University of Macau / Faculty of Science and Technology / Department of Civil and Environmental Engineering

A numerical study of fundamental aspects of turbulent mixing has been performed,with emphasis on the behavior of passive scalars of low molecular diffusivity (high Schmidt number Sc). Direct Numerical Simulation is used to simulate incompressible, stationary and isotropic turbulence carried out at high grid resolution. Data analyses are carried out by separate parallel codes using up to 1024^3 grid points for Taylor-scale Reynolds number (R_lambda) up to 390 and Sc up to 1024.Schmidt number of order 1000 is simulated using a double-precision parallel code in a turbulent flow at a low Reynolds number of R_lambda 8 to reduce computational cost to achievable level. The results on the scalar spectrum at high Schmidt numbers appear to have a k^{-1} scaling range. In the presence of a uniform mean scalar gradient, statistics of scalar gradients are observed to deviate substantially from Kolmogorov's hypothesis of local isotropy, with a skewness factor remaining at order unity as the Reynolds number increases. However, this skewness decreases with Schmidt number suggesting that local isotropy for scalars at high Schmidt number is a better approximation. Intermittency exponents manifested by three types of two-point statistics of energy and scalar dissipation, i.e., the two-point correlator (chi(x)chi(x+r)), the second-order moment of local scalar dissipation (chi_r^2) and the variance of the logarithmic local scalar dissipation sigma^2_{lnchi_r} are discussed. Several basic issues in differential diffusion between two scalars of different molecular diffusivities transported by the same turbule nt flow, the physical process of scalar spectral transfer and subgrid-scale transfer are also briefly addressed.

This dissertation presents several methods for improving statistical and first principles modeling capabilities, with an emphasis on nonlinear, unsteady state batch processes. Batch process online monitoring is chosen as a main research area here due to its importance from both theoretical and practical points of view. Theoretical background and recent developments of PCA/PLS-based online monitoring methodologies are reviewed, along with fault detection metrics, and algorithm variations for different applications. The available commercial softwares are also evaluated based on the corresponding application area. A detailed Multiway PCA based batch online monitoring procedure is used as the starting point for further improvements. The issue of dynamic batch profile synchronization is addressed. By converting synchronization into a dynamic optimization problem, Dynamic Time Warping (DTW) and Derivative DTW (DDTW) show the best performance by far. To deal with the singularity point and numerical derivative estimation problems of DTW and DDTW in the presence of noise, a robust DDTW algorithm is proposed by combining Savitzky-Golay filter and DDTW algorithm together. A comparative analysis of robust DDTW and available methods is performed on simulated and real chemical plant data. As traditional Multiway PCA-based (MPCA) methods consider batch monitoring in a static fashion (fail to consider time dependency between/within process variables with respect to time), an EWMA filtered Hybrid-wise unfolding MPCA (E-HMPCA) is proposed that considers batch dynamics in the model and reduce the number of Type I and II errors in online monitoring. Chemical and biochemical batch examples are used to compare the E-HMPCA algorithm with traditional methods. First principles modeling is known to be time consuming for development. In order to increase modeling efficiency, dynamic Design of Experiments (DOE) is introduced for Dynamic Algebraic Equation (DAE) system parameter estimation. A new criterion is proposed by combining PCA and parameter sensitivity analysis (P-optimal criterion). The new criterion under certain assumptions reduce to several available criteria and is suitable for designing experiments to improve estimation of specific parameter sets. Furthermore, the criterion systematically decomposes a complex system into small pieces according to PCA. Two engineering examples (one batch, one continuous) are used to illustrate the idea and algorithm. / text

Global spread of infectious disease threatens the well-being of human, domestic, and wildlife health. A proper understanding of global distribution of these diseases is an important part of disease management and policy making. However, data are subject to complexities by heterogeneity across host classes and space-time epidemic processes [Waller et al., 1997, Hosseini et al., 2006]. The use of frequentist methods in Biostatistics and epidemiology are common and are therefore extensively utilized in answering varied research questions. In this thesis, we proposed the Hierarchical Bayesian approach to study the spatial and the spatio-temporal pattern of tuberculosis in Kenya [Knorr-Held et al., 1998, Knorr-Held, 1999, L opez-Qu lez and Munoz, 2009, Waller et al., 1997, Julian Besag, 1991]. Space and time interaction of risk (ψ[ij]) is an important factor considered in this thesis. The Markov Chain Monte Carlo (MCMC) method via WinBUGS and R packages were used for simulations [Ntzoufras, 2011, Congdon, 2010, David et al., 1995, Gimenez et al., 2009, Brian, 2003], and the Deviance Information Criterion (DIC), proposed by [Spiegelhalter et al., 2002], used for models comparison and selection. Variation in TB risk is observed among Kenya counties and clustering among counties with high TB relative risk (RR). HIV prevalence is identified as the dominant determinant of TB. We found clustering and heterogeneity of risk among high rate counties and the overall TB risk is slightly decreasing from 2002-2009. Interaction of TB relative risk in space and time is found to be increasing among rural counties that share boundaries with urban counties with high TB risk. This is as a result of the ability of models to borrow strength from neighbouring counties, such that near by counties have similar risk. Although the approaches are less than ideal, we hope that our formulations provide a useful stepping stone in the development of spatial and spatio-temporal methodology for the statistical analysis of risk from TB in Kenya. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2013.

To investigate the effect of environmental pollution on the health of children in the Durban South Industrial Basin (DSIB) due to its proximity to industrial activities, 233 children from five primary schools were considered. Three of these schools were located in the south of Durban while the other two were in the northern residential areas that were closer to industrial activities. Data collected included the participants' demographic, health, occupational, social and economic characteristics. In addition, environmental information was monitored throughout the study specifically, measurements on the levels of some ambient air pollutants. The objective of this thesis is to investigate which of these factors had an effect on the lung function of the children. In order to achieve this objective, different sample survey data analysis techniques are investigated. This includes the design-based and model-based approaches. The nature of the survey data finally leads to the longitudinal mixed model approach. The multicolinearity between the pollutant variables leads to the fitting of two separate models: one with the peak counts as the independent pollutant measures and the other with the 8-hour maximum moving average as the independent pollutant variables. In the selection of the fixed-effects structure, a scatter-plot smoother known as the loess fit is applied to the response variable individual profile plots. The random effects and the residual effect are assumed to have different covariance structures. The unstructured (UN) covariance structure is used for the random effects, while using the Akaike information criterion (AIC), the compound symmetric (CS) covariance structure is selected to be appropriate for the residual effects. To check the model fit, the profiles of the fitted and observed values of the dependent variables are compared graphically. The data is also characterized by the problem of intermittent missingness. The type of missingness is investigated by applying a modified logistic regression model missing at random (MAR) test. The results indicate that school location, sex and weight are the significant factors for the children's respiratory conditions. More specifically, the children in schools located in the northern residential areas are found to have poor respiratory conditions as compared to those in the Durban-South schools. In addition, poor respiratory conditions are also identified for overweight children. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2006.

Šiame darbe pateikta nuosekli statistinės analizės metodika tyrimo rezultatams apdoroti ir nagrinėjamos kriterijų taikymo galimybės. Pasiūlyti kriterijai ryškiai išsiskiriantiems duomenims atmesti, nurodyti kriterijai tyrimo rezultatų atsitiktinumui ir nepriklausomumui bei pasiskirstymo pagal normalųjį dėsnį hipotezėms tikrinti, atlikta tyrimo rezultatų koreliacinė ir regresinė analizė ir pasirinkto regresinio modelio adekvatumo tikrinimas panaudojus Fišerio kriterijų. / The paper provided a consistent statistical analysis techniques to process the results of the study and analyze the possibility of application of the criteria. Propose criteria for emissions during the data significantly rejected by the criteria set out in the survey results to chance and the independence of the distribution under the normal law of hypotheses to verify the results of research carried out correlation and regression analysis and the selected regression model for testing the adequacy of using the Fisher criterion.

Eskom is the major electricity supplier in South Africa and medium term forecasting within the company is a critical activity to ensure that enough electricity is generated to support the country's growth, that the networks can supply the electricity and that the revenue derived from electricity consumption is managed efficiently. This study investigates the most suitable forecasting technique for predicting monthly electricity consumption, one year ahead for four major municipalities within Kwa-Zulu Natal. / Thesis (M.Sc.)-University of Natal, Pietermaritzburg, 1997.

By knowing the incidence of an infectious disease, we can ascertain the high risk factors of the disease as well as the e ectiveness of awareness programmes and treatment strategies. Since the work of Hugo Muench in 1934, many methods of estimating the force of infection have been developed, each with their own advantages and disadvantages. The objective of this thesis is to explore the di erent compartmental models of infectious diseases and establish and interpret the parameters associated with them. Seven models formulated to estimate the force of infection were discussed and applied to data obtained from CAPRISA. The data was agespeci c HIV prevalence data based on antenatal clinic attendees from the Vulindlela district in KwaZulu-Natal. The link between the survivor function, the prevalence and the force of infection was demonstrated and generalized linear model methodology was used i to estimate the force of infection. Parametric and nonparametric force of infection models were used to t the models to data from 2009 to 2010. The best tting model was determined and thereafter applied to data from 2002 to 2010. The occurring trends of HIV incidence and prevalence were then evaluated. It should be noted that the sample size for the year 2002 was considerably smaller than that of the following years. This resulted in slightly inaccurate estimates for the year 2002. Despite the general increase in HIV prevalence (from 54.07% in 2003 to 61.33% in 2010), the rate of new HIV infections was found to be decreasing. The results also showed that the age at which the force of infection peaked for each year increased from 16.5 years in 2003 to 18 years in 2010. Farrington's two parameter model for estimating the force of HIV infection was shown to be the most useful. The results obtained emphasised the importance of HIV awareness campaigns being targeted at the 15 to 19 year old age group. The results also suggest that using only prevalence as a measure of disease can be misleading and should rather be used in conjunction with incidence estimates to determine the success of intervention and control strategies. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2013.

Bibliography: leaves 250-264 / xx. 264, [47] leaves : ill ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--University of Adelaide, Waite Agricultural Research Institute, 1984

Diss. (sammanfattning) Uppsala : Sveriges lantbruksuniv., 2007. / Härtill 4 uppsatser.