Dynamic Adaptive Real-Time Particle Image Velocimetry

Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (pages 65-67).Particle Image Velocimetry (PIV) is a technique that allows for the detailed visualization of fluid flow. By performing computational analysis on images taken by a high-sensitivity camera that monitors the movement of laser-illuminated tracer particles over time, PIV is capable of producing a vector field describing instantaneous velocity measurements of the fluid captured in the field of view. Nearly all PIV implementations perform offline processing of the collected data, a feature that limits the scope of the applications of this technique. Recently, however, researchers have begun to explore the possibility of using FPGAs or PCs to greatly improve the efficiency of these algorithms in order to obtain real-time speeds for use in feedback loops. Such approaches are very promising and can help expand the use of PIV into previously unexplored fields, such as high performance Unmanned Aerial Vehicles (UAVs). Yet these real-time algorithms have the potential to be improved even further. This thesis outlines an approach to make real-time PIV algorithms more accurate and versatile in large part by applying principles from another emerging technique called adaptive PIV, and in doing so will also address new issues created from the conversion of traditional PIV to a real-time context. This thesis also documents the implementation of this Dynamic Adaptive Real- Time PIV (DARTPIV) algorithm on a PC with CUDA parallel computing, and its performance and results analyzed in the context of normal real-time PIV.by Samvaran Sharma.M. Eng

Dual beam swept source optical coherence tomography for microfluidic velocity measurements

Microfluidic flows are an increasing area of interest used for “lab-on-a-chip” bioanalytical techniques, drug discovery, and chemical processing. This requires optical, non-invasive flow-visualization techniques for characterising microfluidic flows. Optical Coherence Tomography (OCT) systems can provide three-dimensional imaging through reasonably-opaque materials with micrometre resolution, coupled to a single optical axis point using optical fibre cables. Developed for imaging the human eye, OCT has been used for the detection of skin cancers and endoscopically in the human body. Industrial applications are growing in popularity including for the monitoring of bond-curing in aerospace, for production-line non-destructive-testing, and for medical device manufacturing and drug encapsulation monitoring. A dual beam Optical Coherence Tomography system has been developed capable of simultaneously imaging microfluidic channel structures, and tracking particles seeded into the flow to measure high velocity flows, using only a single optical access point. This is achieved via a dual optical fibre bundle for light delivery to the sample and a custom high-speed dual channel OCT instrument using an akinetic sweep wavelength laser. The system has 10 μm resolution in air and a sweeping rate of 96 kHz. This OCT system was used to monitor microfluidic flows in 800 μm deep test chips and Poiseuille flows were observed

Real-Time Background Oriented Schlieren: Catching Up With Knife Edge Schlieren

Background Oriented Schlieren (BOS) is a widely used technique that provides density gradient information in flow fields of interest, without imposing stringent optical quality requirements on the facility/experiment windows and/or optics used in the BOS setup. Typically, the BOS reference image is acquired before the test begins (flow off) and then the "live" image data are acquired during the actual testing/experiment (flow on). The raw BOS image data, while displayed in real-time as they are acquired from the camera, unfortunately provide little if any visual indication of the density gradients in the flow. Generally, the "live" images must be processed off-line after the testing is completed, providing no indication of the success of the BOS setup and no feedback on the operational success of the test. Advances in computer processing hardware enables the implementation of real-time processing and display of the BOS image data. Two different approaches to implementing the real-time BOS (RT-BOS) processing capability are described herein. First, a traditional multi-core Central Processing Unit (CPU) based approach using scheduled parallel threads is used to build a RT-BOS processing engine. In the second approach, a Graphical Processing Unit (GPU) approach is used to costruct a RT-BOS processing engine. Generally, high core count CPU processors can provide a useful processing rate for RT-BOS. However, the GPU based approach exceeds the processing capability of the CPU approach, at a fraction of the cost. The GPU approach places no restrictions on the Host PC processing capability, except that it be capable of acquiring the BOS image data from the camera in real-time

Real-Time Riverine Particle Image Velocimetry

A modular particle image velocimetry program was developed and optimized to read and process video of river surface flows from different sensor types. The program was designed for long-term deployment with the ability to sample data continuously in realtime and save the results in a compact format. The time needed to compute a velocity measurement from video input was reduced by using concurrent processing techniques, multi-threading, and a graphics hardware-based correlation algorithm. When used to process field data on a low power Intel Atom based computer the PIV system was capable of computing up to 64 velocity measurements at a rate of 7.5 frames per second. A more powerful computer equipped with a discrete GPU was capable of computing 4800 velocity measurements at a rate of 7.5 frames per second when using the same PIV data and settings. Processing speed of the GPU correlation module was analyzed using a number of different benchmarks. Results show that the GPU-based correlation algorithm has the potential to improve the PIV processing speed of high-end workstations by as much as 2x and low-end portable computers by 10-20x. Methods were also introduced to improve the quality of PIV measurements on river currents. Processing video of river currents with the standard particle image velocimetry technique produced a large number of inaccurate vectors. Most of these inaccurate vectors were correctly identified and removed by using different confidence scoring and filtering techniques. Results from three different experiments were compared to the velocity measurements of other devices to verify the accuracy of the program. These measurements agree to within 16% difference. These results show that accurate PIV measurements of river surface velocity may be computed in real time even on low end and portable computer hardware

Experimental results and three-dimensional simulations of instabilities in a rotating lid-driven cylinder

An experimental setup for a rotating lid-driven cylinder problem is designed and constructed in the context of modeling bulk semiconductor crystal growth techniques. Details concerning construction of the experimental setup are included in the interest of reproducibility. Ultrasonic Doppler Velocimetry (UDV) is tested as a viable visualization technique for the lid-driven cylinder and experimental measurements of the flow field are compared to numerical simulations. The aspect ratio of the cylinder and the Reynolds number are the governing parameters for the problem. Experimental and computation results are presented for aspect ratio of 2.5 and Reynolds numbers up to 3000. Accurate UDV measurements of the steady, axisymmetric base flow are demonstrated for both water and a 20% glycerin-water mixture as the working fluid. The expected periodic, axisymmetric instability at Reynolds number of 3000 was unobserved by the UDV. However, related instabilities were observed at lower Reynolds numbers. Associated strengths and weaknesses of UDV for flow measurement are discussed

Towards real-time reconstruction of velocity fluctuations in turbulent channel flow

We develop a framework for efficient streaming reconstructions of turbulent velocity fluctuations from limited sensor measurements with the goal of enabling real-time applications. The reconstruction process is simplified by computing linear estimators using flow statistics from an initial training period and evaluating their performance during a subsequent testing period with data obtained from direct numerical simulation. We address cases where (i) no, (ii) limited, and (iii) full-field training data are available using estimators based on (i) resolvent modes, (ii) resolvent-based estimation, and (iii) spectral proper orthogonal decomposition modes. During training, we introduce blockwise inversion to accurately and efficiently compute the resolvent operator in an interpretable manner. During testing, we enable efficient streaming reconstructions by using a temporal sliding discrete Fourier transform to recursively update Fourier coefficients using incoming measurements. We use this framework to reconstruct with minimal time delay the turbulent velocity fluctuations in a minimal channel at ${\rm Re}_\tau \approx 186$ from sparse planar measurements. We evaluate reconstruction accuracy in the context of the extent of data required and thereby identify potential use cases for each estimator. The reconstructions capture large portions of the dynamics from relatively few measurement planes when the linear estimators are computed with sufficient fidelity. We also evaluate the efficiency of our reconstructions and show that the present framework has the potential to help enable real-time reconstructions of turbulent velocity fluctuations in an analogous experimental setting.Comment: 36 pages, 22 figures, accepted by Physical Review Fluid

2020 NASA Technology Taxonomy

This document is an update (new photos used) of the PDF version of the 2020 NASA Technology Taxonomy that will be available to download on the OCT Public Website. The updated 2020 NASA Technology Taxonomy, or "technology dictionary", uses a technology discipline based approach that realigns like-technologies independent of their application within the NASA mission portfolio. This tool is meant to serve as a common technology discipline-based communication tool across the agency and with its partners in other government agencies, academia, industry, and across the world

Control of underactuated fluid-body systems with real-time particle image velocimetry

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 141-153).Controlling the interaction of a robot with a fluid, particularly when the desired behavior is intimately related to the dynamics of the fluid, is a difficult and important problem. High-performance aircraft cannot ignore nonlinear stall effects, and robots hoping to fly and swim with performance matching that seen in birds and fish cannot treat fluid flows as quasi-steady. If we wish to match the level of performance seen in nature several major hurdles must be overcome, with one of the most difficult being the poor observability of the fluid state. Fluid dynamicists have long contended with this observability problem, and have used computationally intensive Particle Image Velocimetry (PIV) to gain an understanding of the fluid behavior after the fact. However, improvement in available computational power is now making it possible to perform PIV in real-time. When PIV provides real-time awareness of the fluid state it is no longer just an analysis tool, but rather a valuable sensor that can be integrated into the control loop. In this thesis I present methods for controlling fluid-body systems in which the fluid plays a vital dynamical role, for performing real-time PIV, and for interpreting the output of PIV in a manner useful to control. The utility of these methods is demonstrated on a mechanically simple but dynamically rich experimental platform: the hydrodynamic cartpole. This system is analogous to the well-known cart-pole system in the controls literature, but through its relationship with the surrounding fluid it captures many of the fundamental challenges of general fluid-body control tasks, including: nonlinearity, underactuation, an important and unknown fluid state and a dearth of accurate and tractable models. The first complete demonstration of closed-loop PIV control is performed on this system, and there is a statistically significant improvement in the system's ability to reject fluid disturbances when using real-time PIV for closed-loop control. These results suggest that these new techniques will push the boundaries of what we can expect a robot in a fluid to do.by John W. Roberts.Ph.D

Selected Papers from the 9th World Congress on Industrial Process Tomography

Industrial process tomography (IPT) is becoming an important tool for Industry 4.0. It consists of multidimensional sensor technologies and methods that aim to provide unparalleled internal information on industrial processes used in many sectors. This book showcases a selection of papers at the forefront of the latest developments in such technologies