UMD Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/3
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Item SCHLIEREN SEQUENCE ANALYSIS USING COMPUTER VISION(2013) Smith, Nathanial Timothy; Lewis, Mark J; Aerospace Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Computer vision-based methods are proposed for extraction and measurement of flow structures of interest in schlieren video. As schlieren data has increased with faster frame rates, we are faced with thousands of images to analyze. This presents an opportunity to study global flow structures over time that may not be evident from surface measurements. A degree of automation is desirable to extract flow structures and features to give information on their behavior through the sequence. Using an interdisciplinary approach, the analysis of large schlieren data is recast as a computer vision problem. The double-cone schlieren sequence is used as a testbed for the methodology; it is unique in that it contains 5,000 images, complex phenomena, and is feature rich. Oblique structures such as shock waves and shear layers are common in schlieren images. A vision-based methodology is used to provide an estimate of oblique structure angles through the unsteady sequence. The methodology has been applied to a complex flowfield with multiple shocks. A converged detection success rate between 94% and 97% for these structures is obtained. The modified curvature scale space is used to define features at salient points on shock contours. A challenge in developing methods for feature extraction in schlieren images is the reconciliation of existing techniques with features of interest to an aerodynamicist. Domain-specific knowledge of physics must therefore be incorporated into the definition and detec- tion phases. Known location and physically possible structure representations form a knowledge base that provides a unique feature definition and extraction. Model tip location and the motion of a shock intersection across several thousand frames are identified, localized, and tracked. Images are parsed into physically meaningful labels using segmentation. Using this representation, it is shown that in the double-cone flowfield, the dominant unsteady motion is associated with large scale random events within the aft-cone bow shock. Small scale organized motion is associated with the shock-separated flow on the fore-cone surface. We show that computer vision is a natural and useful extension to the evaluation of schlieren data, and that segmentation has the potential to permit new large scale measurements of flow motion.Item Experimental Characterization of Turbulent Superfluid Helium(2010) Paoletti, Matthew S.; Lathrop, Daniel P; Physics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Fundamental processes in turbulent superfluid 4He are experimentally characterized by refining a visualization technique recently introduced by Bewley et al. A mixture of hydrogen and helium gas is injected into the bulk fluid, which produces a distribution of micron-sized hydrogen tracer particles that are visualized and individually tracked allowing for local velocity measurements. Tracer trajectories are complex since some become trapped on the quantized vortices while others flow with the normal fluid. This technique is first applied to study the dynamics of a thermal counterflow. The resulting observations constitute the first direct confirmation of two-fluid motions in He II and provide a quantitative test of the expression for the dependence of the normal fluid velocity, vn, on the applied heat flux, q, derived by L. D. Landau in 1941. Nearly 20,000 individual reconnection events are identified for the first time and used to characterize the dynamics by the minimum separation distance, $delta(t)$, between two reconnecting vortices. Dimensional arguments predict that this separation behaves asymptotically as $delta(t) approx A left ( kappa vert t-t_0 vert right ) ^{1/2}$, where $kappa=h/m$ is the quantum of circulation. The major finding of the experiments is strong support for this asymptotic form with $kappa$ as the dominant controlling quantity. Nevertheless there are significant event-to-event fluctuations that are equally well fit by two modified expressions: (a) an arbitrary power-law expression $delta(t)=B vert t-t_0 vert ^{alpha}$ and (b) a correction-factor expression $delta(t)=Aleft (kappa vert t-t_0 vert right ) ^{1/2}(1+c vert t-t_0 vert )$. In light of various physical interpretations we regard the correction-factor expression (b), which attributes the observed deviations from the predicted asymptotic form to fluctuations in the local environment and boundary conditions, as best describing the experimental data. The observed dynamics appear statistically time-reversible, suggesting that an effective equilibrium has been established in quantum turbulence on the time scales investigated. The hydrogen tracers allow for the first measurements of the local velocity statistics of a turbulent quantum fluid. The distributions of velocity in the decaying turbulence are strongly non-Gaussian with 1/v3 power-law tails in contrast to the near-Gaussian statistics of homogenous and isotropic turbulence of classical fluids. The dynamics of many vortex reconnection events are examined and simple scaling arguments show that they yield the observed power-law tails.