Thesis (Ph.D.) - University of St Andrews, March 2009.

This thesis contains a thorough investigation of the properties of freely decaying turbulence in a rotating shallow water layer on a sphere. A large number of simulations, covering an extensive range of Froude and Rossby numbers, have been carried out using a novel numerical algorithm that exploits the underly- ing properties of the flow. In general these flows develop coherent structures; vortices interact, merge and migrate polewards or equatorwards depending or their sign, leaving behind regions of homogenized potential vorticity separated by sharp zonal jets. In the first half of the thesis we investigate new ways of looking at these structures. In the second half of the thesis we examine the properties of the potential vorticity (PV) induced, balanced component and the residual, unbalanced component of the flows. Cyclone-anticyclone asymmetry has long been observed in atmospheric and oceanic data, laboratory experiments and numerical simulations. This asymmetry is usually seen to favour anticyclonic vorticity with the asymmetry becoming more pronounced at higher Froude numbers (e.g. Polvani et al. [1994a]). We find a similar result but note that the cyclones, although fewer, are significantly more intense and coherent. We present several ways of quantifying this across the parameter space. Potential vorticity homogenization is an important geophysical mechanism responsible for sharpening jets through the expulsion of PV gradients to the edge of flow structures or domains. Sharp gradients of PV are obvious in contour plots of this field as areas where the contours are bunched together. This suggests that we can estimate the number of zonal jets by performing a cluster analysis on the mean latitude of PV contours (this diagnostic is also examined by Dritschel and McIntyre [2007]). This provides an estimate rather than an exact count of the number of jets because the jets meander signficantly. We investigate the accuracy of the estimates provided by different clustering techniques. We find that the properties of the jets defy such simple classification and instead demand a more local examination. We achieve this by examining the palinstrophy field. This field, calculated by taking the gradient of the PV, highlights the regions where PV contours come closer together, exactly what we would expect in regions of strong jets. Plots of the palinstrophy field reveal the complex structure of these features. The potential vorticity field is even more central to the flow evolution than the strong link with jets suggests. From a knowledge of the spatial distribution of PV, it is possible to diagnose the balanced components of all other fields. These components will not contain inertia-gravity waves but will contain the dominant, large scale features of the flow. This inversion, or decomposition into balanced (vortical) and unbalanced (wave) components, is not unique and can be defined to varying orders of accuracy. We examine the results of four dfferent definitions of this decomposition, two based on truncations of the full equations and two based on an iterative procedure applied to the full equations. We find the iterative procedure to be more accurate in that it attributes more of the flow to the PV controlled, balanced motion. However, the truncated equations perform surprisingly well and do not appear to suffer in accuracy at the equator, despite the fact that the scaling on which they are based has been thought to break down there. We round off this study by considering the impact of the unbalanced motion on the flow. This is accomplished by splitting the integration time of the model into intervals τ < t < τ+dτ and comparing, at the end of each interval, the balanced components of the flow obtained by a) integrating the model from t = 0 and b) integrating the full equations, initialised at t = τ with the balanced components from a) at t = τ. We find that any impact of the unbalanced component of the flow is less than the numerical noise of the model.

In this thesis we study a variety of problems in fluid turbulence, principally in two dimensions. A summary of the main results of our studies is given below; we indicate the Chapters in which we present these. In Chapter 1, we provide an overview of several problems in turbulence with special emphasis on background material for the problems we study in this thesis. In particular, we give (a) natural and laboratory examples of fluid turbulence, (b) and introductory accounts of the equations of hydrodynamics, without and with polymer additives, Eulerian and Lagrangian frameworks, and the equations of motion of inertial particles in fluid flows. We end with a summary of the problems we study in subsequent Chapters of this thesis. In Chapter 2, we carry out the most extensive and high-resolution direct numerical simulation, attempted so far, of homogeneous, isotropic turbulence in two-dimensional fluid films with air-drag-induced friction and with polymer additives. Our study reveals that the polymers (a) reduce the total fluid energy, enstrophy, and palinstrophy, (b) modify the fluid energy spectrum both in inverse- and forward-cascade regimes, (c) reduce small-scale intermittency, (d) suppress regions of large vorticity and strain rate, and (e) stretch in strain-dominated regions. We compare our results with earlier experimental studies and propose new experiments. In Chapter 3, we perform a direct numerical simulation (DNS) of the forced, incompressible two-dimensional Navier-Stokes equation coupled with the FENE-P equations for the polymer- conformation tensor. The forcing is such that, without polymers and at low Reynolds numbers Re, the lm attains a steady state that is a square lattice of vortices and anti-vortices. We nd that, as we increase the Weissenberg number (Wi), this lattice undergoes a series of nonequilibrium phase transitions, first to spatially distorted, but temporally steady, crystals and then to a sequence of crystals that oscillate in time, periodically, at low Wi, and quasiperiodically, for slightly larger Wi. Finally, the system becomes disordered and displays spatiotepmoral chaos and elastic turbulence. We then obtain the nonequilibrium phase diagram for this system, in the Wi − Re plane, and show that (a) the boundary between the crystalline and turbulent phases has a complicated, fractal-type character and (b) the Okubo-Weiss parameter provides us with a natural measure for characterizing the phases and transitions in this diagram. In Chapter 4, our study is devoted to heavy, inertial particles in two-dimensional (2D) tur- bulent, but statistically steady, flows that are homogeneous and isotropic. The inertial particles are distributed uniformly in our simulation domain when St = 0; they start to cluster as St increases; this clustering tendency reaches a maximum at St 1 and decreases thereafter. We then obtain PDFs of and show that their left tails, which come from extensional regions, do not depend sensitively on St; in contrast, their right tails, from the vortical regions of the flow, are consistent with the exponential form ∼ exp ‰− + Ž; and we nd that the scale + decreases with St until St _0:1 and then saturates at a value _0:75. Our persistence-type studies yield the following results, when we consider forcing that leads to an energy spectrum that is dominated by a forward-cascade regime: In strain-dominated or extensional regions of the flow, wend that the cumulative PDF of the persistence time decays exponentially; this decay yields a time scale T−, which increases rapidly with St, at low values of St, but more slowly after St _0:75. By contrast, in vortical regions of the flow, this cumulative PDF displays a tail that has power-law and exponential parts; the power-law part yields the persistence exponent _ and the exponential tail gives a time scale T−; _ increases with St, whereas T− decreases with St; _ and T− reach saturation values as St increases. From the cumulative PDF of the particle mean-square displacement r2, we obtain the time scale Ttrans at which there is a crossover from ballistic to diffusive behavior; we _nd that Ttrans increases with St. The PDFs of v2, the square of the particle velocity, and v2 ejected, the square of the velocity of a particle just as it is ejected from a region with _ > 0 (vortical region) to one that has _ < 0 (extensional region), do not show a significant dependence on St; the tails of these PDFs are characterized by power-law decays with exponents _1 and _5~3, respectively. Our next set of results deal with statistical properties of special combinations of the acceleration a =dv~dt and the velocity v. For instance, the curvature of the trajectory is _ =aÙ~v2, where the subscript Ù denotes the component perpendicular to the particle trajectory; we obtain PDFs of _ and _nd there from that particles in regions of elongational flow have, on average, trajectories with a lower curvature than particles in vortical regions; this . We also determine how the number of number of points NI , at which a ×v changes sign along a particle trajectory, as time increases; we _nd that the increase of NI with time and decrease as St increases. Our ninth set of results show that the characteristic decay time T_ for decreases with St. In Chapter 5, we study the statistical properties of orientation and rotation dynamics of elliptical tracer particles in two-dimensional, homogeneous and isotropic turbulence by direct numerical simulations. We consider both the cases in which the turbulent flow is generated by forcing at large and intermediate length scales. We show that the two cases are qualitatively different. For the large-scale forcing, the spatial distribution of particle orientations forms large- scale structures, which are absent for the intermediate-scale forcing. The alignment with the local directions of the flow is much weaker in the latter case than in the former. For the intermediate- scale forcing, the statistics of rotation rates depends weakly on the Reynolds number and on the aspect ratio of particles. In contrast with what is observed in three-dimensional turbulence, in two dimensions the mean-square rotation rate decreases as the aspect ratio increases. In Chapter 6, we study the issue of intermittency in numerical solutions of the 3D Navier-Stokes equations on a periodic box [0; L]3. This is addressed through four sets of numerical simulations that calculate a new set of variables defined by Dm(t) = where All four simulations unexpectedly show that the Dm are ordered for m =1 ….,9 such that Dm+1 <Dm. Moreover, the Dm squeeze together such that Dm+1/Dm 1 as m increases. The values of D1 lie far above the values of the rest of the Dm, giving rise to a suggestion that a depletion of nonlinearity is occuring which could be the cause of Navier{Stokes regularity. The first simulation, by R. Kerr, is of very anisotropic decaying turbulence ; the second and third, which have been carried out by me, are of decaying isotropic turbulence from random initial conditions and forced isotropic turbulence at fixed Grashof number, respectively ; the fourth, by D. Donzis, is of very-high-Reynolds-number forced, stationary, isotropic turbulence at resolutions up to 40963 collocation points. For the sake of completeness and for a comparison of the data from all these four simulations, all the results are presented; however, in the Sections that deal with the simulations, I indicate who carried out the calculations reported there. I also present an extension of this work to two-dimensional fluid turbulence; this has not been submitted for publication so far. We hope our in silico studies of 2D and 3D turbulence will stimulate new experimental, numerical, and theoretical studies.

No description available.

The study of finite-sized, deformable droplets adverted by turbulent flows is an active area of research. It spans many streams of sciences and engineering, which include chemical engineering, fluid mechanics, statistical physics, nonlinear dynamics, and also biology. Advances in experimental techniques and high-performance computing have made it possible to investigate the properties of turbulent fluids laden with droplets. The main focus of this thesis is to study the statistical properties of the dynamics of such finite-size droplets in turbulent flows by using direct numerical simulations (DNSs). The most important feature of the model we use is that the droplets have a back-reaction on the advecting fluid: the turbulent fluid affects the droplets and they, in turn, affect the turbulence of the fluid. Our study uncovers (a) statistical properties that characterize the spatiotemporal evolution of droplets in turbulent flows, which are statistically homogeneous and isotropic, and (b) the modification of the statistical properties of this turbulence by the droplets. This thesis is divided into seven Chapters. Chapter 1 contains an introduction to the background material that is required for this thesis, especially the details about the equations we use; it also contains an outline of the problems we study in subsequent Chapters. Chapter 2 contains our study of “Droplets in Statistically Homogeneous Turbulence: From Many Droplets to a few Droplets”. Chapter 3 is devoted to our study of “Coalescence of Two Droplets”. Chapter 4 deals with “Binary-Fluid Turbulence: Signatures of Multifractal Droplet Dynamics and Dissipation Reduction”. Chapter 5 deals with “A BKM-type theorem and associated computations of solutions of the three-dimensional Cahn-Hilliard-Navier-Stokes equations”. Chapter 6 is devoted to our study of “Turbulence-induced Suppression of Phase Separation in Binary-Fluid Mixtures”. Chapter 7 is devoted to our study of “Antibubbles: Insights from the Cahn-Hilliard-Navier-Stokes Equations”.

No description available.

We consider the statistical inverse problem of estimating a background flow field (e.g., of air or water) from the partial and noisy observation of a passive scalar (e.g., the concentration of a pollutant). Here the unknown is a vector field that is specified by large or infinite number of degrees of freedom. We show that the inverse problem is ill-posed, i.e., there may be many or no background flows that match a given set of observations. We therefore adopt a Bayesian approach, incorporating prior knowledge of background flows and models of the observation error to develop probabilistic estimates of the fluid flow. In doing so, we leverage frameworks developed in recent years for infinite-dimensional Bayesian inference. We provide conditions under which the inference is consistent, i.e., the posterior measure converges to a Dirac measure on the true background flow as the number of observations of the solute concentration grows large. We also define several computationally-efficient algorithms adapted to the problem. One is an adjoint method for computation of the gradient of the log likelihood, a key ingredient in many numerical methods. A second is a particle method that allows direct computation of point observations of the solute concentration, leveraging the structure of the inverse problem to avoid approximation of the full infinite-dimensional scalar field. Finally, we identify two interesting example problems with very different posterior structures, which we use to conduct a large-scale benchmark of the convergence of several Markov Chain Monte Carlo methods that have been developed in recent years for infinite-dimensional settings. / Ph. D. / We consider the problem of estimating a fluid flow (e.g., of air or water) from partial and noisy observations of the concentration of a solute (e.g., a pollutant) dissolved in the fluid. Because of observational noise, and because there are cases where the fluid flow will not affect the movement of the pollutant, the fluid flow cannot be uniquely determined from the observations. We therefore adopt a statistical (Bayesian) approach, developing probabilistic estimates of the fluid flow using models of observation error and our understanding of the flow before measurements are taken. We provide conditions under which, as the number of observations grows large, the approach is able to identify the fluid flow that generated the observations. We define several efficient algorithms for computing statistics of the fluid flow, one of which involves approximating the movement of individual solute particles to estimate concentrations only where required by the inverse problem. We identify two interesting example problems for which the statistics of the fluid flow are very different. The first case produces an approximately normal distribution. The second example exhibits highly nonGaussian structure, where several different classes of fluid flows match the data very well. We use these examples to test the functionality and efficiency of several numerical (Markov Chain Monte Carlo) methods developed in recent years to compute the solution to similar problems.

Particle laden turbulent flows find applications in many industrial processes such as energy conversion, air pollution control etc. In these types of flows, there are strong coupling between the turbulent fluctuations in the fluid velocity fields, and the fluctuating velocities of the particles. In order to analyze the stresses and the heat and mass transfer properties in turbulent suspensions, it is necessary to have a good understanding of not just the mean flow of the gas and particles, but also of the fluctuations in the two phases. The coupling is a two-way coupling; the fluid turbulence contributes to the velocity fluctuations in the particles, and conversely, the particle velocity fluctuations generate fluctuations in the fluid. Two-phase flow models capture these interactions only in an indirect way, usually through a ‘particle pressure’ term for the particle phase. In the present work the effect of fluid velocity fluctuations on the dynamics of the particles in a turbulent gas-solid suspension is analyzed in the low Reynolds number and high Stokes number limit, where the particle relaxation time is long compared to the correlation time for the fluid velocity fluctuations. The direct numerical simulation (DNS) is used for solving the Navier-Stokes equations for the fluid, the particles are modeled as hard spheres which undergo elastic collisions. A one-way coupling algorithm is used where the force exerted by the fluid on the particles is incorporated, but not the reverse force exerted by the particles on the fluid. This is because the main focus of our study is to examine the effect of the fluid turbulence on the particle fluctuations, and we are interested in examining whether a Langevin model with random forcing can accurately capture the effect of fluid turbulence on the particle phase. First, the turbulent flow in a plane Couette is analyzed. Though this is a model flow which is not encountered often in applications, it is easier to analyze because the turbulent velocity fluctuations are maximum at the center of the channel, in contrast to the Poiseuille flow, where the velocity fluctuations are maximum at a location between the center and the wall. Also, in a Couette flow, the wall-normal and the spanwise root mean square velocities are nearly a constant in the central region in the channel, and the percentage variation in the stream-wise velocity fluctuations is also less than that in a pressure driven Poiseuille flow. Therefore, it is possible to treat the central region as a region with homogeneous, but anisotropic, fluid velocity fluctuations and with a linear mean velocity variation. The particle mean and root mean square fluctuating velocities, as well as the probability distribution function for the fluid velocity fluctuations and the distribution of acceleration of the particles in the central region of the Couette, which comprises about 20% of the entire channel have been studied. It is found that the distribution of particle velocities is very different from a Gaussian, especially in the span-wise and wall-normal directions. However, the distribution of the acceleration fluctuation on the particles is found to be close to a Gaussian, though the distribution is highly anisotropic and there is a correlation between the fluctuations in the flow and gradient directions. The non-Gaussian nature of the fluid velocity fluctuations is found to be due to inter-particle collisions induced by the large particle velocity fluctuations in the flow direction. Another interesting result is a comparison of the distribution of the acceleration on a particle due to the fluid velocity fluctuation at the particle position, and the distribution of the ratio of fluid velocity fluctuation to the viscous relaxation time in the fluid. The comparison shows that these two distributions are almost identical, indicating that the fluid velocity fluctuations are not correlated over time scales comparable to the relaxation time of a particle. This result is important because it indicates that in order to model the fluctuating force on the particle, it is sufficient to obtain the variance of the force distribution from the variance of the fluid velocity distribution function. Finally, the correlation time for the acceleration correlations is calculated along the trajectory of a particle. The correlation time is found to be of the same magnitude as the correlation time for the fluid velocity in an Eulerian reference frame, and much smaller than the viscous relaxation time and the time between collisions of the particles. All of these results indicate that the effect of the turbulent fluid velocity fluctuations can be accurately represented by an anisotropic Gaussian white noise. The above results are used to formulate a ‘fluctuating force’ model for the particle phase alone, where the force exerted by the fluid turbulent velocity fluctuations is modeled as random Gaussian white noise, which is incorporated into the equation of motion for the particles. The variance of the distribution function for the fluctuating force distribution is obtained from the variance of the local turbulent fluid velocity fluctuations, assuming linear Stokes drag law. The force distribution is anisotropic, and it has a non-zero correlation between the flow and gradient directions. It is found that the results of the fluctuating force simulations are in quantitative agreement with the results of the complete DNS, both for the particle concentration and variances of the particle velocity fluctuations, at relatively low volume fractions where the viscous relaxation time is small compared to the time between collisions, as well as at higher volume fractions where the time between collisions is small compared to the viscous relaxation time. The simulations are also able to predict the velocity distributions in the center of the Couette, even in cases where the velocity distribution is very different from a Gaussian distribution. The fluctuating force model is applied to the turbulent flow of a gas-particle suspension in a vertical channel in the limit of high Stokes number. In contrast to the Couette flow analyzed the fluid velocity variances in the different directions in the channel are highly non-homogeneous, and they exhibit a significant variation across the channel. First, we analyze the fluctuating particle velocity and acceleration distributions at different locations across the channel using direct numerical simulation. The distributions are found to be non-Gaussian near the center of the channel, and they exhibit significant skewness. The time correlations of the fluid velocity fluctuations and the acceleration fluctuations on the particles are evaluated and compared. Unlike the case of Couette flow it is found that the time correlation functions for the fluid in the fixed Eulerian frame are not in agreement with the time correlation of the acceleration on the particles. However, the time correlations of the particle acceleration are in good agreement with the velocity time correlations in the fluid in a ‘moving Eulerian’ reference frame, moving with the mean velocity of the fluid. The fluctuating force simulations are used to model the particle phase, where the force on the particles due to the fluid velocity fluctuations are substituted by random white noise in the equations for the particle motion. The random noise is assumed to be Gaussian and anisotropic. The variances of the fluctuating force are calculated form the fluid velocity fluctuations in a moving Eulerian reference frame using DNS. The results from the fluctuating force simulations are then compared with the results obtained from DNS. Quantitative agreement between the two simulations are obtained provided the particle viscous relaxation time is at least five times larger than the fluid integral time. The interactions between the solid particles and the fluid turbulence have been investigated experimentally in a vertical fully developed channel flow of air and solid particles. Experiments are conducted at low volume fraction for which viscous relaxation time of the particle is expected to be lower than the particle particle collision time, as well as at moderately high volume fraction where the particle particle collision time is expected to be lower than the particle relaxation time. Velocity statistics of both the particle and gas phases are obtained using high spatial resolution Particle Image Velocimetry (PIV) system. It is observed that at low solid volume fraction, the particle root mean square velocities and the velocity distribution are in good agreement with those predicted by the fluctuating force simulation, provided the polydispersity in the particle size distribution is incorporated in the fluctuating force simulations. In this case, the modification of turbulence in the center of the channel due to the particles is small. At much higher volume fraction, the mean gas flow is significantly affected by the presence of particles, and the mean flow is no longer symmetric about the center line of the channel. Simultaneously, there is also a significant change in the volume fraction across the channel, and the volume fraction is also not symmetric about the center line. This seems to indicate that there is a spontaneous instability of the symmetric volume fraction and velocity profiles, giving rise to a region of high fluid velocity and high particle volume fraction coexisting with a region of low gas velocity and low particle volume fraction. There is some recirculation of the gas within the channel, and the gas phase turbulence intensity is significantly enhanced when the velocity and volume fraction profiles become asymmetric. As we have considered only one way coupling in the computation of the particle laden flow it is expected that the particle statistics obtained for this condition can not be predicted by our fluctuating force model due to modification of the gas phase statistics.

Turbulent gas-particle suspensions are of great practical importance in many naturally phenomena, such as dust storms and snow avalanches, as well as in industrial applications such as fluidised, circulating bed reactors and pneumatic transport. Due to the difference in mass density of about three orders of magnitude between solids and gases, the mass loading is large, but the volume fraction of the particles is usually small. Since the length scale of these flows ranges from tens of centimeters to hundreds of meters, the Reynolds number based on the flow dimension and velocity is usually large. Due to this, these flows are almost always in the turbulent regime, and the fluid velocity fluctuations are significant. The particle sizes are typically small in these applications, of the order of 100 m or less. Due to this, the Reynolds number (based on the particle size and velocity) is usually low. This implies that the fluid inertia is not important, and the flow dynamics is dominated by fluid viscosity at the particle scale. At the same time, due to the density contrast between the particles and fluid, the Stokes number (ratio of particle inertia and fluid viscosity) is large. The inertia is sufficiently large that the particles cross the fluid streamlines. In this situation, there is a two-way coupling between the fluid turbulence and the particle dynamics. The turbulent fluid velocity fluctuations result in particle velocity fluctuations due to the drag force exerted by the particles on the fluid. In turbulent gas-particle suspensions, the fluctuating velocity of the particles results in a force on the fluid, which could either enhance or dampen the turbulent velocity fluctuations. The finite size of the particles could also result in fluid velocity effects which can not be captured by considering the particles as point masses. The dynamics of turbulent particle suspensions is analysed in the limit of low particle Reynolds number and high particle Stokes number, where there is a balance between particle inertia and fluid viscosity. The turbulent gas flow in a channel is considered for definiteness, in order to analyse the effect of turbulent fluctuations, as well as the effect of cross-stream variations in the turbulent statistics. The particle size is considered to be comparable to the Kolmogorov scales, which are the smallest scales in the turbulent flow. In addition, the fluid inertia at the particle scale is neglected, and the particles are dynamics is modeled using the Stokes equations. However, inertial effects are included at the macroscopic scale, where the Navier-Stokes equations are solved by Direct Numerical Simulations (DNS) using Chebyshev-Fourier spectral techniques. There are three important objectives in the present analysis. 1. The first is to examine the turbulence modification due to the reverse force of the particles. There are two models used for the reverse force of the particles on the fluid. The first is a point force, which is modeled as a delta function in real space. Instead of using smoothing functions for the delta function, we prefer to incorporate the point force in the momentum conservation equation in spectral space. A more complicated representation proposed here involves the inclusion of the symmetric and anti-symmetric force moments, calculated from the solution of Stokes equations for the flow around the sphere. These are represented as gradients of delta functions, and are also included in the momentum conservation equations in the spectral co-ordinates. 2. The second objective is to examine the effect of particle rotation and collisions on the flow dynamics. While particle rotation is usually included in the analysis of granular flows, this is not normally included in the treatment of particle collisions. 3. The third objective is to examine whether the effect of the fluid turbulence can be modeled as a fluctuating force. When the viscous relaxation time of the particles is larger than the integral time for the fluid velocity fluctuations, the fluid velocity fluctuations can be considered as delta function correlated in time, and the effect of these fluctuations can be incorporated using a Langevin description. In this case, the diffusion coeffcients in the Langevin equation for the particles is calculated from the correlation in the fluid velocity fluctuations. The new objective here is to include both the drag force and the torque exerted on the particles in the presence of particle rotation, and to examine whether these are sufficient to capture the effect of ff fluid turbulence on the particle phase. The Direct Numerical Simulations show that there is a significant attenuation of the turbulent velocity fluctuations when the reverse force exerted by the particles is added in the fluid momentum equations, and the particles are considered to be smooth. This turbulence attenuation is greater when the particle volume fraction increases, and when the particle mass density increases. However, when particle rotation is included, the turbulent velocity fluctuations are significantly larger than those without rotation, and in come cases are close the fluctuation levels when the reverse force is included. Thus, the particle rotation has a significant enhancement on the turbulent velocity fluctuations. The attenuation in the fluid turbulence is also reflected in the magnitude of the particle fluctuating velocities. The particle fluctuating velocities are higher when the effect of particle rotation is included. The reason for this is that there is particle rotation induced due to mean fluid shear, and this rotational energy gets transformed into translational energy in inter-particle collisions. The effect of inclusion of the symmetric and anti-symmetric force moments does not result in a significant change in the turbulence intensities for the range of volume fractions and mass densities considered here. There is a small but discernible increase in the turbulence for the largest volume fraction and mass density considered here, but this increase is much smaller than the significant turbulence attenuation due to the inclusion of particle rotation. Systematic trends are also observed in the particle linear and angular velocity distributions. The particle stream-wise linear velocity distribution, and the span-wise angular velocity distribution are broader than a Gaussian distribution near the zero, and exhibit steep decrease at larger velocity. They are also asymmetric, and the distribution depends on the location across the channel. The distribution of the cross-stream and span-wise linear velocity and the stream-wise and cross-stream angular velocity, is narrower than a Gaussian distribution at the center, and exhibits long tails for high velocities. Thus, there are systematic variations in the distribution functions for both the linear and angular velocities, which need to be included in kinetic theory descriptions for the particle phase. The fluctuating force model has also been simulated, where particle dynamics is explicitly simulated, the fluid velocity fields are not simulated, but are modeled as fluctuating forces and torques acting on the particles. The variance in the fluctuating force and torque are determined from the correlations in the fluid velocity and the vorticity fields, and these are modified to include the turbulence attenuation due to the reverse force exerted by the particles. The fluctuating force simulations do accurately capture the trends observed in the mean and fluctuating velocities. They are also able to capture the non-Gaussian nature of the linear and angular velocity distributions of the particles, even though the random forcing is considered to be a Gaussian function. Thus, the fluctuating force formulation can be used to accurately capture the effect of the fluid on the particles, only if the forces are modified to include the effect of turbulence attenuation due to the reverse force exerted by the particles.

The studies of particles advected by tubulent flows is an active area of research across many streams of sciences and engineering, which include astrophysics, fluid mechanics, statistical physics, nonlinear dynamics, and also chemistry and biology. Advances in experimental techniques and high performance computing have made it possible to investigate the properties these particles advected by fluid flows at very high Reynolds numbers. The main focus of this thesis is to study the statistics of Lagrangian tracers and heavy inertial particles in hydrodynamic and magnetohydrodynamic (MHD) turbulent flows by using direct numerical simulations (DNSs). We also study the statistics of particles in model stochastic flows; and we compare our results for such models with those that we obtain from DNSs of hydrodynamic equations. We uncover some of aspects of the statistical properties of particle trajectories that have not been looked at so far. In the last part of the thesis we present some results that we have obtained by solving the three-dimensional Euler equation by using a new method based on the Cauchy-Lagrange formulation. This thesis is divided into 6 chapters. Chapter 1 contains an introduction to the background material that is required for this thesis; it also contains an outline of the problems we study in subsequent Chapters. Chapter 2 contains our study of “Persistence and first-passage time problems with particles in three-dimensional, homogeneous, and isotropic turbulence”. Chapter 3 is devoted to our study of “Universal Statistical Properties of Inertial-particle Trajectories in Three-dimensional, Homogeneous, Isotropic, Fluid Turbulence”. Chapter 4 deals with “Time irreversibility of Inertial-particle trajectories in Homogeneous, Isotropic, Fluid Turbulence”. Chapter 5 contains our study of the “Statistics of charged inertial particles in three-dimensional magnetohydrodynamic (MHD) turbulence”. Chapter 6 is devoted to our study of “The Cauchy-Lagrange method for the numerical integration of the threedimensional Euler equation”.