Theses (Mechanical Engineering)
http://hdl.handle.net/1828/89
2021-04-20T06:44:31ZInfluence of the sweep angle on the leading edge vortex and its relation to the power extraction performance of a fully-passive oscillating-plate hydrokinetic turbine prototype
http://hdl.handle.net/1828/12749
Influence of the sweep angle on the leading edge vortex and its relation to the power extraction performance of a fully-passive oscillating-plate hydrokinetic turbine prototype
Lee, Waltfred
Oscillating-foil hydrokinetic turbines have gained interest over the years to extract energy from renewable sources. The influence of the sweep angle on the performance of a fully-passive oscillating-plate hydrokinetic turbine prototype was investigated experimentally in the present work. The sweep angle was introduced to promote spanwise flow along the plate in order to manipulate the leading edge vortex (LEV) and hydrodynamically optimize the performance of the turbine.
In the present work, flat plates of two configurations were considered: a plate with a 6° sweep angle and an unswept plate (control), which were undergoing fully-passive pitch and heave motions in uniform inflow at the Reynolds numbers ranging from 15 000 to 30 000. The resulting kinematic parameters and the energy extraction performance were evaluated for both plates.
Planar (2D) particle image velocimetry (PIV) was used to obtain patterns of the phase-averaged out-of-plane vorticity during the oscillation cycle. The circulation in the wake was then related to the induced-forces on the plate by calculating the moments of vorticity of the LEV with respect to the pitching axis of the plate.
Tomographic (3D) PIV was implemented in evaluating the influence of the spanwise flow on the dynamics of the vortex structure in three-dimensional space. The rate of deformation of the vortex length was quantified by calculating the deformation terms embedded in the vorticity equations, then linked to the stability of the vortex.
The results show evidence of delay of the shedding of LEV and increased vortex stability, in the case of the swept plate. The manipulation of the LEV by the spanwise flow was related to the induced kinematics exhibited by the prolonged heave forces experienced by the swept plate, which led to the higher power extraction performance at high inflow velocities. In the presence of spanwise flow, positive vortex stretching along the vortex line increased the stabilization of the vortex core and prevented the onset of helical vortex breakdown, observed in the case of the unswept plate. The use of the sweep profile on the plate has led to the improvement of energy extraction performance of the fully-passive hydrokinetic turbine.
2021-03-01T00:00:00ZAperiodically sampled stochastic model predictive control: analysis and synthesis
http://hdl.handle.net/1828/12671
Aperiodically sampled stochastic model predictive control: analysis and synthesis
Chen, Jicheng
Stochastic model predictive control (MPC) is a fascinating field for research and of increasing practical importance since optimal control techniques have been intensively investigated in modern control system design.
With the development of computer technologies and communication networks, networked control systems (NCSs) or cyber-physical systems (CPSs) have become an interest of research due to the comprehensive integration of physical systems, such as sensors, actuators and plants, with intricate cyber components, possessing information communication and computation.
In CPSs, advantages of low installation cost, high reliability, flexible modularity, improved efficiency, and greater autonomy can be obtained by the tight coordination of physical and cyber components.
Several sectors, including robotics, transportation, health care, smart buildings, and smart grid, have witnessed the successful application of CPSs design.
The integration of extensive cyber capability and physical plants with ubiquitous uncertainties also introduces concerns over communication efficiency, robustness and stability of the CPSs.
Thus, to achieve satisfactory performance metrics of efficiency, robustness and stability, a detailed investigation into control synthesis of CPSs under the stochastic model predictive control framework is of importance.
The stochastic model predictive control synthesis plays a vital role in CPSs design since the multivariable stochastic system subject to probabilistic constraints can be controlled in an optimized way.
On the other hand, aperiodically sampled, or event-based, model predictive control has also been applied to CPSs extensively to improve communication efficiency.
In this thesis, the control synthesis and analysis of aperiodically sampled stochastic model predictive control for CPSs is considered.
Chapter 1 provides an introductory literature review of the current development of stochastic MPC, distributed stochastic MPC and event-based MPC.
Chapter 2 presents a stochastic self-triggered model predictive control scheme for linear systems with additive uncertainty and with the states and inputs being subject to chance constraints. In the proposed control scheme, the succeeding sampling time instant and current control inputs are computed online by solving a formulated optimization problem.
Chapter 3 discusses a stochastic self-triggered model predictive control algorithm with an adaptive prediction horizon. The communication cost is explicitly considered by adding a damping factor in the cost function. Sufficient conditions are provided to guarantee closed-loop chance constraints satisfactions. Furthermore, the recursive feasibility of the algorithm is analyzed, and the closed-loop system is shown to be stable.
Chapter 4 proposes a distributed self-triggered stochastic MPC control scheme for CPSs under coupled chance constraints and additive disturbances.
Based on the assumptions on stochastic disturbances, both local and coupled probabilistic constraints are transformed into the deterministic form using the tube-based method, and improved terminal constraints are constructed to guarantee the recursive feasibility of the control scheme. Theoretical analysis has shown that the overall closed-loop CPSs are quadratically stable. Numerical examples illustrate the efficacy of the proposed control method in terms of data transmission reductions.
Chapter 5 concludes the thesis and suggests some promising directions for future research.
2021-02-11T00:00:00ZOptimal performance of airborne wind energy systems subject to realistic wind profiles
http://hdl.handle.net/1828/12559
Optimal performance of airborne wind energy systems subject to realistic wind profiles
Sommerfeld, Markus
The objective of this thesis is to assess the optimal power production and flight trajectories of crosswind, ground-generation or pumping-mode airborne wind energy systems (AWES), subject to realistic onshore and offshore, mesoscale-modeled wind data as well as LiDAR wind resource assessment.
The investigation ranges from small scale AWES with an aircraft wing area of 10 m^2 to utility scale systems of 150 m^2.
In depth knowledge of the wind resource is the basis for the development and deployment of any wind energy generator.
Design and investment choices are made based on this information, which determine instantaneous power, annual energy production and cost of electricity.
In the case of AWES, many preliminary and current analyses of AWES rely on oversimplified analytical or coarsely resolved wind models, which can not represent the complex wind regime within the lower-troposphere.
Furthermore, commonly used, simplified steady state models do not accurately predict AWES power production, which is intrinsically linked to the aircraft's flight dynamics, as the AWES never reaches a steady state over the course of a power cycle.
Therefore, leading to false assumption and unrealistic predictions.
In this work, we try to expand our knowledge of the wind resource at altitudes beyond the commonly investigated lowest hundreds of meters.
The so derived horizontal wind velocity profiles are then implemented in to an optimal control framework to compute power-optimal, dynamically feasible flight trajectories that satisfy operation constraints and structural system limitations.
The so derived trajectories describe an ideal, or at least a local optimum, and not necessarily realistic solution.
It is unlikely that such power generation can be reached in practice, given that disturbances, model assumptions, misalignment with the wind direction, control limitations and estimation errors, will reduce actual performance.
We first analyze wind light detection and ranging (LiDAR) measurements at a potential onshore AWES deployment site in northern Germany.
To complement these measurements we generate and analyze onshore and offshore, mesoscale weather research and forecasting (WRF) simulations.
Using observation nudging, we assimilate onshore LiDAR measurements into the WRF model, to improve wind resource assessment.
We implement representative onshore and offshore wind velocity profiles into the awebox optimization framework, a Python toolbox for modelling and optimal control of AWES, to derive power-optimal trajectories and estimate AWES power curves.
Based on a simplified scaling law, we explore the design space and set mass targets for small to utility-scale, ground-generation, crosswind AWESs.
2021-01-13T00:00:00ZPredicting cavitation-induced noise from marine propellers
http://hdl.handle.net/1828/12552
Predicting cavitation-induced noise from marine propellers
McIntyre, Duncan
Noise pollution threatens marine ecosystems, where animals rely heavily on sound for navigation and communication. The largest source of underwater noise from human activity is shipping, and propeller-induced cavitation is the dominant source of noise from ships. Mitigation strategies require accurate methods for predicting cavitation-induced noise, which remains challenging. The present thesis explores prediction and modelling strategies for cavitation-induced noise from marine propellers, and provides insight into models that can be used both during propeller design and to generate intelligent vessel control strategies. I examined three distinct approaches to predicting cavitation-induced noise, each of which is discussed in one of the three main chapters of this thesis: a high-fidelity computational fluid dynamics scheme, a parametric mapping procedure, and the use of field measurements. Each of these three chapters presents different insight into the acoustic behaviour of cavitating marine propellers, as well both real and potential strategies for mitigating this critical environmental emission.
A combined experimental and numerical study of noise from a cavitating propeller, focused on both the fundamental importance of experimental findings and the effectiveness of the numerical modelling strategy used, is detailed in the first main chapter of this thesis. The experimental results highlighted that loud cavitation noise is not necessarily associated with high-power or high-speed propeller operation, affirming the need for intelligent vessel operation strategies to mitigate underwater noise pollution. Comparison of the experimental measurements and simulations revealed that the simulation strategy resulted in an over-prediction of sound levels from cavitation. Analysis of the numerical results and experiments strongly suggested that the cavitation model implemented in the simulations, a model commonly used for marine propeller simulations, was responsible for the over-prediction of sound levels.
Ships are powered primarily by combustion engines, for which it is possible to generate "maps" relating the emission of pollutants to the engine’s speed and torque; the second main chapter of this thesis presents the methodology I developed for generating similar "maps" relating the level of cavitation-induced noise to the speed and torque of a ship's propeller. A proof-of-concept of the method that used the model propeller from the first main chapter is presented. To generate the maps, I used a low-order simulation technique to predict the cavitation induced by the propeller at a range of different speed and torque combinations. A pair of semi-empirical models found in the literature were combined to provide the framework for predicting noise based on cavitation patterns. The proof-of-concept map shows a clear optimal operating regime for the propeller.
The final main chapter of this thesis presents an analysis of field noise measurements of coastal ferries in commercial operation, the data for which were provided by an industrial partner. The key finding was the identification of cavitation regime changes with variation in vessel speed by their acoustic signatures. The results provide a basis for remotely determining which vessels produce less noise pollution when subject to speed limits, which have been implement in critical marine habitats, and which vessels produce less noise at a specific optimum speed.
2021-01-12T00:00:00Z