This thesis presents a computational fluid dynamics (CFD) model of fluid flow driven by the motion of cilia, a cellular appendage found in organisms used to either move the fluid around them or to move themselves by propelling the fluid. Originating from an initial investigation to the flow patterns inside the third ventricle of a rat’s brain, this project expanded to improve the inadequacies of existing models of ciliary motion in fluid. This model was developed using the actuator line model to include the cilia motion to get an accurate representation of the cilia motion and its effect on the flow. This model not only provides exciting potential in various fields including soft robotics, biomedical research, environmental engineering, but also holds promise for drug delivery systems, and enhancing microfluidic designs. This thesis investigates the effect of the phase difference, the spacing and the frequency of the cilia motion on the fluid flow and the formation of the metachronal waves.

This dissertation investigates the complex dynamics of semi-dilute inertial particles suspended in vortices using the Eulerian-Lagrangian method. The study explores the modulation of flow induced by inertial particles, focusing on the characteristics of a single vortex, instability analysis within particle-laden flows, and the merging process of co-rotating vortices. Simulations reveal a preferential concentration mechanism, where inertial particles cluster around a void fraction bubble, accelerating the decay of the vortex tube. Small-scale clusters, arising from particle-trajectory crossings, induce significant gradients in the fluid vorticity field, contributing to rapid vortex breakdown. Within a specific Stokes number range, increased particle inertia results in faster vortex decay and stronger inhomogeneity in the particle phase. The instability mechanism in particle-laden flows is explored using a Rankine vortex model. Two-way coupling triggers azimuthal perturbations, leading to the breakdown of the vortex structure. Linear Stability Analysis and Two-Fluid modeling demonstrate that the dusty vortex flow exhibits unstable modes, with growth rates increasing with wavenumber. Eulerian-Lagrangian simulations validate these results, showing excellent agreement between computed and predicted growth rates. The dissertation also delves into the co-rotating vortex merger in a semi-dilute dusty flow. For weak inertial effects, merger experiences a delay compared to particle-free vortices. Under moderate inertial conditions, the merger process exhibits repulsion, increased separation, and eventual convective merger stages. Highly inertial particles stretch the vortex core, initiating a merger with an outcome of a particle-free vortex core surrounded by a halo of concentrated particles. In conclusion, the feedback force from the dispersed phase induces instability and significantly influences the dynamics of vortices in particle-laden flows. The findings contribute to a deeper understanding of the intricate interactions between inertial particles and vortical structures.

This thesis focuses on the turbulent bluff body wakes in incompressible and compressible flows. An incompressible wake flow past an axisymmetric body of revolution at a diameter-based Reynolds number Re=5000 is investigated via a direct numerical simulation. It is followed by the development of a compressible solver using a split-form discontinuous Galerkin spectral element method framework with shock capturing. In the study on incompressible wake flows, three dominant coherent vortical motions are identified in the wake: the vortex shedding motion with the frequency of St=0.27, the bubble pumping motion with St=0.02, and the very-low-frequency (VLF) motion originated in the very near wake of the body with the frequencies St=0.002 and 0.005. The very-low-frequency motion is associated with a slow precession of the wake barycenter. The vortex shedding pattern is demonstrated to follow a reflectional symmetry breaking mode, with the detachment location rotating continuously and making a full circle over one vortex shedding period. The VLF radial motion with St=0.005 originates as m = 1 mode, but later transitions into m = 2 mode in the intermediate wake. Proper orthogonaldecomposition (POD) and dynamic mode decomposition (DMD) are further performed to analyze the spatial structure associated with the dominant coherent motions. Results of the POD and DMD analysis are consistent with the results of the azimuthal Fourier analysis. To extend the current incompressible code to be able to solve compressible flows, a computational methodology is developed using a high-order approximation for the compressible Navier-Stokes equations with discontinuities. The methodology is based on a split discretization framework with a summation-by-part operator. An entropy viscosity method and a subcell finite volume method are implemented to capture discontinuities. The developed high-order split-form with shock-capturing methodology is subject to a series of evaluation on cases from subsonic to hypersonic, from one-dimensional to three dimensional. The Taylor-Green vortex case and the supersonic sphere wake case show the capability to handle three-dimensional turbulent flows without and with the presence of shocks. It is also shown that higher-order approximations yield smaller errors than lower-order approximations, for the same number of total degrees of freedom.

This work aims to address the design optimization of bio-inspired locomotive devices in collective swimming by developing a computational methodology which combines surrogate-based optimization with high fidelity fluid-structure interactions (FSI) simulations of thunniform swimmers. Three main phases highlight the contribution and novelty of the current work. The first phase includes the development and bench-marking of a constrained surrogate-based optimization algorithm which is appropriate to the current design problem. Additionally, new FSI techniques, such as a volume-conservation scheme, has been developed to enhance the accuracy and speed of the simulations. The second phase involves an investigation of the optimized hydrodynamics of a solitary accelerating self-propelled thunniform swimmer during start-up. The third phase extends the analysis to include the optimized hydrodynamics of accelerating swimmers in phalanx schools. Future work includes extending the analysis to the optimized hydrodynamics of steady-state and accelerating swimmers in a diamond-shaped school. The results of the first phase indicate that the proposed optimization algorithm maintains a competitive performance when compared to other gradient-based and gradient-free methods, in dealing with expensive simulations-based black-box optimization problems with constraints. In addition, the proposed optimization algorithm is capable of insuring strictly feasible candidates during the optimization procedure, which is a desirable property in applied engineering problems where design variables must remain feasible for simulations or experiments not to fail. The results of the second phase indicate that the optimized kinematic gait of a solitary accelerating swimmer generates the reverse Karman vortex street associated with high propulsive efficiency. Moreover, the efficiency of sub-optimum modes, in solitary swimming, is found to increase with both the tail amplitude and the effective flapping length of the swimmer, and a new scaling law is proposed to capture these trends. Results of the third phase indicate that the optimal midline kinematics in accelerating phalanx schools resemble those of accelerating solitary swimmers. The optimal separation distance in a phalanx school is shown to be around 2L (where L is the swimmer's total length). Furthermore, separation distance is shown to have a stronger effect, ceteris paribus, on the propulsion efficiency of a school when compared to phase synchronization.

Modern aircraft propulsion systems such as the ultra high bypass ratio turbofan impose constraints on engine installation below the wing, causing jet–wing interactions. Similar interactions are encountered when a jet-powered aircraft takes off on airport runway or aircraft carrier deck. High-speed jet flow near a solid surface shows markedly different turbulence characteristics compared with free jet, including attached turbulent jet and development of non-equilibrium boundary layer down- stream. Wall pressure fluctuations tend to be more unsteady and stronger, leading to increased vibration affecting aircraft cabin noise and modified jet noise radiation. Large-eddy simulation (LES) is useful to characterize turbulent jet flows over a solid surface as well as wall pressure distribution to promote physical understanding and modeling studies. In this study, LES is performed for an installed setup of a Mach 0.7 turbulent jet where the jet–plate distance is fixed at 2D where D is the nozzle-exit diameter. Unstructured-grid LES is used to validate the corresponding experiment (from literature). In addition, a high-fidelity numerical database is built for further analysis and modeling. Turbulence statistics and energy spectra show that agreement with the experimental measurement for the installed case is encouraging, paving a way for future analysis and modeling.

Realistic engineering, physical and biological systems are very complex in nature, and their response and performance are governed by multitude of interacting processes. In computational modeling of these systems, the interactive response is most often ignored, and simplifications are made to model one or a few relevant phenomena as opposed to a complete set of interacting processes due to a complexity of integrative analysis. In this thesis, I will develop new high-order computational approaches that reduce the amount of simplifications and model the full response of a complex system by accounting for the interaction between different physical processes as required for an accurate description of the global system behavior. Specifically, I will develop multi-physics coupling techniques based on spectral-element methods for the simulations of such systems. I focus on three specific applications: fluid-structure interaction, conjugate heat transfer, and modeling of acoustic wave propagation in non-uniform media. Fluid-structure interaction illustrates a complex system between a fluid and a solid, where a movable and deformable structure is surrounded by fluid flow, and its deformation caused by fluid affects the fluid flow interactively. To simulate this system, two coupling schemes are developed: 1) iterative implicit coupling, and 2) explicit coupling based on Robin-Neumann boundary conditions. A comprehensive verification strategy of the developed methodology is presented, including a comparison with benchmark flow solutions, h-, p- and temporal refinement studies. Simulation of a turbulent flow in a channel interacting with a compliant wall is attempted as well. Another problem I consider is when a solid is stationary, but a heat transfer occurs on the fluid-solid interface. To model this problem, a conjugate heat transfer framework is introduced. Validation of the framework, as well as studies of an interior thermal environment in a building regulated by an HVAC system with an on/off control model with precooling and multi-zone precooling strategies are presented. The final part of this thesis is devoted to modeling an interaction of acoustic waves with the fluid flow. The development of a spectral-element methodology for solution of Lighthill’s equation, and its application to a problem of leak detection in water pipes is presented.

Compressible fluid flows involving multiple physical states of matter occur in both nature and technical applications such as underwater explosions and implosions, cavitation-induced bubble collapse in naval applications and Richtmyer-Meshkov type instabilities in inertial confinement fusion. Of particular interest is the atomization of fuels that enable shock-induced mixing of fuel and oxidizer in supersonic combustors. Due to low residence times and varying length scales, providing insight through physical experiments is both technically challenging and sometimes unfeasible. Numerical simulations can help provide detailed insight and aid in the engineering design of devices that can harness these physical phenomena.

In this research, computational methods were developed to accurately simulate phase interfaces in compressible fluid flows with a focus on targeting primary atomization. Novel numerical methods which treat the phase interface as a discontinuity, and as a smeared region were developed using low-dissipation, high-order schemes. The resulting methods account for the effects of compressibility, surface tension and viscosity. To aid with the varying length scales and high-resolution requirements found in atomization applications, an adaptive mesh refinement (AMR) framework is used to provide high-resolution only in regions of interest. The developed methods were verified with test cases involving strong shocks, high density ratios, surface tension effects and jumps in the equations of state, in one-, two- and three dimensions, obtaining good agreement with theoretical and experimental results. An application case of the primary atomization of a liquid jet injected into a Mach 2 supersonic crossflow of air is performed with the methods developed.

Lidar has demonstrated its utility in meteorological studies, wind resource assessment, and wind farm control. More recently, lidar has gained widespread attention for autonomous vehicles.

The first part of the dissertation begins with an application of a coherent Doppler lidar to wind gust characterization for wind farm control. This application focuses on wind gusts on a scale from 100 m to 1000 m. A detecting and tracking algorithm is proposed to extract gusts from a wind field and track their movement. The algorithm was implemented for a three-hour, two-dimensional wind field retrieved from the measurements of a coherent Doppler lidar. The Gaussian distribution of the gust spanwise deviation from the streamline was demonstrated. Size dependency of gust deviations is discussed. A prediction model estimating the impact of gusts with respect to arrival time and the probability of arrival locations is introduced. The prediction model was applied to a virtual wind turbine array, and estimates are given for which wind turbines would be impacted.

The second part of this dissertation describes a Time-of-Flight lidar simulation. The lidar simulation includes a laser source module, a propagation module, a receiver module, and a timing module. A two-dimensional pulse model is introduced in the laser source module. The sampling rate for the pulse model is explored. The propagation module takes accounts of beam divergence, target characteristics, atmosphere, and optics. The receiver module contains models of noise and analog filters in a lidar receiver. The effect of analog filters on the signal behavior was investigated. The timing module includes a Time-to-Digital Converter (TDC) module and an Analog-to-Digital converter (ADC) module. In the TDC module, several walk-error compensation methods for leading-edge detection and multiple timing algorithms were modeled and tested on simulated signals. In the ADC module, a benchmark (BM) timing algorithm is proposed. A Neyman-Pearson (NP) detector was implemented in the time domain and frequency domain (fast Fourier transform (FFT) approach). The FFT approach with frequency-domain zero-paddings improves the timing resolution. The BM algorithm was tested on simulated signals, and the NP detector was evaluated on both simulated signals and measurements from a prototype lidar (Bhaskaran, 2018).

This work helps to explain the drag reduction mechanisms at low and moderate turbulent Reynolds numbers in pipe flows. Through direct numerical simulation, the effects of wall oscillations are observed on the turbulence in both the near wall and the bulk region. Analysis of the average Reynolds Stresses at various phases of the flow is provided along with probability density functions of the fluctuating components of velocity and vorticity. The flow is also visualized to observe, qualitatively, changes in the total and fluctuating field of velocity and vorticity. Linear Stochastic Estimation is used to create a conditional eddy (associated with stress production) in the flow and visualize the effects of transverse wall oscillations on hairpin growth, auto-generation and structure.

The goal of this paper was to do an analysis of two-dimensional unsplit mass and momentum conserving Finite Volume Methods for Advection for Volume of Fluid Fields with interfaces and validating their rates of convergence. Specifically three unsplit transport methods and one split transport method were amalgamated individually with four Piece-wise Linear Reconstruction Schemes (PLIC) i.e. Unsplit Eulerian Advection (UEA) by Owkes and Desjardins (2014), Unsplit Lagrangian Advection (ULA) by Yang et al. (2010), Split Lagrangian Advection (SLA) by Scardovelli and Zaleski (2003) and Unsplit Averaged Eulerian-Lagrangian Advection (UAELA) with two Finite Difference Methods by Parker and Youngs (1992) and two Error Minimization Methods by Pilliod Jr and Puckett (2004). The observed order of accuracy was first order in all cases except when unsplit methods and error minimization methods were used consecutively in each iteration, which resulted in second-order accuracy on the shape error convergence. The Averaged Unsplit Eulerian-Lagrangian Advection (AUELA) did produce first-order accuracy but that was due to a temporal error in the numerical setup. The main unsplit methods, Unsplit Eulerian Advection (UEA) and Unsplit Lagrangian Advection (ULA), preserve mass and momentum and require geometric clipping to solve two-phase fluid flows. The Unsplit Lagrangian Advection (ULA) can allow for small divergence in the velocity field perhaps saving time on the iterative solver of the variable coefficient Poisson System.