La tesis doctoral se compone de dos partes fundamentales: El desarrollo teórico de un modelo de simulación para la destilación discontinua y la validación de este mediante experimentos hechos en una planta piloto de destilación discontinua. La parte teórica se divide en la parte de desarrollo del modelo y en la parte de la implementación del modelo en un programa de simulación. El nuevo modelo desarrollado es un modelo de transferencia de materia que se distingue de los desarrollos anteriores por su capacidad de contemplar la cinética de la transferencia de materia tal como la hidrodinámica. La incorporación de efectos hidrodinámicos se basa principalmente en la observación de diferentes geometrías de contacto en una columna de platos perforados. Estas geometrías de contacto son canales de vapor y burbujas. En caso de las burbujas se distingue entre grandes y pequeñas con diferentes propiedades hidrodinámicas. De esta forma el modelo contempla tres diferentes clases de vapor, dos clases de vapor de desequilibrio y una de equilibrio (burbujas pequeñas). Para las clases de vapor de desequilibrio se calcula explícitamente los caudales de materia que traviesen la interfase basándose en la teoría de Maxwell-Stefan de transferencia de materia multicomponente. La parte experimental se divide en la parte de diseño de la columna usada en una planta piloto y en la de la realización de los experimentos. El diseño de la columna tiene como objetivo la obtención de un medio de validación del nuevo modelo desarrollado. Por tanto está equipado con un gran número de sensores de temperatura, de presión y de tomas de muestra. También la realización de los experimentos se adapta al fin de la validación del modelo, ya que la frecuencia de toma de muestra y de capturación de señales de temperatura es elevada. La memoria de la tesis contiene una comparación amplia de los resultados experimentales con los de la simulación. Estas comparaciones demuestran una determinada superioridad del modelo desarrollado sobre desarrollos anteriores.

Five articles describing the impact of surface characteristics, and development of mass transfer models for diffusion controlled membrane applications are published in this dissertation. Article 1 (Chapter 3) describes the impact of membrane surface characteristics and NOM on membrane performance for varying pretreatment and membranes during a field study. Surface charge, hydrophobicity and roughness varied significantly among the four membranes used in the study. Membrane surface characteristics, NOM and SUVA measurements were used to describe mass transfer in a low pressure RO integrated membrane system. Inorganic and organic solute and water mass transfer coefficients were systematically investigated for dependence on membrane surface properties and NOM mass loading. Inorganic MTCs were accurately described by a Gaussian distribution curve. Water productivity, NOM rejection and inorganic rejection increased as membrane surface charge and NOM loading increased. Inorganic MTCs were also correlated to surface hydrophobicity and surface roughness. The permeability change of identical membranes was related to NOM loading, hydrophobicity and roughness. Organic fouling as measured by water, organic and inorganic mass transfer was less for membranes with higher hydrophilicity and roughness. Article 2 (Chapter 4) describes the development of a diffusion controlled solute mass transfer model to assess membrane performance over time. The changing mass transfer characteristics of four low-pressure reverse osmosis (LPRO) membranes was correlated to feed stream water quality in a 2000 hour pilot study. Solute mass transfer coefficients (MTCs) were correlated to initial solute MTCs, solute charge, feed water temperature, monochloramine loading and organic loading (UV254). The model can be used to predict cleaning frequency, permeate water quality and sensitivity of permeate water quality to variation of temperature, organic and monochloramine mass loading. Article 3 (Chapter 5) describes a comparison of the long standing method of assessing membrane performance (ASTM D 45160 and another approach using mass transfer coefficients (MTCs) from the homogenous solution diffusion model (HSDM) using a common data set, water productivity and standardized salt passage. Both methods were shown to provide identical assessments of water productivity, however different assessments of salt passage. ASTM D 4516 salt passage is normalized for pressure and concentration and does not show the effects of flux, recovery, temperature or specific foulants on salt passage. However the MTC HSDM method is shown to consider all those effects and can be easily used to predict membrane performance at different sites and times of operation, whereas ASTM D 45160 can not. The HSDM MTC method of membrane evaluation is more versatile for assessment of membrane performance at varying sites and changing operational conditions. Article 4 (Chapter 6) describes the development of a fully integrated membrane mass transfer model that considers concentration, recovery and osmotic pressure for prediction of permeate water quality and required feed stream pressures. Osmotic pressure is incorporated into the model using correction coefficients that are calculated from boundary conditions determined from stream osmotic pressures of the feed and concentrate streams. Comparison to homogenous solution diffusion model (HSDM) with and without consideration of osmotic pressure and verification of IOPM using independently developed data from full and pilot scale plants is presented. The numerical simulation and statistical assessment show that osmotic pressure corrected models are superior to none-osmotic pressure corrected models, and that IOPM improves model predictability. Article 5 (Chapter 7) describes the development and comparison of a modified solution diffusion model and two newly developed artificial neural network models to existing mechanistic or empirical models that predict finished water quality for diffusion controlled membranes, which are generally restricted to specific solute MTCs that are site and stage specific. These models compensate for the effects of system flux, recovery and feed water quality on solute MTC and predict permeate water quality more accurately than existing models.

<p>Hemometrijskim metodama (deskriptivna statistika, analiza glavnih komponenti, ve&scaron;tačke neuronske mreže i fazi optimizacija) analizirani su rezultati procesa osmotske dehidratacije mesa srebrnog kara&scaron;a, sa ciljem unapređenja efikasnosti osmotskog tretmana i pronalaženja optimalnih tehnolo&scaron;kih parametara.<br />Osmotski tretman se odvijao u tri osmotska rastvora (vodeni rastvor natrijum hlorida i<br />saharoze, kombinacija vodenog rastvora natrijum hlorida i saharoze i melase i melasa &scaron;ećerne repe) različitih koncentracija, na četiri temperature (10&deg;C, 20&deg;C, 35&deg;C i 50&deg;C) i pri tri vremena procesa (1, 3 i 5h). Posmatrani su sledeći odzivi sistema: gubitak vode, prira&scaron;taj suve materije, povećanje sadržaja suve materije, sniženje aktivnosti vode i promena sadržaja minerala (Na, K, Ca i Mg). Karakterizacijom osmotski dehidriranog ribljeg polupoizvoda, poja&scaron;njeni su efekti osmotskog tretmana i inovatinog osmotskog rastvora na senzorne osobine, hemijski i mikrobiolo&scaron;ki profil tretiranog mesa ribe. Rezultati ispitivanja pokazuju da se primenom procesa osmotske dehidratacije povećava gubitak vode, prira&scaron;taj suve materije i sadržaj suve materije u svim uzorcima mesa srebrnog kara&scaron;a. Za sva tri osmotska rastvora, najveće vrednosti dobijene su nakon 5 časova, pri najvi&scaron;im temperaturama i u najvećim koncentracijama rastvora.<br />Povećavanjem temperature procesa, koncentracije rastvora i vremena trajanja procesa, povećan je sadržaj posmatranih minerala u tretiranom mesu ribe. Rezultati<br />ANOVA testa pokazali su da na vrednosti posmatranih odziva statistički značajno utiču<br />sva tri parametra: vreme, temperatura i koncentracija. PCA analizom procesa utvrđeno je da su pri izračunavanju prve glavne komponente najveći uticaj imale vrednosti svih odziva osim aw vrednosti, dok je ona najvi&scaron;e uticala na proračun druge glavne komponente. Iako su modeli ve&scaron;tačkih neuronskih mreža kompleksniji od modela polinoma drugog reda, mreže su pokazale bolji učinak usled visoke<br />nelinearnosti razvijenih sistema. Primenom fazi optimizacije postignute optimalne vrednosti procesnih parametara za vodeni rastvor natrijum hlorida i saharoze su bile na nižim temperaturama i nižim koncentracijama rastvora, dok su za rastvore sa melasom &scaron;ećerne repe optimalne vrednosti na maksimumima posmatranih opsega temperature i koncentracije rastvora. Procesom osmotske dehidratacije smanjen je inicijalni broj bakterija u mesu srebrnog kara&scaron;a. Hemijskim i senzorskim analizama utvrđeno je da je melasa &scaron;ećerne repe zbog svog kompleksnog nutritivnog sastava<br />povoljnije je delovala na promenu hemijskog sastava i senzorne osobine uzoraka u odnosu na druga dva rastvora.</p> / <p>Chemometric methods (descriptive statistics, principal components analysis, artificial neural networks and fuzzy optimization) were used to analyze the results of osmotic dehydration of silver crucian carp, with the aim of improving the efficiency of the osmotic treatment and finding the optimal technological parameters.<br />The osmotic treatment was carried out in three osmotic solution (aqueous sodium chloride and sucrose solution, sugar beet molasses and the combination of these two solutions) of varying concentrations, at four temperatures (10&deg;C, 20&deg;C, 35&deg;C and 50&deg;C) and at three processing times (1, 3 and 5 h). The observed system responses were: water loss, solid gain, increase in dry matter content, reduction of water activity<br />and changes in mineral content (Na, K, Ca and Mg). The characterization of dehydrated fish, explained the effects of osmotic treatment on its sensory properties, chemical and microbiological profile. Results have shown that the application of osmotic dehydration increases water loss, solid gain and dry matter content in all samples of fish meat. For all three osmotic solution, the highest values were obtained after 5h, at the highest temperatures and in the highest concentration of the solution. By increasing the process temperature, concentration and time, increased the mineral content in the fish meat. The results of the ANOVA test have shown that the values of the observed responses significantly affect all three parameters: time, temperature and concentration. PCA analysis process has found that on calculation of the first principal component all response values except aw value had the greatest impact, while aw value had the most influence on the calculation of the other major component. Although models of artificial neural network models are more complex than second order polynomial, the network showed better performance due to the high nonlinearity of the developed system. Application of fuzzy optimization obtained optimal values of the process parameters for aqueous solution of sodium chloride and sucrose were at lower temperatures and lower concentrations of the solution, while the solutions with molasses optimal values of the maxima observed ranges<br />of temperature and solution concentration. The process of osmotic dehydration has reduced the initial number of bacteria in meat silver carp. Chemical and sensory analyzes have shown that the sugar beet molasses due to its complex nutritional composition has a better effect on changing the chemical composition and sensory characteristics of the samples.</p>