This thesis compares the results of two of the more popular flexible aircraft modeling formulations, the mean-axes method and the fixed-axes method, for application in real-time motion simulators. First, the time-domain equations of motion for an elastic body using the fixed-axes are derived. Subsequently, the mean-axes equations are derived by making a few assumptions from the fixed-axis equations. The two formulations are then implemented for a scaled-up beam model of a Cessna Citation aircraft, with the deformations represented by the modal expansion of the whole aircraft from their respective constrained and free-free finite element solutions. Time-domain results, consisting of the acceleration, velocity, and attitude of a point on the aircraft body, are obtained in both models at two beam-stiffness configurations using a quasi-steady aerodynamic model for a single maneuver at one flight condition. The two methods produced similar results with the fixed-axes formulation producing slightly more accurate results.

Molecular docking is a computational tool commonly applied in drug discovery projects and fundamental biological studies of protein-ligand interactions. Traditionally, molecular docking is used to address one of three following questions: (i) given a ligand molecule and a protein receptor, predict the binding mode (pose) of the ligand within the context of a receptor, (ii) screen a collection of small-molecules against a receptor and rank ligands by their likelihood of being active, and (iii) given a ligand molecule and a target receptor, predict the binding affinity of the two. Here, we focus on the first two questions, namely ranking and pose prediction. Currently, state-of-the-art docking algorithms predict poses within 2A of the native pose in a rate lower than ∼60% and in many cases, below 40%. In ranking, their ability to identify active ligands is inconsistent and generally suffers from high false-positive rate. In this thesis we present novel algorithms to enhance the ability of molecular docking to address these two questions. These algorithms do not substitute traditional docking but rather being applied on top of them to provide synergistic effect. Our algorithms improve pose predictions by 0.5-1.0A and ranking order for 23% of the targets in gold-standard benchmarks. As importantly, the algorithms improve the consistence of the posing and ranking predictions over diverse sets of targets and screening libraries. In addition to the posing and ranking, we present the pharmacophore concept. A pharmacophore is an ensemble of physiochemical descriptors associated with a biological target that elucidates common interaction patterns of ligands with that target. We introduce a novel pharmacophore inference algorithm and demonstrate its utilization in molecular docking. This thesis is outlined as follow. First we introduce the molecular docking approach for pose prediction and ranking. Second, we discuss the pharmacophore concept and present algorithms for pharmacophore inference. Third, we demonstrate the utilization of pharmacophores for pose prediction by re-scoring candidate poses generated by docking algorithms. Finally, we present algorithms to improve ranking by reducing bias in scoring functions employed by docking algorithms.

This thesis compares the results of two of the more popular flexible aircraft modeling formulations, the mean-axes method and the fixed-axes method, for application in real-time motion simulators. First, the time-domain equations of motion for an elastic body using the fixed-axes are derived. Subsequently, the mean-axes equations are derived by making a few assumptions from the fixed-axis equations. The two formulations are then implemented for a scaled-up beam model of a Cessna Citation aircraft, with the deformations represented by the modal expansion of the whole aircraft from their respective constrained and free-free finite element solutions. Time-domain results, consisting of the acceleration, velocity, and attitude of a point on the aircraft body, are obtained in both models at two beam-stiffness configurations using a quasi-steady aerodynamic model for a single maneuver at one flight condition. The two methods produced similar results with the fixed-axes formulation producing slightly more accurate results.

The aim of this thesis was to develop a new energy model that predicts the energy infrastructure required to maintain the oil production in the Oil Sands operation at minimum cost. Previous studies in this area have focused on the energy infrastructure for fixed energy demands, i.e., the production schemes that produce synthetic crude oil (SCO) and commercial diluted bitumen remained fixed in the optimal infrastructure calculation. The key novelty of this work is that the model searches simultaneously for the most suitable set of oil production schemes and the corresponding energy infrastructures that satisfy the total production demands under environmental constraints, i.e., CO2 emissions targets. The proposed modeling tool was validated using historical data and previous simulations studies for the Oil Sands operation in 2003. Likewise, the proposed model was used to study the 2020 Oil Sands operations under three different production scenarios. Also, the 2020 case study was used to show the effect of CO2 capture constraints on the oil production schemes and the energy producers. The results show that the proposed model is a practical tool to determine the production costs for the Oil Sands operations, evaluate future production schemes and energy demands scenarios, and identify the key parameters that affect the Oil Sands operation

Tillage erosion is a major contributor to the total soil erosion in cultivated topographically complex lands. No study has been carried out on tillage erosion associated with cereal-based production systems in the Canadian Prairies, and there is a need to examine tillage erosivity of secondary tillage and seeding implements and the effect of slope curvature on tillage translocation. With both tillage and water erosion occurring in a cultivated topographically complex landscape, it is valuable to investigate the relative contributions of and the possible linkage and interactions between these two erosion processes. Tillage translocation causes the mixture of subsoil into the till-layer, which may considerably affect soil properties and therefore the related biophysical processes. In this study, using plot tracers, we examined tillage translocation caused by four tillage implements: air-seeder, spring-tooth-harrow, light-cultivator and deep-tiller in southern Manitoba, Canada. We determined that secondary tillage and seeding implements could be as erosive as primary tillage implements in a cereal-based production system. In the majority of cases, tillage translocation could be explained by slope gradient alone; however, slope curvature also significantly affected tillage translocation. In two field sites in the North America Great Plains (NAGP), measured 137Cs inventories were converted into total soil erosion rates. Tillage and water erosion rates were estimated using models. The comparisons of the model estimates to 137Cs estimates showed that both tillage and water erosion significantly contributed to the total soil erosion in undulating slopes while tillage erosion was the predominant erosion process in hummocky hilltops. The contributions of and the linkage and interactions between water and tillage erosion showed predictable patterns in different landform elements, with the knowledge of which, landscape segmentation could be used to assess the potential of soil erosion. Further investigation of tillage translocation was demonstrated with four hypothetic landscapes: plane slope, symmetric hill, asymmetric hill and irregular hill, and is tested against field data. A Visual Basic coded program (TillTM) was developed to simulate the redistribution of soil constituents and soil mass. We determined that the pattern of soil mass redistribution was dependent on topography, while the pattern of soil constituent redistribution was affect by topographic features, tillage patterns and temporal scales.

The formation of aeolian ripples has been modeled, quite successfully, using discrete approaches like cellular automaton models. Numerical analysis of continuum models to obtain similar success in modeling ripple evolution, however, has not been studied extensively. A numerical model based on continuum theories expedites calculations, as opposed to discrete approaches which model trajectory of each and every sand grain, and are hence relatively more economical. The numerical analysis strives to contribute to the field of study of aeolian ripple migration by an extensive comparison and discussion of modeled ripple evolution results with those of a particular laboratory based wind-tunnel experiment. This research also endeavors to under- stand the physics behind ripple generation and what parameters to be modified to account for multiple grain sizes. Incorporation of multiple grain sizes would enable us to study the stratigraphy of the generated bed-forms. To obtain smoother and realistic ripple surfaces, a sixth-order compact finite difference numerical scheme is used for spatial derivates and fourth-order Runge-Kutta scheme for time derivates. The boundary conditions incorporated are periodic and the initial condition employed to generate ripple is a rough sand surface. The numerical model is applied to study the effect of varying the angle, at which the sand bed gets impacted by sand grains, on the evolution of ripples. Ripples are analyzed qualitatively and quantitatively by considering the contribution of processes involved in the evolution process. The ripple profiles and the time taken to reach equilibrium state, obtained by numerical experiments, are in close agreement with the ones obtained by the wind-tunnel experiment.

The present work used ab initio density functional theory (DFT) to study two different physical phenomena crystallization fouling and clay-based polymer nanocomposites. In the first part, two foulant materials were studied including calcium carbonate, and calcium sulfate. The lattice energy and enthalpy of formations of each crystal system were predicted using DFT methods. The most stable forms of calcium carbonate foul ant, calcite and aragonite, were investigated. For calcium sulfate, both gypsum and anhydrite crystals were investigated. The thermodynamic solubility product of each crystal system, for both foul ants, was predicted from the lattice energy and enthalpy of formations. Comparison of the stability between the different crystal systems for the same foul ant material was carried out to elucidate the effect of crystal atomic configuration and space group on the stability of foulant materials. The effect of temperature on the formation and stability of foulant material was also carried out. The results obtained using DFT methods, for enthalpy of formation and thermodynamic solubility products, were comparable with the experimental data reported in the literature. In the second part, study has been made on the clay-based nylon 6 nanocomposite materials. The purpose was to understand the interfacial interactions between clay and polymer with and without surfactant component. Both sides of the clay were examined with nylon 6. In order to determine specifically the type of interfacial interaction between clay and nylon 6, the electron distribution around the whole system was predicted. The study was carried out at various isomorphic substitutions. The substitutions took place at both octahedral and tetrahedral layers of the clay. The strength between clay and nylon 6 was predicted by calculating the binding energy. The results obtained revealed that, the strength increases with the increase in the degree of isomorphic substitutions. The type of bond between nylon 6 and basal surface of the clay was found to be basically electrostatic interactions, and particularly hydrogen bonds. Whilst, the type of interactions between nylon 6 and clay edge surface was found to include covalent bonds as well as electrostatic interactions. The formation and breakage of covalent bonds between nylon 6 and clay means that, a chemical decomposition of the clay can happen when it is mixed with certain type of polymers. The presence of surfactant can decrease the interfacial interactions between clay and nylon 6.

In 2003, Pomeroy et al. published a research study that described a gene expression based prediction of central nervous system embryonal tumour (CNS) outcome. Over a half of decade, many models and approaches have been developed based on experimental data consisting of 99 samples with 7,129 genes. The way, how meaningful knowledge from these models can be extracted, and how this knowledge for further research is still a hot topic. This thesis addresses this and has developed an information method that includes modelling of interactive patterns, important genes discovery and visualisation of the obtained knowledge. The major goal of this thesis is to discover important genes responsible for CNS tumour and import these genes into a well structured knowledge framework system, called Brain-Gene-Ontology. In this thesis, we take the first step towards finding the most accurate model for analysing the CNS tumour by offering a comparative study of global, local and personalised modelling. Five traditional modelling approaches and a new personalised method – WWKNN (weighted distance, weighted variables K-nearest neighbours) – are investigated. To increase the classification accuracy and one-vs.-all based signal to- noise ratio is also developed for pre-processing experimental data. For the knowledge discovery, CNS-based ontology system is developed. Through ontology analysis, 21 discriminate genes are found to be relevant for different CNS tumour classes, medulloblastoma tumour subclass and medulloblastoma treatment outcome. All the findings in this thesis contribute for expanding the information space of the BGO framework.

This thesis reports the development of potent and selective inhibitors of m-calpain for the treatment of cataract. SJA6017 has been proven to prevent lens opacity in rat and has been our lead compound. A series of Val-Leu peptidyl aldehyde inhibitors (33a-e, 33g, 33i and 35) have been designed, synthesized, and tested for therapeutic potential as cataract inhibitors. Chapter 1 is an introduction to calpain and the diseases associated with it's over activation. A review of the literature on calpain inhibition is given. Structure activity relationship (SAR) theory is presented. The techniques that have been applied in our research group to drug design include molecular modeling, synthesis, assay and animal studies which are all briefly discussed. The importance of a -strand conformation for an inhibitor to bind to calpain is discussed. Chapter 2 describes the synthesis of m-calpain inhibitors. This comprises the preparation of the Val-Leu dipeptide core 29, Val-Leu dipeptidyl alcohols 31a-g and 31i, and the synthesis of dipeptidyl aldehydes 33a-e, 33g, 33i and 35. The choice of coupling regents and conditions in the coupling reactions is investigated. Sulfur trioxide pyridine oxidation for the conversion of Val-Leu dipeptidyl alcohols to aldehydes is discussed. The molecular modeling and biological assay results are presented.

Thesis (M.S. in Mechanical Engineer and M.S. in Mechanical Engineering)--Naval Postgraduate School, September 2009. / Thesis Advisor(s): Kwon, Young W. ; Pollak, Randall D. "September 2009." Description based on title screen as viewed on November 5, 2009. Author(s) subject terms: Lamb Waves, modeling, finite element, longitudinal, and shear mode, ANSYS, debonding, sensor, piezoelectric. Includes bibliographical references (p. 93-96). Also available in print.