<p>Uncertainty analysis is of great use both for calculating outputs that are more akin to real<br> flight, and for optimization to more robust shapes. However, implementation of uncertainty<br> has been a longstanding challenge in the field of aerodynamics due to the computational cost<br> of simulations. Geometric uncertainty in particular is often left unexplored in favor of uncer-<br> tainties in freestream parameters, turbulence models, or computational error. Therefore, this<br> work proposes a method of geometric uncertainty analysis for aerodynamic shapes that miti-<br> gates the barriers to its feasible computation. The process takes a two- or three-dimensional<br> shape and utilizes a combination of multifidelity meshes and Gaussian process regression<br> (GPR) surrogates in a multifidelity Monte Carlo (MFMC) algorithm. Multifidelity meshes<br> allow for finer sampling with a given budget, making the surrogates more accurate. GPR<br> surrogates are made practical to use by parameterizing major factors in geometric uncer-<br> tainty with only four variables in 2-D and five in 3-D. In both cases, two parameters control<br> the heights of steps that occur on the top and bottom of airfoils where leading and trailing<br> edge devices are attached. Two more parameters control the height and length of waves<br> that can occur in an ideally smooth shape during manufacturing. A fifth parameter controls<br> the depth of span-wise skin buckling waves along a 3-D wing. Parameters are defined to<br> be uniformly distributed with a maximum size of 0.4 mm and 0.15 mm for steps and waves<br> to remain within common manufacturing tolerances. The analysis chain is demonstrated<br> with two test cases. The first, the RAE2822 airfoil, uses transonic freestream parameters<br> set by the ADODG Benchmark Case 2. The results show a mean drag of nearly 10 counts<br> above the deterministic case with fixed lift, and a 2 count increase for a fixed angle of attack<br> version of the case. Each case also has small variations in lift and angle of attack of about<br> 0.5 counts and 0.08◦, respectively. Variances for each of the three tracked outputs show that<br> more variability is possible, and even likely. The ONERA M6 transonic wing, popular due<br> to the extensive experimental data available for computational validation, is the second test<br> case. Variation is found to be less substantial here, with a mean drag increase of 0.5 counts,<br> and a mean lift increase of 0.1 counts. Furthermore, the MFMC algorithm enables accurate<br> results with only a few hours of wall time in addition to GPR training. </p>

The design and optimization of entrained flow gasifiers is conducted more and more via computational fluid dynamics (CFD). A detailed resolution of single coal particles within such simulations is nowadays not possible due to computational limitations. Therefore the coal particle conversion is often represented by simple 0-D models. For an optimization of such 0-D models a precise understanding of the physical processes at the boundary layer and within the particle is necessary. In real gasifiers the particles experience Reynolds numbers up to 10000. However in the literature the conversion of coal particles is mainly regarded under quiescent conditions. Therefore an analysis of the conversion of single particles is needed. Thereto the computational fluid dynamics can be used. For the detailed analysis of single reacting particles under flow conditions a CFD model is presented. Practice-oriented parameters as well as features of the CFD model result from CFD simulations of a Siemens 200MWentrained flow gasifier. The CFD model is validated against an analytical model as well as two experimental data-sets taken from the literature. In all cases good agreement between the CFD and the analytics/experiments is shown. The numerical model is used to study single moving solid particles under combustion conditions. The analyzed parameters are namely the Reynolds number, the ambient temperature, the particle size, the operating pressure, the particle shape, the coal type and the composition of the gas. It is shown that for a wide range of the analyzed parameter range no complete flame exists around moving particles. This is in contrast to observations made by other authors for particles in quiescent atmospheres. For high operating pressures, low Reynolds numbers, large particle diameters and high ambient temperatures a flame exists in the wake of the particle. The impact of such a flame on the conversion of the particle is low. For high steam concentrations in the gas a flame appears, which interacts with the particle and influences its conversion. Furthermore the impact of the Stefan-flow on the boundary layer of the particle is studied. It is demonstrated that the Stefan-flow can reduce the drag coefficient and the Nusselt number for several orders of magnitude. On basis of the CFD results two new correlations are presented for the drag coefficient and the Nusselt number. The comparison between the correlations and the CFD shows a significant improvement of the new correlations in comparison to archived correlations. The CFD-model is further used to study moving single porous particles under gasifying conditions. Therefore a 2-D axis-symmetric system of non-touching tori as well as a complex 3-D geometry based on the an inverted settlement of monodisperse spheres is utilized. With these geometries the influence of the Reynolds number, the ambient temperature, the porosity, the intrinsic surface and the size of the radiating surface is analyzed. The studies show, that the influence of the flow on the particle conversion is moderate. In particular the impact of the flow on the intrinsic transport and conversion processes is mainly negligible. The size of the radiating surface has a similar impact on the conversion as the flow in the regarded parameter range. On basis of the CFD calculations two 0-D models for the combustion and gasification of moving particles are presented. These models can reproduce the results predicted by the CFD sufficiently for a wide parameter range.

Cette thèse expérimentale s’inscrit dans le domaine des sciences séparatives et se base sur la technique de SPLITT (SPLIT-flow Thin fractionation). Son objectif consiste en l’étude des mécanismes qui sont à l’origine de la séparation, en continu et sans membrane, d’objets de taille micrométrique dans des mini-séparateurs fluidiques (Step-SPLITT). Les expériences menées, en laboratoire et lors de vols paraboliques, ont révélé le couplage complexe comme l’influence des effets hydrodynamiques et du champ gravitationnel sur la migration transverse des espèces en écoulement. Des visualisations tridimensionnelles par holographie digitale ont corroboré nos résultats et dévoilé des comportements inattendus. Les capacités séparatives des Step-SPLITT ont rendu possible l’analyse et la séparation d’objets biologiques et biomimétiques. Enfin, cette étude complétée par une modélisation tridimensionnelle de l’écoulement nous a permis de mettre au point un nouveau prototype de séparateur. This experimental thesis belongs to the field of separative sciences and is based on the SPLITT technique (SPLIT-flow Thin fractionation). The objective is to study the mechanisms that are at the origin of continuous and membraneless separation of micron-size species in mini fluidic separators (Step-SPLITT). Experiments undertaken in laboratory and during parabolic flights revealed the complex coupling of the hydrodynamic effects and the gravitational field influencing the transverse migration of the flowing species. Three-dimensional visualizations performed by digital holography confirmed our results and disclosed unexpected behaviours. The separation capacities of Step-SPLITT made the analysis and the separation of biological and biomimetic species possible. In addition this study in conjunction with a three-dimensional flow modelling enabled us to develop a new prototype of separator.

Cette thèse expérimentale s’inscrit dans le domaine des sciences séparatives et se base sur la technique de SPLITT (SPLIT-flow Thin fractionation). Son objectif consiste en l’étude des mécanismes qui sont à l’origine de la séparation, en continu et sans membrane, d’objets de taille micrométrique dans des mini-séparateurs fluidiques (Step-SPLITT). Les expériences menées, en laboratoire et lors de vols paraboliques, ont révélé le couplage complexe comme l’influence des effets hydrodynamiques et du champ gravitationnel sur la migration transverse des espèces en écoulement. Des visualisations tridimensionnelles par holographie digitale ont corroboré nos résultats et dévoilé des comportements inattendus. Les capacités séparatives des Step-SPLITT ont rendu possible l’analyse et la séparation d’objets biologiques et biomimétiques. Enfin, cette étude complétée par une modélisation tridimensionnelle de l’écoulement nous a permis de mettre au point un nouveau prototype de séparateur.<p><p>This experimental thesis belongs to the field of separative sciences and is based on the SPLITT technique (SPLIT-flow Thin fractionation). The objective is to study the mechanisms that are at the origin of continuous and membraneless separation of micron-size species in mini fluidic separators (Step-SPLITT). Experiments undertaken in laboratory and during parabolic flights revealed the complex coupling of the hydrodynamic effects and the gravitational field influencing the transverse migration of the flowing species. Three-dimensional visualizations performed by digital holography confirmed our results and disclosed unexpected behaviours. The separation capacities of Step-SPLITT made the analysis and the separation of biological and biomimetic species possible. In addition this study in conjunction with a three-dimensional flow modelling enabled us to develop a new prototype of separator. / Doctorat en sciences appliquées / info:eu-repo/semantics/nonPublished

The aim of the dissertation thesis is the control of the tube bundle on the cyclic fatigue caused by the flow past tube bundle. Fatigue due to flow is caused by flow-induced vibrations. Examined vibrations are caused by the mutual interaction of two phases (solid and liquid). The present work is focused mainly on the interaction of tube bundles with fluid. The current level of knowledge in this field allows to predict mainly static respectively quazi-static loading. These predictions are based on methods of comparing key vibration variables such as frequencies, amplitudes or speeds (see TEMA [1]). In this way, it is possible to determine quickly and relatively precisely the occurrence of a vibrational phenomenon, but it is not possible to quantitatively assess the effect of these vibrations on the damage of to the tube beam and to predict its lifespan, which would require the determination of the temperature field and the distribution of forces from the fluid on the beam. The aim of the work is to evaluate the-state-of-the-art, to perform a numerical simulation of the flow of fluids in the area of shell side under the inlet nozzle. Current methods of numerical analyses very well solve this problem, but at the expense of computing time, devices and expensive licences. The benefit of this work is the use of user-defined function (UDF) as a method for simulating interaction with fluid and structure in ANSYS Fluent software. This work places great emphasis on using the current state of knowledge for verifying and validation. Verifying and validation of results include, for example, experimentally measured Reynolds and Strouhal numbers, the drag coefficients and for example magnitude of pressure coefficient around the tube. At the same time, it uses the finite element method as a tool for the stress-strain calculation of a key part on tube such as a pipe-tube joint. Another benefit of this work is the extension of the graphical design of heat exchanger according to Poddar and Polley by vibration damages control according to the method described in TEMA [1]. In this section, the author points out the enormous influence of flow velocity on both the tube side and the shell side for design of the heat exchanger to ensure faultless operation. As an etalon of damage, the author chose a heat exchanger designated 104 from the Heat Exchanger Tube Vibration Data Bank [3]. With this heat exchanger, vibrational damage has been proven to be due to cutting of the tubes over the baffles. The last part outlines the possibilities and limits of further work.

The design and optimization of entrained flow gasifiers is conducted more and more via computational fluid dynamics (CFD). A detailed resolution of single coal particles within such simulations is nowadays not possible due to computational limitations. Therefore the coal particle conversion is often represented by simple 0-D models. For an optimization of such 0-D models a precise understanding of the physical processes at the boundary layer and within the particle is necessary. In real gasifiers the particles experience Reynolds numbers up to 10000. However in the literature the conversion of coal particles is mainly regarded under quiescent conditions. Therefore an analysis of the conversion of single particles is needed. Thereto the computational fluid dynamics can be used. For the detailed analysis of single reacting particles under flow conditions a CFD model is presented. Practice-oriented parameters as well as features of the CFD model result from CFD simulations of a Siemens 200MWentrained flow gasifier. The CFD model is validated against an analytical model as well as two experimental data-sets taken from the literature. In all cases good agreement between the CFD and the analytics/experiments is shown. The numerical model is used to study single moving solid particles under combustion conditions. The analyzed parameters are namely the Reynolds number, the ambient temperature, the particle size, the operating pressure, the particle shape, the coal type and the composition of the gas. It is shown that for a wide range of the analyzed parameter range no complete flame exists around moving particles. This is in contrast to observations made by other authors for particles in quiescent atmospheres. For high operating pressures, low Reynolds numbers, large particle diameters and high ambient temperatures a flame exists in the wake of the particle. The impact of such a flame on the conversion of the particle is low. For high steam concentrations in the gas a flame appears, which interacts with the particle and influences its conversion. Furthermore the impact of the Stefan-flow on the boundary layer of the particle is studied. It is demonstrated that the Stefan-flow can reduce the drag coefficient and the Nusselt number for several orders of magnitude. On basis of the CFD results two new correlations are presented for the drag coefficient and the Nusselt number. The comparison between the correlations and the CFD shows a significant improvement of the new correlations in comparison to archived correlations. The CFD-model is further used to study moving single porous particles under gasifying conditions. Therefore a 2-D axis-symmetric system of non-touching tori as well as a complex 3-D geometry based on the an inverted settlement of monodisperse spheres is utilized. With these geometries the influence of the Reynolds number, the ambient temperature, the porosity, the intrinsic surface and the size of the radiating surface is analyzed. The studies show, that the influence of the flow on the particle conversion is moderate. In particular the impact of the flow on the intrinsic transport and conversion processes is mainly negligible. The size of the radiating surface has a similar impact on the conversion as the flow in the regarded parameter range. On basis of the CFD calculations two 0-D models for the combustion and gasification of moving particles are presented. These models can reproduce the results predicted by the CFD sufficiently for a wide parameter range.:List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IX List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .XIII Nomenclature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . XV Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . XIX 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1 1.1 State of the Art in Carbon Conversion Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.1.1 Combustion of Solid Particles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.1.2 Gasification of Porous Particles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.2 Classification of the Present Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7 1.3 Overview of the Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7 2 Basic Theory and Model Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.1 Geometry and Length Scales of Coal Particles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .9 2.2 Conditions in a Siemens Like 200 MW Entrained Flow Gasifier . . . . . . . . . . . . . . . . . . . . 11 2.2.1 Velocity Field . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .12 2.2.2 Temperature Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.2.3 Particle Volume Fraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .19 2.3 Time Scales of the Physical Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 2.4 Basic Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .21 2.5 Conservation Equations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 2.6 Gas Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .26 2.7 Boundary Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 2.8 Numerics and Solution Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .30 2.9 Mesh and Domain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .31 3 CFD-based Oxidation Modeling of a Non-Porous Carbon Particle . . . . . . . . . . . . . . . . . . . . .37 3.1 Chemical Reaction System for Combustion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .37 3.1.1 Heterogeneous Reactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .37 3.1.2 Homogeneous Reactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .40 3.1.3 Comparison of the Semi-Global vs. Reduced Reaction Mechanisms for the Gas Phase . .41 3.2 Validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .43 3.2.1 Validation Against an Analytical Solution of the Two-Film Model . . . . . . . . . . . . . . . . . .43 3.2.2 Validation Against Experiments I . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 3.2.3 Validation Against Experiments II . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .49 3.3 Influence of Ambient Temperature and Reynolds Number . . . . . . . . . . . . . . . . . . . . . . . .51 3.4 Influence of Heterogeneous Kinetics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 3.5 Influence of Atmosphere . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .61 3.6 Influence of Operating Pressure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .66 3.7 Influence of Particle Diameter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .70 3.8 The influence of Particle Shape . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 3.9 Impact of Stefan Flow on the Boundary Layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 3.9.1 Impact of Stefan Flow on the Drag Coefficient . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .83 3.9.2 Impact of Stefan Flow on the Nusselt and Sherwood Number . . . . . . . . . . . . . . . . . . . .85 3.10 Single-Film Sub-Model vs. CFD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 3.11 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 4 CFD-based Numerical Modeling of Partial Oxidation of a Porous Carbon Particle . . . . . . . . . .99 4.1 Chemical Reaction System for Gasification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 4.1.1 Heterogeneous Chemistry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .100 4.1.2 Homogeneous Chemistry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 4.2 Two-Dimensional Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 4.2.1 Geometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 4.2.2 Influence of Reynolds Number and Ambient Temperature . . . . . . . . . . . . . . . . . . . . . .109 4.2.3 Influence of Porosity and Internal Surface . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . 120 4.3 Comparative Three-Dimensional Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 4.3.1 Geometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .126 4.3.2 Results of the 3-D Calculations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 4.4 Extended Sub-Model for Gasification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .133 4.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .138 5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . .141 5.1 Summary of This Work . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . .141 5.2 Recommendations for Future Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .145 6 Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 6.1 Appendix I: Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 6.2 Appendix II: Two-Film Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 6.3 Appendix III: Sub-Model for the Combustion of Solid Particles . . . . . . . . . . . . . . . . . . . . 160 6.4 Appendix IV: Sub-Model for the Gasification of Porous Particles . . . . . . . . . . . . . . . . . . . 161

A multitude of processes cooperate to produce the sensation of sound. The key initial step, the transformation from mechanical motion into an electrical signal, takes place in highly specialized mechanosensitive organelles that are called hair bundles due to their characteristic appearance. Each hair bundle comprises many apposed cylindrical stereocilia that are located in a liquid-filled compartment of the inner ear. The viscous liquid surrounding the hair bundle dissipates energy and dampens oscillations, which poses a fundamental physical challenge to the high sensitivity and sharp frequency selectivity of hearing. To understand the structure-function relationship in this complex system, a realistic physical model of the hair bundle with an appropriate representation of the fluid-structure interactions is needed to identify the relevant physical effects. In this work a novel approach is introduced to analyze the mechanics of the fluid-structure interaction problem in the inner ear. Because the motions during normal mechanotransduction are much smaller than the geometrical scales, a unified linear system of equations describes with sufficient accuracy the behavior of the liquid and solid in terms of a displacement variable. The finite-element method is employed to solve this system of partial differential equations. Based on data from the hair bundle of the bullfrog's sacculus, a detailed model is constructed that resolves simultaneously the interaction with the surrounding liquid as well as the coupling liquid in the narrow gaps between the individual stereocilia. The experimental data are from high-resolution interferometric measurements at physiologically relevant amplitudes in the range from a fraction of a nanometer to several tens of nanometers and over a broad range of frequencies from one millihertz to hundred kilohertz. Different modes of motion are analyzed and their induced viscous drag is calculated. The investigation reveals that grouping stereocilia in a bundle dramatically reduces the total drag as compared to the sum of the drags on individual stereocilia moving in isolation. The stereocilia in a hair bundle are interconnected by oblique tip links that transmit the energy in a sound to the mechanotransduction channels and by horizontal top connectors that provide elastic coupling between adjacent stereocilia. During hair-bundle deflections, the tip links induce additional drag by causing small but very dissipative relative motions between stereocilia; this effect is offset by the horizontal top connectors that restrain such relative movements, assuring that the hair bundle moves as a unit and keeping the total drag low. In the model the stiffness of the links, the stiffness of the stereocilia, and the geometry are carefully adjusted to match experimental observations. The references are stiffness and drag measurements, as well as the coherence measurements for the bundle's opposite edges, both with and without the tip links. The results are further validated by a comparison with the relative motions measured in a sinusoidally stimulated bundle for the distortion frequencies at which movements are induced by the nonlinearity imposed by channel gating. The model of the fluid-structure interactions described here provides insight into the key step in the perception of sound and the method presented provides an efficient and reliable approach to fluid-structure interaction problems at small amplitudes. / Bei der Hörwahrnehmung eines Klangs spielen viele komplexe Prozesse zusammen. Der Schlüsselprozess, die Umwandlung mechanischer Schwingungsbewegung in elektrische Signale, findet in den Haarbündeln im Innenohr statt. Diese Haarbündel sind hoch entwickelte mechanosensitive Organellen, bestehend aus vielen nahe beieinander stehenden Stereozilien umgeben von Flüssigkeit. Die beträchtliche Viskosität dieser Flüssigkeit führt zur Energiedissipation und zur Schwingungsdämpfung, was im Gegensatz zur bekannten hohen Empfindlichkeit und der ausgezeichneten Frequenzselektivität der Hörwahrnehmung steht. Um die Komponenten des Haarbündelsystems in ihrem funktionalen Zusammenspiel besser zu verstehen, bedarf es eines wirklichkeitsgetreuen Modells unter Einbeziehung der Wechselwirkung zwischen Flüssigkeit und Struktur. Mit dieser Arbeit wird ein neuer Ansatz vorgestellt, um die Mechanik der Fluid-Struktur-Wechselwirkung im Innenohr zu analysieren. Da die Bewegungen bei der normalen Mechanotransduktion wesentlich kleiner als die geometrischen Abmessungen sind, ist es möglich, das Verhalten von Fluid und Struktur in Form der Verschiebungsvariable in einem linearen einheitlichen System von Gleichungen ausreichend genau zu beschreiben. Dieses System von partiellen Differentialgleichungen wird mit der Finite-Elemente-Methode gelöst. Basierend auf experimentell ermittelten Daten vom Haarbündel des Ochsenfrosches wird ein detailliertes Modell erstellt, welches sowohl die Interaktion mit der umgebenden Flüssigkeit als auch die koppelnde Flüssigkeit in den engen Spalten zwischen den einzelnen Stereozilien erfasst. Die experimentellen Daten sind Ergebnisse von hochauflösenden interferometrischen Messungen bei physiologisch relevanten Bewegungsamplituden im Bereich von unter einem Nanometer bis zu mehreren Dutzend Nanometern, sowie über einen breiten Frequenzbereich von einem Millihertz bis hundert Kilohertz. Das Modell erlaubt die Berechnung der auftretenden viskosen Widerstände aus der numerischen Analyse der verschiedenen beobachteten Bewegungsmoden. Es kann gezeigt werden, dass durch die Gruppierung zu einem Bündel der Gesamtwiderstand drastisch reduziert ist, im Vergleich zur Summe der Widerstände einzelner Stereozilien, die sich individuell und unabhängig voneinander bewegen. Die einzelnen Stereozilien in einem Haarbündel sind durch elastische Strukturen mechanisch miteinander verbunden: Die Energie des Schalls wird durch schräg angeordnete sogenannte Tiplinks auf die mechanotransduktiven Kanäle übertragen, wohingegen horizontale Querverbindungen die Stereozilien direkt koppeln. Während der Haarbündelauslenkung verursachen die Tiplinks zusätzlichen Widerstand durch stark dissipative Relativbewegungen zwischen den Stereozilien. Die horizontalen Querverbindungen unterdrücken diese Bewegungen und sind dafür verantwortlich, dass sich das Haarbündel als Einheit bewegt und der Gesamtwiderstand gering bleibt. Die Steifigkeit der Stereozilien und der Verbindungselemente sowie deren Geometrie sind in dem Modell sorgfältig angepasst, um eine Übereinstimmung mit den Beobachtungen aus verschiedenen Experimenten zu erzielen. Als Referenz dienen Steifigkeits- und Widerstandsmessungen, sowie Kohärenzmessungen für die gegenüberliegenden Außenkanten des Bündels, die jeweils mit und ohne Tiplinks durchgeführt wurden. Darüberhinaus sind die Ergebnisse durch den Vergleich mit experimentell beobachteten Relativbewegungen validiert, die das Haarbündel infolge von sinusförmiger Anregung bei Distorsionsfrequenzen zeigt. Diese haben ihren Ursprung in dem nichtlinearen Prozess des öffnens von Ionenkanälen. Das entwickelte Modell eines Haarbündels liefert neue Einblicke in den Schlüsselprozess der auditiven Wahrnehmung. Zur Behandlung von Problemen der Fluid-Struktur-Wechselwirkungen bei kleinen Amplituden hat sich der hier ausgearbeitete Ansatz als effizient und zuverlässig erwiesen.

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.

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