This thesis deals with the reliability analysis of a fuel pump driver circuit (FPDC), which regulates the amount of fuel pumped to a turbojet engine. Reliability analysis in such critical circuits has great importance since unexpected failures may cause serious financial loss and even human death. In this study, two types of reliability analysis are used: &ldquo / Worst Case Circuit Tolerance Analysis&rdquo / (WCCTA) and &ldquo / Failure Modes and Effects Analysis&rdquo / (FMEA). WCCTA involves the analysis of the circuit operation under varying parameters in their tolerance bands. These parameters include the resistances of the resistors, operating temperature and voltage input value. The operation of FPDC is checked and the most critical parameters are determined in the worst case conditions. While performing WCCTA, a method that guarantees the exact worst case conditions is used rather than probabilistic methods like Monte Carlo analysis. The results showed that the parameter variations do not affect the circuit operation unfavorably / operating temperature, voltage input variation and tolerance bands for the resistances are fairly compatible with the circuit operation. FMEA is implemented according to the short circuit and open circuit failures of all the electronic components used in FPDC. The components whose failure has catastrophic effect on the circuit operation have been determined and some preventive actions have been offered for some catastrophic failures.

This dissertation investigates the implementation of S-parameter based network techniques for the analysis of multiconductor, high speed VLSI integrated circuit and packaging interconnects. The S-parameters can be derived from three categories of input parameters: (1) lossy quasi-static R,L,C and G, (2) lossy frequency dependent (dispersive) R,L,C,G and (3) the propagation constants, Γ, the characteristic impedance, Z(c) and the conductor eigencurrents, I, derived from full wave analysis. The S-parameter network techniques developed allow for: the analysis of periodic waveform excitation, the incorporation of externally measured or calculated scattering parameter data and large system analysis through macro decomposition. The inclusion of non-linear terminations has also been developed.

The rapid development in renewable generation technologies and flexible distribution networks requires current infrastructure to be modified and developed to adapt high penetration levels of distributed generation. Existing distribution networks were not initially designed and anticipated to accommodate generators on large scale. Short circuit studies ensure the effectiveness of protection equipment settings and coordination is maintained in case of short circuit, despite any additional distributed generation is connected to the distribution network. This research aims to study and compare the different network fault situations for wind energy systems with induction generators, photovoltaic energy systems, and diesel generators connected to distribution networks. The simulation study will be conducted on the existing IEEE case study systems including 13 bus and 30 bus distribution test systems, using ETAP software. Short circuit analysis will be performed twice to include the ANSI/IEEE and the IEC methods for short circuit currents calculation. Simulated results showed that the wind energy systems have significant impact on the short circuit currents, whereas the photovoltaic energy systems are found to have inconsequential effect. The most moderate solution is found to be a distributed generation mix.

The performance of SPICE and Network C (NC) circuit simulator when simulating MOS transistor circuits has been investigated and compared. SPICE analog model, NC analog model and NC MOS_PWL model are the three MOS transistor models being used. The comparison between SPICE and NC includes five areas. They are MOS transistor model, circuit analysis and computational methods, limitation on the ability to simulate circuits containing the MOS transistor diode configuration, run time and the ability to build new circuit component models using derived equations.

No description available.

Thesis (Ph.D.) - Carleton University, 2002. / Includes bibliographical references (p. 159-172). Also available in electronic format on the Internet.

Thesis (M.App.Sc.) - Carleton University, 2006. / Includes bibliographical references (p. 103-107). Also available in electronic format on the Internet.

Thesis (M.App.Sc.) - Carleton University, 2007. / Includes bibliographical references (p. 106-108). Also available in electronic format on the Internet.

This research presents various intelligent optimisation methods which are: genetic algorithm (GA), particle swarm optimisation (PSO), artificial bee colony algorithm (ABCA), firefly algorithm (FA) and bacterial foraging optimisation (BFO). It attempts to minimise analogue electronic filter and amplifier circuits, taking a cascode amplifier design as a case study, and utilising the above-mentioned intelligent optimisation algorithms with the aim of determining the best among them to be used. Small signal analysis (SSA) conversion of the cascode circuit is performed while mesh analysis is applied to transform the circuit to matrices form. Computer programmes are developed in Matlab using the above mentioned intelligent optimisation algorithms to minimise the cascode amplifier circuit. The objective function is based on input resistance, output resistance, power consumption, gain, upperfrequency band and lower frequency band. The cascode circuit result presented, applied the above-mentioned existing intelligent optimisation algorithms to optimise the same circuit and compared the techniques with the one using Nelder-Mead and the original circuit simulated in PSpice. Four circuit element types (resistors, capacitors, transistors and operational amplifier (op-amp)) are targeted using the optimisation techniques and subsequently compared to the initial circuit. The PSO based optimised result has proven to be best followed by that of GA optimised technique regarding power consumption reduction and frequency response. This work modifies symbolic circuit analysis in Matlab (MSCAM) tool which utilises Netlist from PSpice or from simulation to generate matrices. These matrices are used for optimisation or to compute circuit parameters. The tool is modified to handle both active and passive elements such as inductors, resistors, capacitors, transistors and op-amps. The transistors are transformed into SSA and op-amp use the SSA that is easy to implement in programming. Results are presented to illustrate the potential of the algorithm. Results are compared to PSpice simulation and the approach handled larger matrices dimensions compared to that of existing symbolic circuit analysis in Matlab tool (SCAM). The SCAM formed matrices by adding additional rows and columns due to how the algorithm was developed which takes more computer resources and limit its performance. Next to this, this work attempts to reduce component count in high-pass, low-pass, and all- pass active filters. Also, it uses a lower order filter to realise same results as higher order filter regarding frequency response curve. The optimisers applied are GA, PSO (the best two methods among them) and Nelder-Mead (the worst method) are used subsequently for the filters optimisation. The filters are converted into their SSA while nodal analysis is applied to transform the circuit to matrices form. High-pass, low-pass, and all- pass active filters results are presented to demonstrate the effectiveness of the technique. Results presented have shown that with a computer code, a lower order op-amp filter can be applied to realise the same results as that of a higher order one. Furthermore, PSO can realise the best results regarding frequency response for the three results, followed by GA whereas Nelder- Mead has the worst results. Furthermore, this research introduced genetic folding (GF), MSCAM, and automatically simulated Netlist into existing genetic programming (GP), which is a new contribution in this work, which enhances the development of independent Matlab toolbox for the evolution of passive and active filter circuits. The active filter circuit evolution especially when operational amplifier is involved as a component is of it first kind in circuit evolution. In the work, only one software package is used instead of combining PSpice and Matlab in electronic circuit simulation. This saves the elapsed time for moving the simulation between the two platforms and reduces the cost of subscription. The evolving circuit from GP using Matlab simulation is automatically transformed into a symbolic Netlist also by Matlab simulation. The Netlist is fed into MSCAM; where MSCAM uses it to generate matrices for the simulation. The matrices enhance frequency response analysis of low-pass, high-pass, band-pass, band-stop of active and passive filter circuits. After the circuit evolution using the developed GP, PSO is then applied to optimise some of the circuits. The algorithm is tested with twelve different circuits (five examples of the active filter, four examples of passive filter circuits and three examples of transistor amplifier circuits) and the results presented have shown that the algorithm is efficient regarding design.

abstract: Conceptual knowledge and self-efficacy are two research topics that are well-established at universities, however very little has been investigated about these at the community college. A sample of thirty-seven students enrolled in three introductory circuit analysis classes at a large southwestern community college was used to answer questions about conceptual knowledge and self-efficacy of community college engineering students. Measures included a demographic survey and a pre/post three-tiered concept inventory to evaluate student conceptual knowledge of basic DC circuit analysis and self-efficacy for circuit analysis. A group effect was present in the data, so descriptive statistics were used to investigate the relationships among students' personal and academic characteristics and conceptual knowledge of circuit analysis. The a priori attribute approach was used to qualitatively investigate misconceptions students have for circuit analysis. The results suggest that students who take more credit hours score higher on a test of conceptual knowledge of circuit analysis, however additional research is required to confirm this, due to the group effect. No new misconceptions were identified. In addition to these, one group of students received more time to practice using the concepts. Consequently, that group scored higher on the concept inventory, possibly indicating that students who have extra practice time may score higher on a test of conceptual knowledge of circuit analysis. Correlation analysis was used to identify relationships among students' personal and academic characteristics and self-efficacy for circuit analysis, as well as to investigate the relationship between self-efficacy for circuit analysis and conceptual knowledge of circuit analysis. Subject's father's education level was found to be inversely correlated with self-efficacy for circuit analysis, and subject's age was found to be directly correlated with self-efficacy for circuit analysis. Finally, self-efficacy for circuit analysis was found to be positively correlated with conceptual knowledge of circuit analysis. / Dissertation/Thesis / Ph.D. Curriculum and Instruction 2014