[pt] Foi desenvolvido um sistema de mediação de campo completo de velocidade de escoamento de fluidos. A técnica empregada é conhecida como Particle Tracking Velocimetry (PTV). As medidas foram determinadas a partir de imagens de trajetórias de partículas em suspensão no fluido. As imagens foram digitalizadas e processadas automaticamente em um microcomputador. O processamento foi feito por um software dedicado que identifica as trajetórias e calcula as velocidades associadas. Para comparação dos resultados obtidos o sistema desenvolvido foi aplicado a um escoamento cujo perfil de velocidade é conhecido. Foram analisadas as influências nos resultados de características das imagens e de seu processamento. / [en] A system for full field velocity measurement in fluid flows has been developed. The technique employed is known as Particle Tracking Velocimetry (PTV). Velocity measurements have been performed based on images of particles seeded in the fluid. The images have been digitized and automatically processed in a micro-computer. Image processing tecniques have been employed using a dedicated software that identifies particles trajectories and calculates associated velocities. To compare the results obtained, the system developed was applied to test flows with known velocity profiles. A detailed uncertainty analisys developed revealed the influence. On the results. of the image characteristics and processing procedures.

The objective of this research is to evaluate a coastal prediction system under various real world scenarios to test the efficacy of the system as a management tool in Tampa Bay. The prediction system, comprised of a three-dimensional numerical circulation model and a Lagrangian based particle tracking model, simulates oceanographic scenarios in the bay for past (hindcast), present (nowcast) and future (forecast) time frames. Instantaneous velocity output from the numerical circulation model drives the movement of particles, each representing a fraction of the total material, within the model grid cells. This work introduces a probability calculation that allows for rapid analysis of bay-wide particle transport. At every internal time step a ratio between the number of particles in each individual model grid cell to the total number of particles in the entire model domain is calculated. These ratios, herein called transport quotients, are used to construct probability maps showing locations in Tampa Bay most likely to be impacted by the contaminant. The coastal prediction system is first evaluated using dimensionless particles during an anhydrous ammonia spill. In subsequent studies biological and chemical characteristics are incorporated into the transport quotient calculations when constructing probability maps. A salinity tolerance is placed on particles representing Karenia brevis during hindcast simulations of a harmful algal bloom in the bay. Photobleaching rates are incorporated into probability maps constructed from hindcast simulations of seasonal colored dissolved organic matter (CDOM) transport. The coastal prediction system is made more robust with the inclusion of biological parameters overlaid on top of the circulation dynamics. The system successfully describes the basic physical mechanisms underlying the transport of contaminants in the bay under various real world scenarios. The calculation of transport quotients during the simulations in order to develop probability maps is a novel concept when simulating particle transport but one which can be used in real-time to support the management decisions of environmental agencies in the bay area.

L'objet de cette thèse est l'étude quantitative du mouvement des particules intracellulaires, comme les protéines ou les molécules. L'estimation du mouvement des particules au sein de la cellule est en effet d'un intérêt majeur en biologie cellulaire puisqu'il permet de comprendre les interactions entre les différents composants de la cellule. Dans cette thèse, nous modélisons les trajectoires des particules avec des processus stochastiques puisque le milieu intra-cellulaire est soumis à de nombreux aléas. Les diffusions, des processus à trajectoires continues, permettent de modéliser un large panel de mouvements intra-cellulaires. Les biophysiciens distinguent trois principaux types de diffusion: le mouvement brownien, la super-diffusion et la sous-diffusion. Ces différents types de mouvement correspondent à des scénarios biologiques distincts. Le déplacement d'une particule évoluant sans contrainte dans le cytosol ou dans le plasma membranaire est modélisée par un mouvement brownien; la particule ne se déplace pas dans une direction précise et atteint sa destination en un temps long en moyenne. Les particules peuvent aussi être propulsées par des moteurs moléculaires le long des microtubules et filaments d'actine du cytosquelette de la cellule. Leur mouvement est alors modélisé par des super-diffusions. Enfin, la sous-diffusion peut être observée dans deux situations: i/ lorsque la particule est confinée dans un micro domaine, ii/ lorsqu’elle est ralentie par l'encombrement moléculaire et doit se frayer un chemin parmi des obstacles mobiles ou immobiles. Nous présentons un test statistique pour effectuer la classification des trajectoires en trois groupes: brownien, super-diffusif et sous-diffusif. Nous développons également un algorithme pour détecter les ruptures de mouvement le long d’une trajectoire. Nous définissons les temps de rupture comme les instants où la particule change de régime de diffusion (brownien, sous-diffusif ou super-diffusif). Enfin, nous associons une méthode de regroupement avec notre procédure de test pour identifier les micro domaines dans lesquels des particules sont confinées. De telles zones correspondent à des lieux d’interactions moléculaires dans la cellule. / In this thesis, we are interested in quantifying the dynamics of intracellular particles, as proteins or molecules, inside living cells. In fact, inference on the modes of mobility of molecules is central in cell biology since it reflects the interactions between the structures of the cell. We model the particle trajectories with stochastic processes as the interior of a living cell is a fluctuating environment. Diffusions are stochastic processes with continuous paths and can model a large range of intracellular movements. Biophysicists distinguish three main types of diffusions, namely Brownian motion, superdiffusion and subdiffusion. These different diffusion processes correspond to distinct biological scenarios. A particle evolving freely inside the cytosol or along the plasma membrane is modelled by Brownian motion; the particle does not travel along any particular direction and can take a very long time to go to a precise area in the cell. Active intracellular transport can overcome this difficulty so that motion is faster and direct specific. In this case, particles are carried by molecular motors along microtubular filament networks and their motion is modelled with superdiffusions. Subdiffusion can be observed in two cases i/ when the particle is confined in a microdomain, ii/ when the particle is hindered by molecular crowding and encounters dynamic or fixed obstacles. We develop a statistical test for classifying the observed trajectories into the three groups of diffusion of interest namely Brownian motion, super-diffusion and subdiffusion. We also design an algorithm to detect the changes of dynamics along a single trajectory. We define the change points as the times at which the particle switches from one diffusion type (Brownian motion, superdiffusion or subdiffusion) to another. Finally, we combine a clustering algorithm with our test procedure to identify micro domains that is zones where the particles are confined. Molecular interactions of great importance for the functioning of the cell take place in such areas.

Regional deposition and ventilation of particles by generation, lobe and lung during steady inhalation in a computed tomography (CT) based human airway model are investigated numerically. The airway model consists of a seven-generation human airway tree, with oral cavity, pharynx and larynx. The turbulent flow in the upper respiratory tract is simulated by large-eddy simulation. The flow boundary conditions at the peripheral airways are derived from CT images at two lung volumes to produce physiologically-realistic regional ventilation. Particles with diameter less than 2.5 microns are selected for study because smaller particles tend to penetrate to the more distal parts of the lung. The current generational particle deposition efficiencies agree well with existing measurement data. Generational deposition efficiencies exhibit similar dependence on particle Stokes number regardless of generation, whereas deposition and ventilation efficiencies vary by lobe and lung, depending on airway morphology and airflow ventilation. In particular, regardless of particle size, the left lung receives a greater proportion of the particle bolus as compared to the right lung in spite of greater flow ventilation to the right lung. This observation is supported by the left-right lung asymmetry of particle ventilation observed in medical imaging. It is found that the particle-laden turbulent laryngeal jet flow, coupled with the unique geometrical features of the airway, causes a disproportionate amount of particles to enter the left lung.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第22894号 / 工博第4791号 / 新制||工||1749(附属図書館) / 京都大学大学院工学研究科原子核工学専攻 / (主査)教授 横峯 健彦, 教授 佐々木 隆之, 講師 河原 全作 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DGAM

Understanding the dynamics of micro- and nanometer-sized objects like molecules, particles, and living cells in biological systems and biomaterials has become a key component in biomedical research. Consequently, significant progress has been made for the development of imaging platforms, fluorescent probes, and computational tools to visualize and quantify biological processes at different length and time scales. However, despite such advances, achieving a reliable measurement accuracy on the dynamic behavior of these microscopic vehicles in diverse biological contexts is challenging. Subsequently, the motivation behind this dissertation is to develop new robust microfluidic velocimetry techniques to investigate molecular transport and cell migration within an in-vitro microfluidic platform.

This study was concerned with the most common reverse flow type of cyclones where the flow enters the cyclone through a tangential inlet and leaves via an axial outlet pipe at the top of the cyclone. Numerical computations of two different cyclones were based on the so-called Stairmand cyclone. The difference in geometry between these two cyclones was basically characterized by the geometrical swirl number Sg of 3.5 and 4. Turbulent secondary flows inside a straight square channel have been studied numerically by using Large Eddy Simulation (LES) in order to verify the implementation process. Prandtl’s secondary motion calculated by LES shows satisfying agreement with both, Direct Numerical Simulation (DNS) and experimental results. Numerical calculations were carried out at various axial positions and at the apex cone of a gas cyclone separator. Two different NS-solvers (a commercial one, and a research code), based on a pressure correction algorithm of the SIMPLE method have been applied to predict the flow behavior. The flow was assumed as unsteady, incompressible and isothermal. A k − epsilon turbulence model has been applied first using the commercial code to investigate the gas flow. Due to the nature of cyclone flows, which exhibit highly curved streamlines and anisotropic turbulence, advanced turbulence models such as RSM (Reynolds Stress Model) and LES (Large Eddy Simulation) have been used as well. The RSM simulation was performed using the commercial package CFX4.4, while for the LES calculations the research code MISTRAL/PartFlow-3D code developed in our multiphase research group has been applied utilizing the Smagorinsky model. It was found that the k − epsilon model cannot predict flow phenomena inside the cyclone properly due to the strong curvature of the streamlines. The RSM results are comparable with LES results in the area of the apex cone plane. However, the application of the LES reveals qualitative agreement with the experimental data, but requires higher computer capacity and longer running times than RSM. These calculations of the continuous phase flow were the basis for modeling the behavior of the solid particles in the cyclone separator. Particle trajectories, pressure drop and the cyclone separation efficiency have been studied in some detail. This thesis is organized into five chapters. After an introduction and overview, chapter 2 deals with continuous phase flow turbulence modeling including the governing equations. The emphasis will be based on LES modelling. Furthermore, the disperse phase motion is treated in chapter 3. In chapter 4, the validation process of LES implementation with channel flow is presented. Moreover, prediction profiles of the gas flow are presented and discussed. In addition, disperse phase flow results are presented and discussed such as particle trajectories; pressure drop and cyclone separation efficiency are also discussed. Chapter 5 summarizes and concludes the thesis.

No description available.

Diabetes has gained growing attendance as one of the key non communicable diseases (NCD) with the World Health Organization identifying it as the focus of the World Health Day 2016. It is reported that more than 420 million people suffer from diabetes, a number predicted to rise in the coming years. This report forms part of a broader, long term focus project that aims to establish a systems approach to type 2 diabetes (T2D), the variant that accounts for more than 90% of reported diabetes cases. The broader project objectives are to identify possible biomarkers for the onset and the progression of T2D as a precursor to enable potential future approaches to delay onset, or even reverse disease states, via active bio-compounds and/or establishment of beneficial nutritional patterns. The 6-month master’s work reported here is sub-project that focused specifically on cell level vesicle trafficking processes. These processes are believed to be crucial in understanding the formation amyloid plaques, which compromise or kill the insulin secreting beta cells. Up until now, there has been a lack of appropriate experimental techniques to directly observe this process in live cells.  Hence we have developed 2 new techniques: (i)               a method of imaging the actin and tubulin network reorganization during exocytosis of the insulin containing granules while exploring novel ways of characterizing the network. (ii)             a method of imaging the granules themselves and using particle tracking microrheology to analyze their movement patterns during stimulation with glucose. These new techniques open the door to follow up experiments which would allow development of a cell scale mathematical model or simulation correlating short term glucose dynamics to risk of amyloid plaque formation and T2D.

The work is focused on experimental study and modelling of spacer grid influence on single- and two-phase flow. In the experimental study a mock-up of a realistic fuel bundle with five spacer grids of thin plate spring construction was investigated. A special pressure measuring technique was used to measure pressure distribution inside the spacer. Five pressure taps were drilled in one of the rods, which could exchange position with other rods, in this way providing a large degree of freedom. Laser Doppler Velocimetry was used to measure mean local axial velocity and its fluctuating component upstream and downstream of the spacer in several subchannels with differing spacer part. The experimental study revealed an interesting behaviour. Subchannels from the interior part of the bundle display a different effect on the flow downstream of the spacer compared to subchannels close to the box wall, even if the spacer part is the same. This behaviour is not reflected in modern correlations. The modelling part, first, consisted in comparing the present experimental data to Computational Fluid Dynamics calculations. It was shown that stand-alone subchannel models could predict the local velocity, but are unreliable in prediction of turbulence enhancement due to spacer. The second part of the modelling consisted in developing a deposition model for increase due to spacer. In this study Lagrangian Particle Tracking (LPT) coupled to Discrete Random Walk (DRW) technique was used to model droplet movements through turbulent flow. The LPT technique has an advantage to model the influence of turbulence structure effect on droplet deposition, in this way presenting a generalized model in view of spacer geometry change. The verification of the applicability of LPT DRW method to model deposition in annular flow at Boiling Water Reactor conditions proved that the method is unreliable in its present state. The model calculations compare reasonably well to air-water deposition data, but display a wrong trend if the fluids have a different density ratio than air-water.