This dissertation includes a theoretical and numerical development to simulate liquid-vapor flows and the applications to microchannels. First, we obtain a consistent non-local pressure equation for simulating liquid-vapor interfacial flows using mean-field free-energy theory. This new pressure equation is shown to be the general form of the classical van der Waals" square-gradient theory. The new equation is implemented in two-dimensional (2D) D2Q7, D2Q9, and three-dimensional (3D) D3Q19 lattice Boltzmann method (LBM). The three LBM models are validated successfully in a number of analytical solutions of liquid-vapor interfacial flows. Second, we have shown that the common bounceback condition in the literature leads to an unphysical velocity at the wall in the presence of surface forces. A few new consistent mass and energy conserving velocity-boundary conditions are developed for D2Q7, D2Q9, and D3Q19 LBM models, respectively. The three LBM models are shown to have the capabilities to successfully simulate different wall wettabilities, the three typical theories or laws for moving contact lines, and liquid-vapor channel flows. Third, proper scaling laws are derived to represent the physical system in the framework of the LBM. For the first time, to the best of the author's knowledge, we obtain a flow regime map for liquid-vapor channel flows with a numerical method. Our flow map is the first flow regime map so far for submicrochannel flows, and also the first iso-thermal flow regime map for CO₂ mini- and micro-channel flows. Our results show that three major flow regimes occur, including dispersed, bubble/plug, and liquid strip flow. The vapor and liquid dispersed flows happen at the two extremities of vapor quality. When vapor quality increases beyond a threshold, bubble/plug patterns appear. The bubble/plug regimes include symmetric and distorted, submerged and non-wetting, single and train bubbles/plugs, and some combination of them. When the Weber number<10, the bubble/plug flow regime turns to a liquid strip pattern at the increased vapor quality of 0.5~0.6. When the Weber number>10, the regime transition occurs around a vapor quality of 0.10~0.20. In fact, when an inertia is large enough to destroy the initial flow pattern, the transition boundary between the bubble and strip regimes depends only on vapor quality and exists between x=0.10 and 0.20. The liquid strip flow regimes include stratified strip, wavy-stratified strip, intermittent strip, liquid lump, and wispy-strip flow. We also find that the liquid-vapor interfaces become distorted at the Weber number of 500~1000, independent of vapor quality. The comparisons of our flow maps with two typical experiments show that the simulations capture the basic and important flow mechanisms for the flow regime transition from the bubble/plug regimes to the strip regimes and from the non-distorted interfaces to the distorted interfaces. Last, our available results show that the flow regimes of both 2D and 3D fall in the same three broad categories with similar subdivisions of the flow regimes, even though the 3D duct produces some specific 3D corner flow patterns. The comparison between 2D and 3D flows shows that the flow map obtained from 2D flows can be generally applied to a 3D situation, with caution, when 3D information is not available. In addition, our 3D study shows that different wettabilities generate different flow regimes. With the complete wetting wall, the flow pattern is the most stable. / Ph. D.

Liquid film flow is an important flow type in many applications of process engineering. For supporting experiments, theoretical and numerical investigations are required. The present state of the art is to model the liquid film flow with Navier--Stokes-based methods, whereas the lattice Boltzmann method is employed here. The final model has been developed within this treatise by means of a two-phase flow and a heat transfer model, and boundary and initial conditions. All these sub-models have been applied to simple test cases. It could be found that the two-phase model is capable of solving flow phenomena with a large density ratio which has been shown impressively in conjunction with wall boundary conditions. The heat transfer model was tested against spectral method results with a transient non-uniform flow field. It was possible to find optimal parameters for computation. The final model has been applied to steady-state film flow, and showed very good agreement to OpenFOAM simulations. Tests with transient film flow demonstrated that the model is also able to predict these flow phenomena. / Flüssigkeitsfilmströmungen kommen in vielen verfahrenstechnischen Prozessen zum Einsatz. Zur Unterstützung von Experimenten sind theoretische und numerische Untersuchungen nötig. Stand der Technik ist es, Navier--Stokes-basierte Modelle zu verwenden, wohingegen hier die Lattice-Boltzmann-Methode verwendet wird. Das finale Modell wurde unter Verwendung eines Zweiphasen- und eines Wärmeübertragungsmodell entwickelt und geeignete Rand- und Anfangsbedingungen formuliert. Alle Untermodelle wurden anhand einfacher Testfälle überprüft. Es konnte herausgefunden werden, dass das Zweiphasenmodell Strömungen großer Dichteunterschiede rechnen kann, was eindrucksvoll im Zusammenhang mit Wandrandbedingungen gezeigt wurde. Das Wärmeübertragungsmodell wurde gegen eine Spektrallösung anhand eines transienten und nichtuniformen Strömungsproblemes getestet. Stationäre Filmströmungen zeigten sehr gute Übereinstimmungen mit OpenFOAM-Lösungen und instationäre Berechungen bewiesen, dass das Model auch solche Strömungen abbilden kann.

L'ablation par radiofréquence (ARF) de tumeurs abdominales est rendue difficile par l’influence des vaisseaux sanguins et les variations de la conductivité thermique, compliquant la planification spécifique à un patient donné. En fournissant des outils prédictifs, les modèles biophysiques pourraient aider les cliniciens à planifier et guider efficacement la procédure. Nous introduisons un modèle mathématique détaillé des mécanismes impliqués dans l’ARF des tumeurs du foie comme la diffusion de la chaleur et la nécrose cellulaire. Il simule l’étendue de l’ablation à partir d’images médicales, d’après lesquelles des modèles personnalisés du foie, des vaisseaux visibles et des tumeurs sont segmentés. Dans cette thèse, une nouvelle approche pour résoudre ces équations basée sur la méthode de Lattice Boltzmann est introduite. Le modèle est d’abord évalué sur des données de patients qui ont subi une ARF de tumeurs du foie. Ensuite, un protocole expérimental combinant des images multi-modales, anatomiques et fonctionnelles pré- et post-opératoires, ainsi que le suivi de la température et de la puissance délivrée pendant l'intervention est présenté. Il permet une validation totale du modèle qui considère des données les plus complètes possibles. Enfin, nous estimons automatiquement des paramètres personnalisés pour mieux prédire l'étendu de l’ablation. Cette stratégie a été validée sur 7 ablations dans 3 cas cliniques. A partir de l'étude préclinique, la personnalisation est améliorée en comparant les simulations avec les mesures faites durant la procédure. Ces contributions ont abouti à des résultats prometteurs, et ouvrent de nouvelles perspectives pour planifier et guider l’ARF. / The outcome of radiofrequency ablation (RFA) of abdominal tumors is challenged by the presence of blood vessels and time-varying thermal conductivity, which make patient-specific planning extremely difficult. By providing predictive tools, biophysical models may help clinicians to plan and guide the procedure for an effective treatment. We introduce a detailed computational model of the biophysical mechanisms involved in RFA of hepatic tumors such as heat diffusion and cellular necrosis. It simulates the extent of ablated tissue based on medical images, from which patient-specific models of the liver, visible vessels and tumors are segmented. In this thesis, a new approach for solving these partial differential equations based on the Lattice Boltzmann Method is introduced. The model is first evaluated against clinical data of patients who underwent RFA of liver tumors. Then, a comprehensive pre-clinical experiment that combines multi-modal, pre- and post-operative anatomical and functional images, as well as the interventional monitoring of the temperature and delivered power is presented. This enables an end-to-end validation framework that considers the most comprehensive data set for model validation. Then, we automatically estimate patient-specific parameters to better predict the ablated tissue. This personalization strategy has been validated on 7 ablations from 3 clinical cases. From the pre-clinical study, we can go further in the personalization by comparing the simulated temperature and delivered power with the actual measurements during the procedure. These contributions have led to promising results, and open new perspectives in RFA guidance and planning.

Efficient memory usage is crucial for data-intensive applications as a smaller memory footprint ensures better cache performance and allows one to run a larger problem size given a axed amount of main memory. The solutions found by existing techniques for automatic storage optimization for arrays in a new loop-nests, which minimize the storage requirements for the arrays, are often far from good or optimal and could even miss nearly all storage optimization potential. In this work, we present a new automatic storage optimization framework and techniques that can be used to achieve intra-array as well as inter-array storage reuse within a new loop-nests with a pre-determined schedule. Over the last two decades, several heuristics have been developed for achieving complex transformations of a new loop-nests using the polyhedral model. However, there are no comparably strong heuristics for tackling the problem of automatic memory footprint optimization. We tackle the problem of storage optimization for arrays by formulating it as one of ending the right storage partitioning hyperplanes: each storage partition corresponds to a single storage location. Statement-wise storage partitioning hyperplanes are determined that partition a unit end global array space so that values with overlapping live ranges are not mapped to the same partition. Our integrated heuristic for exploiting intra-array as well as inter-array reuse opportunities is driven by a fourfold objective function that not only minimizes the dimensionality and storage requirements of arrays required for each high-level statement, but also maximizes inter-statement storage reuse. We built an automatic polyhedral storage optimizer called SMO using our storage partitioning approach. Storage reduction factors and other results we report from SMO demon-strate the e activeness of our approach on several benchmarks drawn from the domains of image processing, stencil computations, high-performance computing, and the class of tiled codes in general. The reductions in storage requirement over previous approaches range from a constant factor to asymptotic in the loop blocking factor or array extents { the latter being a dramatic improvement for practical purposes. As an incidental and related topic, we also studied the problem of polyhedral compilation of graphical data programs. While polyhedral techniques for program transformation are now used in several proprietary and open source compilers, most of the research on poly-herald compilation has focused on imperative languages such as C, where the computation is species in terms of statements with zero or more nested loops and other control structures around them. Graphical data ow languages, where there is no notion of statements or a schedule specifying their relative execution order, have so far not been studied using a powerful transformation or optimization approach. The execution semantics and ref-eventual transparency of data ow languages impose a di errant set of challenges. In this work, we attempt to bridge this gap by presenting techniques that can be used to extract polyhedral representation from data ow programs and to synthesize them from their equivalent polyhedral representation. We then describe Polyglot, a framework for automatic transformation of data ow programs that we built using our techniques and other popular research tools such as Clan and Pluto. For the purpose of experimental evaluation, we used our tools to compile LabVIEW, one of the most widely used data ow programming languages. Results show that data ow programs transformed using our framework are able to outperform those compiled otherwise by up to a factor of seventeen, with a mean speed-up of 2.30 while running on an 8-core Intel system.

Liquid film flow is an important flow type in many applications of process engineering. For supporting experiments, theoretical and numerical investigations are required. The present state of the art is to model the liquid film flow with Navier--Stokes-based methods, whereas the lattice Boltzmann method is employed here. The final model has been developed within this treatise by means of a two-phase flow and a heat transfer model, and boundary and initial conditions. All these sub-models have been applied to simple test cases. It could be found that the two-phase model is capable of solving flow phenomena with a large density ratio which has been shown impressively in conjunction with wall boundary conditions. The heat transfer model was tested against spectral method results with a transient non-uniform flow field. It was possible to find optimal parameters for computation. The final model has been applied to steady-state film flow, and showed very good agreement to OpenFOAM simulations. Tests with transient film flow demonstrated that the model is also able to predict these flow phenomena. / Flüssigkeitsfilmströmungen kommen in vielen verfahrenstechnischen Prozessen zum Einsatz. Zur Unterstützung von Experimenten sind theoretische und numerische Untersuchungen nötig. Stand der Technik ist es, Navier--Stokes-basierte Modelle zu verwenden, wohingegen hier die Lattice-Boltzmann-Methode verwendet wird. Das finale Modell wurde unter Verwendung eines Zweiphasen- und eines Wärmeübertragungsmodell entwickelt und geeignete Rand- und Anfangsbedingungen formuliert. Alle Untermodelle wurden anhand einfacher Testfälle überprüft. Es konnte herausgefunden werden, dass das Zweiphasenmodell Strömungen großer Dichteunterschiede rechnen kann, was eindrucksvoll im Zusammenhang mit Wandrandbedingungen gezeigt wurde. Das Wärmeübertragungsmodell wurde gegen eine Spektrallösung anhand eines transienten und nichtuniformen Strömungsproblemes getestet. Stationäre Filmströmungen zeigten sehr gute Übereinstimmungen mit OpenFOAM-Lösungen und instationäre Berechungen bewiesen, dass das Model auch solche Strömungen abbilden kann.

<p>  </p> <p>With the recent advancement of computation and imaging technology, Image-based computational fluid dynamics (ICFD) has emerged as a great non-invasive capability to study biomedical flows. These modern technologies increase the potential of computation-aided diagnostics and therapeutics in a patient-specific environment. I studied three components of this image-based computational fluid dynamics process in this work.</p> <p>To ensure accurate medical assessment, realistic computational analysis is needed, for which patient-specific image segmentation of the diseased vessel is of paramount importance. In this work, image segmentation of several human arteries, veins, capillaries, and organs was conducted to use them for further hemodynamic simulations. To accomplish these, several open-source and commercial software packages were implemented. </p> <p>This study incorporates a new computational platform, called <em>InVascular</em>, to quantify the 4D velocity field in image-based pulsatile flows using the Volumetric Lattice Boltzmann Method (VLBM). We also conducted several parametric studies on an idealized case of a 3-D pipe with the dimensions of a human renal artery. We investigated the relationship between stenosis severity and Resistive index (RI). We also explored how pulsatile parameters like heart rate or pulsatile pressure gradient affect RI.</p> <p>As the process of ICFD analysis is based on imaging and other hemodynamic data, it is often time-consuming due to the extensive data processing time. For clinicians to make fast medical decisions regarding their patients, we need rapid and accurate ICFD results. To achieve that, we also developed surrogate models to show the potential of supervised machine learning methods in constructing efficient and precise surrogate models for Hagen-Poiseuille and Womersley flows.</p>

With the advent of low-energy buildings, the need for accurate building performance simulations has significantly increased. However, for the time being, the thermo-aeraulic effects are often taken into account through simplified or even empirical models, which fail to provide the expected accuracy. Resorting to computational fluid dynamics seems therefore unavoidable, but the required computational effort is in general prohibitive. The joint use of innovative approaches such as the lattice Boltzmann method (LBM) and massively parallel computing devices such as graphics processing units (GPUs) could help to overcome these limits. The present research work is devoted to explore the potential of such a strategy. The lattice Boltzmann method, which is based on a discretised version of the Boltzmann equation, is an explicit approach offering numerous attractive features: accuracy, stability, ability to handle complex geometries, etc. It is therefore an interesting alternative to the direct solving of the Navier-Stokes equations using classic numerical analysis. From an algorithmic standpoint, the LBM is well-suited for parallel implementations. The use of graphics processors to perform general purpose computations is increasingly widespread in high performance computing. These massively parallel circuits provide up to now unrivalled performance at a rather moderate cost. Yet, due to numerous hardware induced constraints, GPU programming is quite complex and the possible benefits in performance depend strongly on the algorithmic nature of the targeted application. For LBM, GPU implementations currently provide performance two orders of magnitude higher than a weakly optimised sequential CPU implementation. The present thesis consists of a collection of nine articles published in international journals and proceedings of international conferences (the last one being under review). These contributions address the issues related to single-GPU implementations of the LBM and the optimisation of memory accesses, as well as multi-GPU implementations and the modelling of inter-GPU and internode communication. In addition, we outline several extensions to the LBM, which appear essential to perform actual building thermo-aeraulic simulations. The test cases we used to validate our codes account for the strong potential of GPU LBM solvers in practice.

粉体の微粒子化に伴い，固液分離操作の中でも高精度かつ多量処理が可能なろ過の重要性はますます高まっている．しかしながら，微粒子スラリーのろ過抵抗は非常に大きく，所望の処理能力を得られないことが多い．本論文では，ろ過操作設計におけるろ材抵抗，スラリー凝集・分散状態，ケークろ過抵抗の予測に関して数値シミュレーションを利用した検討を行うことで，微粒子スラリーのろ過抵抗の低減に有用な知見を得ることができた． / 著者名の「吉」は「土」の下に「口」の置き換え / 博士(工学) / Doctor of Philosophy in Engineering / 同志社大学 / Doshisha University

Extracellular neuroelectronic interfacing has important applications in the fields of neural prosthetics, biological computation and whole-cell biosensing for drug screening and toxin detection. While the field of neuroelectronic interfacing holds great promise, the recording of high-fidelity signals from extracellular devices has long suffered from the problem of low signal-to-noise ratios and changes in signal shapes due to the presence of highly dispersive dielectric medium in the neuron-microelectrode cleft. This has made it difficult to correlate the extracellularly recorded signals with the intracellular signals recorded using conventional patch-clamp electrophysiology. For bringing about an improvement in the signalto-noise ratio of the signals recorded on the extracellular microelectrodes and to explore strategies for engineering the neuron-electrode interface there exists a need to model, simulate and characterize the cell-sensor interface to better understand the mechanism of signal transduction across the interface. Efforts to date for modeling the neuron-electrode interface have primarily focused on the use of point or area contact linear equivalent circuit models for a description of the interface with an assumption of passive linearity for the dynamics of the interfacial medium in the cell-electrode cleft. In this dissertation, results are presented from a nonlinear dynamic characterization of the neuroelectronic junction based on Volterra-Wiener modeling which showed that the process of signal transduction at the interface may have nonlinear contributions from the interfacial medium. An optimization based study of linear equivalent circuit models for representing signals recorded at the neuron-electrode interface subsequently iv proved conclusively that the process of signal transduction across the interface is indeed nonlinear. Following this a theoretical framework for the extraction of the complex nonlinear material parameters of the interfacial medium like the dielectric permittivity, conductivity and diffusivity tensors based on dynamic nonlinear Volterra-Wiener modeling was developed. Within this framework, the use of Gaussian bandlimited white noise for nonlinear impedance spectroscopy was shown to offer considerable advantages over the use of sinusoidal inputs for nonlinear harmonic analysis currently employed in impedance characterization of nonlinear electrochemical systems. Signal transduction at the neuron-microelectrode interface is mediated by the interfacial medium confined to a thin cleft with thickness on the scale of 20-110 nm giving rise to Knudsen numbers (ratio of mean free path to characteristic system length) in the range of 0.015 and 0.003 for ionic electrodiffusion. At these Knudsen numbers, the continuum assumptions made in the use of Poisson-Nernst-Planck system of equations for modeling ionic electrodiffusion are not valid. Therefore, a lattice Boltzmann method (LBM) based multiphysics solver suitable for modeling ionic electrodiffusion at the mesoscale neuron-microelectrode interface was developed. Additionally, a molecular speed dependent relaxation time was proposed for use in the lattice Boltzmann equation. Such a relaxation time holds promise for enhancing the numerical stability of lattice Boltzmann algorithms as it helped recover a physically correct description of microscopic phenomena related to particle collisions governed by their local density on the lattice. Next, using this multiphysics solver simulations were carried out for the charge relaxation dynamics of an electrolytic nanocapacitor with the intention of ultimately employing it for a simulation of the capacitive coupling between the neuron and the v planar microelectrode on a microelectrode array (MEA). Simulations of the charge relaxation dynamics for a step potential applied at t = 0 to the capacitor electrodes were carried out for varying conditions of electric double layer (EDL) overlap, solvent viscosity, electrode spacing and ratio of cation to anion diffusivity. For a large EDL overlap, an anomalous plasma-like collective behavior of oscillating ions at a frequency much lower than the plasma frequency of the electrolyte was observed and as such it appears to be purely an effect of nanoscale confinement. Results from these simulations are then discussed in the context of the dynamics of the interfacial medium in the neuron-microelectrode cleft. In conclusion, a synergistic approach to engineering the neuron-microelectrode interface is outlined through a use of the nonlinear dynamic modeling, simulation and characterization tools developed as part of this dissertation research.