum machine le↗
NASA NTRS1942

Tests If a Highly Cambered Low-Drag-Airfoil Section with a Lift-Control Flap, Special Report

Tests were made in the NACA two-dimensional low turbulence pressure tunnel of a highly cambered low-drag airfoil (NACA 65,3-618) with a plain flap designed for lift control. The results indicate that such a combination offers attractive possibilities for obtaining low profile-drag coefficients over a wide range of lift coefficients without large reductions of critical speed.

Abbott, Ira H.↗
NASA NTRS2022

Resolving the fine structure in the energy landscapes of repeat proteins

Ankyrin (ANK) repeat proteins are coded by tandem occurrences of patterns with around 33 amino acids. They often mediate protein–protein interactions in a diversity of biological systems. These proteins have an elongated non-globular shape and often display complex folding mechanisms. This work investigates the energy landscape of representative proteins of this class made up of 3, 4 and 6 ANK repeats using the energy-landscape visualisation method (ELViM). By combining biased and unbiased coarse-grained molecular dynamics AWSEM simulations that sample conformations along the folding trajectories with the ELViM structure-based phase space, one finds a three-dimensional representation of the globally funnelled energy surface. In this representation, it is possible to delineate distinct folding pathways. We show that ELViMs can project, in a natural way, the intricacies of the highly dimensional energy landscapes encoded by the highly symmetric ankyrin repeat proteins into useful low-dimensional representations. These projections can discriminate between multiplicities of specific parallel folding mechanisms that otherwise can be hidden in oversimplified depictions.

Murilo N. Sanches↗
NASA NTRS1990

Development of high-lift wing modifications for an advanced capability EA-6B aircraft

NASA-Langley has been in a development program aimed at improvements of the EA-6B electronic countermeasures aircraft's maneuvering capabilities; one objective of this effort is the investigation of relatively simple wing design modifications which could yield improved low speed high lift performance with minimum degradation of higher-speed performance. Various two- and three-dimensional low speed and transonic CFD techniques have accordingly been used during the design effort, which involved leading-edge slat and trailing-edge flap contour evaluations by both computation and wind tunnel experiment. Significant low-speed maximum-lift enhancements were obtained without cruise-speed deterioration.

Waggoner, Edgar G.↗
NASA NTRS2000

Near-Limit Flamelet Phenomena in Buoyant Low Stretch Diffusion Flames Beneath a Solid Fuel

A unique near-limit low stretch multidimensional stable flamelet phenomena has been observed for the first time which extends the material flammability limit beyond the one-dimensional low stretch flammability limit to lower burning rates and higher relative heat losses than is possible with uniform flame coverage. During low stretch experiments burning the underside of very large radii (greater than or = 75 cm stretch rate less than or = 3/s) cylindrical cast PMMA samples, multidimensional flamelets were observed, in contrast with a one-dimensional flame that was found to blanket the surface for smaller radii samples ( higher stretch rate). Flamelets were observed by decreasing the stretch rate or by increasing the conductive heat loss from the flame. Flamelets are defined as flames that cover only part of the burning sample at any given time, but persist for many minutes. Flamelet phenomena is viewed as the flame's method of enhancing oxygen flow to the flame, through oxygen transport into the edges of the flamelet. Flamelets form as heat losses (surface radiation and solid-phase conduction) become large relative to the weakened heat release of the low stretch flame. While heat loss rates remain fairly constant, the limiting factor in the heat release of the flame is hypothesized to be the oxygen transport to the flame in this low stretch (low convective) environment. Flamelet extinction is frequently caused by encroachment of an adjacent flamelet. Large-scale whole-body flamelet oscillations at 1.2 - 1.95 Hz are noted prior to extinction of a flamelet. This oscillation is believed to be due a repeated process of excess fuel leakage through the dark channels between the flamelets, fuel premixing with slow incoming oxidizer, and subsequent rapid flame spread and retreat of the flamelet through the premixed layer. The oscillation frequency is driven by gas-phase diffusive time scales.

Olson, S. L.↗
NASA NTRS1990

Numerical Simulation of Flow Past a Tapered Cylinder

We have computed the unsteady three-dimensional low Reynolds number flow past a tapered cylinder. The spanwise variation in natural shedding frequency results in interesting three-dimensional flow phenomena. Our computed hot-wire and spectral data are very similar to experimental results. The computation was done on the Connection Machine, a massively parallel computer, we highlight the capabilities of the Connection Machine, for computation and visualization of three-dimensional unsteady flow fields.

Jespersen, Dennis↗
NASA NTRS1991

Numerical simulation of flow past a tapered cylinder

The unsteady three-dimensional low Reynolds number flow past a tapered cylinder is computed. The spanwise variation in natural shedding frequency results in interesting three-dimensional flow phenomena. The computed hot-wire and spectral data are very similar to experimental results. The computation was done on the Connection Machine, a massively parallel computer; highlights of the capabilities of the Connection Machine for computation and visualization of three-dimensional unsteady flow fields are shown.

Jespersen, Dennis C.↗
NASA NTRS1989

Dimensionality of high temperature superconductivity in oxides

Many models have been proposed to account for the high temperature superconductivity observed in oxide systems. Almost all of these models proposed are based on the uncoupled low dimensional carrier Cu-O layers of the oxides. Results of several experiments are presented and discussed. They suggest that the high temperature superconductivity observed cannot be strictly two- or one-dimensional, and that the environment between the Cu-O layers and the interlayer coupling play an important role in the occurrence of such high temperature superconductivity. A comment on the very short coherence length reported is also made.

Chu, C. W.↗
NASA NTRS2023

The Impact of Dimensionality Reduction of Ion Counts Distributions on Preserving Moments, With Applications to Data Compression

The field of space physics has a long history of utilizing dimensionality reduction methods to distill data, including but not limited to spherical harmonics, the Fourier Transform, and the wavelet transform. Here, we present a technique for performing dimensionality reduction on ion counts distributions from the Multiscale Mission/Fast Plasma Investigation (MMS/FPI) instrument using a data-adaptive method powered by neural networks. This has applications to both feeding low-dimensional parameterizations of the counts distributions into other machine learning algorithms, and the problem of data compression to reduce transmission volume for space missions. The algorithm presented here is lossy, and in this work, we present the technique of validating the reconstruction performance with calculated plasma moments under the argument that preserving the moments also preserves fluid-level physics, and in turn a degree of scientific validity. The method presented here is an improvement over other lossy compressions in loss-tolerant scenarios like the Multiscale Mission/Fast Plasma Investigation Fast Survey or in non-research space weather applications.

D. da Silva↗
NASA NTRS1991

The attractor dimension of solar decimetric radio pulsations

The temporal characteristics of decimetric pulsations and related radio emissions during solar flares are analyzed using statistical methods recently developed for nonlinear dynamic systems. The results of the analysis is consistent with earlier reports on low-dimensional attractors of such events and yield a quantitative description of their temporal characteristics and hidden order. The estimated dimensions of typical decimetric pulsations are generally in the range of 3.0 + or - 0.5. Quasi-periodic oscillations and sudden reductions may have dimensions as low as 2. Pulsations of decimetric type IV continua have typically a dimension of about 4.

Kurths, J.↗
NASA NTRS2013

Nano-Ceramic Coated Plastics

Plastic products, due to their durability, safety, and low manufacturing cost, are now rapidly replacing cookware items traditionally made of glass and ceramics. Despite this trend, some still prefer relatively expensive and more fragile ceramic/glassware because plastics can deteriorate over time after exposure to foods, which can generate odors, bad appearance, and/or color change. Nano-ceramic coatings can eliminate these drawbacks while still retaining the advantages of the plastic, since the coating only alters the surface of the plastic. The surface coating adds functionality to the plastics such as self-cleaning and disinfectant capabilities that result from a photocatalytic effect of certain ceramic systems. These ceramic coatings can also provide non-stick surfaces and higher temperature capabilities for the base plastics without resorting to ceramic or glass materials. Titanium dioxide (TiO2) and zinc oxide (ZnO) are the candidates for a nano-ceramic coating to deposit on the plastics or plastic films used in cookware and kitchenware. Both are wide-bandgap semiconductors (3.0 to 3.2 eV for TiO2 and 3.2 to 3.3 eV for ZnO), so they exhibit a photocatalytic property under ultraviolet (UV) light. This will lead to decomposition of organic compounds. Decomposed products can be easily washed off by water, so the use of detergents will be minimal. High-crystalline film with large surface area for the reaction is essential to guarantee good photocatalytic performance of these oxides. Low-temperature processing (<100 C) is also a key to generating these ceramic coatings on the plastics. One possible way of processing nanoceramic coatings at low temperatures (< 90 C) is to take advantage of in-situ precipitated nanoparticles and nanostructures grown from aqueous solution. These nanostructures can be tailored to ceramic film formation and the subsequent microstructure development. In addition, the process provides environment- friendly processing because of the aqueous solution. Low-temperature processing has also shown versatility to generate various nanostructures. The growth of low-dimensional nanostructures (0-D, 1-D) provides a means of enhancing the crystallinity of the solution-prepared films that is of importance for photocatalytic performance. This technology can generate durable, fully functional nano-ceramic coatings (TiO2, ZnO) on plastic materials (silicone, Teflon, PET, etc.) that can possess both photocatalytic oxide properties and flexible plastic properties. Processing cost is low and it does not require any expensive equipment investment. Processing can be scalable to current manufacturing infrastructure.

Cho, Junghyun↗