No description available.

published_or_final_version / abstract / Economics and Finance / Doctoral / Doctor of Philosophy

This thesis is concerned with the developments of analysis, modelling and optimization techniques and computer program algorithms, with the ultimate aim of control of water supply and distribution systems to lead to overall optimal operation. Typical system features and operational conditions are analyzed, and the requirements for the overall objective are examined, to determine an overall control strategy which is subsequently developed and tested on real systems throughout this thesis. As a prerequisite, short-term water demand forecasting is extensively studied by employing time series analysis. Special consideration is given to improving the forecasting accuracy of the method and its on-line implementation. In order to speed up the solution time of optimal system operation, simplified system models -- namely, piecewise macroscopic model and equivalent network model -- are developed respectively. Then by employing the piecewise macroscopic model, a nonlinear programming method is developed to cater for the optimal operation of a class of multi-source systems without significant storage. The optimal operation policy obtained by this method is realized at two levels: the first level calculates the optimized apportioning of water to be delivered by different sources; the second level decides the least cost pump schedules to supply the optimized apportioning of water. Based on the equivalent network model, a linear programming method is developed for optimization of a class of multi-source, multi-reservoir systems with a mixture of fixed speed pumps and variable speed and/or variable throttle pumps. This method yields directly optimized pump schedules and reservoir trajectories in terms of least cost system operation. The integration of the developments results in a scheme which can be applied to give overall dynamic control of a wide range of water supply and distribution systems. The application results presented in this thesis justify the theoretical developments and show that benefits can be obtained from these developments.

Counting data without zero category often occur in various _elds. Examples include days of hospital stay for patients, numbers of publication for tenure-tracked faculty in a university, numbers of tra_c violation for drivers during a certain period and so on. A class of zero-truncated discrete models such as zero-truncated Poisson, zero-truncated binomial and zero-truncated negative-binomial distributions are proposed in literature to model such count data. In this thesis, firstly, literature review is presented in Chapter 1 on a class of commonly used univariate zero-truncated discrete distributions. In Chapter 2, a unified method is proposed to derive the distribution of the sum of i.i.d. zero-truncated distribution random variables, which has important applications in the construction of the shortest Clopper-Person confidence intervals of parameters of interest and in the calculation of the exact p-value of a two-sided test for small sample sizes in one sample problem. These problems are discussed in Section 2.4. Then a novel expectation-maximization (EM) algorithm is developed for calculating the maximum likelihood estimates (MLEs) of parameters in general zero-truncated discrete distributions. An important feature of the proposed EM algorithm is that the latent variables and the observed variables are independent, which is unusual in general EM-type algorithms. In addition, a unified minorization-maximization (MM) algorithm for obtaining the MLEs of parameters in a class of zero-truncated discrete distributions is provided. The first objective of Chapter 3 is to propose the multivariate zero-truncated Charlier series (ZTCS) distribution by developing its important distributional properties, and providing efficient MLE methods via a novel data augmentation in the framework of the EM algorithm. Since the joint marginal distribution of any r-dimensional sub-vector of the multivariate ZTCS random vector of dimension m is an r-dimensional zero-deated Charlier series (ZDCS) distribution (1 6 r < m), it is the second objective of Chapter 3 to propose a new family of multivariate zero-adjusted Charlier series (ZACS) distributions (including the multivariate ZDCS distribution as a special member) with a more flexible correlation structure by accounting for both inflation and deflation at zero. The corresponding distributional properties are explored and the associated MLE method via EM algorithm is provided for analyzing correlated count data. / published_or_final_version / Statistics and Actuarial Science / Master / Master of Philosophy

No description available.

No description available.

No description available.

No description available.

No description available.

For many decades gas turbine engineers have investigated methods to improve engine efficiency further. These methods include advances in the composition and processing of materials, intricate cooling techniques, and the use of protective coatings. Thermal barrier coatings (TBCs) are the most promising development in superalloy coatings research in recent years with the potential to reduce metal surface temperature, or increase turbine entry temperature, by 70-200°C. In order for TBCs to be exploited to their full potential, they need to be applied to the most demanding of stationary and rotating components, such as first stage blades and vanes. Comprehensive reviews of coating processes indicate that this can only be achieved on rotating components by depositing a strain-tolerant layer applied by the electron beam-physical vapour deposition (EB-PVD) coating process. A computer program has been developed in Visual c++ based on the Knudsen cosine law and aimed at calculating the coating thickness distribution around any component, but typically turbine blades. This should permit the controlled deposition to tailor the TBC performance and durability. Various evaporation characteristics have been accommodated by developing a generalised point source evaporation model that involves real and virtual sources. Substrates with complex geometry can be modelled by generating an STL file from a CAD package with the geometric information of the component, which may include shadow-masks. Visualisation of the coated thickness distributions around components was achieved using OpenGL library functions within the computer model. This study then proceeded to verify the computer model by first measuring the coating thickness for experimental trial runs and then comparing the calculated coating thickness to that measured using a laboratory coater. Predicted thickness distributions are in good agreement even for the simplified evaporation model, but can be improved further by increasing the complexity of the source model.