Wave energy is one of the most promising renewable energy sources for future exploitation. This thesis focuses on thermodynamic effects within Oscillating Water Column (OWC) devices equipped withWells turbines, particularly humidity effects. Previous theoretical studies of the operation of OWCs have resulted in expressions for the oscillation of the water surface in the chamber of an OWC based on linear wave theory, and the air expansion{compression cycle inside the air chamber based on ideal gas theory. Although in practice high humidity levels occur in OWC devices open to the sea, the influence of atmospheric conditions such as temperature and moisture on the performance of Wells turbines has not yet been studied in the field of ocean energy. Researchers have reported substantial differences between predicted and measured power output, and performance rates of OWCs presently coming into operation. The effect of moisture in the air chamber of the OWC causes variations on the atmospheric conditions near the turbine, modifying its performance and efficiency. Discrepancies in available power to the turbine are believed to be due to the humid air conditions, which had not been modelled previously. This thesis presents a study of the influence of humid air on the performance of an idealised Wells turbine in the chamber of an OWC using a real gas model. A new formulation is presented, including a modified adiabatic index, and subsequent modified thermodynamic state variables such as enthalpy, entropy and specific heat. The formulation is validated against experimental data, and found to exhibit better agreement than the ideal approach. The analysis indicates that the real gas behaviour can be explained by a non{dimensional number which depends on the local pressure and temperature in the OWC chamber. A first approach to the OWC formulation through the calculation of real air flow in the OWC is given, which predicts a 6% decrease in efficiency with respect to the ideal case when it is tested with a hypothetical pulse of pressure. This is important because accurate prediction of efficiency is essential for the optimal design and management of OWC converters. A numerical model has also been developed using computational fluid dynamics (CFD) to simulate the OWC characteristics in open sea. The performance of an OWC turbine is studied through the implementation of an actuator disk model in Fluent®. A set of different regular wave tests is developed in a 2D numerical wave flume. The model is tested using information obtained from experimental tests on a Wells{type turbine located in a wind tunnel. Linear response is achieved in terms of pressure drop and air flow in all cases, proving effectively the applicability of the actuator disk model to OWC devices. The numerical model is applied first to an OWC chamber containing dry air, and then to an OWC chamber containing humid air. Results from both cases are compared, and it is found that the results are sensitive to the degree of humidity of the air. Power decreases when humidity increases. Finally, results from the analytical real gas and numerical ideal gas models are compared. Very satisfactory agreement is obtained between the analytical and the numerical models when humidity is inserted in the gaseous phase. Both analytical and numerical models with humid air show considerable differences with the numerical model when dry air is considered. However, at the resonance frequency, results are independent of the gas model used. At every other frequency analysed, the real gas model predicts reduced values of power that can fall to 50% of the ideal power value when coupled to the radiation-diffraction model for regular waves. It is recommended that real gas should be considered in future analyses of Wells turbines in order to calculate accurately the efficiency and expected power of OWC devices.

Many highly developed physical models poorly approximate actual physical systems due to natural random noise. For example, convection in the earth's mantle—a fundamental process for understanding the geochemical makeup of the earth's crust and the geologic history of the earth—exhibits chaotic behavior, so it is difficult to model accurately. In addition, it is impossible to directly measure temperature and fluid viscosity in the mantle, and any indirect measurements are not guaranteed to be highly accurate. Over the last 50 years, mathematicians have developed a rigorous framework for reconciling noisy observations with reasonable physical models, a technique called data assimilation. We apply data assimilation to the problem of mantle convection with the infinite-Prandtl Boussinesq approximation to the Navier-Stokes equations as the model, providing rigorous conditions that guarantee synchronization between the observational system and the model. We validate these rigorous results through numerical simulations powered by a flexible new Python package, Dedalus. This methodology, including the simulation and post-processing code, may be generalized to many other systems. The numerical simulations show that the rigorous synchronization conditions are not sharp; that is, synchronization may occur even when the conditions are not met. These simulations also cast some light on the true relationships between the system parameters that are required in order to achieve synchronization. To conclude, we conduct experiments for two closely related data assimilation problems to further demonstrate the limitations of the rigorous results and to test the flexibility of data assimilation for mantle-like systems.

This thesis focuses on providing the means to use vertical-axis wind turbines (VAWTs) in wind farms as an alternative form of harnessing wind energy in offshore and urban environments where both wake and acoustic effects of turbines are important considerations. In order for VAWTs to be used in wind farm layout analysis and optimization, a reduced-order wake model is needed to calculate velocities around a turbine quickly and accurately. However, a VAWT wake model has not been available to accomplish this task. Using vorticity data from computational fluid dynamic (CFD) simulations of VAWTs and cross-validated Gaussian distribution and polynomial surface fitting, a wake model is produced that can estimate a wake velocity deficit of an isolated VAWT at any downstream and lateral position based on nondimensional parameters describing the turbine speed and geometry. When compared to CFD, which takes over a day to run one simulation, the wake model predicts the velocity deficit at any location with a normalized root mean squared error of 0.059 in about 0.02 seconds. The model agrees with two experimental VAWT wake studies with a percent difference of the maximum wake deficit of 6.3% and 14.6%. Using the actuator cylinder model with predicted wake velocities of multiple turbines, aerodynamic loads can be calculated on the turbine blades to estimate the power production of a VAWT wind farm. As VAWTs could be used in urban environments near residential areas, the noise disturbance coming from the turbine blades is an important consideration in the layout of a wind farm. Noise restrictions may be imposed on a wind farm to limit the disturbance, often impacting the wind farm's power producing capability. Two specific horizontal-axis wind turbine farm designs are studied and optimized using the FLORIS wake model and an acoustic model based on semi-empirical turbine noise calculations to demonstrate the impact a noise level constraint has on maximizing wind farm power production. When a noise level constraint was not active, the average power production increased, up to 8.01% in one wind farm and 3.63% in the other. Including a noise restriction in the optimization had about a 5% impact on the optimal average power production over a 5 decibel range. By analyzing power and noise together, the multi-modality of the optimization problem can be used to find solutions were noise impact can be improved while still maximizing wind farm power production.

Most fighters use the convergent-divergent nozzle configuration to accelerate into the supersonic realm. This nozzle configuration greatly increases the thrust potential of the aircraft compared to the simpler convergent nozzle. The nozzle design is not only crucial for thrust, but also for the drag since the afterbody drag can be as high as 15% of the total. Engine manufacturers optimize the engine and the nozzle configurations for the uninstalled conditions, but these may not be optimal when the engine is installed in the aircraft. The purpose of this study is to develop a methodology to optimize axisymmetric nozzle settings in order to maximize the net thrust. This was accomplished by combining both simulations of thrust and drag. The thrust model was created in an engine performance tool, called EVA, with the installed engine performance of a low bypass turbofan jet engine at maximum afterburner power setting. The drag model was created with CFD, where the mesh was built in ICEM Mesh and the simulations were run with the CFD solver M-Edge. Five Mach numbers in the range from 0.6 to 1.6 were simulated at an altitude of 12 km. The results showed that the afterbody drag generally decreased when increasing jet pressure ratio at both subsonic and supersonic velocities. At subsonic conditions, increasing nozzle area ratio for underexpanded nozzles would decrease the drag. Increasing nozzle area ratio for fully expanded or overexpanded nozzles would instead increase the drag to an intermediate point from where it would decrease. At supersonic condition, increasing nozzle area ratio would generally cause reduction in drag for all cases. The optimization showed that a net thrust increase of 0.02% to 0.09% could be gained for subsonic conditions while the supersonic optimization had negligible gain in thrust.

This dissertation presents the development and application of a computational model called BioChemFOAM developed using the computation fluid dynamic software OpenFOAM (Open source Field Operation And Manipulation). BioChemFOAM is a three dimensional incompressible unsteady-flow model that is coupled with a water-quality model via the Reynolds Average Navier-Stokes (RANS) equations. BioChemFOAM was developed to model nutrient dynamics in inland riverine aquatic ecosystems. BioChemFOAM solves the RANS equations for the hydrodynamics with an available library in OpenFOAM and implements a new library to include coupled systems of species transport equations with reactions. Simulation of the flow and multicomponent reactive transport are studied in detail for fundamental numerical experiments as well as for a real application in a backwater area of the Mississippi River. BioChemFOAM is a robust model that enables the flexible parameterization of processes for the nitrogen cycle. The processes studied include the following main components: algae, organic carbon, phosphorus, nitrogen, and dissolved oxygen. In particular, the research presented has three phases. The first phase involves the identification of the common processes that influence the nitrogen removal. The second phase covers the development and validation of the model that uses common parameterization to simulate the main features of an aquatic ecosystem. The main processes considered in the model and implemented in BioChemFOAM are: fully resolved hydraulic parameters (velocity and pressure), temperature variation, light's influence on the ecosystem, nutrients dynamics, algae growth and death, advection and diffusion of species, and isotropic turbulence (using a two-equation k-epsilon model). The final phase covers the application and analysis of the model and is divided in two sub stages: 1) a qualitative comparison of the main processes involved in the model (validation with the exact solution of different components of the model under different degrees of complexity) and 2) the quantification of main processes affecting nitrate removal in a backwater floodplain lake (Round Lake) in Pool 8 of the Mississippi River near La Crosse, WI. The BioChemFOAM model was able to reproduce different levels of complexity in an aquatic ecosystem and expose several main features that may help understand nutrient dynamics. The validation process with fabricated numerical experiments, discussed in Chapter 4, not only presents a detailed evaluation of the equations and processes but also introduces a step-by-step method of validating the model, given a level of complexity and parameterization when modeling nutrient dynamics in aquatic ecosystems. The study cases maintain fixed coefficients and characteristic values of the concentration in order to compare the influences that increasing or decreasing complexity has on the model, BioChemFOAM. Chapter 4, which focuses on model validation with numerical experiments, demonstrates that, with characteristic concentration and coefficients, some processes do not greatly influence the nutrient dynamics for algae. Chapters 5 and 6 discuss how BioChemFOAM was subsequently applied to an actual field case in the Mississippi River to show the model's ability to reproduce real world conditions when nitrate samples are available and other concentrations are used from typical monitored values. The model was able to reproduce the main processes affecting nutrient dynamics in the proposed scenarios and for previous studies in the literature. First, the model was adapted to simulate one species, nitrate, and its concentration was comparable to measured data. Second, the model was tested under different initial conditions. The model shows independence on initial conditions when reaching a steady mass flow rate for nitrate. Finally, a sensitivity analysis was performed using all eleven species in the model. The sensitivity takes as its basis the influence of processes on nitrate fate and transport and it defines eight scenarios. It was found in the present parameterization that green algae as modeled does not have a significant influence on improving nitrate spatial distributions and percentage of nitrate removal (PNR). On the other hand, reaction rates for denitrification at the bed and nitrification in the water shows an important influence on the nitrate spatial distribution and the PNR. One physical solution, from the broad range of scenarios defined in the sensitivity analysis, was selected as most closely reproducing the backwater natural system. The selection was based on published values of the percentage of nitrate removal (PNR), nitrate spatial concentrations, total nitrogen spatial concentrations and mass loading rate balances. The scenario identified as a physically valid solution has a reaction rate of nitrification and denitrification at the bed of 2.37x10-5 s-1. The PNR was found to be 39% when reaching a steady solution for the species transport. The denitrification at the bed process was about 6.7% of the input nitrate mass loading rate and the nitrification was about 7.7% of the input nitrate mass loading rate. The present research and model development highlight the need for additional detailed field measurements to reduce the uncertainty of common processes included in advanced models (see Chapter 2 for a review of models and Chapter 3 for the proposed model). The application presented in Chapter 6 utilizes only spatial variations of nitrate and total nitrogen to validate the model, which limits the validation of the remaining species. Despite the fact that some species are not known a priori, numerical experiments serve as a guide that helps explain how the aquatic ecosystem responds under different initial and boundary conditions. In addition, the PNR curves presented in this research were useful when defining realistic removal rates in a backwater area. BioChemFOAM's ability to formulate scenarios under different driving forces makes the model invaluable in terms of understanding the potential connections between species concentration and flow variables. In general, the case study presents trends in spatial and temporal distributions of non-sampled species that were comparable to measured data.

An imaging-based computational framework for simulation of airflow in subject specific breathing human lungs is established. The three-dimensional (3D) airways of up to 9 generations and lobes are segmented and reconstructed from computed tomography (CT) images. Beyond the CT-resolved 3D airways, a volume filling method is applied to generate the one-dimensional (1D) conducting airway tree that bridges the central airway with the lung parenchyma. Through 3D-1D airway coupling, a novel image-registration-based boundary condition (BC) is proposed to derive physiologically-consistent regional ventilation for the whole lung and provide flow-rate fractions needed for the 3D airway model via the 1D-tree connectivity and the mass conservation. The in-house parallel finite-element large-eddy simulation (LES) code enables to capture genuinely complex airflow characteristics in a computationally-efficient manner. The 3D-1D coupling framework is multiscale because it can not only predict detailed flows in the 3D central airways at a local level, but also yields subject-specific physiologically-consistent regional ventilation at the whole lung level. The framework has been applied to investigate pulmonary airflow and lung physiology. For example, the study of intra- and inter-subject variability provides insight into the effect of airway geometry on airflow structure. The relations between airflow structure, energy dissipation, and airway resistance under normal breathing condition have also been studied, showing similarity behaviors for inspiratory and expiratory flows. In the study of high-frequency oscillatory ventilation, we have compared counter-flow structures near flow reversal (namely phase change between inspiration and expiration) and quantified associated convective mixing in both idealized and CT-based airway models. Furthermore, the image-registration-derived displacement field is used to deform 3D-1D airway models for breathing lung simulation and estimate diameter changes of 1D airway segments during deformation. In conjunction with an arbitrary Lagrangian Eulerian method, airflow in a breathing lung has been simulated and compared with that of a rigid airway model. The results show that the proposed computational framework is promising in better understanding the human lung physiology and improving the treatment of diseased lung.

This thesis focuses on the effects of wave-induced motions on the airwake of a ship and on the operation of a helicopter in the airwake. While the topic is broad, efforts are concentrated on understanding fundamentals of the ship’s airwake structure at varying Reynolds (Re) numbers without motions, using available experimental data for validation of the computational fluid dynamics (CFD) methodology used, and on studying the effects of waves and motions on the airwake of a ship and a helicopter operating above a ship’s flight deck in full-scale. The static ONR Tumblehome (ONRT) ship geometry with a solid boundary representative of the free surface is simulated at three different Re numbers, 3.2x104, 1x106, and 1.3x108. Validation is performed against experimental measurements at model-scale Re=1x106. Full-scale simulations of the ONRT are carried out in head winds and regular waves approximately equivalent to conditions seen at sea states 3 and 6. Effects of waves and motions are isolated for both sea states using simulations with combinations of waves and motions, waves and no motions, no waves with motions, and no motions or waves. A triple velocity decomposition is conducted in order to quantify changes in the airwake due to motions and waves. The operation of rotorcraft in the ONRT airwake is analyzed using one-way and two-way coupling approaches. The one-way coupling approach uses the velocity field data from the full-scale ONRT simulations and disk actuator theory to calculate thrust fluctuations for three different rotor sizes. The results of the one-way coupling approach show that the smallest rotor is much more affected by small scale turbulence, while small scale fluctuations are filtered out by larger rotor diameters. In the two-way coupling approach, a helicopter based on the Sikorsky SH-60 hovering above the flight deck is simulated, including explicitly moving grids to discretize the main rotor, tail rotor, and fuselage. This method captures the effects of the interaction between the rotor downwash and the ONRT airwake. The study shows that for the mild conditions of sea state 3 the motions have little effect on the airwake behavior. At sea state 6 the airwake behavior is significantly altered, which is reflected in the resulting forces on the helicopter body operating in this condition.

Cardiovascular modeling has the capability to provide valuable information allowing clinicians to better classify patients and aid in surgical planning. Modeling is advantageous for being non-invasive, and also allows for quantification of values not easily obtained from physical measurements. Hemodynamics are heavily dependent on vessel geometry, which varies greatly from patient to patient. For this reason, clinically relevant approaches must perform these simulations on patient-specific geometry. Geometry is acquired from various imaging modalities, including magnetic resonance imaging, computed tomography, and ultrasound. The typical approach for generating a computational model requires construction of a triangulated surface mesh for use with finite volume or finite element solvers. Surface mesh construction can result in a loss of anatomical features and often requires a skilled user to execute manual steps in 3rd party software. An alternative to this method is to use a Cartesian grid solver to conduct the fluid simulation. Cartesian grid solvers do not require a surface mesh. They can use the implicit geometry representation created during the image segmentation process, but they are constrained to a cuboidal domain. Since patient-specific geometry usually deviate from the orthogonal directions of a cuboidal domain, flow extensions are often implemented. Flow extensions are created via a skilled user and 3rd party software, rendering the Cartesian grid solver approach no more clinically useful than the triangulated surface mesh approach. This work presents an alternative to flow extensions by developing a method of applying vessel inlet and outlet boundary conditions to regions inside the Cartesian domain.

Dust is ubiquitous in underground mine activities. Continuous inhalation of dust could lead to irreversible occupational diseases. Dust particles of size lower than 75.0 µm, also known as float coal dust, can trigger a coal dust explosion following a methane ignition. Ventilation air carries the float coal dust from the point of production to some distance before it’s deposited on the surfaces of underground coal mine. Sources of dust are widely studied, but study of dust transportation has been mainly based on experimental data and simplified models. An understanding of dust transportation in the mine airways is instrumental in the implementation of local dust control strategies. This thesis presents techniques for sampling float coal dust, computational fluid dynamics (CFD) analysis, and mathematical modeling to estimate average dust deposition in an underground coal mine. Dust samples were taken from roof, ribs, and floor at multiple areas along single air splits from longwall and room and pillar mines. Thermogravimetric analysis of these samples showed no conclusive trends in float coal dust deposition rate with location and origin of dust source within the mine network. CFD models were developed using the Lagrangian particle tracking approach to model dust transportation in reduced scale model of mine. Three dimensional CFD analysis showed random deposition pattern of particle on the mine model floor. A pseudo 2D model was generated to approximate the distance dust particles travel when released from a 7 ft. high coal seam. The models showed that lighter particles released in a high airflow field travel farthest. NIOSH developed MFIRE software was adopted to simulate dust transportation in a mine airway analogous to fume migration. The simulations from MFIRE can be calibrated using the dust sampling results to estimate dust transportation in the ventilation network.

Computational Fluid Dynamics (CFD) has been applied to investigate two aspects of a mixing process for high level nuclear waste tanks. Through CFD the applicability of Poreh’s correlations that are currently used to describe the radial wall jets in the Pulse Jet Mixing (PJM) process were assessed. In addition, simulations were conducted in order to investigate mean hydrodynamic characteristics of sparged non-Newtonian fluids for the use in the PJM process. Three single phase turbulent simulations using the commercial package STAR-CCM+ were successively conducted. A model validated with experimental data was developed and successively altered to see effects of low characteristic ratio and a curved impingement surface. Results suggested that Poreh’s correlations are applicable under PJM conditions and geometry. Lastly, multi-phase Eulerian-Eulerian Simulations were conducted using the commercial software package ANSYS Fluent. Altering the characteristic ratio (h/D) of a sparged non-Newtonian fluid system resulted in a trend of flattening air volume fraction and air axial velocity profiles with decreasing characteristic ratio.