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We present a new method for resolving three-dimensional (3D) fluid velocity fields using a technique called synthetic aperture particle image velocimetry (SAPIV). By fusing methods from the imaging community pertaining to light field imaging with concepts that drive experimental fluid mechanics, SAPIV overcomes many of the inherent challenges of 3D particle image velocimetry (3D PIV). This method offers the ability to digitally refocus a 3D flow field at arbitrary focal planes throughout a volume. The viewable out-of-plane dimension (Z) can be on the same order as the viewable in-plane dimentions (X-Y), and these dimensions can be scaled from tens to hundreds of millimeters. Furthermore, the digital refocusing provides the ability to 'see-through' partial occlusions, enabling measurements in densely seeded volumes. The advantages are achieved using a camera array (typically at least five cameras) to image the seeded fluid volume. The theoretical limits on refocused plane spacing and viewable depth are derived and explored as a function of camera optics and spacing of the array. A geometric optics model and simulated PIV images are used to investigate system performance for various camera layouts, measurement volume sizes and seeding density; performance is quantified by the ability to reconstruct the 3D intensity field, and resolve 3D vector fields in densely seeded simulated flows. SAPIV shows the ability to reconstruct fields with high seeding density and large volume size. Finally, results from an experimental implemnetation of SAPIV using a low cost eight-camer aarray to study a vortex ring in a 65 x 40 x32 mm3 volume are presented. The 3D PIV results are compared with 2D PIV data to demonstrate the capability of the 3D SAPIV technique.
This thesis presents a numerical study of the effects of radial image distortion and spherical aberration on reconstruction quality of synthetic aperture particle image velocimetry (SAPIV) measurements. A simulated SAPIV system is used to image a synthetic particle volume. An idealized pinhole camera model is used for image formation with distortion and spherical aberration being added with a polynomial model and a Fourier waveform model, respectively. Images from a simulated 5 x 5 camera array are taken, distorted and/or aberrated, realigned and averaged to form synthetic aperture images at a set of depths within the particle volume. These images are thresholded to recover three-dimensional particle locations and a reconstructed three-dimensional intensity field is formed. This reconstructed field is then evaluated according to intensity data and a signal-to-noise ratio (SNR). Results show that even small amounts of image distortion and spherical aberration can lead to degradation of SNR and information loss.
Fluid mechanics and instrumentation have a long history together, as experimental fluids studies play an important role in describing a more complete physical picture in a variety of problems. Presently. state-of-the-art instruments for fluid flows aim to resolve various quantities in three-dimensions. This thesis describes a novel three dimensional imaging system intended to extend laboratory measurement capabilities in complicated flows where knowledge is incomplete. In particular, the imaging system is designed to perform three-dimensional velocimetry in densely seeded flows where object geometry may partially occlude the field as well as to measure and locate bubbles, droplets and particles in three-dimensions in multiphase flows. An instrument of this kind has ramifications in a variety of engineering applications from air-sea interaction to Naval hydrodynamics to turbulence and beyond. The imaging system is based upon synthetic aperture (SA) imaging, which has received much attention in the computer vision community recently. In focus images from an array of synchronized cameras are recombined in software post-capture using a refocusing algorithm to generate a focal stack of synthetic images. Each synthetic image has a narrow depth of field, and objects residing at this depth appear sharp while off-plane objects appear blurred. The refocusing algorithm not only allows for 3D reconstruction of a scene, but also enables "see-through" effects, whereby an object occluded in some of the camera views will be seen in the synthetic images. In this thesis, considerations for development of a three-dimensional measurement system for fluid flows based on the SA imaging field are made. A high-performance three-dimensional particle image velocimetry technique is described and validated. Also, a method for auto-calibration of mutli-camera setups for fluids experiments is derived and developed. Finally, algorithms are generated for application to multiphase flows and the technique is applied to a circular plunging jet with results showing excellent agreement to prior literature and yielding new insight into the problem.
3D visualization of fluid flow is of critical significance to a number of applications ranging from micro-scale medical devices to design of ships and airplanes. Of the various techniques currently used to visualize flow fields, particle image velocimetry (PIV) offers great advantages because of the high resolution quantitative results it provides. The feasibility of using synthetic aperture (SA) imaging to conduct 3D Particle Image Velocimetry (PIV) has been previously demonstrated. This thesis presents the development of a technique that extends SA imaging to 3D Particle Tracking Velocimetry (PTV), adding the ability to conduct Lagrangian studies on flow fields over time. A new method has been developed to accurately locate seeding particles in volumes reconstructed using SA imaging, based on a proposed thresholding and average intensity based scheme, which is able to locate particles in densely seeded flows. In addition, a new and much faster method for reconstructing volumes, based on a homography fit (HF) refocusing method, is proposed which facilitates rapid processing of large amounts of data recorded using high speed cameras for example. The capability of using SA imaging to conduct PTV is demonstrated by tracking located particles using the relaxation based algorithm. The developed technique provides accurate and high resolution PTV results at a much higher computation speed compared to other state of the art techniques. If engineered further,the presented technique has the potential to become the method of choice to conduct velocimetry.
This immensely practical guide to PIV provides a condensed, yet exhaustive guide to most of the information needed for experiments employing the technique. This second edition has updated chapters on the principles and extra information on microscopic, high-speed and three component measurements as well as a description of advanced evaluation techniques. What’s more, the huge increase in the range of possible applications has been taken into account as the chapter describing these applications of the PIV technique has been expanded.
Particle image velocimetry, or PIV, refers to a class of methods used in experimental fluid mechanics to determine instantaneous fields of the vector velocity by measuring the displacements of numerous fine particles that accurately follow the motion of the fluid. Although the concept of measuring particle displacements is simple in essence, the factors that need to be addressed to design and implement PIV systems that achieve reliable, accurate, and fast measurements and to interpret the results are surprisingly numerous. The aim of this book is to analyze and explain them comprehensively.
The Particle Image Velocimetry is undoubtedly one of the most important technique in Fluid-dynamics since it allows to obtain a direct and instantaneous visualization of the flow field in a non-intrusive way. This innovative technique spreads in a wide number of research fields, from aerodynamics to medicine, from biology to turbulence researches, from aerodynamics to combustion processes. The book is aimed at presenting the PIV technique and its wide range of possible applications so as to provide a reference for researchers who intended to exploit this innovative technique in their research fields. Several aspects and possible problems in the analysis of large- and micro-scale turbulent phenomena, two-phase flows and polymer melts, combustion processes and turbo-machinery flow fields, internal waves and river/ocean flows were considered.
This book constitutes the refereed proceedings of the First International Conference on Dynamic Data-Driven Environmental Systems Science, DyDESS 2014, held in Cambridge, MA, USA, in November 2014.The 24 revised full papers and 7 short papers were carefully reviewed and selected from 62 submissions and cover topics on sensing, imaging and retrieval for the oceans, atmosphere, space, land, earth and planets that is informed by the environmental context; algorithms for modeling and simulation, downscaling, model reduction, data assimilation, uncertainty quantification and statistical learning; methodologies for planning and control, sampling and adaptive observation, and efficient coupling of these algorithms into information-gathering and observing system designs; and applications of methodology to environmental estimation, analysis and prediction including climate, natural hazards, oceans, cryosphere, atmosphere, land, space, earth and planets.
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