An overview of an existing hierarchical reconfiguration scheme for a fault-tolerant two-dimensional cellular architecture is presented, wherein an array of finite state machine cells controls the processing and switching elements. This allows the array to either reconfigure in the presence of faults, or to perform different processing functions. Since the control mechanism is distributed, the system is not subject to single-point "hard core" failures, as in the case of a global control mechanism. Unlike other fault-tolerant systems, the proposed method does not assume the existence of components which never fail. The processing elements in the array are logically connected in a mesh pattern, and are provided with additional physical connections to other cells. A local reconfiguration scheme allows faulty cells to be bypassed via these additional connections, so that the logical mesh can be restored. This technique allows the array to quickly reconfigure in the presence of up to triple faults. When local reconfiguration fails, the array can still reconfigure by using a global reconfiguration scheme, in which the functional part of the array relocates itself to a faultfree area. The process is "global" in the sense that the entire functional part of the array is involved in the process, but the mechanism to accomplish this is still distributed in nature. With the framework of the system established, the results of this research are presented. The hardware complexities of the existing global reconfiguration scheme are analyzed, and compared with the complexities of previous work in this area. A distributed diagnosis algorithm is also developed, which works in conjunction with the local reconfiguration mechanism to quickly detect and isolate faults in the array. Using these results, the foundations are laid for a totally self-checking implementation of the control cells, which allows online concurrent fault detection in the array. / Master of Science

A large number of errors in digital systems are due to the presence of transient faults. This is especially true of microprocessor-based systems working in a radiation environment that experience transient faults due to single event upsets. These upsets cause a temporary change in the state of the system without any permanent damage. Because of their random and non-recurring nature, transient faults are difficult to detect and isolate, hence they become a source of major concern, especially in critical real-time application areas. Concurrent detection of these errors is necessary for real-time operation. Most existing fault tolerance schemes either use redundancy to mask effects of transient faults or monitor the system for abnormal operations and then perform recovery operation. Although very effective, redundancy schemes incur substantial overhead that makes them unsuitable for small systems. Most monitoring schemes, on the other hand, only detect control flow errors. A new approach called Concurrent Processor Monitoring for on-line detection of transient faults is proposed that attempts to achieve high error coverage with small error detection latency. The concept of the execution profile of an instruction is defined and is used for detecting control flow and execution errors. To implement this scheme, a watchdog processor is designed for monitoring operation of the main processor. The effectiveness of this technique is demonstrated through computer simulations. / Ph. D.

Carbonate reservoirs contain approximately two-thirds of the world's oil and gas reserves (Al-Anzi et al., 2003). Carbonates often pose a significant problem when it comes to understanding their reservoir quality because of their heterogeneous nature, which is caused by both the variety of processes occurring depositionally and their high susceptibility to diagenetic alterations. In order to fully characterise the behaviour of carbonate rocks in the subsurface is it important to understand their textural heterogeneity and also how faulting can modify their textures. Deformation in fault zones causes the petrophysical properties (e.g. porosity, permeability and velocity) to alter from the background values. For example, fracturing in damage zones surrounding faults increase the permeability, creating conduits to fluids, conversely, fault cores often act as barriers, created by pore occluding processes. However, faulting in carbonate rocks is often complicated by their textural variations, leading to a variety of deformation microstructures, and each will create different petrophysical properties. This thesis aims to understand how faulting effects different carbonate rocks and analyse the controls on any alterations to the petrophysical properties (porosity, permeability and velocity) into the fault zones. Alterations to the permeability are important to unravel in order to assess the fluid flow potential and hydraulic properties of a rock. Understanding the alterations to the velocity can help to better image faults at depth and to provide information on their microstructures.

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published_or_final_version / Computer Science and Information Systems / Doctoral / Doctor of Philosophy

published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy

published_or_final_version / Mechanical Engineering / Doctoral / Doctor of Philosophy

An application of a recently introduced framework for isolating unprecedented faults for an automotive engine EGR valve system is presented. Using normal behavior data generated by a high fidelity engine simulation, the Growing Structure Multiple Model System (GSMMS) is used to construct models of normal behavior for EGR valve system and its various subsystems. Using the GSMMS models as a foundation, anomalous behavior of the entire system is then detected as statistically significant departures of the most recent modeling residuals from the modeling residuals during normal behavior. By reconnecting anomaly detectors to the constituent subsystems, the anomaly can be isolated without the need for prior training using faulty data. Furthermore, faults that were previously encountered (and modeled) are recognized using the same approach as the anomaly detectors. / text

This report introduces the concept of three-dimensional (3D) radial plots for the visualization of multivariate large scale datasets in plant operations. A key concept of this representation of data is the introduction of time as the third dimension in a two dimensional radial plot, which allows for the display of time series data in any number of process variables. This report shows the ability of 3D radial plots to conduct systemic fault detection and classification in chemical processes through the use of confidence ellipses, which capture the desired operating region of process variables during a defined period of steady-state operation. Principal component analysis (PCA) is incorporated into the method to reduce multivariate interactions and the dimensionality of the data. The method is applied to two case studies with systemic faults present (compressor surge and column flooding) as well as data obtained from the Tennessee Eastman simulator, which contained localized faults. Fault classification using the interior angles of the radial plots is also demonstrated in the paper. / text