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.

Investigation of multisensory processing and structural brain differences in Autism Spectrum Disorder

This thesis is an investigation of structural brain abnormalities, as well as multisensory and unisensory processing deficits in autistic traits and Autism Spectrum Disorder (ASD). To achieve this, structural and functional magnetic resonance imaging (fMRI) and psychophysical techniques were employed. ASD is a neurodevelopmental condition which is characterised by the social communication and interaction deficits, as well as repetitive patterns of behaviour, interests and activities. These traits are thought to be present in a typical population. The Autism Spectrum Quotient questionnaire (AQ) was developed to assess the prevalence of autistic traits in the general population. Von dem Hagen et al. (2011) revealed a link between AQ with white matter (WM) and grey matter (GM) volume (using voxel-based-morphometry). However, their findings revealed no difference in GM in areas associated with social cognition. Cortical thickness (CT) measurements are known to be a more direct measure of cortical morphology than GM volume. Therefore, Chapter 2 investigated the relationship between AQ scores and CT in the same sample of participants. This study showed that AQ scores correlated with CT in the left temporo-occipital junction, left posterior cingulate, right precentral gyrus and bilateral precentral sulcus, in a typical population. These areas were previously associated with structural and functional differences in ASD. Thus the findings suggest, to some extent, autistic traits are reflected in brain structure - in the general population. The ability to integrate auditory and visual information is crucial to everyday life, and results are mixed regarding how ASD influences audiovisual integration. To investigate this question, Chapter 3 examined the Temporal Integration Window (TIW), which indicates how precisely sight and sound need to be temporally aligned so that a unitary audiovisual event can be perceived. 26 adult males with ASD and 26 age and IQ-matched typically developed males were presented with flash-beep (BF), point-light drummer, and face-voice (FV) displays with varying degrees of asynchrony and asked to make Synchrony Judgements (SJ) and Temporal Order Judgements (TOJ). Analysis of the data included fitting Gaussian functions as well as using an Independent Channels Model (ICM) to fit the data (Garcia-Perez & Alcala-Quintana, 2012). Gaussian curve fitting for SJs showed that the ASD group had a wider TIW, but for TOJ no group effect was found. The ICM supported these results and model parameters indicated that the wider TIW for SJs in the ASD group was not due to sensory processing at the unisensory level, but rather due to decreased temporal resolution at a decisional level of combining sensory information. Furthermore, when performing TOJ, the ICM revealed a smaller Point of Subjective Simultaneity (PSS; closer to physical synchrony) in the ASD group than in the TD group. Finding that audiovisual temporal processing is different in ASD encouraged us to investigate the neural correlates of multisensory as well as unisensory processing using functional magnetic resonance imaging fMRI. Therefore, Chapter 4 investigated audiovisual, auditory and visual processing in ASD of simple BF displays and complex, social FV displays. During a block design experiment, we measured the BOLD signal when 13 adults with ASD and 13 typically developed (TD) age-sex- and IQ- matched adults were presented with audiovisual, audio and visual information of BF and FV displays. Our analyses revealed that processing of audiovisual as well as unisensory auditory and visual stimulus conditions in both the BF and FV displays was associated with reduced activation in ASD. Audiovisual, auditory and visual conditions of FV stimuli revealed reduced activation in ASD in regions of the frontal cortex, while BF stimuli revealed reduced activation the lingual gyri. The inferior parietal gyrus revealed an interaction between stimulus sensory condition of BF stimuli and group. Conjunction analyses revealed smaller regions of the superior temporal cortex (STC) in ASD to be audiovisual sensitive. Against our predictions, the STC did not reveal any activation differences, per se, between the two groups. However, a superior frontal area was shown to be sensitive to audiovisual face-voice stimuli in the TD group, but not in the ASD group. Overall this study indicated differences in brain activity for audiovisual, auditory and visual processing of social and non-social stimuli in individuals with ASD compared to TD individuals. These results contrast previous behavioural findings, suggesting different audiovisual integration, yet intact auditory and visual processing in ASD. Our behavioural findings revealed audiovisual temporal processing deficits in ASD during SJ tasks, therefore we investigated the neural correlates of SJ in ASD and TD controls. Similar to Chapter 4, we used fMRI in Chapter 5 to investigate audiovisual temporal processing in ASD in the same participants as recruited in Chapter 4. BOLD signals were measured while the ASD and TD participants were asked to make SJ on audiovisual displays of different levels of asynchrony: the participants’ PSS, audio leading visual information (audio first), visual leading audio information (visual first). Whereas no effect of group was found with BF displays, increased putamen activation was observed in ASD participants compared to TD participants when making SJs on FV displays. Investigating SJ on audiovisual displays in the bilateral superior temporal gyrus (STG), an area involved in audiovisual integration (see Chapter 4), we found no group differences or interaction between group and levels of audiovisual asynchrony. The investigation of different levels of asynchrony revealed a complex pattern of results indicating a network of areas more involved in processing PSS than audio first and visual first, as well as areas responding differently to audio first compared to video first. These activation differences between audio first and video first in different brain areas are constant with the view that audio leading and visual leading stimuli are processed differently.