Hydrolysis of lactose: estimation of kinetic parameters using Artificial Neural Networks

The analysis of any kinetic process involves the development of a mathematical model with predictive purposes. Generally, those models have characteristic parameters that should be estimated experimentally. A typical example is Michaelis-Menten model for enzymatic hydrolysis. Even though conventional kinetic models are very useful, they are only valid under certain experimental conditions. Besides, frequently large standard errors of estimated parameters are found due to the error of experimental determinations and/or insufficient number of assays. In this work, we developed an artificial neural network (ANN) to predict the performance of enzyme reactors at various operational conditions. The net was trained with experimental data obtained under different hydrolysis conditions of lactose solutions or cheese whey and different initial concentrations of enzymes or substrates. In all the experiments, commercial beta-galactosidase either free or immobilized in a chitosan support was used. The neural network developed in this study had an average absolute relative error of less than 5% even using few experimental data, which suggests that this tool provides an accurate prediction method for lactose hydrolysisFil: Cuellas, Anahí V.. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología. Área Ingeniería en Alimentos; ArgentinaFil: Oddone, Sebastián. Universidad Argentina de la Empresa. Facultad de Ingeniería y Ciencias Exactas; ArgentinaFil: Mammarella, Enrique José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); ArgentinaFil: Rubiolo, Amelia Catalina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química (i); Argentin

Model-Based Parameter Estimation for Fault Detection Using Multiparametric Programming

Fault detection has become increasingly important for improving the reliability and safety of process systems. This paper presents a model-based fault detection methodology for nonlinear process systems. The objective of this work is to detect faults by estimating the model parameters using multiparametric programming. The parameter estimates are obtained as an explicit function of the measurements by using multiparametric programming. The diagnosis of fault is carried out by monitoring the changes in the residual of model parameters. Case studies of fault detection for a single stage evaporator system and quadruple tank system are presented. A number of faulty and fault-free scenarios are considered to show the effectiveness of the presented approach. The proposed approach successfully estimates the model parameters and detects the faults through a simple function evaluation of explicit functions

MANUFACTURE OF INDIVIDUALIZED DOSING: DEVELOPMENT AND CONTROL OF A DROPWISE ADDITIVE MANUFACTURING PROCESS FOR MELT BASED PHARMACEUTICAL PRODUCTS

The improvements in healthcare systems and the advent of precision medicine initiative have created the need to develop more innovative manufacturing methods for the delivery of individualized dosing and personalized treatments. In recent years, the US Food and Drug Administration (FDA) introduced the Quality by Design (QbD) and Process Analytical Technology (PAT) guidelines to encourage innovation and efficiency in pharmaceutical development, manufacturing and quality assurance. As a result of emerging technologies and encouragement from the regulatory authorities, the pharmaceutical industry has begun to develop more efficient production systems with more intensive use of on-line measurement and sensing, real time quality control and process control tools, which offer the potential for reduced variability, increased flexibility and efficiency, and improved product quality

A Meshless Modelling Framework for Simulation and Control of Nonlinear Synthetic Biological Systems

Synthetic biology is a relatively new discipline that incorporates biology and engineering principles. It builds upon the advances in molecular, cell and systems biology and aims to transform these principles to the same effect that synthesis transformed chemistry. What distinguishes synthetic biology from traditional molecular or cellular biology is the focus on design and construction of components (e.g. parts of a cell) that can be modelled, characterised and altered to meet specific performance criteria. Integration of these parts into larger systems is a core principle of synthetic biology. However, unlike some areas of engineering, biology is highly non-linear and less predictable. In this thesis the work that has been conducted to combat some of the complexities associated with dynamic modelling and control of biological systems will be presented. Whilst traditional techniques, such as Orthogonal Collocation on Finite Elements (OCFE) are common place for dynamic modelling they have significant complexity when sampling points are increased and offer discrete solutions or solutions with limited differentiability. To circumvent these issues a meshless modelling framework that incorporates an Artificial Neural Network (ANN) to solve Ordinary Differential Equations (ODEs) and model dynamic processes is utilised. Neural networks can be considered as mesh-free numerical methods as they are likened to approximation schemes where the input data for a design of a network consists of a set of unstructured discrete data points. The use of the ANN provides a solution that is differentiable and is of a closed analytic form, which can be further utilised in subsequent calculations. Whilst there have been advances in modelling biological systems, there has been limited work in controlling their outputs. The benefits of control allow the biological system to alter its state and either upscale production of its primary output, or alter its behaviour within an integrated system. In this thesis a novel meshless Nonlinear Model Predictive Control (NLMPC) framework is presented to address issues related to nonlinearities and complexity. The presented framework is tested on a number of case studies. A significant case study within this work concerns simulation and control of a gene metabolator. The metabolator is a synthetic gene circuit that consists of two metabolite pools which oscillate under the influence of glycolytic flux (a combination of sugars, fatty acids and glycerol). In this work it is demonstrated how glycolytic flux can be used as a control variable for the metabolator. The meshless NLMPC framework allows for both Single-Input Single-Output (SISO) and Multiple-Input Multiple-Output (MIMO) control. The dynamic behaviour of the metabolator allows for both top-down control (using glycolytic flux) and bottom-up control (using acetate). The benefit of using MIMO (by using glycolytic flux and acetate as the control variables) for the metabolator is that it allows the system to reach steady state due to the interactions between the two metabolite pools. Biological systems can also encounter various uncertainties, especially when performing experimental validation. These can have profound effect on the system and can alter the dynamics or overall behaviour. In this work the meshless NLMPC framework addresses uncertainty through the use of Zone Model Predictive Control (Zone MPC), where the control profile is set as a range, rather than a fixed set point. The performance of Zone MPC under the presence of various magnitudes of random disturbances is analysed. The framework is also applied to biological systems architecture, for instance the development of biological circuits from well-characterised and known parts. The framework has shown promise in determining feasible circuits and can be extended in future to incorporate a full list of biological parts. This can give rise to new circuits that could potentially be used in various applications. The meshless NLMPC framework proposed in this work can be extended and applied to other biological systems and heralds a novel method for simulation and control

Diseño de reactores de burbujeo para el tratamiento de aguas residuales mediante ozono. Caracterización física, análisis cinético y optimización con redes neuronales artificiales

Tesis por compendioThe water ozonation processes are really interesting to remove some organic compounds that are recalcitrant to the conventional water treatments. To adequately design and control the gas-liquid reactors it is necessary to use proper mathematical models that describe the behaviour of those reactors. However, the definition of suitable models is complex, since the performance of these reactors is defined by the interaction of the hydrodynamic processes of the gas and liquid phases, the transfer processes between the different phases and the chemical reactions. The present work intends to do the definition of suitable mathematical models of the bubble column reactors and the reactive schemes of the ozone. To validate them, the experimental designs are proposed for: i) the determination of physical parameters of the reactors, such as the gas holdup and the volumetric mass transfer coefficient; ii) the estimation of reaction rates of ozone decomposition and the elimination of some pollutants; and iii) the calculation of ozone properties, such as the molar extinction coefficient or solubility. The study of ozone solubility has demonstrated that the molar extinction coefficient of the dissolved ozone obtained in this work differs from the corresponding value traditionally used in the literature. This fact has been verified with different analytical methodologies. The estimation of kinetic constants fitting the mathematical models to the experimental results is usually carried out by optimization using classical gradient algorithms, which is sometimes quite complex. To facilitate these procedures, in this thesis an algorithm has been developed based on artificial neural networks to estimate the initial values of the classical methodologies. The developed algorithm is sensitive enough to estimate suitable values of kinetic constants, as it was demonstrated. A microscopic transfer model for bubble column reactors was formulated allowing the implementation of any type of reaction mechanism for the ozone. The sensitivity analysis of this model shows that the kinetic constant can be determined by knowing the evolution of a substrate, and if the evolution of the ozone gas phase concentration is also known, the volumetric mass transfer coefficient can be determined at the same time. On the other hand, a reactive model of the ozone chemical decay process has been developed. The application of a sensitivity analysis on this model shows that knowing the evolution of the ozone concentration and the initial and final concentration of hydrogen peroxide we can determine three kinetic constants of the chemical mechanism. Finally, as an example of application, we study the elimination of cytostatic compounds in hospital raw waters by ozone. The experimental results were used to estimate the kinetic rate constants of the reaction of some of these compounds with the ozone. Using these constants we carried out a preliminary economical study of the operating costs of an ozone plant to treat water of these characteristics.Los procesos de ozonización de aguas ofrecen una serie de ventajas muy interesantes para la eliminación de ciertos compuestos orgánicos que resultan recalcitrantes a los procesos de tratamiento de aguas convencionales. El correcto diseño y control de los reactores gas-líquido necesarios para su implementación industrial precisa de adecuados modelos matemáticos que describan el comportamiento de los mismos. Sin embargo, la definición de modelos adecuados resulta compleja, ya que el rendimiento de estos reactores viene definido por la interacción de los procesos hidrodinámicos de las fases gas y líquida, los procesos de transferencia entre las fases y las reacciones químicas. Con el presente trabajo se pretende la definición de modelos matemáticos adecuados de los reactores de burbujeo y de los esquemas reactivos del ozono. Para validarlos se realizan diseños experimentales para: i) la determinación de parámetros físicos de los reactores, como la fracción de gas y el coeficiente volumétrico de transferencia de materia; ii) la estimación de velocidades de reacción de la descomposición del ozono y de la eliminación de algunos contaminantes; y iii) el cálculo de propiedades del ozono, como el coeficiente de extinción molar o la solubilidad. Los estudios de solubilidad del ozono realizados en esta tesis han demostrado que el coeficiente de extinción molar del ozono disuelto obtenido difiere del valor utilizado tradicionalmente en la bibliografía. Este hecho se ha verificado con diferentes metodologías analíticas. El cálculo de constantes cinéticas por medio del ajuste de los modelos matemáticos a los resultados experimentales suele realizarse mediante optimización por algoritmos clásicos de gradiente, lo que resulta en ocasiones bastante complejo. Para facilitar estos procedimientos, en esta tesis se desarrolla un algoritmo basado en redes neuronales artificiales para estimar los parámetros de inicio de las metodologías clásicas. Se ha comprobado que el algoritmo desarrollado es sensible por sí mismo para estimar valores adecuados de las constantes cinéticas. La metodología desarrollada ha permitido establecer un modelo de transferencia microscópico para reactores de burbujeo al que se le puede implementar cualquier tipo de mecanismo de reacción para el ozono. El análisis de sensibilidad de este modelo demuestra que conociendo la evolución de un substrato se puede determinar la constante cinética, y si también se conoce la evolución de la concentración de ozono en fase gas se puede determinar al mismo tiempo el coeficiente de transferencia de materia volumétrico. Por otra parte, se ha desarrollado un modelo reactivo del proceso de descomposición química del ozono. La aplicación de un análisis de sensibilidad sobre este modelo demuestra que conociendo la evolución de la concentración de ozono y la concentración inicial y final de peróxido de hidrógeno se pueden determinar un máximo de 3 constantes cinéticas del mecanismo utilizado. Finalmente, como ejemplo de aplicación de esta tecnología, se estudia la eliminación de compuestos citostáticos en aguas hospitalarias mediante ozono. A partir de los resultados experimentales se han determinado las constantes cinéticas de la reacción de alguno de estos compuestos con el ozono. Haciendo uso de estas constantes se realiza un estudio económico preliminar de los costes de operación de una planta de ozono para tratar aguas de estas características.Els processos d'ozonització d'aigües ofereixen alguns avantatges molt interessants per a l'eliminació de certs compostos orgànics que són recalcitrants als processos de tractament d'aigües convencionals. Per a dissenyar i controlar correctament els reactors gas-líquid, per a la seua implementació industrial, es necessari utilitzar models matemàtics que descriguen adequadament el seu comportament. Però, la definició de models adequats resulta complexa, ja que el rendiment d'aquests reactors ve definit per la interacció dels processos hidrodinàmics de les fases gas i líquida, els processos de transferència entre ambdues fases i les reaccions químiques. La present tesi pretén la definició de models matemàtics adequats del reactors de bombolleig i dels esquemes reactius de l'ozó. Per a validar-los es realitzaran dissenys experimentals amb la finalitat de: i) determinar paràmetres físics dels reactors, com la fracció de gas i el coeficient volumètric de transferència de matèria; ii) l'estimació de velocitats de reacció de descomposició de l'ozó i de l'eliminació d'alguns contaminants; i iii) el càlcul de propietats de l'ozó, com el coeficient d'extinció molar o la solubilitat. Els estudis de solubilitat de l'ozó realitzats en aquesta tesi han demostrat que el coeficient d'extinció molar de l'ozó dissolt determinat difereix del valor utilitzat tradicionalment a la bibliografia. Aquest fet s'ha verificat amb diferents metodologies analítiques. El càlcul de constants cinètiques per mitjà de l'ajust dels models matemàtics als resultats experimentals sol realitzar-se mitjançant algoritmes d'optimització clàssics basats en el gradient, el que resulta bastant complex en algunes ocasions. Per facilitar aquests procediments, en aquesta tesi es desenvolupa un algoritme basat en xarxes neuronals artificials per a estimar els paràmetres d'inici de les metodologies clàssiques. S'ha comprovat que l'algoritme desenvolupat es sensible per sí mateix per a estimar valors adequats per a les constants cinètiques. La metodologia desenvolupada ha permès establir un model de transferència microscòpic per a reactors de bombolleig al que es pot implementar qualsevol mecanisme de reacció per a l'ozó. L'anàlisi de sensibilitat d'aquest model demostra que coneixent l'evolució d'un substrat es pot determinar la constant cinètica. A més a més, si es coneix l'evolució de la concentració d'ozó en fase gas es pot determinar al mateix temps el coeficient volumètric de transferència de matèria. D'altra banda, s'ha desenvolupat un model reactiu del procés de descomposició química de l'ozó. L'aplicació d'un anàlisis de sensibilitat sobre aquest model demostra que coneixent l'evolució de la concentració d'ozó i la concentració inicial i final de peròxid d'hidrogen es pot determinar una màxim de tres constants cinètiques del mecanisme utilitzat. Finalment, com a exemple d'aplicació d'aquesta tecnologia, s'estudia l'eliminació de compostos citostàtics en aigües hospitalàries mitjançant l'ozó. A partir dels resultats experimentals s'han determinat les constants cinètiques de la reacció d'algun d'aquests compostos amb l'ozó. Fent ús d'aquestes constants es realitza un estudi econòmic preliminar dels costos d'operació d'una planta d'ozó per a tractar aigües d'aquestes característiques.Ferre Aracil, J. (2017). Diseño de reactores de burbujeo para el tratamiento de aguas residuales mediante ozono. Caracterización física, análisis cinético y optimización con redes neuronales artificiales [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/86163TESISCompendi