Numerical simulations have been here carried out for turbulent flows in geometries relevant to electronic systems. These include plane and ribbed channels and a central processor unit (CPU). Turbulent flows are random, three-dimensional and time-dependent. Their physics covers a wide range of time and space scales. When separation and reattachment occur, together with streamline curvature, modelling of these complex flows is further complicated. It is well known that, when simulating unsteady flows, the traditional, steady, linear Reynolds-averaged Navier-Stokes (RANS) models often do not give satisfactory predictions. By contrast, unsteady, non-linear RANS models may perform better. Hence the application of these models is considered here. The non-linear models studied involve explicit algebraic stress and cubic models. The Reynolds Stress Model (RSM) has been also evaluated. Modelling strategies more advanced than RANS, i.e. Large Eddy Simulation (LES) and zonal LES (ZLES), have also been tested. Validation results from URANS, LES and ZLES indicate that the level of agreement of predictions with benchmark data is generally consistent with that gained by the work of others. For the CPU case, flow field and heat transfer predictions from URANS, LES ; and ZLES are compared with measurements. Overall, for the flow field, ZLES and LES are more accurate than URANS. Zonal low Reynolds number URANS models (using a hear wall k-l model) perform better than high Reynolds number models. However, for heat transfer prediction, none of the low Reynolds number models investigated performed well.

The behaviour of steel plates and reinforced concrete slabs which undergo large deflections has been investigated using the finite element method. Geometric and material nonlinearities are both considered in the study. Two computer programs have been developed for the analysis of plates and slabs. Ihe first program is for the elastic stability of plates. The elastic buckling loads obtained for plates with and without openings and under different edge loading conditions have been compared with the analytical and numerical results obtained by other investigators using different techniques of analyses. Good correlation between the results obtained and those given by others has been achieved. Improvements in the accuracy of the results and the efficiency of the analysis for plates with openings have been achieved. The second program is for the full range analysis of steel plates and reinforced concrete slabs up to collapse. The analysis can trace the load-deflection response up to collapse including snap-through behaviours. The program allows for the yielding of steel and the cracking and crushing of concrete. The modified Newton-Raphson with load control and displacement control methods is used to trace the structural response up to collapse. The line search technique has been included to improve the rate of convergence in the analysis of reinforced concrete slabs. The program has been tested against experimental and numerical results obatined by other investigators and has been shown to give good agreement. The accuracy of a number of integration rules usually adopted in nonlinear finite elecent analyses to evaluate the stress resultants from the stress distribution throughout concrete sections has been investigated. A new integration rule has been proposed for the integration of stress distributions through cracked concrete sections or cracked and crushed concrete sections.

This thesis describes the research and development of a decision support tool for determining a medical patient's suitability for surgical anaesthesia. At present, there is a change in the way that patients are clinically assessedp rior to surgery. The pre-operative assessment, usually conducted by a qualified anaesthetist, is being more frequently performed by nursing grade staff. The pre-operative assessmenet xists to minimise the risk of surgical complications for the patient. Nursing grade staff are often not as experienced as qualified anaesthetists, and thus are not as well suited to the role of performing the pre-operative assessment. This research project used data collected during pre-operative assessments to develop a decision support tool that would assist the nurse (or anaesthetist) in determining whether a patient is suitable for surgical anaesthesia. The three main objectives are: firstly, to research and develop an automated intelligent systems technique for classifying heart and lung sounds and hence identifying cardio-respiratory pathology. Secondly, to research and develop an automated intelligent systems technique for assessing the patient's blood oxygen level and pulse waveform. Finally, to develop a decision support tool that would combine the assessmentsa bove in forming a decision as to whether the patient is suitable for surgical anaesthesia. Clinical data were collected from hospital outpatient departments and recorded alongside the diagnoses made by a qualified anaesthetist. Heart and lung sounds were collected using an electronic stethoscope. Using this data two ensembles of artificial neural networks were trained to classify the different heart and lung sounds into different pathology groups. Classification accuracies up to 99.77% for the heart sounds, and 100% for the lung sounds has been obtained. Oxygen saturation and pulse waveform measurements were recorded using a pulse oximeter. Using this data an artificial neural network was trained to discriminate between normal and abnormal pulse waveforms. A discrimination accuracy of 98% has been obtained from the system. A fuzzy inference system was generated to classify the patient's blood oxygen level as being either an inhibiting or non-inhibiting factor in their suitability for surgical anaesthesia. When tested the system successfully classified 100% of the test dataset. A decision support tool, applying the genetic programming evolutionary technique to a fuzzy classification system was created. The decision support tool combined the results from the heart sound, lung sound and pulse oximetry classifiers in determining whether a patient was suitable for surgical anaesthesia. The evolved fuzzy system attained a classification accuracy of 91.79%. The principal conclusion from this thesis is that intelligent systems, such as artificial neural networks, genetic programming, and fuzzy inference systems, can be successfully applied to the creation of medical decision support tools.

Thesis (Ph. D.)--Georgia State University, 2007. / Title from file title page. Ying Zhu, committee chair; Xiaolin Hu, Geoffrey Hubona, Roy Johnson, Rajshekhar Sunderraman, committee members. Electronic text (216 p. : ill. (some col.)) : digital, PDF file. Description based on contents viewed Nov. 29, 2007. Includes bibliographical references (p. 209-216).

Thesis (M. Sc.)--Carleton University, 2004. / Includes bibliographical references (p. 138-140). Also available in electronic format on the Internet.

Thesis (M.App.Sc.) - Carleton University, 2005. / Includes bibliographical references (p. 141-149). Also available in electronic format on the Internet.

Thesis (M.C.S.) - Carleton University, 2006. / Includes bibliographical references (p. 114-116). Also available in electronic format on the Internet.

Thesis (Ph.D.) - Carleton University, 2007. / Includes bibliographical references (p. 158-167). Also available in electronic format on the Internet.

Thesis (M.App.Sc.) - Carleton University, 2007. / Includes bibliographical references (p. 77-79). Also available in electronic format on the Internet.

Thesis (M.App.Sc.) - Carleton University, 2007. / Includes bibliographical references (p. 150-154). Also available in electronic format on the Internet.