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The key objective of this research is to develop a generic simulation modelling methodology that can be used to model stochastic continuous systems effectively. The generic methodology renders simulation models that exhibit the following characteristics: short development and maintenance times, user-friendliness, short simulation runtimes, compact size, robustness, accuracy and a single software application. The research was initiated by the shortcomings of a simulation modelling method that is detailed in a Magister dissertation. A system description of a continuous process plant (referred to as the Synthetic Fuel plant) is developed. The decision support role of simulation modelling is considered and the shortcomings of the original method are analysed. The key objective, importance and limitations of the research are also discussed. The characteristics of stochastic continuous systems are identified and a generic methodology that accommodates these characteristics is conceptualised and developed. It consists of the following eight methods and techniques: the variables technique, the iteration time interval evaluation method, the event-driven evaluation method, the Entity-represent-module method, the Fraction-comparison method, the iterative-loop technique, the time “bottleneck” identification technique and the production lost “bottleneck” identification technique. Five high-level simulation model building blocks are developed. The generic methodology is demonstrated and validated by the development and use of two simulation models. The five high-level building blocks are used to construct identical simulation models of the Synthetic Fuel plant in two different simulation software packages, namely: Arena and Simul8. An iteration time interval and minimum sufficient sample sizes are determined and the simulation models are verified, validated, enhanced and compared. The simulation models are used to evaluate two alternative scenarios. The results of the scenarios are compared and conclusions are presented. The factors that motivated the research, the process that was followed and the generic methodology are summarised. The original method and the generic methodology are compared and the strengths and weaknesses of the generic methodology are discussed. The contribution to knowledge is explained and future developments are proposed. The possible range of application and different usage perspectives are presented. To conclude, the lessons learnt and reinforced are considered. / Thesis (PhD (Industrial Engineering))--University of Pretoria, 2004. / Industrial and Systems Engineering / unrestricted

Classical Continuous System Simulation (CSS) is restricted to modelling continuous flows, and therefore, cannot correctly realise a conceptual model with discrete objects. The development of Full Potential CSS solves this problem by (1) handling discrete quantities as discrete and continuous matter as continuous, (2) preserving the sojourn time distribution of a stage, (3) implementing attributes correctly, and (4) describing different types of uncertainties in a proper way. In order to apply Full Potential CSS a new software, StochSD, has been developed. This thesis evaluates StochSD's ability to model Full Potential CSS, where the points 1-4 above are included. As a test model a well-defined conceptual epidemic model, which includes all aspects of Full Potential CSS, was chosen. The study was performed by starting with a classical SIR model and then stepwise add the different aspects of the Conceptual Model. The effects of each step were demonstrated in terms of size and duration of the epidemic. Finally, the conceptual model was also realised as an Agent Based Model (ABM). The results from 10 000 replications each of the CSS and ABM models were compared and no statistical differences could be confirmed. The conclusion is that StochSD passed the evaluation.

Made available in DSpace on 2016-08-17T14:53:17Z (GMT). No. of bitstreams: 1 Freud Sebastian Bach Carvalho Lima.pdf: 1668786 bytes, checksum: 953b0905b2e9bcd1cefb5702b8c6b362 (MD5) Previous issue date: 2011-07-29 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / In activated sludge systems, the dissolved oxygen is used by microorganisms to decompose organic matter and treatment of wastewater. In these systems the dynamics of dissolved oxygen has been seen as the main source of information to obtain online information about the treatment process. Thus, the development of an appropriate model for the dynamics of dissolved oxygen and estimation of the parameters of this model can improve the quality of the estimates of process parameters and, consequently, the measurement system. In this study, a model of the bench-scale reactor is developed considering the dynamics associated with the operation of the aeration system and the dissolved oxygen sensor. The aeration system consists of air pumps with two operating states: on or off, and dissolved oxygen measurement is made by electrochemical cell based on Clark. Approach was used identification systems in continuous time and state variable filters with the least squares estimator for estimating the parameters of the model developed. Simulations and experimental results, using a bench scale reactor developed in the laboratory, are presented to illustrate the proposed model. / Em sistemas de lodo ativado, o oxigênio dissolvido é utilizado por microorganismos para decomposição de matéria orgânica e tratamento de água residuárias. Nestes sistemas, a dinâmica de oxigênio dissolvido tem sido vista como a principal fonte de informação para obtenção de informações online sobre o processo de tratamento. Com isso, o desenvolvimento de um modelo apropriado para dinâmica do oxigênio dissolvido e a estimação dos parâmetros deste modelo, pode melhorar a qualidade das estimativas dos parâmetros do processo e, consequentemente, do sistema de medição. No presente trabalho, um modelo do reator em escala de bancada é desenvolvido considerando as dinâmicas relacionadas com a operação do sistema de aeração e com o sensor de oxigênio dissolvido. O sistema de aeração é composto por bombas de ar com dois estados de operação: ligada ou desligada, e a medição de oxigênio dissolvido é realizada por sensor eletroquímico baseado em célula de Clark. Usa-se abordagem de identificação de sistemas em tempo contínuo e filtros de variável de estado junto com o estimador dos mínimos quadrados para estimação dos parâmetros do modelo desenvolvido. Simulações e resultados experimentais, utilizando um reator em escala de bancada desenvolvido no laboratório, são apresentados para ilustrar o modelo proposto.