Probabilistic design optimization of horizontal axis wind turbine rotors

Considerable interest in renewable energy has increased in recent years due to the concerns raised over the environmental impact of conventional energy sources and their price volatility. In particular, wind power has enjoyed a dramatic global growth in installed capacity over the past few decades. Nowadays, the advancement of wind turbine industry represents a challenge for several engineering areas, including materials science, computer science, aerodynamics, analytical design and analysis methods, testing and monitoring, and power electronics. In particular, the technological improvement of wind turbines is currently tied to the use of advanced design methodologies, allowing the designers to develop new and more efficient design concepts. Integrating mathematical optimization techniques into the multidisciplinary design of wind turbines constitutes a promising way to enhance the profitability of these devices. In the literature, wind turbine design optimization is typically performed deterministically. Deterministic optimizations do not consider any degree of randomness affecting the inputs of the system under consideration, and result, therefore, in an unique set of outputs. However, given the stochastic nature of the wind and the uncertainties associated, for instance, with wind turbine operating conditions or geometric tolerances, deterministically optimized designs may be inefficient. Therefore, one of the ways to further improve the design of modern wind turbines is to take into account the aforementioned sources of uncertainty in the optimization process, achieving robust configurations with minimal performance sensitivity to factors causing variability. The research work presented in this thesis deals with the development of a novel integrated multidisciplinary design framework for the robust aeroservoelastic design optimization of multi-megawatt horizontal axis wind turbine (HAWT) rotors, accounting for the stochastic variability related to the input variables. The design system is based on a multidisciplinary analysis module integrating several simulations tools needed to characterize the aeroservoelastic behavior of wind turbines, and determine their economical performance by means of the levelized cost of energy (LCOE). The reported design framework is portable and modular in that any of its analysis modules can be replaced with counterparts of user-selected fidelity. The presented technology is applied to the design of a 5-MW HAWT rotor to be used at sites of wind power density class from 3 to 7, where the mean wind speed at 50 m above the ground ranges from 6.4 to 11.9 m/s. Assuming the mean wind speed to vary stochastically in such range, the rotor design is optimized by minimizing the mean and standard deviation of the LCOE. Airfoil shapes, spanwise distributions of blade chord and twist, internal structural layup and rotor speed are optimized concurrently, subject to an extensive set of structural and aeroelastic constraints. The effectiveness of the multidisciplinary and robust design framework is demonstrated by showing that the probabilistically designed turbine achieves more favorable probabilistic performance than those of the initial baseline turbine and a turbine designed deterministically.

Towards in silico IBV vaccine design: defining the role of polymorphism in viral attenuation

The gammacoronavirus, Infectious Bronchitis Virus (IBV), is a respiratory pathogen of chickens. IBV is a constant threat to poultry production as established vaccines are often ineffective against emerging strains. This requires constant and rapid vaccine production by a process of viral attenuation by egg passage, but the essential forces leading to attenuation in the virus have not yet been characterised. Knowledge of these factors will lead to the development of more effective, rationally attenuated, live vaccines and reduction of the mortality and morbidity caused by this pathogen. M41 CK strain was egg passaged four times many years ago at Houghton Poultry Research Station and stored as M41-CK EP4 (stock virus at The Pirbright Institute since 1992). It was the first egg passage to have its genome pyrosequenced and was therefore used as the baseline reference. The overall aim of this project was to analyse deep sequence data obtained from four IBV isolates (called A, A1, C and D) each originating from the common M41-CK EP4 (ep4) and independently passaged multiple times in embryonated chicken eggs (figure 1.1). Highly polymorphic encoding regions of the IBV genome were then identified which are likely involved in the attenuation process through the formation of independent SNPs and/or SNP clusters. This was then used to direct targeted investigation of SNPs during the attenuation process of the four IBV passages. A previously generated deep sequence dataset was used as a preliminary map of attenuation for one virulent strain of IBV. This investigation showed the nucleocapsid and spike as two highly polymorphic encoding regions within the IBV genome with the highest proportion of SNPs compared to encoding region size. This analysis then led to more focussed studies of the nucleocapsid and spike encoding region with the ultimate aim of mapping key attenuating regions and nucleotide positions. The 454 pyrosequencing data and further investigation of nucleocapsid and spike encoding regions have identified the SNPs present at the same nucleotide positions within analysed A, A1, C and D isolates. These SNPs probably play a crucial role in viral attenuation and universal vaccine production but it is not clear if independent SNPs are also involved in loss of virulence. The majority of SNPs accumulated at different nucleotide positions without further continuation in Sanger sequenced egg passages presenting S2 subunit (spike) and nucleocapsid as polymorphic encoding regions which in nature remain highly conserved.