This thesis concentrates on accuracy improvements for an existing software package that solves the three dimensional Reynolds Averaged Navier-Stokes equations in rotating coordinates. It is a cell centred explicit time marching code. Two topics are considered: improvement to the discretization scheme, and reduction of the artificial dissipation. The first topic is the analysis of the straight averaging process which demonstrates that the process can result in inconsistency with a skewed grid. An alternative consistent scheme is proposed which is based upon quadratic interpolation. Improved accuracy can also be obtained by modifying the grid or adopting a cell vertex scheme. The stability of the iterative process is also shown to depend on the time step. The reduction of artificial dissipation (second topic) first considers the role of the so called aspectratio and velocity functions. These are found to be limited in influence and a new function is proposed based upon the local flow gradient. Both two and three dimensional turbomachinery cases are tested and improvements demonstrated. In the second part of the analysis, the eigenvalues of the stability matrix are used to reduce the dissipation in overdamped regions. Again this method is applied to various test cases and improvements demonstrated. The management part of this Total Technology PhD Program discusses topics concerned with collaboration and technology development in the aero engine industry with particular emphasis on the role of an 'emerging' partner.

Calculations of fluvial flows are strongly influenced by geometry complexity and large overall uncertainty on every single measurable property, such as velocity and shear. Moreover, a considerable portion of the data obtained from computational simulations arose from two-dimensional, steady-state models. The present work states a different approach to perform computer-based simulations and analyze fluvial flows. For the first part, the suitability of OpenFOAM to be used as the main CFD solver to analyze fluvial flows is studied. Initially, two well documented channel configurations are computationally studied using OpenFOAM. Finally, these results are compared to the output obtained from one of the widely used quasi-3D CFD solvers used to perform studies about environmental hydraulics.

Control of underactuated mechanical systems is of interest as it allows for control authority over all of a system's degrees of freedom without requiring actuation of the full system. In addition to this, open-loop control of a system provides the advantage of applying to systems with unmeasurable states or where sensor integration is not feasible. Vibrational control is an open-loop control strategy that uses high-frequency, high-amplitude forcing to control underactuated mechanical systems. This thesis is concerned with exploring two underactuated mechanical systems that are controlled using vibrational inputs. The first system, a 3 degrees of freedom (DOFs) 2-link mechanism with 1 actuated DOF which is an example of a vibrational control system with 1 input and 2 unactuated DOFs, is used to review analytical results of stability analysis using the averaged potential. Theoretical and numerical results are presented for the achievable stable configurations of the system and the effects of changing the physical parameters on the achievable stable configurations are studied. The primary contribution of this effort is the development of an experimental apparatus where vibrational control is implemented. The second system is a 4DOF system composed of a 2DOF spherical pendulum supported by an actuated 2DOF cart used to study the effects of multiple vibrational inputs acting on a system. Theoretical and numerical analysis results are presented for three variants of harmonic forcing applied to the two actuated degrees of freedom: 1) identical input waveforms, except for the amplitudes, 2) identical input waveforms, except for the amplitudes and a phase shift, and 3) identical input waveforms, but at different frequencies and amplitudes. The equilibrium sets under open-loop vibrational forcing are determined for all three cases. A general closed-loop vibrational control scheme is presented using proportional feedback of the unactuated coordinates superposed with the zero-mean, $T$-periodic vibrational input. / M.S. / Underactuated mechanical systems are systems where the driven degrees of freedom are fewer than the total degrees of freedom of the system. These systems can be controlled using vibrational control which is an open-loop control strategy that uses high-frequency, high-amplitude forcing to control the states of a system. An open-loop control strategy is one in which there are no measurements of the system states required in the control scheme. This allows for control of systems where sensor integration is not feasible. This thesis is concerned with exploring vibrational control of two underactuated mechanical systems. The stability of the equilibrium sets of these systems is assessed using the averaged potential, which is an energy-like quantity used to determine stability of equilibria of systems with high-frequency inputs. Theoretical and numerical results are presented for both systems and the effects of physical parameters and variants of harmonic forcing on the achievable stable configurations of the systems are studied. The two main contributions of the thesis are the development of an experimental apparatus where vibrational control is physically implemented for one system and the outline of the closed-loop vibrational control scheme.

Le but de cette thèse est de faire des simulations prédictives à partir de modèles de turbulence de type RANS (Reynolds-Averaged Navier-Stokes). Ces simulations font l'objet d'un traitement systématique du modèle, de son incertitude et de leur propagation par le biais d'un modèle de calcul prédictif aux incertitudes quantifiées. Pour faire cela, nous utilisons le cadre robuste de la statistique Bayesienne.La première étape vers ce but a été d'obtenir une estimation de l'erreur de simulations RANS basées sur le modèle de turbulence de Launder-Sharma k-e. Nous avons recherché en particulier à estimer des incertitudes pour les coefficients du modele, pour des écoulements de parois en gradients favorable et défavorable. Dans le but d'estimer la propagation des coefficients qui reproduisent le plus précisemment ces types d'écoulements, nous avons étudié 13 configurations différentes de calibrations Bayesienne. Chaque calibration était associée à un gradient de pression spécifique gràce à un modèle statistique. Nous representont la totalite des incertitudes dans la solution avec une boite-probabilite (p-box). Cette boîte-p représente aussi bien les paramètres de variabilité de l'écoulement que les incertitudes epistemiques de chaque calibration. L'estimation d'un nouvel écoulement de couche-limite est faite pour des valeurs d'incertitudes générées par cette information sur l'incertitude elle-même. L'erreur d'incertitude qui en résulte est consistante avec les mesures expérimentales.Cependant, malgré l'accord avec les mesures, l'erreur obtenue était encore trop large. Ceci est dû au fait que la boite-p est une prédiction non pondérée. Pour améliorer cela, nous avons développé une autre approche qui repose également sur la variabilité des coefficients de fermeture du modèle, au travers de multiples scénarios d'écoulements et de multiples modèles de fermeture. La variabilité est là encore estimée par le recours à la calibration Bayesienne et confrontée aux mesures expérimentales de chaque scénario. Cependant, un scénario-modèle Bayesien moyen (BMSA) est ici utilisé pour faire correspondre les distributions a posteriori à un scénario (prédictif) non mesuré. Contrairement aux boîtes-p, cette approche est une approche pondérée faisant appel aux probabilités des modèles de turbulence, déterminée par les données de calibration. Pour tous les scénarios de prédiction considérés, la déviation standard de l'estimation stochastique est consistante avec les mesures effectuées.Les résultats de l'approche BMSA expriment des barres d'erreur raisonnables. Cependant, afin de l'appliquer à des topologies plus complexes et au-delà de la classe des écoulements de couche-limite, des techniques de modeles de substitution doivent être mises en places. La méthode de la collocation Stochastique-Simplex (SSC) est une de ces techniques et est particulièrement robuste pour la propagation de distributions d'entrée incertaines dans un code de calcul. Néanmois, son utilisation de la triangulation Delaunay peut entrainer un problème de coût prohibitif pour les cas à plus de 5 dimensions. Nous avons donc étudié des moyens pour améliorer cette faible scalabilité. En premier lieu, c'est dans ce but que nous avons en premier proposé une technique alternative d'interpolation basée sur le probleme 'Set-Covering'. Deuxièmement, nous avons intégré la méthode SSC au cadre du modèle de réduction à haute dimension (HDMR) dans le but d'éviter de considérer tous les espaces de haute dimension en même temps.Finalement, avec l'utilisation de notre technique de modelisation de substitution (surrogate modelling technique), nous avons appliqué le cadre BMSA à un écoulement transsonique autour d'un profil d'aile. Avec cet outil nous sommes maintenant capable de faire des simulations prédictives d'écoulements auparavant trop coûteux et offrant des incertitudes quantifiées selon les imperfections des différents modèles de turbulence. / The goal of this thesis is to make predictive simulations with Reynolds-Averaged Navier-Stokes (RANS) turbulence models, i.e. simulations with a systematic treatment of model and data uncertainties and their propagation through a computational model to produce predictions of quantities of interest with quantified uncertainty. To do so, we make use of the robust Bayesian statistical framework.The first step toward our goal concerned obtaining estimates for the error in RANS simulations based on the Launder-Sharma k-e turbulence closure model, for a limited class of flows. In particular we searched for estimates grounded in uncertainties in the space of model closure coefficients, for wall-bounded flows at a variety of favourable and adverse pressure gradients. In order to estimate the spread of closure coefficients which reproduces these flows accurately, we performed 13 separate Bayesian calibrations. Each calibration was at a different pressure gradient, using measured boundary-layer velocity profiles, and a statistical model containing a multiplicative model inadequacy term in the solution space. The results are 13 joint posterior distributions over coefficients and hyper-parameters. To summarize this information we compute Highest Posterior-Density (HPD) intervals, and subsequently represent the total solution uncertainty with a probability box (p-box). This p-box represents both parameter variability across flows, and epistemic uncertainty within each calibration. A prediction of a new boundary-layer flow is made with uncertainty bars generated from this uncertainty information, and the resulting error estimate is shown to be consistent with measurement data.However, although consistent with the data, the obtained error estimates were very large. This is due to the fact that a p-box constitutes a unweighted prediction. To improve upon this, we developed another approach still based on variability in model closure coefficients across multiple flow scenarios, but also across multiple closure models. The variability is again estimated using Bayesian calibration against experimental data for each scenario, but now Bayesian Model-Scenario Averaging (BMSA) is used to collate the resulting posteriors in an unmeasured (prediction) scenario. Unlike the p-boxes, this is a weighted approach involving turbulence model probabilities which are determined from the calibration data. The methodology was applied to the class of turbulent boundary-layers subject to various pressure gradients. For all considered prediction scenarios the standard-deviation of the stochastic estimate is consistent with the measurement ground truth.The BMSA approach results in reasonable error bars, which can also be decomposed into separate contributions. However, to apply it to more complex topologies outside the class of boundary-layer flows, surrogate modelling techniques must be applied. The Simplex-Stochastic Collocation (SSC) method is a robust surrogate modelling technique used to propagate uncertain input distributions through a computer code. However, its use of the Delaunay triangulation can become prohibitively expensive for problems with dimensions higher than 5. We therefore investigated means to improve upon this bad scalability. In order to do so, we first proposed an alternative interpolation stencil technique based upon the Set-Covering problem, which resulted in a significant speed up when sampling the full-dimensional stochastic space. Secondly, we integrated the SSC method into the High-Dimensional Model-Reduction framework in order to avoid sampling high-dimensional spaces all together.Finally, with the use of our efficient surrogate modelling technique, we applied the BMSA framework to the transonic flow over an airfoil. With this we are able to make predictive simulations of computationally expensive flow problems with quantified uncertainty due to various imperfections in the turbulence models.

This thesis describes the experimental realisation and characterisation of three non-trivial trapping geometries for ultracold atoms. The double-well, ring and to some degree shell trap are examples of a highly versatile class of traps called time-averaged adiabatic potentials (TAAPs). In this experiment the TAAPs arise from the combination of three independent magnetic fields; a static quadrupole field dressed by a uniform radio-frequency field is time-averaged by a bias field oscillating at in the kHz regime. The result is a very smooth potential, within which ultracold atoms can be evaporatively cooled to quantum degeneracy, and subsequently manipulated into new geometries without destroying the quantum coherence. The vertically offset double-well potential provided the first example of ultracold atoms confined in a TAAP. The same potential is used to demonstrate efficient evaporative cooling across the Bose-Einstein condensate (BEC) phase transition using only the Landau-Zener loss mechanism. Switching off the time-averaging fields loads atoms from the double-well TAAP into the rf-dressed shell trap. A characterisation of this potential measured low heating rates and lifetimes of up to 58s. With efforts ongoing to increase the trap anisotropy, this potential shows promise for research into the static and rapidly rotating 2D systems. In the presence of a single time-averaging field, the shell geometry is transformed into a ring-shaped trap with an adjustable radius. The ring trap can be controllably tilted and progress towards multiply connected condensates is being made. A rotation scheme to spin up atoms in the ring trap has been demonstrated, presenting the opportunity to investigate the dynamics of superflow in degenerate quantum gases.

No description available.

The objective of the study is to investigate the capability of PANS (Partially Averaged Navier-Stokes Simulation) model over a wide range of Reynolds numbers and flow physics. In this regard, numerical simulations of turbulent flow past a circular cylinder are performed at ReD 140,000 and ReD 3900 using the PANS model. The high Reynolds number PANS results are compared with experimental results from Cantwell and Coles, Large Eddy Simulation results from Breuer, and Detached Eddy Simulation results from Travin et al. Low Reynolds number PANS results are compared with experimental results from Ong and Wallace and Large Eddy Simulation results from Breuer. The effects of the various PANS parameters (fk, fε, σku, σεu) on the ability to capture turbulence physics at various Reynolds numbers are studied. It is confirmed, as previously predicted from theoretical considerations that: (i) for high Reynolds number flow fε = 1 and σku = σk × fk2 / fε are most appropriate; and (ii) for low Reynolds number flow fε = fk and σku = σk are most suitable. These choices for the parameters stem from the fact that there is no clear separation of scales between the energy scales and the dissipation scales at low Reynolds number unlike in the high Reynolds number where there is a clear separation of scales between the energy containing scales and the dissipation scales. Also, in both cases it is found that decreasing fk leads to improved accuracy in predicting the flow statistics.

Yes / The flow in the main channel of a meandering compound channel does not occur in the ridge direction because of the effect of the upstream floodplain flows. This study proposes a model for estimating the flow direction in the depth-averaged two-dimensional domain (depth-averaged flow angles) between the entrance and the apex sections. Detailed velocity measurements were performed in the region between the meander entrance section and apex section in a large-scale meandering compound channel. The vertical size of the secondary current cell is highly related to the depth-averaged flow angle; thus, the means of the local flow angles above the secondary current cell and within the cell are separately discussed. The experimental measurements indicate that the mean local flow angle above the cell is equal to the section angle, whereas the mean local flow angle within the cell is equal to zero. The proposed model is validated using published data from five sources. Good agreement is obtained between the predictions and measurements, indicating that the proposed model can accurately estimate the depth-averaged flow direction in the meandering compound channels. Finally, the limitations and application ranges of the model are discussed. / National Key Research and Development Program of China (No. 2016YFC0402302), the National Natural Science Foundation of China (Nos. 51539007 and 51609160)

Wave energy converters are devices that are designed to extract power from ocean waves. Existing wave energy converter technologies are not financially viable yet. Control systems have been identified as one of the areas that can contribute the most towards the increase in energy absorption and reduction of loads acting on the structure, whilst incurring only minimal extra hardware costs. In this thesis, control schemes are developed for wave energy converters, with the focus on single isolated devices. Numerical models of increasing complexity are developed for the simulation of a point absorber, which is a type of wave energy converter with small dimensions with respect to the dominating wave length. After investigating state-of-the-art control schemes, the existing control strategies reported in the literature have been found to rely on the model of the system dynamics to determine the optimal control action. This is despite the fact that modelling errors can negatively affect the performance of the device, particularly in highly energetic waves when non-linear effects become more significant. Furthermore, the controller should be adaptive so that changes in the system dynamics, e.g. due to marine growth or non-critical subsystem failure, are accounted for. Hence, machine learning approaches have been investigated as an alternative, with a focus on neural networks and reinforcement learning for control applications. A time-averaged approach will be employed for the development of the control schemes to enable a practical implementation on WECs based on the standard in the industry at the moment. Neural networks are applied to the active control of a point absorber. They are used mainly for system identification, where the mean power is related to the current sea state and parameters of the power take-off unit. The developed control scheme presents a similar performance to optimal active control for the analysed simulations, which rely on linear hydrodynamics. Reinforcement learning is then applied to the passive and active control of a wave energy converter for the first time. The successful development of different control schemes is described in detail, focusing on the encountered challenges in the selection of states, actions and reward function. The performance of reinforcement learning is assessed against state-of-the-art control strategies. Reinforcement learning is shown to learn the optimal behaviour in a reasonable time frame, whilst recognizing each sea state without reliance on any models of the system dynamics. Additionally, the strategy is able to deal with model non-linearities. Furthermore, it is shown that the control scheme is able to adapt to changes in the device dynamics, as for instance due to marine growth.

Threshold dynamics used to control the spread of the disease in infectious disease phenomena has an overwhelming importance and interest in mathematical epidemiology. One of the famous threshold quantity is known to be the basic reproduction ratio. Its formulation as well as computation is the main concern of infectious diseases. The aim of this thesis is to analyze the basic reproduction ratio in both autonomous and periodic systems via defining R0 as the spectral radius of the next generation operator. This thesis presents the vector host model for the diseases Dengue fever and avian influenza. As emerging of the diseases shows periodicity, systems of periodic ordinary differential equations are considered for both types of diseases. Simple implementation of the time-averaged systems gives rise to the comparison of these with the periodic systems. Thus, we investigate the occurence of the existence of underestimation or overestimation of the basic reproduction ratio in timeaveraged systems.