Thesis (M.App.Sc.) - Carleton University, 2002. / Includes bibliographical references (p. 123-127). Also available in electronic format on the Internet.

Thesis (M. App. Sc.)--Carleton University, 2005. / Includes bibliographical references (p. 181-186). Also available in electronic format on the Internet.

Thesis (M.S.)--University of Alabama at Birmingham, 2007. / Description based on contents viewed July 8, 2009; title from PDF t.p. Includes bibliographical references (p. 115-116).

Thesis (M. Eng.)--Carleton University, 1999. / Also available in electronic format on the Internet.

Thesis (MTech (Mechanical Engineering))--Cape Peninsula University of Technology, 2015. / Currently non-destructive testing techniques for composite aircraft structures are disadvantaged when compared to online Structural Health Monitoring (SHM) systems that monitor the structure while in-service and give real time data. The present research work looks at developing a protocol for online structural health monitoring of a UAV wing structure using PVDF film sensors, especially including the monitoring of structural changes caused by defects. Different types of SHM techniques were studied in relation to carbon fibre composites. Laminate composite make-up and manufacturing process was investigated and vacuum infusion process was used to manufacture the samples that resemble the Guardian II wing structure, then the three-point bending test was used to determine the material properties. Digital Shearography was employed as a stationery non-destructive technique to determine the sensor to structure attachment, type and position of defects that affect the state of performance. Finite Element Analysis (FEA) was done using ANSYS Workbench which served as a modelling tool using a drawing imported from Solid-works. Experimental investigation was done using PVDF sensor embedded on the surface of the sample in a cantilever setup and a vertical Vernier scale to measure the deflection due to impact and vibration loading. A Fluke-View oscilloscope was used as a data logger when the measurement of the output voltage and the natural frequency were recorded. The techniques of using FEA and experimental investigation were then compared. The findings of this study showed that the PVDF sensor is suitable for condition monitoring of a UAV wing structure.

M.Sc. (Computer Science) / Please refer to full text to view abstract

Please read the abstract in the section 00front of this document / Dissertation (M Eng (Structural Engineering))--University of Pretoria, 2006. / Civil Engineering / unrestricted

In structural analysis and design it is important to consider the effects of uncertainties in loading and material properties in a rational way. Uncertainty in material properties such as heterogeneity in elastic and mass properties can be modeled as a random field. For computational purpose, it is essential to discretize and represent the random field. For a field with known second order statistics, such a representation can be achieved by Karhunen-Lo`eve (KL) expansion. Accordingly, the random field is represented in a truncated series expansion using a few eigenvalues and associated eigenfunctions of the covariance function, and corresponding random coefficients. The eigenvalues and eigenfunctions of the covariance kernel are obtained by solving a second order Fredholm integral equation. A closed-form solution for the integral equation, especially for arbitrary domains, may not always be available. Therefore an approximate solution is sought. While finding an approximate solution, it is important to consider both accuracy of the solution and the cost of computing the solution. This work is focused on exploring a few numerical methods for estimating the solution of this integral equation. Three different methods:(i)using finite element bases(Method1),(ii) mid-point approximation(Method2), and(iii)by the Nystr¨om method(Method3), are implemented and numerically studied. The methods and results are compared in terms of accuracy, computational cost, and difficulty of implementation. In the first method an eigenfunction is first represented in a linear combination of a set of finite element bases. The resulting error in the integral equation is then minimized in the Galerkinsense, which results in a generalized matrix eigenvalue problem. In the second method, the domain is partitioned into a finite number of subdomains. The covariance function is discretized by approximating its value over each subdomain locally, and thereby the integral equation is transformed to a matrix eigenvalue problem. In the third method the Fredholm integral equation is approximated by a quadrature rule, which also results in a matrix eigenvalue problem. The methods and results are compared in terms of accuracy, computational cost, and difficulty of implementation. The first part of the numerical study involves comparing these three methods. This numerical study is first done in one dimensional domain. Then for study in two dimensions a simple rectangular domain(referred toasDomain1)is taken with an uncertain material property modeled as a Gaussian random field. For the chosen covariance model and domain, the analytical solutions are known, which allows verifying the accuracy of the numerical solutions. There by these three numerical methods are studied and are compared for a chosen target accuracy and different correlation lengths of the random field. It was observed that Method 2 and Method 3 are much faster than the Method 1. On the other hand, for Method 2 and 3, additional cost for discretizing the domain into nodes should be considered whereas for a mechanics-related problem, Method 1 can use the available finite element mesh used for solving the mechanics problem. The second part of the work focuses on studying on the effect of the geometry of the model on realizations of the random field. The objective of the study is to see the possibility of generating the random field for a complicated domain from the KL expansion for a simpler domain. For this purpose, two KL decompositions are obtained: one on the Domain1, and another on the same rectangular domain modified with a rectangular hole (referredtoasDomain2) inside it. The random process is generated and realizations are compared. It was observed from the studies that probability density functions at the nodes on both the domains, that is, on Domain 1 and Domain 2, are similar. This observation leads to a possibility that a complicated domain can be replaced by a corresponding simpler domain, thereby reducing the computational cost.

M.Ed. (Curriculum Studies) / According to Jansen van Rensburg (1987:62) the watchword in the present-day world is productivity and this necessitates that, that which the student learns must be relevant to particularly the needs of the practice for functional skills. As a result of the above-mentioned, the following questions were posed: * Does the existing Strength of Materials and Structures N5 curriculum conform to scientific justifiable criteria for curriculum development? * Does the contents of strength of Materials and Structures N5 conform to the needs of the Industry? * Is the purpose with the contents clear? To answer the above-mentioned questions a questionnaire was used. R.A. Kruger's evaluation model was used to evaluate the present Strength of Materials and Structures N5 syllabus. The following conclusions, inter alia, were arrived at: * Students who study at Technical Colleges, work mainly with maintenance aspects. A very small percentage indicated that design and drawing aspects are regarded as important in practice. However, the present Strength of Materials and Structures N5 syllabus makes very 1ittle provision for the maintenance of such contents. * Furthermore it was found that there is a particularly great need for practical elucidation of the theory. * The present document (syllabus) does not conform to scientific justifiable criteria. No objectives or aims are reflected in the document. The contents are listed point by point without any order.

Indiana University-Purdue University Indianapolis (IUPUI) / Nanocomposite ceramics have been widely studied in order to tailor desired properties at high temperatures. Methodologies for development of material design are still under effect. While finite element modeling (FEM) provides significant insight on material behavior, few design researchers have addressed the design paradox that accompanies this rapid design space expansion. A surrogate optimization model management framework has been proposed to make this design process tractable. In the surrogate optimization material design tool, the analysis cost is reduced by performing simulations on the surrogate model instead of high fidelity finite element model. The methodology is incorporated to and the optimal number of silicon carbide (SiC) particles, in a silicon-nitride(Si3N4) composite with maximum fracture energy [2]. Along with a deterministic optimization algorithm, model uncertainties have also been considered with the use of robust design optimization (RDO) method ensuring a design of minimum sensitivity to changes in the parameters. These methodologies applied to nanocomposites design have a significant impact on cost and design cycle time reduced.