Machine Learning for Fluid Mechanics

The field of fluid mechanics is rapidly advancing, driven by unprecedented volumes of data from field measurements, experiments and large-scale simulations at multiple spatiotemporal scales. Machine learning offers a wealth of techniques to extract information from data that could be translated into knowledge about the underlying fluid mechanics. Moreover, machine learning algorithms can augment domain knowledge and automate tasks related to flow control and optimization. This article presents an overview of past history, current developments, and emerging opportunities of machine learning for fluid mechanics. It outlines fundamental machine learning methodologies and discusses their uses for understanding, modeling, optimizing, and controlling fluid flows. The strengths and limitations of these methods are addressed from the perspective of scientific inquiry that considers data as an inherent part of modeling, experimentation, and simulation. Machine learning provides a powerful information processing framework that can enrich, and possibly even transform, current lines of fluid mechanics research and industrial applications.Comment: To appear in the Annual Reviews of Fluid Mechanics, 202

Mapping the Substrate of Atrial Fibrillation: Tools and Techniques

Atrial fibrillation (AF) is the most common cardiac arrhythmia that affects an estimated 33.5 million people worldwide. Despite its prevalence and economic burden, treatments remain relatively ineffective. Interventional treatments using catheter ablation have shown more success in cure rates than pharmacologic methods for AF. However, success rates diminish drastically in patients with more advanced forms of the disease. The focus of this research is to develop a mapping strategy to improve the success of ablation. To achieve this goal, I used a computational model of excitation in order to simulate atrial fibrillation and evaluate mapping strategies that could guide ablation. I first propose a substrate guided mapping strategy to allow patient-specific treatment rather than a one size fits all approach. Ablation guided by this method reduced AF episode durations compared to baseline durations and an equal amount of random ablation in computational simulations. Because the accuracy of electrogram mapping is dependent upon catheter-tissue contact, I then provide a method to identify the distance between the electrode recording sites and the tissue surface using only the electrogram signal. The algorithm was validated both in silico and in vivo. Finally, I develop a classification algorithm for the identification of activation patterns using simultaneous, multi-site electrode recordings to aid in the development of an appropriate ablation strategy during AF. These findings provide a framework for future mapping and ablation studies in humans and assist in the development of individualized ablation strategies for patients with higher disease burden

A Deep Chandra ACIS Study of NGC 4151. I. the X-ray Morphology of the 3 kpc-diameter Circum-nuclear Region and Relation to the Cold Interstellar Medium

We report on the imaging analysis of 200 ks sub-arcsecond resolution Chandra ACIS-S observations of the nearby Seyfert 1 galaxy NGC 4151. Bright, structured soft X-ray emission is observed to extend from 30 pc to 1.3 kpc in the south-west from the nucleus, much farther than seen in earlier X-ray studies. The terminus of the north-eastern X-ray emission is spatially coincident with a CO gas lane, where the outflow likely encounters dense gas in the host galactic disk. X-ray emission is also detected outside the boundaries of the ionization cone, which indicates that the gas there is not completely shielded from the nuclear continuum, as would be the case for a molecular torus collimating the bicone. In the central r<200 pc region, the subpixel processing of the ACIS data recovers the morphological details on scales of <30~pc (<0.5") first discovered in Chandra HRC images. The X-ray emission is more absorbed towards the boundaries of the ionization cone, as well as perpendicular to the bicone along the direction of a putative torus in NGC 4151. The innermost region where X-ray emission shows the highest hardness ratio, is spatially coincident with the near-infrared resolved H_2 emission and dusty spirals we find in an HST V-H color image. The agreement between the observed H_2 line flux and the value predicted from X-ray-irradiated molecular cloud models supports photo-excitation by X-rays from the active nucleus as the origin of the H_2 line, although contribution from UV fluorescence or collisional excitation cannot be fully ruled out with current data. The discrepancy between the mass of cold molecular gas inferred from recent CO and near-infrared H_2 observations may be explained by the anomalous CO abundance in this X-ray dominated region. The total H_2 mass derived from the X-ray observation agrees with measurement in Storchi-Bergmann et al.Comment: 33 pages, 9 figures and 2 table

Very High Angular Resolution Science with the Square Kilometre Array

Preliminary specifications for the Square Kilometre Array (SKA) call for 25% of the total collecting area of the dish array to be located at distances greater than 180 km from the core, with a maximum baseline of at least 3000 km. The array will provide angular resolution ~ 40 - 2 mas at 0.5 - 10 GHz with image sensitivity reaching < 50 nJy/beam in an 8 hour integration with 500 MHz bandwidth. Given these specifications, the high angular resolution component of the SKA will be capable of detecting brightness temperatures < 200 K with milliarcsecond-scale angular resolution. The aim of this article is to bring together in one place a discussion of the broad range of new and important high angular resolution science that will be enabled by the SKA, and in doing so, address the merits of long baselines as part of the SKA. We highlight the fact that high angular resolution requiring baselines greater than 1000 km provides a rich science case with projects from many areas of astrophysics, including important contributions to key SKA science.Comment: 13 pages, 6 figure

COBE's search for structure in the Big Bang

The launch of Cosmic Background Explorer (COBE) and the definition of Earth Observing System (EOS) are two of the major events at NASA-Goddard. The three experiments contained in COBE (Differential Microwave Radiometer (DMR), Far Infrared Absolute Spectrophotometer (FIRAS), and Diffuse Infrared Background Experiment (DIRBE)) are very important in measuring the big bang. DMR measures the isotropy of the cosmic background (direction of the radiation). FIRAS looks at the spectrum over the whole sky, searching for deviations, and DIRBE operates in the infrared part of the spectrum gathering evidence of the earliest galaxy formation. By special techniques, the radiation coming from the solar system will be distinguished from that of extragalactic origin. Unique graphics will be used to represent the temperature of the emitting material. A cosmic event will be modeled of such importance that it will affect cosmological theory for generations to come. EOS will monitor changes in the Earth's geophysics during a whole solar color cycle

Approximating nonequilibrium processes using a collection of surrogate diffusion models

The surrogate process approximation (SPA) is applied to model the nonequilibrium dynamics of a reaction coordinate (RC) associated with the unfolding and refolding processes of a deca-alanine peptide at 300 K. The RC dynamics, which correspond to the evolution of the end-to-end distance of the polypeptide, are produced by steered molecular dynamics (SMD) simulations and approximated using overdamped diffusion models. We show that the collection of (estimated) SPA models contain structural information "orthogonal" to the RC monitored in this study. Functional data analysis ideas are used to correlate functions associated with the fitted SPA models with the work done on the system in SMD simulations. It is demonstrated that the shape of the nonequilibrium work distributions for the unfolding and refolding processes of deca-alanine can be predicted with functional data analysis ideas using a relatively small number of simulated SMD paths for calibrating the SPA diffusion models.Comment: 13 pages, 7 figure

Time domain analysis of switching transient fields in high voltage substations

Switching operations of circuit breakers and disconnect switches generate transient currents propagating along the substation busbars. At the moment of switching, the busbars temporarily acts as antennae radiating transient electromagnetic fields within the substations. The radiated fields may interfere and disrupt normal operations of electronic equipment used within the substation for measurement, control and communication purposes. Hence there is the need to fully characterise the substation electromagnetic environment as early as the design stage of substation planning and operation to ensure safe operations of the electronic equipment. This paper deals with the computation of transient electromagnetic fields due to switching within a high voltage air-insulated substation (AIS) using the finite difference time domain (FDTD) metho