The process of automated cartographic generalization is critically reviewed, and methods developed for implementation and analysis are discussed. The manner in which automated generalization relates to manual cartographic methods and feature representation is analyzed. It is suggested that the nature of representation of linear features on maps be considered in the analysis of effectiveness of automated generalization. The development of a computer platform for evaluating linear generalization algorithms is described and three studies which make use of the platform are discussed. An analysis of the performance of five simplification algorithms is compared to performance of a random simplification algorithm. It was found that in most cases tested, the five simplification algorithms performed better than random. An analysis of the stability of fractal dimension estimated on simplified lines was conducted and it is suggested that the fractal dimension is a poor guide for linear simplification due the instability in measurement. An examination of the effect of generalization on linear features as represented by contoured topography and paired stream bank lines was performed. Through the use of measurements of slope on contour lines and width on stream lines, it was determined that automated generalization has an effect on linear feature representations. Guidelines for application of linear generalization algorithms are suggested and needs and direction for future research are discussed. / Master of Science

The primary purpose of this thesis is to present, in clear and logical form, an analysis of high-frequency modulation. This will be done in order to explain each of the various methods of obtaining modulation, and the characteristics of the resultant waves. The question of side bands will be considered in detail. The subject of circuits and associated apparatus is of secondary importance, emphasis being placed on the fundamental electric theory. From this point of view, possibilities for improvement and new developments will be investigated. / Master of Science

This thesis contains a brief review of some of the work that has been done concerning the generation and testing of pseudo-random numbers. Computer subroutine programs written in FORTRAN IV are given for the generation of pseudo-random numbers from Pearson distributions as well as from any combination of mixtures of two Pearson distributions, a normal distribution with arbitrary mean and variance and a uniform distribution on any finite interval. The Pearson distribution may be specified either by the first four moments or from sample data, then the parameters of the fitted distribution are printed and, if desired, a graph of the distribution. A graph of the mixture of distributions may be obtained from 10,000 pseudo-random numbers from the mixture. The speed of generation varies from about 10,000 random numbers per minute (on the IBM 7040), for a Pearson distribution with moments calculated from the generated numbers, to more than 100,000 numbers per minute if mixtures are used. The subroutines are applied to a Monte Carlo investigation of the robustness of several methods of confidence interval estimation. / M.S.

The unsteady interaction of a vortex core with a NACA 0015 airfoil is studied in two dimensions. A two-component, three-beam Helium-Neon laser-Doppler Velocimetry system is used to take data in a water tunnel. Ensemble-averaged velocity fields are obtained in the region of the leading edge of the airfoil. Finite-difference algorithms were written to obtain vorticity and pressure in the data field. Computer animation of the unsteady vorticity was accomplished first with a Fortran code written for an Apple Macintosh computer and later with a commercial software package for a SUN Microsystems graphics terminal. / Master of Science

Yes / New Artificial Intelligence (AI) approaches such as simulated annealing, genetic algorithms, simulated evolution, neural networks, tabu search, fuzzy logic and their hybrid techniques have been applied in recent years to solving Generator Maintenance Scheduling (GMS) problems. This paper presents a review of these AI approaches for the GMS problem. The formulation of problems and the methodologies of solution are discussed and analysed. A case study is also included which presents the application of a genetic algorithm to a test system based on a practical power system scenario.

Maintenance of power plants is aimed at extending the life and reducing the risk of sudden breakdown of power generating units. Traditionally, power generating units have been scheduled for maintenance in periods to ensure that the demand of the system is fully met and the reliability of the system is maximized. However, in a deregulated power industry, the pressure of maintaining generating units is also driven by the potential revenue received by participating in the electricity market. Ideally, hydropower generating units are required to operate during periods when electricity prices are high and to be able to be taken offline for maintenance when the price is low. Therefore, determination of the optimum time periods for maintenance of generating units in a power system has become an important task from both a system reliability and an economic point of view. Due to the extremely large number of potential maintenance schedules, a systematic approach is required to ensure that optimal or near-optimal maintenance schedules are obtained within an acceptable timeframe. Metaheustics are high-level algorithmic frameworks that aim to solve combinatorial optimisation problems with a large search space in a reasonable computational run time. Inspired by the foraging behavior of ant colonies, Ant Colony Optimisation (ACO) is a relatively new metaheuristic for combinatorial optimisation. The application of ACO to a number of different applications has provided encouraging results when applied to scheduling, including the job-shop, flow-shop, machine tardiness and resource-constrained project scheduling problems. In this thesis, a formulation is developed that enables ACO to be applied to the generalized power plant maintenance scheduling optimisation (PPMSO) problem. The formulation caters for all constraints generally encountered as part of real-world PPMSO problems, including system demands and reliability levels, precedence rules between maintenance tasks, public holidays and minimum outage durations in the case of shortening of maintenance tasks. As part of the formulation, a new heuristic and a new local search strategy have been developed. The new ACO-PPMSO formulation has been tested extensively on two benchmark PPMSO problems from the literature, including a 21-unit and a 22-unit problem. It was found that the ACOPPMSO formulation resulted in significant improvements in performance for both case studies compared with the results obtained in previous studies. In addition, the new heuristic formulation was found to be useful in finding maintenance schedules that result in more evenly spread reserve capacity and resource allocations. When tested using a modified version of the 21-unit and the 22-unit problems, the new local search strategy specifically designed for duration shortening was found to be effective in searching locally for maintenance schedules that require minimal shortening of outage duration. The ACO-PPMSO formulation was also successfully able to cater for all constraints as specified in both original and the modified versions of the two benchmark case studies. In order to further test the ACO-PPMSO formulation developed, it was first applied to a scaled-down version of the Hydro Tasmania hydropower system (five power stations) and then to the full system (55 generating units). As part of the studies, the ACO-PPMSO formulation was linked with the simulation model used by Hydro Tasmania to assess the impact of various maintenance schedules on the total energy in storage of the system at the end of the planning horizon, the total thermal generation, the total number of days where the reliability level is not met, as well as the total unserved energy throughout the planning horizon. A number of constraints were considered, including the anticipated system demands, a 30% capacity reliability level, the minimum and maximum durations between related maintenance tasks, the precedence constraints and the minimum outage duration of each task in the case of shortening of maintenance tasks. The maintenance schedule was optimised for the maximum end-of-horizon total energy in storage, the minimum thermal generation and the minimum total outage durations shortened and deferred, under 77 different inflow conditions. The optimal maintenance schedule obtained compared favourably with that obtained by Hydro Tasmania over many years based on experience. Specifically, the ACO-PPMSO schedule results in higher end-of-horizon total energy in storage and satisfies both hard and soft constraints, which overall equates to over $0.5 million dollars of savings when compared to the schedule obtained using the practitioners’ experience and engineering judgment. The ACO-PPMSO algorithm was also shown to be a useful decision-making tool for scheduling maintenance under different circumstances when tested with four scenarios commonly encountered in practical maintenance scheduling problems. In conclusion, the ACO-PPMSO formulation developed, tested and applied as part of this thesis research provides a powerful and flexible means of obtaining optimal or near-optimal maintenance schedules for power plants. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1294672 / Thesis (Ph.D.) -- University of Adelaide, School of Civil and Environmental Engineering, 2007

The human central auditory system can automatically extract abstract regularities from a variant auditory input. To this end, temporarily separated events need to be related. This study tested whether the timing between events, falling either within or outside the temporal window of integration (~350 ms), impacts the extraction of abstract feature relations. We utilized tone pairs for which tones within but not across pairs revealed a constant pitch relation (e.g., pitch of second tone of a pair higher than pitch of first tone, while absolute pitch values varied across pairs). We measured the mismatch negativity (MMN; the brain’s error signal to auditory regularity violations) to second tones that rarely violated the pitch relation (e.g., pitch of second tone lower). A Short condition in which tone duration (90 ms) and stimulus onset asynchrony between the tones of a pair were short (110 ms) was compared to two conditions, where this onset asynchrony was long (510 ms). In the Long Gap condition, the tone durations were identical to Short (90 ms), but the silent interval was prolonged by 400 ms. In Long Tone, the duration of the first tone was prolonged by 400 ms, while the silent interval was comparable to Short (20 ms). Results show a frontocentral MMN of comparable amplitude in all conditions. Thus, abstract pitch relations can be extracted even when the within-pair timing exceeds the integration period. Source analyses indicate MMN generators in the supratemporal cortex. Interestingly, they were located more anterior in Long Gap than in Short and Long Tone. Moreover, frontal generator activity was found for Long Gap and Long Tone. Thus, the way in which the system automatically registers irregular abstract pitch relations depends on the timing of the events to be linked. Pending that the current MMN data mirror established abstract rule representations coding the regular pitch relation, neural processes building these templates vary with timing.

Η διπλωματική εργασία που ακολουθεί, παρουσιάζει τη μελέτη και μοντελοποίηση ενός αυτόνομου υβριδικού συστήματος. Το αυτόνομο σύστημα που εξετάζεται είναι ένα υβριδικό σύστημα ηλεκτροπαραγωγής που αποτελείται από μια γεννήτρια diesel, μια ανεμογεννήτρια και ένα φωτοβολταϊκό σύστημα. Για τη μοντελοποίηση του συστήματος χρησιμοποιείται το πρόγραμμα σχεδίασης και προσομοίωσης ηλεκτρικών συστημάτων PSCAD. Στην εργασία αυτή το ενδιαφέρον επικεντρώνεται στη συμπεριφορά του συστήματος στη μόνιμη κατάσταση λειτουργίας και στη συμπεριφορά σε κάποια μεταβατικά φαινόμενα. Τα μεταβατικά φαινόμενα που εξετάζονται είναι τα εξής: - Συμπεριφορά συστήματος σε απότομη αποσύνδεση ανεμογεννήτριας - Βραχυκύκλωμα των τριών φάσεων ως προς γη στο ζυγό της σύγχρονης γεννήτριας diesel Στο Κεφάλαιο 1 γίνεται μια γενικότερη αναφορά στις ανανεώσιμες πηγές ενέργειας και στη συνέχεια περιγράφονται τα υβριδικά συστήματα ηλεκτροπαραγωγής και οι εφαρμογές τους. Αναλύεται η δομή τους και μελετώνται-συγκρίνονται οι διάφορες αρχιτεκτονικές τους. Στο Κεφάλαιο 2 περιγράφεται η δομή και τα στοιχεία που αποτελούν το αυτόνομο υβριδικό δίκτυο ηλεκτροπαραγωγής και αναπτύσσεται όλο το απαραίτητο μαθηματικό υπόβαθρο που πραγματεύεται η εργασία αυτή. Στο Κεφάλαιο 3 περιγράφεται η δομή και τα στοιχεία που αποτελούν το αυτόνομο υβριδικό δίκτυο ηλεκτροπαραγωγής στο περιβάλλον του προγράμματος μοντελοποίησης, του PSCAD και παρουσιάζονται τα μοντέλα που απαρτίζουν το συνολικό σύστημα. Στο Κεφάλαιο 4 εξετάζεται η συμπεριφορά του συστήματος στη μόνιμη κατάσταση λειτουργίας. Στο Κεφάλαιο 5 εξετάζεται η συμπεριφορά του συστήματος στα δύο μεταβατικά φαινόμενα που έχουν προαναφερθεί, στην απότομη αποσύνδεση ανεμογεννήτριας και στο βραχυκύκλωμα των τριών φάσεων ως προς γη στο ζυγό της σύγχρονης γεννήτριας diesel Στο Κεφάλαιο 6 παρατίθενται οι προδιαγραφές των ποιοτικών χαρακτηριστικών των δικτύων και διατυπώνονται τα συμπεράσματα που προέκυψαν από τη μελέτη του υβριδικού συστήματος που παρουσιάστηκε. / The thesis that follows, presents the study and modelling of autonomous hybrid system. The autonomous system that is examined is a hybrid system of generation of electricity that is constituted by a generator diesel, a wind generator and a photovoltaic system. For the modelling of system is used the program of designing and simulation of electric systems PSCAD. At this project the interest is focused in the behavior of system in the permanent situation of operation and in the behavior in certain transient phenomena. The transient phenomena that are examined are following: - Behavior of system in abrupt detachment of wind generator - Short-circuit of three phases as for ground in the balance of modern generator diesel In Capital 1 becomes a more general report in the renewable sources of energy and afterwards is described the hybrid systems of generation of electricity and their applications. Is analyzed their structure and study-is compared their various architectures. In Capital 2 are described the structure and the elements that constitute the autonomous hybrid network of electric generation and is developed the all essential mathematic background that are necessary for this project. In Capital 3 are described the structure and the elements that constitute the autonomous hybrid system of electric generation in the environment of program of modelling, PSCAD and are presented the models that compose the total system. In Capital 4 is examined the reaction of system in the permanent situation of operation. In Capital 5 is examined the reaction of system in the two transient phenomena that have been mentioned before, in the abrupt detachment of wind generator and in the short-circuit of three phases as for ground in the balance of synchronous generator. In Capital 6 are mentioned the specifications of qualitative characteristics of networks and are formulated the conclusions that resulted from the study of hybrid system that was presented.

Among the renewable energies, wind energy presents the highest growth in installed capacity and penetration in modern power systems. This is why reliability of wind turbines becomes an important topic in research and industry. To this end, condition monitoring (or health monitoring) systems are needed for wind turbines. The core of any condition monitoring system (CMS) are fault diagnosis algorithms whose task is to provide early warnings upon the occurrence of incipient (small magnitude) faults. Thanks to the use of CMS we can avoid premature breakdowns and reduce significatively maintenance costs.<p><p>The present thesis deals with fault diagnosis in sensors of a doubly-fed induction generator (DFIG) for wind turbine (WT) applications. In particular we are interested in performing fault detection and isolation (FDI) of incipient faults affecting the measurements of the three-phase signals (currents and voltages) in a controlled DFIG. Although different authors have dealt with FDI for sensors in induction machines and in DFIGs, most of them rely on the machine model with<p>constant parameters. However, the parameter uncertainties due to changes in the operating conditions will produce degradation in the performance of such FDI systems.<p><p>In this work we propose a systematic methodology for the design of sensor FDI systems with the following characteristics: i) capable of detecting and isolating incipient additive (bias, drifts) and multiplicative (changes in the sensor<p>gain) faults, ii) robust against changes in the references/disturbances affecting the controlled DFIG as well as modelling/parametric uncertainties, iii) residual generation system based on a multi-observer strategy to enhance the isolation process, iv) decision system based on statistical-change detection algorithms to treat the entire residual and perform fault detection and isolation at once.<p><p>Three novel sensor FDI approaches are proposed. The first is a signal-based approach, that uses the model of the balanced three-phase signals (currents or voltages) for residual generation purposes. The second is a model-based approach<p>that accounts for variation in the parameters. Finally, a third approach that combines the benefits of both the signal- and the model-based approaches is proposed. The designed sensor FDI systems have been validated using measured voltages, as well as simulated data from a controlled DFIG and a speed-controlled induction<p>motor. <p><p>In addition, in this work we propose a discrete-time multiple input multiple output (MIMO) regulator for each power converter, namely for the rotor side converter (RSC) and for the grid side converter (GSC). In particular, for RSC<p>control, we propose a modified feedback linearization technique to obtain a linear time invariant (LTI) model dynamics for the compensated DFIG. The novelty of this approach is that the compensation does not depend on highly uncertain parameters such as the rotor resistance. For GSC control, a LTI model dynamics<p>is derived using the ideas behind feedback linearization. The obtained LTI model dynamics are used to design Linear Quadratic Gaussian (LQG) regulators. A single design is needed for all the possible operating conditions. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished

This paper defines generalized binomial coefficients and shows that they can be used to generate generalized Pascal's Triangles and have properties analogous to binomial coefficients. It uses the generalized binomial coefficients to compute the Dilworth number and the Sperner number of certain rings.