It is estimated that approximately 10-12% of the adult population suffers from osteoarthritis (OA), with long reaching burdens personally and socioeconomically. OA also causes mild discomfort to severe pain in those suffering from the disease. The incidence rate of OA for individuals with transtibial amputations is much than average in the tibiofemoral joint (TF). It is well understood that abnormal articular cartilage stress, whether that be magnitude or location, increases the risk of developing OA. Finite element (FE) simulations can predict stress in the TF joint, many studies throughout the years have validated the technology used for this purpose. This thesis is the first to successfully validate a procedure for creating subject-specific FE models for transtibial amputees to simulate the TF joint in gait, cycling and elliptical exercises. Maximum tibial cartilage pressure was extracted post-simulation and compared to historical data. The body weight normalized contact pressure on the tibial articular cartilage for the two amputee participants was larger in magnitude than the control participant in all but the medial compartment in cycling. Additionally, cycling exercise produced the smallest values of contact pressure with elliptical and gait producing similar max values but different areas of effect. The results from this thesis align with the body of work preceding it and further the goal of a FE model that predicts in-vivo articular cartilage stress in the TF joint. Future studies can further refine this methodology and create additional subject-specific models to allow for a statistical analysis of the observed differences to find if the results are significantly different. Refining the methodology could include investigating the full effect of the damping factor on contact pressure and exploring alternative methods of mesh generation.

Accurate mechanical analysis of composite structures is necessary for the prediction of laminate behavior. Cylindrical composite tubes are a mainstay in many structural applications. The fundamental design of circular composite cross-sections necessitates the development of a comprehensive composite lamination theory. A new analytical method is developed to characterize the behavior of thin-walled composite cylindrical tubes using a modified plate theory. A generated numerical solver can predict properties such as axial stiffness, bending stiffness, layer stresses, and layer strains in composite tubes subjected to combined mechanical loading and thermal effects. The model accounts for the curvature by transforming and translating the material in-plane lamina properties over a global reference coordinate system. A MATLAB-based solver is used to determine the lamina stiffness and stress outcomes with adjustable parameters, including elastic material properties, thermal coefficients, tubing radius, the orientation of fibers, and the ply stacking sequence. The results are then validated using a FE model developed in ABAQUS using a simple quadrature S4R element type. Parametric case studies confirm the validity of the analytical model by accounting for different ply orientations, stacking sequence, and thermal, mechanical loading.

<p dir="ltr">The most predominantly used rotating electric machines today are the radial and axial flux varieties (denoted RFM and AFM, respectively). There is another category of machines called the transverse flux machines (denoted TFMs) which are best suitable for high torque low speed applications such as in wind energy conversion systems, ship propulsion systems, and other direct drive applications. In this work, a design methodology based on a magnetic equivalent circuit (MEC) model for a three-phase stacked transverse flux machine is presented. Using this MEC model, an optimization-based design paradigm is created. Finite element analysis is used to validate a design obtained from the proposed algorithm. </p>

Yes / The current UK rail network is managed by Network Rail, which requires an investment of £5.2bn per year to cover operational costs [1]. These expenses include the maintenance and repairs of the railway rails. This paper aims to create a proof of concept for an autonomous health monitoring system of the rails using an integrated finite element analysis (FEA) and artificial neural network (ANN) approach. The FEA is used to model worn profiles of a standard rail and predict the stress field considering the material of the rail and the loading condition representing a train travelling on a straight line. The generated FEA data is used to train an ANN model which is utilised to predict the stress field of a worn rail using optically scanned data. The results showed that the stress levels in a rail predicted with the ANN model are in an agreement with the FEA predictions for a worn rail profile. These initial results indicate that the ANN can be used for the rapid prediction of stresses in worn rails and the FEA-ANN based approach has the potential to be applied to autonomous health monitoring of rails using fast scanners and validated ANN models. However, further development of this technology would be required before it could be used in the railway industry, including: real time data processing of scanned rails; improved scanning rates to enhance the inspection efficiency; development of fast computational methods for the ANN model; and training the ANN model with a large set of representative data representing application specific scenarios.

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Additive manufacturing has shown the ability to produce highly complex geometries that are not easily manufactured through traditional means. However, the implications of building these complex geometries regarding thermal history requires more attention. AM process simulations have proven to be computationally expensive and require large amounts of pre-processing to execute. This thesis will start with a review of additive manufacturing along with current modeling efforts. Then, the development of a pre-processing tool for finite element simulations of these processes is presented. It is shown that the pre-processing tool significantly decreases the total time-to-simulation by removing manual steps. Finally, a study using this tool is conducted to analyze the thermal histories of a cube and a cylinder with two different scan strategies and explore differences in resulting thermal history. It is shown that less temperature fluctuations and a lower final temperature result from an offset scan strategy and a cylindrical geometry.

The benefits of lighter auto bodies are discussed, and aluminum is compared to steel as an alternative material for auto body construction. The concept of a structural index, lambda, is developed using the simple example of a hollow beam of wall thickness, t, with a cantilever load case. It is shown that the bending stiffness, K, of the beam can be defined as a function of t^lambda, that 1 < lambda < 3, and that lambda can be used to predict the weight savings from material substitution where stiffness is held constant. It is then demonstrated that lambda can be used to predict the weight savings from material substitution in the more complex cases of the joints of a light truck cab.

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