Dense Motion Estimation for Smoke

Motion estimation for highly dynamic phenomena such as smoke is an open challenge for Computer Vision. Traditional dense motion estimation algorithms have difficulties with non-rigid and large motions, both of which are frequently observed in smoke motion. We propose an algorithm for dense motion estimation of smoke. Our algorithm is robust, fast, and has better performance over different types of smoke compared to other dense motion estimation algorithms, including state of the art and neural network approaches. The key to our contribution is to use skeletal flow, without explicit point matching, to provide a sparse flow. This sparse flow is upgraded to a dense flow. In this paper we describe our algorithm in greater detail, and provide experimental evidence to support our claims.Comment: ACCV201

The effective temperature

This review presents the effective temperature notion as defined from the deviations from the equilibrium fluctuation-dissipation theorem in out of equilibrium systems with slow dynamics. The thermodynamic meaning of this quantity is discussed in detail. Analytic, numeric and experimental measurements are surveyed. Open issues are mentioned.Comment: 58 page

Quantifizierung von Porosität, getrennten Scherwellenfelder der festen und flüssigen Phasen sowie Kopplungsdichte mittels Inversion-Recovery-Magnetresonanzelastographie in porösen Phantomen und In-vivo-Gehirnen

Magnetic resonance elastography (MRE) is an emerging noninvasive technique based on magnetic resonance imaging (MRI) and shear waves that depicts biomechanical properties of biological tissues. In MRE, quantitative parameter maps are usually reconstructed under the assumption of monophasic viscoelastic media. Conversely, the poroelastic model, consisting of a solid porous matrix permeated by a fluid, can better describe the behavior of multiphasic soft tissues, e.g., the brain. However, the assumption of two media and their interactions increases the complexity of the underlying motion equations, impeding their solution without independent information on fluid and solid wavefields and prior porosity quantification. Therefore, the aim of this thesis was threefold: 1) to develop an MRI method for determining porosity; 2) to develop an MRE method for separately encoding shear wave fields of fluid and solid fractions in biphasic tissues; and 3) to estimate coupling density ρ12 and thus experimentally validate the poroelastic model equations. Methods Inversion recovery MRI (IR-MRI) and IR-MRE are introduced for voxel-wise quantification of porosity, shear strain of solid and fluid compartments, and ρ12. Porosity was estimated in fluid phantoms of different relaxation times, fluid-solid tofu phantoms, and in in vivo, in the brains of 21 healthy volunteers. Reference values of phantom porosity were obtained by microscopy and draining the fluid from the matrix. Solid and fluid shear-strain amplitudes and ρ12 were quantified in three tofu phantoms and seven healthy volunteers. Results Phantom porosity measured by IR-MRI agreed well with reference values (R=0.99, P<.01). Average brain tissue porosity was 0.14–0.02 in grey matter and 0.05–0.01 in white matter (P<.001). Fluid shear strain was phase-locked with solid shear strain but had lower amplitudes in both phantoms and brains (P<.05). ρ12 was negative in all materials and biological tissues investigated. Conclusions IR-MRI for the first time allowed noninvasive mapping of in vivo brain porosity and yielded consistent results in tissue-mimicking phantoms. IR-MRI combined with IR-MRE allowed us to separately encode shear strain fields of solid and fluid motion in phantoms and human brain. This led to the quantification of coupling density ρ12, which was negative, as predicted. IR-MRE opens horizons for the development and application of novel imaging markers based on the poroelastic behavior of soft biological tissues. Moreover, quantification of subvoxel multicompartmental interactions provides insight into multiscale mechanical properties, which are potentially relevant for various diagnostic applications.Die Magnetresonanz-Elastographie (MRE) ist eine neuartige Technik, welche die Magnetresonanztomographie (MRT) mit Scherwellen kombiniert, um so die nichtinvasive Darstellung der biomechanischen Gewebeeigenschaften zu ermöglichen. In der MRE werden quantitative Parameterkarten von Weichgewebe unter der Annahme monophasischer, viskoelastischer Materialeigenschaften rekonstruiert. Das in dieser Arbeit verwendete poroelastische Modell hingegen berücksichtigt bei Weichgewebe wie dem Gehirn die Mehrphasigkeit des Gewebe bestehend aus einer festen porösen Matrix und flüssigen Kompartimenten. Deren unabhängige mechanische Eigenschaften und ihre Wechselwirkungen erhöhen die Komplexität der zugrundeliegenden Bewegungsgleichungen in der Poroelastographie, wodurch die Lösung ohne zusätzliche Informationen über die Wellenfelder und vorherige Quantifizierung der Gewebeporosität erschwert wird. Diese Arbeit hatte daher drei Ziele: 1) eine MRT-Methode zur Messung der Gewebeporosität zu entwickeln, 2) eine MRE-Methode zur getrennten Kodierung der Scherwellenfelder von flüssigen und festen Anteilen in biphasischen Geweben zu entwickeln, und 3) die Kopplungsdichte p12 zu bestimmen um so die biphasischen Modellgleichungen experimentell zu validieren. Methoden: Diese Arbeit stellt die Inversion-Recovery-MRT (IR-MRI) sowie die neuartige Inversion-Recovery-MRE (IR-MRE) vor, womit sich die Porosität, die Scherwellenauslenkung der festen und porösen flüssigen Phasen sowie die Kopplungsdichte p12 in Weichgeweben quantifizieren lassen. Porosität wurde in Flüssig-Phantomen unterschiedlicher Relaxationszeiten, Flüssig- Festkörper-Phantomen auf Tofubasis sowie in vivo im Gehirn bei 21 gesunden Probanden ermittelt. Referenzwerte der Porosität wurden in Phantomen durch Mikroskopie sowie Flüssigkeitsdrainage bestimmt. Feste und flüssige Scherauslenkungsamplituden und p12 wurden in drei Tofuphantomen und bei sieben gesunden Probanden quantifiziert. Ergebnisse: Die mittels IR-MRI gemessene Porosität der Phantome stimmte gut mit den Referenzwerten überein (R=0.99, P<.01). Die durchschnittliche Porosität der grauen und weißen Substanz betrug 0.14±0.02 und 0.05±0.01 (P<.001). Die Scherwellenamplituden der flüssigen Anteile und der festen Matrix waren phasengekoppelt, jedoch geringer in den flüssigen Anteilen (P<.05). p12 war in allen untersuchten Materialien und Geweben negativ. Schlussfolgerung: Mittels der IR-MRI konnten erstmals die Porosität von Hirngewebe in vivo nichtinvasiv abgebildet und die Konsistenz der Werte in gewebeähnlichen, porösen Phantomen nachgewiesen werden. Die Kombination von IR-MRI mit IR-MRE ermöglichte die getrennte Kodierung von Scherwellenfeldern fester und flüssiger Phasen und damit die Quantifizierung der Kopplungsdichte p12, welche, wie theoretisch vorhergesagt, negative Werte aufwies. Die IR-MRE eröffnet vielfältige Möglichkeiten zur Entwicklung und Anwendung neuartiger Bildgebungsmarker auf der Grundlage poroelastischer Kenngrößen von Weichgeweben und ermöglicht somit potenziell eine Vielzahl diagnostischer Anwendungen

MODELING OF AN AIR-BASED DENSITY SEPARATOR

There is a lack of fundamental studies by means of state of the art numerical and scale modeling techniques scrutinizing the theoretical and technical aspect of air table separators as well as means to comprehend and improve the efficiency of the process. The dissertation details the development of a workable empirical model, a numerical model and a scale model to demonstrate the use of a laboratory air table unit. The modern air-based density separator achieves effective density-based separation for particle sizes greater than 6 mm. Parametric studies with the laboratory scale unit using low rank coal have demonstrated the applicability with regards to finer size fractions of the range 6 mm to 1 mm. The statistically significant empirical models showed that all the four parameters, i.e, blower and table frequency, longitudinal and transverse angle were significant in determining the separation performance. Furthermore, the tests show that an increase in the transverse angle increased the flow rate of solids to the product end and the introduction of feed results in the dampening of airflow at the feed end. The higher table frequency and feed rate had a detrimental effect on the product yield due to low residence time of particle settlement. The research further evaluated fine particle upgrading using various modeling techniques. The numerical model was evaluated using K-Epsilon and RSM turbulence formulations and validated using experimental dataset. The results prove that the effect of fine coal vortices forming around the riffles act as a transport mechanism for higher density particle movement across the table deck resulting in 43% displacement of the midlings and 29% displacement of the heavies to the product side. The velocity and vector plots show high local variance of air speeds and pressure near the feed end and an increase in feed rate results in a drop in deshaling capability of the table. The table was further evaluated using modern scale-modeling concepts and the scaling laws indicated that the vibration velocity has an integral effect on the separation performance. The difference between the full-scale model and the scaled prototype was 3.83% thus validating the scaling laws

Separation of fluid and solid shear wave fields and quantification of coupling density by magnetic resonance poroelastography

Purpose: Biological soft tissues often have a porous architecture comprising fluid and solid compartments. Upon displacement through physiological or externally induced motion, the relative motion of these compartments depends on poroelastic parameters, such as coupling density (rho 12) and tissue porosity. This study introduces inversion recovery MR elastography (IR-MRE) (1) to quantify porosity defined as fluid volume over total volume, (2) to separate externally induced shear strain fields of fluid and solid compartments, and (3) to quantify coupling density assuming a biphasic behavior of in vivo brain tissue. Theory and Methods: Porosity was measured in eight tofu phantoms and gray matter (GM) and white matter (WM) of 21 healthy volunteers. Porosity of tofu was compared to values obtained by fluid draining and microscopy. Solid and fluid shear-strain amplitudes and rho 12were estimated both in phantoms and in in vivo brain. Results T-1-based measurement of tofu porosity agreed well with reference values (R = 0.99,P < .01). Brain tissue porosity was 0.14 ± 0.02 in GM and 0.05 ± 0.01 in WM (P < .001). Fluid shear strain was found to be phase-locked with solid shear strain but had lower amplitudes in both tofu phantoms and brain tissue (P < .05). In accordance with theory, tofu and brain rho 12were negative. Conclusion: IR-MRE allowed for the first time separation of shear strain fields of solid and fluid compartments for measuring coupling density according to the biphasic theory of poroelasticity. Thus, IR-MRE opens horizons for poroelastography-derived imaging markers that can be used in basic research and diagnostic applications

Cosmic inhomogeneities in the early Universe: A numerical relativity approach

Cosmic inflation is arguably the most favoured paradigm of the very early Universe. It postulates an early phase of fast, nearly exponential, and accelerated expansion. Inflationary models are capable of explaining the overall flatness and homogeneity of today's Universe at large scales. Despite being widely accepted by the physics community, these models are not absent from criticism. In scalar field inflation, a necessary condition to begin inflation is the requirement of a Universe dominated by the field's potential, which implies a subdominant contribution from the scalar field dynamics. This has originated to large amounts of scientific debate and literature on the naturalness, and possible fine-tuning of the initial conditions for inflation. Another controversial issue concerns the end of inflation, and the fact that a preheating mechanism is necessary to originate the hot big bang plasma after inflation. In this thesis, we present full general relativistic simulations to study these two problems, with a particular focus on the Starobinsky and Higgs models of inflation. First, we consider the fine-tuning problem of beginning inflation from a highly dynamical and inhomogeneous "preinflation" epoch in the single-field case. In our second study, we approach the multifield paradigm of preinflation, together and consistently, with the preheating phase. These investigations confirm the robustness of these inflationary models to generic initial conditions, while putting in evidence the non-negligible gravitational effects during preheating. At the end of the manuscript, we discuss potential applications of numerical simulations in cosmology, including our preliminary investigations on primordial black hole formation.Comment: PhD thesis of Cristian Joana defended in October 2022. Chapters 5 and 6 corresponds to articles arXiv:2011.12190 and arXiv:2202.07604, respectivel