Master of Science

thesisConsistency analysis and data collaboration is a relatively new scientific area. It deals with quantifying how well scientific models approximate empirical reality. Consistency analysis is based on methodically comparing model predictions with experimental measurements, but this task is made more difficult by the fact that both models and experiments have their own inherent uncertainties. Computational fluid dynamics (CFD) models are numerical methods able to solve complicated discrete fluid dynamics problems. They are used thoroughly in mechanical, aerospace and energy science. As CFD models are being applied to more and more critical systems, there is a growing need to improve the reliability of CFD model predictions. This work addresses this need by presenting consistency analysis results for a simple CFD model and an experiment in which the concentration field of a buoyant helium plume had been studied by holographic interferometry. A detailed procedure is presented for carrying out data collaboration between simulation and experimental data. This work is novel in a sense that it is the first to present the specific difficulties of collaborating interferometric data. These difficulties arise from the encoded nature of information being present in interferometric fringe images

The 2D Continuous Wavelet Transform: Applications in Fringe Pattern Processing for Optical Measurement Techniques

Optical metrology and interferometry are widely known disciplines that study and develop techniques to measure physical quantities such as dimensions, force, temperature, stress, etc. A key part of these disciplines is the processing of interferograms, also called fringe patterns. Owing that this kind of images contains the information of interest in a codified form, processing them is of main relevance and has been a widely studied topic for many years. Several mathematical tools have been used to analyze fringe patterns, from the classic Fourier analysis to regularization methods. Some methods based on wavelet theory have been proposed for this purpose in the last years and have evidenced virtues to consider them as a good alternative for fringe pattern analysis. In this chapter, we resume the theoretical basis of fringe pattern image formation and processing, and some of the most relevant applications of the 2D continuous wavelet transform (CWT) in fringe pattern analysis

Sonar Data Simulation

International audienceTherefore, the proposed chapter will first present such diversity in order to clearly understand the crucial needs for simulation and the involved consequences. Moreover, our goal is to keep all these descriptions along with existing methods and possibilities, within a common frame. Thus, responding to the presented needs,we have developed a framework for simulators allowing both underwater scene design and computational simulation engine choices. More precisely, this generic framework provides the reader with a common and simple software system in which various sensors, environments and computational engines can be plugged in. Subsequent sections of the chapter will then describe this common representation with all the phenomena to be considered and the problems to be answered in order to produce realistic simulated sonar data. We will introduce ray and tube engines in order to collect exhaustively all the backscattered acoustic waves resulting from scene interactions with the transmitting acoustic wave. This allows mainly imaging sonars to be simulated (sidescan, front-looking sonars), as only energy is considered for these engines. Another engine will then be introduced to allow the simulation of a full signal (both intensity and phase). The new resulting local signal/scene interactions will be explained and results shown through the simulation of an interferometry system. Finally, the chapter objectives are twofold: presenting a generic framework for simulation while dealing with actual, specific sensors features and chosen acoustic models

Anisotropic phase-map denoising using a regularized cost-function with complex-valued Markov-random-fields

In our recently reported work [1] (Villa et al., 2009) we derived a regularized quadratic-cost function, which includes fringe orientation information, for denosing fringe pattern images. In this work we adopt such idea for denoising wrapped phase-maps. We use a regularized cost-function that uses complex-valued Markov random fields (CMRFs) with orientation information of the filtering direction along isophase lines. The advantage of using an anisotropic filter along isophase lines is that phase and noise can be properly separated while 2 pi phase jumps are preserved even in high frequency zones. Apart from its robustness, the outstanding advantage of our method is its minimal computational effort. We present some results processing simulated and real phase-maps

2D Phase Unwrapping via Graph Cuts

Phase imaging technologies such as interferometric synthetic aperture radar (InSAR), magnetic resonance imaging (MRI), or optical interferometry, are nowadays widespread and with an increasing usage. The so-called phase unwrapping, which consists in the in- ference of the absolute phase from the modulo-2π phase, is a critical step in many of their processing chains, yet still one of its most challenging problems. We introduce an en- ergy minimization based approach to 2D phase unwrapping. In this approach we address the problem by adopting a Bayesian point of view and a Markov random field (MRF) to model the phase. The maximum a posteriori estimation of the absolute phase gives rise to an integer optimization problem, for which we introduce a family of efficient algo- rithms based on existing graph cuts techniques. We term our approach and algorithms PUMA, for Phase Unwrapping MAx flow. As long as the prior potential of the MRF is convex, PUMA guarantees an exact global solution. In particular it solves exactly all the minimum L p norm (p ≥ 1) phase unwrapping problems, unifying in that sense, a set of existing independent algorithms. For non convex potentials we introduce a version of PUMA that, while yielding only approximate solutions, gives very useful phase unwrap- ping results. The main characteristic of the introduced solutions is the ability to blindly preserve discontinuities. Extending the previous versions of PUMA, we tackle denoising by exploiting a multi-precision idea, which allows us to use the same rationale both for phase unwrapping and denoising. Finally, the last presented version of PUMA uses a frequency diversity concept to unwrap phase images having large phase rates. A representative set of experiences illustrates the performance of PUMA

High-speed 3D imaging of liquid jets, surfaces and respiratory droplets

Sprays are commonly found in, among other, combustion, agriculture and food processing. For each of these applications, the understanding of spray liquid dynamics is crucial for optimization of efficiency, accuracy, and robustness of the spray­-system in use. Sprays are also found as a collection of respiratory droplets ejected when people are speaking, yelling, coughing etc. that is one of the main transmission routes for viral disease in the recent COVID­19 pandemic. The experimental research performed on these sprays is often in 2D and not seldom on average data. However, the spray dynamics of interest acts in 3D space, during very short timescales and are stochastically unique. Here, instantaneous high-­speed 3D imaging is required to fully characterize these events.This thesis applies and analyses three different laser­-based instantaneous high­-speed 3D imaging techniques on three different liquid dynamics. These include, (1) volumetric Laser Induced Fluorescence (LIF) imaging of liquid jets, (2) LIF structured illumination for surface 3D reconstruction of a liquid hollow cone sheet and (3) stereoscopic particle tracking velocimetry of respiratory droplets. The volumetric imaging was found to be challenging because of refractive effects at the liquid­-air interface. The structured illumination 3D reconstruction technique managed to reconstruct a transient 3D event where liquid breakups, ruptures, surface ­waves, and ejection angles were extracted. Simulations found that the used reconstruction was accurate to below 1% of the structure and could resolve small surface waves with a height up to 65% of the theoretical limit. Finally, the stereoscopic imaging extracted 3D tracks of respiratory droplets with found experimental average speed uncertainties around 0.3 m/s. In addition, this experiment enabled simultaneous estimation of speed and size of respiratory droplets that give valuable information on the risks of disease spreading.The presented instantaneous high­-speed 3D reconstruction techniques can provide data that paves the way towards a deeper understanding of liquid dynamics in general and sprays in particular. The data is advantageous partly since it can be directly applied by modellers to improve and validate their simulations. In the future, both more validation and application of the presented techniques are required which is enabled by the open-­sourced software and data that this thesis provides

New Techniques for Coherence Imaging Fusion Plasmas

Imaging diagnostic techniques are desirable for fusion plasma experiments for their wide coverage and high spatial resolution, which allows for a more complete comparison with the predictions made by plasma physics models than traditional techniques. Benchmarking models against measurements made on current experiments improves our understanding of the physics and reduces the uncertainties involved with designing future experiments and reactors. This thesis presents new techniques for coherence imaging (CI), an interferometric narrowband spectral imaging technique used to measure the brightness, shift and width of spectral lines emitted by the plasma in the visible range. From these measurements, 2-D maps of emitting species flow velocity, and temperature can be inferred via Doppler shifts and broadening respectively. For passive hydrogen Balmer series emission in the tokamak divertor, Stark broadening is strong enough to provide a 2-D map of electron density $n_e$. First, we introduce novel CI instrument designs based on pixelated phase-mask (PPM) interferometry, which improve spatial resolution and robustness over typical linear carrier designs. Secondly, we introduce a new method for absolute calibration of CI flow velocity measurements using emission lines from standard gas-discharge lamps instead of a tuneable laser. This method significantly reduces hardware costs while maintaining high measurement accuracy — ±1 km/s compared to typical ion flows in the tokamak plasma edge of < 30 km/s. Lastly, we present improved methods for CI measurement of ne, using modern lineshape models to improve accuracy and using a multi-delay PPM-CI instrument design to minimise errors caused by Doppler broadening, extending the valid measurement range to lower $n_e$. This is demonstrated with experimental measurements of H$_\gamma$ and H$_\delta$ emission on the Magnum-PSI linear plasma experiment with a direct comparison to Thomson scattering measurements