No description available.

No description available.

No description available.

No description available.

Seakeeping analysis involving violent flows is still quite challenging because the conventional Reynolds Averaged Navier-Stokes (RANS) approaches are not effective for such flow simulations. Different techniques and numerical tools are required to obtain approximate solutions. This research aims to apply Smoothed Particle Hydrodynamics (SPH), a fully Lagrangian meshless method to investigate the behaviour of ships in realistic waves. SPH has been used in a wide variety of hydrodynamic problems overcoming the limitation of finite volume or element type methods. This makes it a suitable alternative for simulating a range of hydrodynamic problems, especially those involving severe flow discontinuities, such as deformable boundary, wave breaking and fluid fragmentation, around complex hull shapes. The main goal of this research is to investigate the possibility of implementing SPH in 3-dimensional problems for the seakeeping analysis of ships treated as rigid and flexible bodies operating in reasonably rough seas. The outcomes of the research will focus on predicting wave-induced motions, distortions and loads with particular references to response in waves of reasonably large amplitude. The initial work deals with modifying standard Incompressible SPH (ISPH) formulation in generating free surface waves. It was observed that the kernel summation of standard ISPH formulation is not sufficiently accurate in obtaining the velocity and pressure fields. Therefore, a range of solutions were proposed to improve the prediction and the following were considered: i) employing collision control, ii) shifting technique to maintain uniform particle distribution, iii) improving the accuracy of gradient estimations up to 2nd order with kernel renormalization technique, iv) applying an artificial free surface viscosity and v) adapting new arc method for accurate free surface recognition. In addition, the weakly compressible SPH (WCSPH) from DualSPHysics was also applied to similar problems. It was found that WCSPH performed better in accuracy and was then adopted further in the analysis of hydrodynamic and hydroelasticity. The research studies were extended to investigate 2-D problems of radiation, diffraction and wave-induced motion. Comparisons were made with available potential flow solutions, numerical results and experimental data. Overall, a satisfactory agreement has been achieved in determining i) added mass and damping coefficients and ii) responses of fixed and floating body in waves. Convergence studies were carried out for particle density influences, as well as sensitivity and stability of implemented parameters. In the extension of the model to 3-D framework, both cases of floating rigid and flexible barges in regular waves were modelled. For this particular case, vertical bending moment (VBM) was obtained using the one-way coupling approach. Comparisons to two other numerical methods and experimental data in the prediction of RAOs, motion responses and vertical bending moments have shown consistent performance of WCSPH. Finally, the success of WCSPH was highlighted by solving the hydrodynamic coefficients for a 3-D flexible structure oscillating in rigid body motions of heave and pitch, as well as 2-node and 3-node of distortion modes.

To date no generally accepted prediction method is available for a low pressure turbine designer. Detailed information about the flow field that can be used to improve turbulence models is difficult to obtain from experiments. Direct numerical simulations (DNS), capable of delivering that information, have been published and showed the ability of this method to accurately predict the flow field. However, in these previous studies detailed turbulence information was not published and to date detailed information about turbulence in LPT flows is missing. In this work compressible DNS were conducted and turbulence was investigated in detail. First a method was developed that enables large scale numerical simulations of low pressure turbines on state of the art high performance computers. Particular emphasis was put on boundary conditions with respect to reflections and an efficient way of generating inlet turbulence. To allow for efficient computation the computational performance was examined and optimized and showed good scaling up to large numbers of cores and GPUs, allowing the exploitation of large parallel computing systems. A grid convergence study is presented showing that while large scales are grid converged at similar resolutions to previously published work, convergence of quantities related to ne scales required a substantially higher resolution than published work. Budgets of the transport equations of Favre averaged momentum, total energy and TKE are presented in the vortex shedding region, the developed wake and the blade boundary layer. These are useful for turbulence modellers to understand the accuracy of a particular turbulence model. Energy transport mechanisms were discussed to provide an understanding of the important mechanisms and their variation with Reynolds number. Finally a local assessment of linear eddy-viscosity models was presented where a turbulence model based on an optimized turbulence viscosity was compared to the standard k- model. It was found that in the vortex shedding region there was scope for improvement of the k- model. However, the remaining modelling error of the optimized model was large highlighting the limitation of linear eddy viscosity models. Further, regions with large errors in the turbulence model were identified close to leading and trailing edge.

The study of turbulence in superfluid Helium II suggests that at least in part the rules of classical turbulence are obeyed. The question posed is, whether the tangles of quantised vorticity that represent turbulence in a superfluid are directly analogous to the swirls and eddies found in turbulent classical fluids. A cornerstone of classical turbulence has been the evidence of the Kolmogorov scaling and this has been observed in some experimental studies of superfluid turbulence. Here we contrast quantum turbulence in various scenarios to further our understanding and confidence in such modelling as well as to search for evidence of any adherence to Kolmogorov. In all numerical simulations presented here turbulence in the superfluid is driven by motions of the normal fluid. My work approaches the superfluid turbulence through three distinct normal fluid models. In most physical experiments with superfluid helium, turbulence is generated in two ways. Firstly, thermally (by applying a heat flux, as in thermal counterflow) and we model this by using a uniform normal fluid. Secondly, mechanically (by stirring the liquid) and we model this in one of two ways; either a synthetic turbulence using a kinematic simulations (KS) flow or with a frozen snapshot from a direct numerical simulation (DNS). We determine the difference between thermally and mechanically driven quantum turbulence. Using the kinematic simulations model we find that in the latter the energy is concentrated at the large scales, the spectrum obeys Kolmogorov scaling, vortex lines have small curvature, and the presence of coherent vortex structures induces vortex reconnections at small angles. In contrast, when we employ our uniform normal fluid we find the energy is concentrated at the mesoscales, the curvature is larger, the vorticity field is featureless and reconnections occur at larger angles. Our results suggest a method to experimentally detect the presence of superfluid vortex bundles. We show that vortex tangles with the same vortex line density have different energy spectra, depending on the driving normal fluid, and identify the spectral signature of two forms of superfluid turbulence: Kolmogorov tangles and Vinen tangles. By decomposing the superfluid velocity field into local and nonlocal contributions, we find that in Vinen tangles the motion of vortex lines depends mainly on the local curvature, whereas in Kolmogorov tangles the long-range vortex interaction is dominant and leads to the formation of clustering of lines, in analogy to the ‘worms’ of classical turbulence. Finally, we compute the frequency spectrum of superfluid vortex density fluctuations for tangles of the same vortex line density, but which are driven by two different normal fluid models. Taking our measurements in a sufficiently small cube to eliminate any filtering effect, we observe the f−5/3 that has been experimentally observed within the Kolmogorov tangles whereas for the Vinen tangles we find a flat and featureless spectrum.

We formulate a fluid-dynamical model describing the behaviour of solutions consisting of a fluid solvent and a dissolved solute, and whose surface tension depends on the concentration of the solute. By considering the surface excess of the dissolved solute, this model can describe the Marangoni-driven flow both of fluids in which there is a surfactant present (which decreases surface tension) and of fluids in which there is an anti-surfactant present (which increases surface tension). By investigating the linear stability of an initially quiescent fluid layer, we predict a novel instability that is possible for anti-surfactant solutions, but not for surfactant solutions, and analyse the conditions for the onset of this instability. We formulate the equations governing the flow of a thin film of surfactant or anti-surfactant solution, and demonstrate the wide range of dynamical behaviour that may be displayed by such solutions. In particular, we perform fully non-linear,unsteady numerical computations, and compare the results obtained with the linear approximation for an initially quiescent thin film subject to both small and large perturbations. We analyse the difference in behaviour between surfactants and anti-surfactants when the thin film is subject to large, local disturbances to either the surface concentration or the bulk concentration. We also obtain analytical solutions to reduced versions of the equations governing the flow of a thin film when the Marangoni effect is dominant. We focus on so-called â€perfectly soluble”anti-surfactants for which the surface concentration is identically zero. For problems in which the initial condition is discontinuous, the method of characteristicsis employed to obtain simple-wave solutions. Finally, we derive a general,doubly-infinite family of similarity solutions of the reduced (i.e., Marangoni-only)equations, and investigate two of the most interesting cases in detail.

No description available.

The oil and gas industry’s goal of developing high performing multiphase flow metering systems capable of reducing costs in the exploitation of marginal oil and gas reserves, especially in remote environments, cannot be over emphasised. Development of a cost-effective multiphase flow meter to determine the individual phase flow rates of oil, water and gas was experimentally investigated by means of low cost, simple and non-intrusive commercially available sensors. Features from absolute pressure, differential pressure (axial), gamma densitometer, conductivity and capacitance meters, in combination with pattern recognition techniques were used to detect shifts in flow conditions, such as flow structure, pressure and salinity changes and measured multiphase flow parameters simultaneously without the need for preconditioning or prior knowledge of either phase. The experiments were carried out at the National Engineering Laboratory (NEL) Multiphase facility. Data was sampled at 250 Hz across a wide spectrum of flow conditions. Fluids used were nitrogen gas, oil (Forties and Beryl crude oil – D80, 33o API gravity) and water (salinity levels of 50 and 100 g/l MgSO4). The sensor spool piece was horizontally mounted on a 4-inch (102mm) pipe, and the database was obtained from two different locations on the flow loop. The ability to learn from ‘experience’ is a feature of neural networks. The use of neural networks allows re-calibration of the measuring system on line through a retraining process when new information becomes available. Some benefits and capabilities of intelligent multiphase flow systems include:  Reduction in the physical size of installations.  Sensor fusion by merging the operating envelopes of different sensors employed provided even better results.  Monitoring of flow conditions, not just flow rate but also composition of components.  Using conventional sensors within the system will present the industry with a much lower cost multiphase meter, and better reliability. Comment [HS1]: I think this word should be measured to make the sentence read correctly.