The aim of this project was to explore the shapes of dark matter halos using high resolution N-body simulations. One of the main aspects explored was how well the shape can be measured through weak lensing. To explore this, simulations were run using the GADGET-2 code \cite{SPRING05} and a method used to measure ellipticities was tested \cite{oguri1}. It was found that Large Scale Structure along the line of sight diluted the measurements and made halos appear more spherical. On the other hand, substructure close to the halo introduced a bias where intrinsically elliptical halos appeared to be slightly more spherical and intrinsically spherical halos appeared to be slightly more elliptical. The effects of projection on concentration were also explored, it was concluded that halos which are most elliptical in 3D tend to appear the most concentrated in projection. Finally, we tested the possibility of using shape or concentration measurements to help break the degeneracy in $\Omega_M$ and $\sigma_8$. We found that this may be possible with $\sim$ 3000-4000 shape measurements or $\sim$ 400-500 concentration measurements.

The total worldwide base of installed wind energy peak capacity reached 94 GW by the end of 2007, including 1846 MW in Canada. Wind turbine systems are being installed throughout Canada and often in mountains and cold weather regions, due to their high wind energy potential. Harsh cold weather climates, involving turbulence, gusts, icing and lightning strikes in these regions, affect wind turbine performance. Ice accretion and irregular shedding during turbine operation lead to load imbalances, often causing the turbine to shut off. They create excessive turbine vibration and may change the natural frequency of blades as well as promote higher fatigue loads and increase the bending moment of blades. Icing also affects the tower structure by increasing stresses, due to increased loads from ice accretion. This can lead to structural failures, especially when coupled to strong wind loads. Icing also affects the reliability of anemometers, thereby leading to inaccurate wind speed measurements and resulting in resource estimation errors. Icing issues can directly impact personnel safety, due to falling and projected ice. It is therefore important to expand research on wind turbines operating in cold climate areas. This study presents an experimental investigation including three important fundamental aspects: 1) heat transfer characteristics of the airfoil with and without liquid water content (LWC) at varying angles of attack; 2) energy losses of wind energy while a wind turbine is operating under icing conditions; and 3) aerodynamic characteristics of an airfoil during a simulated icing event. A turbine scale model with curved 3-D blades and a DC generator is tested in a large refrigerated wind tunnel, where ice formation is simulated by spraying water droplets. A NACA 63421 airfoil is used to study the characteristics of aerodynamics and convective heat transfer. The current, voltage, rotation of the DC generator and temperature distribution along the airfoil, which are used to calculate heat transfer coefficients, are measured using a Data Acquisition (DAQ) system and recorded with LabVIEW software. The drag, lift and moment of the airfoil are measured by a force balance system to obtain the aerodynamics of an iced airfoil. This research also quantifies the power loss under various icing conditions. The data obtained can be used to valid numerical data method to predict heat transfer characteristics while wind turbine blades worked in cold climate regions.

The total worldwide base of installed wind energy peak capacity reached 94 GW by the end of 2007, including 1846 MW in Canada. Wind turbine systems are being installed throughout Canada and often in mountains and cold weather regions, due to their high wind energy potential. Harsh cold weather climates, involving turbulence, gusts, icing and lightning strikes in these regions, affect wind turbine performance. Ice accretion and irregular shedding during turbine operation lead to load imbalances, often causing the turbine to shut off. They create excessive turbine vibration and may change the natural frequency of blades as well as promote higher fatigue loads and increase the bending moment of blades. Icing also affects the tower structure by increasing stresses, due to increased loads from ice accretion. This can lead to structural failures, especially when coupled to strong wind loads. Icing also affects the reliability of anemometers, thereby leading to inaccurate wind speed measurements and resulting in resource estimation errors. Icing issues can directly impact personnel safety, due to falling and projected ice. It is therefore important to expand research on wind turbines operating in cold climate areas. This study presents an experimental investigation including three important fundamental aspects: 1) heat transfer characteristics of the airfoil with and without liquid water content (LWC) at varying angles of attack; 2) energy losses of wind energy while a wind turbine is operating under icing conditions; and 3) aerodynamic characteristics of an airfoil during a simulated icing event. A turbine scale model with curved 3-D blades and a DC generator is tested in a large refrigerated wind tunnel, where ice formation is simulated by spraying water droplets. A NACA 63421 airfoil is used to study the characteristics of aerodynamics and convective heat transfer. The current, voltage, rotation of the DC generator and temperature distribution along the airfoil, which are used to calculate heat transfer coefficients, are measured using a Data Acquisition (DAQ) system and recorded with LabVIEW software. The drag, lift and moment of the airfoil are measured by a force balance system to obtain the aerodynamics of an iced airfoil. This research also quantifies the power loss under various icing conditions. The data obtained can be used to valid numerical data method to predict heat transfer characteristics while wind turbine blades worked in cold climate regions.

Proteins are the basic building blocks of biological organisms, and are responsible for a variety of functions within them. Proteins are composed of unique amino acid sequences. Some has only one sequence, while others contain several sequences that are combined together. These combined amino acid sequences fold to form a unique three-dimensional (3D) shape. Although the sequences may fold proteins into different 3D shapes in diverse environments, proteins with similar amino acid sequences typically have similar 3D shapes and functions. Knowledge of the 3D shape of a protein is important in both protein function analysis and drug design, for example when assessing the toxicity reduction associated with a given drug. Due to the complexity of protein 3D shapes and the close relationship between shapes and functions, the prediction of protein 3D shapes has become an important topic in bioinformatics. This research introduces a new approach to predict proteins’ 3D shapes, utilizing a multilayer artificial neural network. Our novel solution allows one to learn and predict the representations of the 3D shape associated with a protein by starting directly from its amino acid sequence descriptors. The input of the artificial neural network is a set of amino acid sequence descriptors we created based on a set of probability density functions. In our algorithm, the probability density functions are calculated by the correlation between the constituent amino acids, according to the substitution matrix. The output layer of the network is formed by 3D shape descriptors provided by an information retrieval system, called CAPRI. This system contains the pose invariant 3D shape descriptors, and retrieves proteins having the closest structures. The network is trained by proteins with known amino acid sequences and 3D shapes. Once the network has been trained, it is able to predict the 3D shape descriptors of the query protein. Based on the predicted 3D shape descriptors, the CAPRI system allows the retrieval of known proteins with 3D shapes closest to the query protein. These retrieved proteins may be verified as to whether they are in the same family as the query protein, since proteins in the same family generally have similar 3D shapes. The search for similar 3D shapes is done against a database of more than 45,000 known proteins. We present the results when evaluating our approach against a number of protein families of various sizes. Further, we consider a number of different neural network architectures and optimization algorithms. When the neural network is trained with proteins that are from large families where the proteins in the same family have similar amino acid sequences, the accuracy for finding proteins from the same family is 100%. When we employ proteins whose family members have dissimilar amino acid sequences, or those from a small protein family, in which case, neural networks with one hidden layer produce more promising results than networks with two hidden layers, and the performance may be improved by increasing the number of hidden nodes when the networks have one hidden layer.

The inelastic scattering reaction ¹⁶0+¹²C has been studied in the centre-of-mass energy region from 37.7 MeV to 51.4 MeV, in a search for evidence for a seven-alpha chain state in ²⁸Si. The decay products were detected in coincidence at angular separations around 90° in the centre of mass using two position-sensitive strip detectors. Kinematic reconstruction of the quasi-three body final states yielded the differential cross-sections for the decay channels leading to excited states in ¹²C, ¹⁶0 and ²⁰Ne. The excitation functions measured for the <sup>12 C(0+₂)-¹²C(0+₂)-U+03B1 and 12^C(0₂)-⁸Be-⁸Be final states agree broadly between the three experiments that were performed, but contain no structure. Reaction channels have also been identified leading to the ⁸Be-²⁰Ne* and ¹²C*-<sup>16<sup>0* final states. The cross-sections for the ⁸Be-²⁰Ne* decay channels, with the ²⁰ Ne in its lowest excited states, have been compared with previous measurements and provide good agreement. However, none of the excitation functions for these channels contain any structure. The absence of structure in any of the final states, that were identified in this study, indicates that a ²⁸Si chain state is probably not being observed. The same model, that predicts that the seven-alpha chain state should lie in this excitation region in ²⁸Si, has also been used to assign a six alpha chain structure to a resonance at E_x=46.6 MeV in ²⁴ Mg. These two results are compared, and possible reasons for the absence of evidence for a ²⁸Si chain structure are discussed.

The aim of this project was to explore the shapes of dark matter halos using high resolution N-body simulations. One of the main aspects explored was how well the shape can be measured through weak lensing. To explore this, simulations were run using the GADGET-2 code \cite{SPRING05} and a method used to measure ellipticities was tested \cite{oguri1}. It was found that Large Scale Structure along the line of sight diluted the measurements and made halos appear more spherical. On the other hand, substructure close to the halo introduced a bias where intrinsically elliptical halos appeared to be slightly more spherical and intrinsically spherical halos appeared to be slightly more elliptical. The effects of projection on concentration were also explored, it was concluded that halos which are most elliptical in 3D tend to appear the most concentrated in projection. Finally, we tested the possibility of using shape or concentration measurements to help break the degeneracy in $\Omega_M$ and $\sigma_8$. We found that this may be possible with $\sim$ 3000-4000 shape measurements or $\sim$ 400-500 concentration measurements.

Composite materials are supplanting conventional metals in aerospace, automotive, civil and marine industries in recent times. This is mainly due to their high strength and light weight characteristics. But with all the advantages they have, they are prone to delamination or matrix cracking. These types of damage are often invisible and if undetected, could lead to appalling failures of structures. Although there are systems to detect such damage, the criticality assessment and prognosis of the damage is often more difficult to achieve. The research study conducted here primarily deals with the structural health monitoring of composite materials by analysing vibration signatures acquired from a laser vibrometer. The primary aim of the project is to develop a vibration based structural health monitoring (SHM) method for detecting flaws such as delamination within the composite beams. Secondly, the project emphasises on the method's ability to recognise the locatio n and severity of the damage within the structure. The system proposed relies on the examination of the displacement mode shapes acquired from the composite beams using the laser vibrometer and later processing them to curvature mode shapes for damage identification and characterization. Other identification techniques such as a C-scan has been applied to validate the location and size of the defects with the structures tested. The output from these plots enabled the successful identification of both the location and extent of damage within the structure with an accuracy of 96.5%. In addition to this, this project also introduces a method to experimentally compute the critical stress intensity factor, KIC for the composite beam. Based on this, a technique for extending the defect has been proposed and validated using concepts of fatigue and fracture mechanics. A composite specimen with a 40 mm wide delamination embedded within was loaded under fatigue conditions and extension of the defect by 4mm on either s ide of the specimen's loading axis was achieved satisfactorily. The experimental procedure to extend the defect using fatigue was validated using the SLV system. Displacement and Curvature mode shapes were acquired post-fatigue crack extension. Upon analysing and comparing the displacement and curvature mode shapes before and after crack extension, the extended delamination was identified satisfactorily.

Composite materials are supplanting conventional metals in aerospace, automotive, civil and marine industries in recent times. This is mainly due to their high strength and light weight characteristics. But with all the advantages they have, they are prone to delamination or matrix cracking. These types of damage are often invisible and if undetected, could lead to appalling failures of structures. Although there are systems to detect such damage, the criticality assessment and prognosis of the damage is often more difficult to achieve. The research study conducted here primarily deals with the structural health monitoring of composite materials by analysing vibration signatures acquired from a laser vibrometer. The primary aim of the project is to develop a vibration based structural health monitoring (SHM) method for detecting flaws such as delamination within the composite beams. Secondly, the project emphasises on the method's ability to recognise the locatio n and severity of the damage within the structure. The system proposed relies on the examination of the displacement mode shapes acquired from the composite beams using the laser vibrometer and later processing them to curvature mode shapes for damage identification and characterization. Other identification techniques such as a C-scan has been applied to validate the location and size of the defects with the structures tested. The output from these plots enabled the successful identification of both the location and extent of damage within the structure with an accuracy of 96.5%. In addition to this, this project also introduces a method to experimentally compute the critical stress intensity factor, KIC for the composite beam. Based on this, a technique for extending the defect has been proposed and validated using concepts of fatigue and fracture mechanics. A composite specimen with a 40 mm wide delamination embedded within was loaded under fatigue conditions and extension of the defect by 4mm on either s ide of the specimen's loading axis was achieved satisfactorily. The experimental procedure to extend the defect using fatigue was validated using the SLV system. Displacement and Curvature mode shapes were acquired post-fatigue crack extension. Upon analysing and comparing the displacement and curvature mode shapes before and after crack extension, the extended delamination was identified satisfactorily.

In recent years, the use of composite structures in engineering application has increased. This is mainly due to their special advantages such as high structural performance, high corrosion resistance, tolerance of temperature; extreme fatigue resistance and high strength/weight ratio. However, some disorders like fibre breakage, matrix cracking and delaminations could be caused by operational loading, aging, chemical attack, mechanical vibration, changing of ambient conditions and shock etc. during the service. Although these disorders are hardly visible, they can severely reduce the mechanical properties and the load carrying capability of the composite structure. The aim of this research project is to develop a Vibration-based Structural Health Monitoring (SHM) method for carbon/epoxy composite beam specimens with the embedded artificial delaminations. The Laser Vibrometer Machine was used to excite the beams and gather the responses of the structure to the excitations. The physical properties such as frequency, velocity, mode shapes, and damping of the defective beams were measured. By using a C-SCAN machine, the accuracy of the positions of the delaminations was verified to be about 95% is accurate. Curvature mode shapes as a scalable damage detection parameter is calculated using an analytical model based on the Heaviside step function and the Central Difference Approximation (CDA) technique. The vibration-based damage detection method is then obtained using the difference between curvature mode shapes of the intact and damaged carbon/epoxy beams. An accurate prediction of 90% was attained. These results are proposed and discussed in detail in this study. Finally, the Fatigue Crack Propagation Test was applied on Samples with embedded delamination to extend the crack. The ASTM E399-90 standard is used for the experiment and a careful fatigue crack growth routine was designed and implemented to advance the delamination in a controlled manner. The total extension of 17 mm was observed with Microscope. The total propagation as determined by the curvature mode plots was 17.84 mm.

Thesis (Ph.D.)--University of Western Australia, 2006.