Yes / Desalination has become one of the obvious solutions for the global water crisis due to affording high-quality water from seawater and brackish water resources. As a result, there are continuing efforts being made to improve desalination technologies, especially the one producing high-quantity freshwater, i.e., thermal desalination. This improvement must be accomplished via enhancement of process design through optimization which is implicitly dependent on providing a generic process model. Due to the scarcity of a comprehensive review paper for modeling multi-effect distillation (MED) process, this topic is becoming more important. Therefore, this paper intends to capture the evolution of modeling the forward feed MED (most common type) and shed a light on its branches of steady-state and dynamic modeling. The maturity of the models developed for MED will be thoroughly reviewed to clarify the general efforts made highlighting the advantages and disadvantages. Depending on the outputs of this review, the requirements of process development and emerging challengeable matters of modeling will be specified. This, in turn, would afford a possible improvement strategy to gain a reliable and sustainable thermal desalination process.

Yes / Natural draft cooling towers are subjected to dynamic air temperature and humidity ratio of air throughout the day. Their performances based on steady state model is restricted to single air temperature and humidity ratio of air values and thus are not accurate. In this work, a dynamic model for a natural draft cooling tower is developed. Air temperature and relative humidity data for Johannesburg were acquired to develop dynamic correlations for these two parameters and are embedded in the process model together with the dynamic model of the collection basin of the tower. A simple algorithm is proposed to solve the resulting boundary value problem. Finally, the common perception that seawater/river water should be used instead of freshwater as cooling medium is tested via optimisation where the operating costs of the process for two cooling mediums is minimised. The freshwater has been found to be cost effective cooling medium.

Este trabalho de pesquisa objetivou a obtenção de uma nova política de operação que melhor caracterizasse o comportamento ótimo dos sistemas hidrelétricos de potência, mesmo diante das mais variadas condições hidrológicas. Este trabalho teve duas linhas de investigação. Uma tratou do problema de previsão de vazões afluentes mensais, na busca por abordagens e técnicas que definissem bons modelos de previsão. A outra linha de pesquisa tratou de encontrar uma nova política de operação, para o problema de planejamento da operação, que fosse capaz de definir uma seqüência de decisões operativas mais estáveis, confiáveis e de menor custo operativo. Na primeira linha de pesquisa, investigou-se três aspectos importantes na definição de um modelo de previsão: técnicas de pré-processamento dos dados, definição automática do espaço de entrada e avaliação do desempenho de alguns modelos de redes neurais e sistemas Fuzzy como modelos de previsão. Nestes aspectos foram investigadas a utilização da análise dos componentes principais e o tratamento da série temporal de vazões afluentes como um sinal discreto, utilizando-se a representação \"analytic signal\". Para a definição do espaço de entrada de maneira automática utilizou-se a abordagem da \"dynamic modelling\", empregando-se a \"average mutual information\" e \"false nearest neighbors\". Para implementação dos modelos de previsão foram estudados e avaliados quatro modelos inteligentes: rede SONARX, rede SONARX-RBF, modelo ANFIS e a rede ESN. Já na outra linha de pesquisa, foi proposta uma política de operação que fosse capaz de estabilizar os despachos de geração termelétrica e conseqüentemente o custo marginal de operação. A política de operação preditiva estabilizada via termo inercial produziu excelentes resultados operativos, melhorando de forma significativa a performance da política preditiva. / This research work aimed at obtaining a new operation policy which could better describe the optimal behavior of hydropower systems, even when faced with the most varied hydrological conditions. This research had two lines of investigation. The first one dealt with the monthly water inflow forecasting problem, searching for approaches and techniques which could define efficient forecasting models. Three important aspects to define a forecasting model were investigated: data pre-processing techniques, automatic definition of the embedding and the performance assessment of some artificial neural networks and Fuzzy systems. Hence, the use of the principal components analysis was investigated and, considering the water inflow time series as a discrete signal, the analytic signal representation could be used to preprocess the data. Furthermore, the embedding was automatically defined using the dynamic modelling approach, by using the average mutual information and the false nearest neighbors techniques. The forecasting models were implemented by four intelligent models: SONARX network, SONARX-RBF network, ANFIS model and the ESN network. The other line of investigation came up with a new operation policy to solve the operation planning problem, defining a more stable, reliable and less costly operative decision sequence. It was proposed an approach to stabilize the thermoelectric generation dispatches and, as a result, the operative marginal cost. The predictive operation policy stabilized via inertial term produced excellent operation results, improving the performance of the predictive policy.

Este trabalho de pesquisa objetivou a obtenção de uma nova política de operação que melhor caracterizasse o comportamento ótimo dos sistemas hidrelétricos de potência, mesmo diante das mais variadas condições hidrológicas. Este trabalho teve duas linhas de investigação. Uma tratou do problema de previsão de vazões afluentes mensais, na busca por abordagens e técnicas que definissem bons modelos de previsão. A outra linha de pesquisa tratou de encontrar uma nova política de operação, para o problema de planejamento da operação, que fosse capaz de definir uma seqüência de decisões operativas mais estáveis, confiáveis e de menor custo operativo. Na primeira linha de pesquisa, investigou-se três aspectos importantes na definição de um modelo de previsão: técnicas de pré-processamento dos dados, definição automática do espaço de entrada e avaliação do desempenho de alguns modelos de redes neurais e sistemas Fuzzy como modelos de previsão. Nestes aspectos foram investigadas a utilização da análise dos componentes principais e o tratamento da série temporal de vazões afluentes como um sinal discreto, utilizando-se a representação \"analytic signal\". Para a definição do espaço de entrada de maneira automática utilizou-se a abordagem da \"dynamic modelling\", empregando-se a \"average mutual information\" e \"false nearest neighbors\". Para implementação dos modelos de previsão foram estudados e avaliados quatro modelos inteligentes: rede SONARX, rede SONARX-RBF, modelo ANFIS e a rede ESN. Já na outra linha de pesquisa, foi proposta uma política de operação que fosse capaz de estabilizar os despachos de geração termelétrica e conseqüentemente o custo marginal de operação. A política de operação preditiva estabilizada via termo inercial produziu excelentes resultados operativos, melhorando de forma significativa a performance da política preditiva. / This research work aimed at obtaining a new operation policy which could better describe the optimal behavior of hydropower systems, even when faced with the most varied hydrological conditions. This research had two lines of investigation. The first one dealt with the monthly water inflow forecasting problem, searching for approaches and techniques which could define efficient forecasting models. Three important aspects to define a forecasting model were investigated: data pre-processing techniques, automatic definition of the embedding and the performance assessment of some artificial neural networks and Fuzzy systems. Hence, the use of the principal components analysis was investigated and, considering the water inflow time series as a discrete signal, the analytic signal representation could be used to preprocess the data. Furthermore, the embedding was automatically defined using the dynamic modelling approach, by using the average mutual information and the false nearest neighbors techniques. The forecasting models were implemented by four intelligent models: SONARX network, SONARX-RBF network, ANFIS model and the ESN network. The other line of investigation came up with a new operation policy to solve the operation planning problem, defining a more stable, reliable and less costly operative decision sequence. It was proposed an approach to stabilize the thermoelectric generation dispatches and, as a result, the operative marginal cost. The predictive operation policy stabilized via inertial term produced excellent operation results, improving the performance of the predictive policy.

L’eau est une ressource qui va manquer dans les prochaines années, pourtant l’eau couvre ¾ de la planète et environ 97% de l’eau sur Terre est de l’eau salée. Du fait de sa nette abondance, dessaler l’eau de mer, ou les eaux saumâtres, est une solution présentant un immense attrait. C’est dans ce contexte global que s’inscrivent ces travaux. Le but de cette thèse est de modéliser des installations de dessalement d’eau de mer, basées sur la distillation multiple-effets (MED), soumises à des régimes transitoires. Ce procédé permet d’assurer à la fois une grande flexibilité aux variations de charge et des performances énergétiques élevées. Dans le cadre de cette étude, un couplage d’une usine MED avec une source d’énergie renouvelable, donc intermittente, est envisagé. Pour étudier le potentiel et la faisabilité d’un tel couplage, un modèle dynamique représentatif des installations MED est présenté. Ce modèle permet le suivi et l’étude de toutes les variables agissant sur les performances globales de l’installation ainsi que l’identification des variables critiques pouvant nuire au fonctionnement de ces installations en régime transitoire. Ce modèle a ensuite été couplé à un modèle d’une centrale solaire à concentration afin de conclure sur le potentiel d’une telle association. Pour pouvoir assurer un fonctionnement optimal de l’installation MED en régime transitoire, une stratégie de régulation est présentée et intégrée / Demand for water will continue to increase over the next decades, leading to more stress on limited resources and ecosystems. However, ¾ of the Earth is water and 97% of it is seawater. Therefore, it is highly interesting to desalinate seawater. It is within this framework that this work was carried out. The goal of this PhD was to model desalination plants, based on the Multiple-Effect Distillation (MED) process, when they are operated under dynamic conditions. The MED plants are mature desalination processes with high energetic performances and are very flexible to load variations. For this study, a coupling between a MED plant and a renewable energy source, therefore transient, was assumed. To study the potential and the feasibility of such an association, a dynamic model representative of the MED plants was developed. With this, it is now possible to study the evolution of all the variables that have a consequence on the plant’s performances as well as to identify which variables are the most critical to the dynamic operation of the MED plant. This model was then combined with a concentrated solar power plant to conclude about the potential of this coupling. To assure an optimal operation of the MED plant under dynamic conditions, a regulation strategy was developed and implemented

Many potentially useful applications that broadly fall under the umbrella of payload transportation operations have been proposed for aerial towed-cable (ATC) systems, namely the precise capture and delivery of payloads. There remain outstanding issues concerning the dynamics and control of ATC systems that are inhibiting the near-term demonstration of these applications. The development of simplified representations of ATC systems that retain the important dynamics, yet are simple enough for use in control system development is limited. Likewise, little research exists into the development of controllers for ATC systems, especially the development of towing strategies and cable-based control techniques for rendezvous and payload transportation. Thus, this thesis presents novel research into the development of control strategies and simulation facilities that redress these two major anomalies, thereby overcoming a number of hitherto unresolved issues. The primary objective of this thesis is to develop innovative non-linear optimal control systems to manoeuvre a cable towed beneath an aircraft to transport payloads both to and from surface locations. To appropriately satisfy this objective, accurate and efficient modelling capabilities are proposed, yielding the equations of motion for numerous models of the ATC system. A series of techniques for improving the representativeness of simple dynamical models were developed. The benefits of using these procedures were shown to be significant and possible without undue complexity or computational expense. Use of such techniques result in accurate simulations and allow representative control systems to be designed. A series of single and multi-phase non-linear optimal control problems for ATC systems are then formally proposed, which were converted into non-linear programming problems using direct transcription for expedient solution. The possibility of achieving accurate, numerous instantaneous rendezvous of the cable tip with desired surface locations on the ground, in two and three-dimensions, is successfully demonstrated. This was achieved through the use of deployment and retrieval control of the cable and/or aircraft manoeuvring. The capability of the system to safely and accurately transport payloads to and from the surface via control of the cable and/or aircraft manoeuvring is also established. A series of parametric studies were conducted to establish the impact that various parameters have on the ability of the system to perform various rendezvous and payload transportation operations. This allowed important insights into to the nature of the system to be examined. In order for the system to perform rendezvous and payload transportation operations in the presence of wind gusts, a number of simple closed loop optimal feedback controllers were developed. These feedback controllers are based on the linear quadratic regulator control methodology. A preliminary indication of the robustness of ATC systems to wind gusts is provided for through a succession of parametric investigations. The performance of the closed-loop system demonstrates that precise and robust control of the ATC system can be achieved for a wide variety of operating conditions. The research presented in this thesis will provide a solid foundation for further advancing the development of aerial tether payload transportation technology.

Co-rotating twin-screw extruders are unique and versatile machines that are used widely in the plastics and food processing industries. Due to the large number of operating variables and design parameters available for manipulation and the complex interactions between them, it cannot be claimed that these extruders are currently being optimally utilised. The most significant improvement to the field of twin-screw extrusion would be through the provision of a generally applicable dynamic process model that is both computationally inexpensive and accurate. This would enable product design, process optimisation and process controller design to be performed cheaply and more thoroughly on a computer than can currently be achieved through experimental trials. This thesis is divided into three parts: dynamic modelling, measurement and control. The first part outlines the development of a dynamic model of the extrusion process which satisfies the above mentioned criteria. The dynamic model predicts quasi-3D spatial profiles of the degree of fill, pressure, temperature, specific mechanical energy input and concentrations of inert and reacting species in the extruder. The individual material transport models which constitute the dynamic model are examined closely for their accuracy and computational efficiency by comparing candidate models amongst themselves and against full 3D finite volume flow models. Several new modelling approaches are proposed in the course of this investigation. The dynamic model achieves a high degree of simplicity and flexibility by assuming a slight compressibility in the process material, allowing the pressure to be calculated directly from the degree of over-fill in each model element using an equation of state. Comparison of the model predictions with dynamic temperature, pressure and residence time distribution data from an extrusion cooking process indicates a good predictive capability. The model can perform dynamic step-change calculations for typical screw configurations in approximately 30 seconds on a 600 MHz Pentium 3 personal computer. The second part of this thesis relates to the measurement of product quality attributes of extruded materials. A digital image processing technique for measuring the bubble size distribution in extruded foams from cross sectional images is presented. It is recognised that this is an important product quality attribute, though difficult to measure accurately with existing techniques. The present technique is demonstrated on several different products. A simulation study of the formation mechanism of polymer foams is also performed. The measurement of product quality attributes such as bulk density and hardness in a manner suitable for automatic control is also addressed. This is achieved through the development of an acoustic sensor for inferring product attributes using the sounds emanating from the product as it leaves the extruder. This method is found to have good prediction ability on unseen data. The third and final part of this thesis relates to the automatic control of product quality attributes using multivariable model predictive controllers based on both direct and indirect control strategies. In the given case study, indirect control strategies, which seek to regulate the product quality attributes through the control of secondary process indicators such as temperature and pressure, are found to cause greater deviations in product quality than taking no corrective control action at all. Conversely, direct control strategies are shown to give tight control over the product quality attributes, provided that appropriate product quality sensors or inferential estimation techniques are available.

La peronospora della vite è causata dall’Oomicete eterotallico Plasmopara viticola ed è ampiamente diffusa in tutte le aree caratterizzate da primavere miti e piovose. Gli organi svernanti di questo patogeno sono le oospore, che rappresentano l’unica fonte di inoculo per le infezioni primarie. Recenti studi molecolari hanno evidenziato l’importanza delle infezioni primarie e suggerito una revisione dell’epidemiologia di P. viticola. Questa tesi è costituita dagli studi epidemiologici realizzati per indagare il processo di maturazione e germinazione delle oospore mirati all’elaborazione di un modello dinamico per la simulazione delle infezioni primarie di P. viticola. Il modello è stato successivamente validato in diverse aree viticole italiane e, inoltre, utilizzato come base per un warning system in tempo reale per la gestione dei trattamenti in vigneto. / The heterothallic Oomycete Plasmopara viticola represents the causal agent of downy mildew of grapevine (Vitis spp.). The unique source of inoculum is represented by the overwintering sexual spores, originated by the fusion between anteridium and oogonium, so called oospores. Despite their critical impact on the epidemiology of this disease, knowledge about oospores presents some inconsistencies that are engaged in the present dissertation. Initially, the effect of water moistening the grape leaf litter holding overwintering P. viticola oospores was investigated. A close relationship was found between vapour pressure deficit (VPD in hPa) and aW (water activity) of the leaf litter, so that when VPD is lower than 2.13 hPa there is sufficient water for oospores to develop. Results showed that moisture of the leaf litter due to the water flow from the atmosphere makes the oospore development possible also during non rainy periods. Then, the effects of environmental conditions on the variability in germination dynamics of Plasmopara viticola oospores were studied over five years. The germination course was determined indirectly as the relative infection incidence (RII) occurring on grape leaf discs kept in contact with oospores sampled from a vineyard between March and July. The time elapsed between the 1st of January and the infection occurrence was expressed as physiological time, using sums of hourly rates from a temperature-dependent function only in hours when VPD was not a limiting factor (hydro-thermal time, HT). The Gompertz equation calculated over hydro-thermal time produced a consistent modelling of the general relationships between the germination dynamics of a population of P. viticola oospores and weather conditions. It represents the relative density of the seasonal oospores that should have produced sporangia when they have experienced favourable conditions for germination. Finally, a dynamic model for Plasmopara viticola primary infections on grapevine was elaborated according to a mechanistic approach. Development of the sexual stage of the pathogen was split into different state variables, in which changes from one state to another were regulated by rates depending on environmental conditions. The conceptual model was based on the definition of a primary inoculum season, a seasonal oospore (inoculum) dose, and its division into many coeval cohorts. Each cohort progresses along the primary infection cycle (production and survival of sporangia, release, survival and dispersal of zoospores, infection, appearance of disease symptoms) simultaneously, with a time step of one hour. The model was evaluated by comparing model predictions with disease onset in: i) 100 vineyards of Northern, Southern and Insular Italy (1995 to 2007); ii) 42 groups of potted grapevine plants exposed to inoculum (2006 to 2008). Most of the wrong positive predictions occurred in early season, when the host was in the earlier growth stages, or when the oospore germination was triggered by isolated weak rain events. Considering that neither calibration nor empirical adjustment of model parameters were necessary to obtain accurate simulation, it was concluded that this model produces a reasonable approximation of the primary infection processes underlying oospore development. A warning system based on such a model and on short-term weather forecasts was developed and its use was evaluated in experimental vineyards over a 3-year period in North Italy. An unsprayed control was compared with a “warning” treatment (fungicides were applied when the warning system predicted an infection), a “threshold” treatment (fungicides were applied as in the warning treatment, but only for the oospore cohorts higher than a fixed threshold), and the grower’s schedule. Average efficacy in decreasing disease incidence on leaves compared to the unsprayed control was > 90% for all treatments. On the average, 6.8 sprays were applied following the grower’s schedule; use of the warning system reduced applications by about one half (warning treatment) or two third (threshold treatment). The grower’s schedule was the most expensive control strategy, with average of 337 €/ha; the average saving was 174 and 224 €/ha for the warning and the threshold treatments, respectively. The value of this dissertation consists in two relevant and connected aspects. From one side the studies performed on the oospore maturation and germination allowed to better understand and clarify a key point of the downy mildew epidemics still wrapped by a lack of information. From the other side the model elaborated during this thesis represents a practical and efficient tool that leads to the reduction both of growers’ costs and chemical input in the environment.

Commodity and specialty-grade rubbers, such as styrene-butadiene (SBR) or nitrile-butadiene (NBR), are industrially produced in large trains of continuous reactors using an emulsion polymerization process. Both SBR and NBR systems are largely unstudied. Furthermore, the studies that have been published on NBR have been typically limited to issues concerning the characteristics of the product behaviour (i.e. oil/fuel resistance, tensile strength, hardness, compression set). In this work a detailed mathematical model has been developed in order to simulate the industrial production of NBR via emulsion copolymerization of acrylonitrile (AN) and butadiene (Bd) in batch, continuous and trains of continuous reactors. Model predictions include monomer conversion, polymerization rate, copolymer composition, number- and weight-average molecular weights, tri- and tetra-functional branching frequencies, and the number and average size of polymer latex particles. NBR is typically produced at low temperatures (5 to 10 degrees C) using a redox initiation system to generate free radicals. The system is typically composed of three phases, water, polymer particles, and monomer. Surfactants and electrolytes are used to stabilize the particle and monomer phases as polymerization proceeds. Of particular industrial importance, in today's world of tailor-made products, is detailed control over the polymerization reaction. Such control requires a deep understanding of the influence of various reactant feed rates and reactor operating conditions on the process response. In particular, policies to minimize copolymer composition drift and to control molecular weight, polydispersity and chain branching at desirable levels. The model is cast in a dynamic form using ordinary differential equations to describe the change of each species, the average number of particles, total average polymer volume, and the first three leading moments of the molecular weight distribution. With a multiphase system it is necessary to determine the concentration of each component in each phase. For this, a constant partition coefficient approach was adopted, as opposed to a purely thermodynamic approach. Particle generation was modelled considering both micellar and homogeneous mechanisms. Model parameters were obtained from the open literature or arrived at after sensitivity analysis. Simulations starting the reactors full of water, feeding all ingredients to the first reactor and using an average residence time of 60 minutes revealed considerable copolymer drift starting in the forth reactor (33% conversion), and heightened molecular weights and chain branching once the monomer phase disappeared (50% conversion). Further simulations revealed that both copolymer drift and the growth of molecular weight and branching could be controlled through additional feed streams of AN and chain transfer agent to downstream reactors. Furthermore, polymer productivity could be increased by appropriately splitting the total monomer feed between the first couple of reactors in the train.

Commodity and specialty-grade rubbers, such as styrene-butadiene (SBR) or nitrile-butadiene (NBR), are industrially produced in large trains of continuous reactors using an emulsion polymerization process. Both SBR and NBR systems are largely unstudied. Furthermore, the studies that have been published on NBR have been typically limited to issues concerning the characteristics of the product behaviour (i.e. oil/fuel resistance, tensile strength, hardness, compression set). In this work a detailed mathematical model has been developed in order to simulate the industrial production of NBR via emulsion copolymerization of acrylonitrile (AN) and butadiene (Bd) in batch, continuous and trains of continuous reactors. Model predictions include monomer conversion, polymerization rate, copolymer composition, number- and weight-average molecular weights, tri- and tetra-functional branching frequencies, and the number and average size of polymer latex particles. NBR is typically produced at low temperatures (5 to 10 degrees C) using a redox initiation system to generate free radicals. The system is typically composed of three phases, water, polymer particles, and monomer. Surfactants and electrolytes are used to stabilize the particle and monomer phases as polymerization proceeds. Of particular industrial importance, in today's world of tailor-made products, is detailed control over the polymerization reaction. Such control requires a deep understanding of the influence of various reactant feed rates and reactor operating conditions on the process response. In particular, policies to minimize copolymer composition drift and to control molecular weight, polydispersity and chain branching at desirable levels. The model is cast in a dynamic form using ordinary differential equations to describe the change of each species, the average number of particles, total average polymer volume, and the first three leading moments of the molecular weight distribution. With a multiphase system it is necessary to determine the concentration of each component in each phase. For this, a constant partition coefficient approach was adopted, as opposed to a purely thermodynamic approach. Particle generation was modelled considering both micellar and homogeneous mechanisms. Model parameters were obtained from the open literature or arrived at after sensitivity analysis. Simulations starting the reactors full of water, feeding all ingredients to the first reactor and using an average residence time of 60 minutes revealed considerable copolymer drift starting in the forth reactor (33% conversion), and heightened molecular weights and chain branching once the monomer phase disappeared (50% conversion). Further simulations revealed that both copolymer drift and the growth of molecular weight and branching could be controlled through additional feed streams of AN and chain transfer agent to downstream reactors. Furthermore, polymer productivity could be increased by appropriately splitting the total monomer feed between the first couple of reactors in the train.