Wavelengths in bioconvection patterns

Unicellular bottom-heavy swimming microorganisms are usually denser than the fluid in which they swim. In shallow suspensions, the bottom heaviness results in a gravitational torque that orients the cells to swim vertically upwards in the absence of fluid flow. Swimming cells thus accumulate at the upper surface to form a concentrated layer of cells. When the cell concentration is high enough, the layer overturns to form bioconvection patterns. Thin concentrated plumes of cells descend rapidly and cells return to the upper surface in wide, slowly moving upwelling plumes. When there is fluid flow, a second viscous torque is exerted on the swimming cells. The balance between the local shear flow viscous and the gravitational torques determines the cells' swimming direction, (gyrotaxis). In this thesis, the wavelengths of bioconvection patterns are studied experimentally as well as theoretically as follow; First, in aquasystem it is rare to find one species lives individually and when they swim they can form complex patterns. Thus, a protocol for controlled experiments to mix two species of swimming algal cells of \emph{C. rienhardtii} and \emph{C. augustae} is systematically described and images of bioconvection patterns are captured. A method for analysing images using wavelets and extracting the local dominant wavelength in spatially varying patterns is developed. The variation of the patterns as a function of the total concentration and the relative concentration between two species is analysed. Second, the linear stability theory of bioconvection for a suspension of two mixed species is studied. The dispersion relationship is computed using Fourier modes in order to calculate the neutral curves as a function of wavenumbers $k$ and $m$. The neutral curves are plotted to compare the instability onset of the suspension of the two mixed species with the instability onset of each species individually. This study could help us to understand which species contributes the most in the process of pattern formation. Finally, predicting the most unstable wavelength was studied previously around a steady state equilibrium situation. Since assuming steady state equilibrium contradicts with reality, the pattern formation in a layer of finite depth of an evolving basic state is studied using the nonnormal modes approach. The nonnormal modes procedure identifies the optimal initial perturbation that can be obtained for a given time $t$ as well as a given set of parameters and wavenumber $k$. Then, we measure the size of the optimal perturbation as it grows with time considering a range of wavenumbers for the same set of parameters to be able to extract the most unstable wavelength.

Heat transfer performance investigation of nanofluids flow in pipe

Different types of base fluids, such as water, engine oil, kerosene, ethanol, methanol, ethylene glycol etc. are usually used to increase the heat transfer performance in many engineering applications. But these conventional heat transfer fluids have often several limitations. One of those major limitations is that the thermal conductivity of each of these base fluids is very low and this results a lower heat transfer rate in thermal engineering systems. Such limitation also affects the performance of different equipments used in different heat transfer process industries. To overcome such an important drawback, researchers over the years have considered a new generation heat transfer fluid, simply known as nanofluid with higher thermal conductivity. This new generation heat transfer fluid is a mixture of nanometre-size particles and different base fluids. Different researchers suggest that adding spherical or cylindrical shape of uniform/non-uniform nanoparticles into a base fluid can remarkably increase the thermal conductivity of nanofluid. Such augmentation of thermal conductivity could play a more significant role in enhancing the heat transfer rate than that of the base fluid. Nanoparticles diameters used in nanofluid are usually considered to be less than or equal to 100 nm and the nanoparticles concentration usually varies from 5% to 10%. Different researchers mentioned that the smaller nanoparticles concentration with size diameter of 100 nm could enhance the heat transfer rate more significantly compared to that of base fluids. But it is not obvious what effect it will have on the heat transfer performance when nanofluids contain small size nanoparticles of less than 100 nm with different concentrations. Besides, the effect of static and moving nanoparticles on the heat transfer of nanofluid is not known too. The idea of moving nanoparticles brings the effect of Brownian motion of nanoparticles on the heat transfer. The aim of this work is, therefore, to investigate the heat transfer performance of nanofluid using a combination of smaller size of nanoparticles with different concentrations considering the Brownian motion of nanoparticles. A horizontal pipe has been considered as a physical system within which the above mentioned nanofluid performances are investigated under transition to turbulent flow conditions. Three different types of numerical models, such as single phase model, Eulerian-Eulerian multi-phase mixture model and Eulerian-Lagrangian discrete phase model have been used while investigating the performance of nanofluids. The most commonly used model is single phase model which is based on the assumption that nanofluids behave like a conventional fluid. The other two models are used when the interaction between solid and fluid particles is considered. However, two different phases, such as fluid and solid phases is also considered in the Eulerian-Eulerian multi-phase mixture model. Thus, these phases create a fluid-solid mixture. But, two phases in the Eulerian-Lagrangian discrete phase model are independent. One of them is a solid phase and the other one is a fluid phase. In addition, RANS (Reynolds Average Navier Stokes) based Standard κ-ω and SST κ-ω transitional models have been used for the simulation of transitional flow. While the RANS based Standard κ-ϵ, Realizable κ-ϵ and RNG κ-ϵ turbulent models are used for the simulation of turbulent flow. Hydrodynamic as well as temperature behaviour of transition to turbulent flows of nanofluids through the horizontal pipe is studied under a uniform heat flux boundary condition applied to the wall with temperature dependent thermo-physical properties for both water and nanofluids. Numerical results characterising the performances of velocity and temperature fields are presented in terms of velocity and temperature contours, turbulent kinetic energy contours, surface temperature, local and average Nusselt numbers, Darcy friction factor, thermal performance factor and total entropy generation. New correlations are also proposed for the calculation of average Nusselt number for both the single and multi-phase models. Result reveals that the combination of small size of nanoparticles and higher nanoparticles concentrations with the Brownian motion of nanoparticles shows higher heat transfer enhancement and thermal performance factor than those of water. Literature suggests that the use of nanofluids flow in an inclined pipe at transition to turbulent regimes has been ignored despite its significance in real-life applications. Therefore, a particular investigation has been carried out in this thesis with a view to understand the heat transfer behaviour and performance of an inclined pipe under transition flow condition. It is found that the heat transfer rate decreases with the increase of a pipe inclination angle. Also, a higher heat transfer rate is found for a horizontal pipe under forced convection than that of an inclined pipe under mixed convection.