Bayesian learning methods are the basis of many powerful analysis techniques in neuroimaging, permitting probabilistic inference on hierarchical, generative models of data. This thesis primarily develops Bayesian analysis techniques for magnetic resonance imaging (MRI), which is a noninvasive neuroimaging tool for probing function, perfusion, and structure in the human brain. The first part of this work fits nonlinear biophysical models to multimodal functional MRI data within a variational Bayes framework. Simultaneously-acquired multimodal data contains mixtures of different signals and therefore may have common noise sources, and a method for automatically modelling this correlation is developed. A Gaussian process prior is also used to allow spatial regularization while simultaneously applying informative priors on model parameters, restricting biophysically-interpretable parameters to reasonable values. The second part introduces a novel data fusion framework for multivariate data analysis which finds a joint decomposition of data across several modalities using a shared loading matrix. Each modality has its own generative model, including separate spatial maps, noise models and sparsity priors. This flexible approach can perform supervised learning by using target variables as a modality. By inferring the data decomposition and multivariate decoding simultaneously, the decoding targets indirectly influence the component shapes and help to preserve useful components. The same framework is used for unsupervised learning by placing independent component analysis (ICA) priors on the spatial maps. Linked ICA is a novel approach developed to jointly decompose multimodal data, and is applied to combined structural and diffusion images across groups of subjects. This allows some of the benefits of tensor ICA and spatially-concatenated ICA to be combined, and allows model comparison between different configurations. This joint decomposition framework is particularly flexible because of its separate generative models for each modality and could potentially improve modelling of functional MRI, magnetoencephalography, and other functional neuroimaging modalities.

Computational modelling and simulation, in close interaction with experiments, has provided invaluable insight into the biochemical, mechanical and electrophysiological function and dysfunction of the heart. However, limitations in imaging techniques and computing resources have precluded the analysis of tissue architecture near the cellular scale and the effect of this architecture on cardiac function. It is the wider aim of this thesis to develop a framework to characterise cardiac microstructure and to investigate the role of microstructure in cardiac propagation dynamics and arrhythmogenesis. An initial modelling study elucidates the effect of blood vessels in sustaining arrhythmic episodes, and how the accurate modelling of fibre direction in the vicinity of the vessels mitigates this detrimental mechanism. A mathematical model of fibre orientation in a simple geometry around blood vessels has been developed, based on information obtained from highly detailed histological and MRI datasets. A simulation regime was chosen, guided by the vasculature extracted from whole heart MRI images, to analyse ventricular wavefront propagation for different orientations and positions of blood vessels. Our results demonstrate not only that the presence of the blood vessels encourages curvature in the activation wavefront around the blood vessels, but further that vessels act to restrict and prolong phase singularities. When compared to a more simplistic implementation of fibre orientation, the model is shown to weaken wavefront curvature and reduce phase singularity anchoring. Having established the importance of microstructural detail in computational models, it seems expedient to generate accurate data in this regard. An automated registration toolchain is developed to reconstruct histological slices based on coherent block face volumes, in order to present the first 3-D sub-cellular resolution images of cardiac tissue. Although mesoscopic geometry is faithfully reproduced throughout much of the dataset, low levels of transformational noise obfuscate tissue microstructure. These distortions are all but eradicated by a novel transformational diffusion algorithm, with characteristics that outperform any previous method in the literature in this domain, with respect to robustness, conservation of geometry and extent of information transfer. Progress is made towards extracting microstructural models from the resultant histological volumes, with a view to incorporating this detail into simulations and yielding a deeper understanding of the role of microstructure in arrhythmia.

Although the tensile mechanical properties of tendon have been well characterised, the viscoelastic and anisotropic properties remain uncertain. This thesis addresses the anisotropic and viscoelastic material properties of tendon. A method to characterise the three-dimensional shape of tendon is reported and experiments to characterise the fibre-aligned and fibre-transverse viscoelastic properties of tendon are presented. The cross-sectional profiles of bovine digital extensor tendons were determined by a laser-slice method. Linear dimensions were measured within 0.15 mm and cross-sectional areas within 1.7 mm². Tendons were compressed between two glass plates in creep loading at multiple loads. Compression was then modelled in a finite element environment. Tendon was found to be nearly incompressible and reproduction of its isochronal load-displacement curve was achieved with a neo-Hookean material model (E ≃ 0.3 MPa). The fibre-aligned tensile mechanical properties were described using a Quasi-Linear Viscoelastic model. The model was effective at reproducing cyclic loading; however, it was ineffective at predicting stress relaxation outside the scope of data used to fit the model. When all experimental results are considered together, two significant conclusions are made: (1) tendon is much stiffer in fibre-aligned tension than in fibre-transverse compression and (2) the fibre-aligned tensile response is strain dependant, while the transverse response is not.

An estimated 85% of haemorrhagic strokes are secondary to the rupture of an intracranial aneurysm (IA), a localised, blood-filled dilation of the artery wall. The clinically observed rupture of occluded IAs has led to hypothesise that the presence of thrombus may restrict the transport of nutrients, most notably oxygen, to the aneurysmal wall, thus heightening the risk of rupture through the deleterious effects of hypoxia on cellular functionality. The limited research into O2 transport within IAs demonstrate the need for further exploration into the possible detrimental hypoxic conditions as a result of intrasaccular haemodynamics and thrombusformation in untreated, treated and evolving IAs, with the ultimate goal of further understanding disease evolution and developing prognostic decision support models for clinical intervention. Preliminary computational fluid dynamic simulations conducted on a 2Daxisymmetric model of a thrombosed artery highlighted the relative importance of wall-side versus the fluid-side mass transport of oxygen. A sensitivity analysis demonstrated that variations in thrombus thickness, and arterial wall cellular respiration rates have the greatest influence on the oxygen distribution to the portion of wall in direct contact with the thrombus. The results of the coupled flow-mass transport computational fluid dynamic simulations within patient-specific IA show that a reduction in intrasaccular flow as a consequence of stent deployment affects the rate at which oxygenated blood reaches the entirety of the dome. Nonetheless, the distribution ofO2 to the aneurysmal wall itself does not differ from the observed oxygen distribution across the wall when the same IA is left untreated. Conversely, the low velocity recirculations observed in an IA presenting with a very high aspect ratio (i.e a narrow neck and high sack height) limited the transport of oxygen to such an extent as to completely deprive the delivery of oxygen to the fundus. The presence of thrombus within the IA dome results in a dramatic reduction in oxygen delivery to the wall, the extent of which is dependent on the local thrombus thickness. Finally, a novel fluid-solid-growth-mass transport (FSGT) mathematical model is conceived to explore the biochemical role of thrombus on the evolution of an IA. The shear-regulate propagation of a thrombus layer during membrane expansion leads to the gradual decrease in oxygen tension within the wall. Moreover, as a consequence of coupling this oxygen deficiency to fibroblast functionality, the collagen fibre mass density was shown to increase at an insufficient rate to compensate for the transfer in load from the degrading elastinous consitituents to the collagenous constituents, thus resulting in the increased stretch of collagen fibres in order to maintain mechanical equilibrium. Moreover this over-expansion results in the gradual unstable evolution of the IA. The observed obstruction to oxygen delivery as a result of intrasaccular haemodynamics and thrombosis compounds the need for further development of more comprehensive chemo-mechano-biological models of IAs so as to better ascertain the level of rupture risk posed by a hypoxic environment. Refinement to the models proposed within this work would prove invaluable to creating a fully integrated multi-physics, multi-scale in silico framework in aid to patient diagnostics and individual treatment planning of IAs.

Using some form of dynamical model in a visual tracking system is a well-known method for increasing robustness and indeed performance in general. Often, quite simple models are used and can be effective, but prior knowledge of the likely motion of the tracking target can often be exploited by using a specially-tailored model. Specifying such a model by hand, while possible, is a time-consuming and error-prone process. Much more desirable is for an automated system to learn a model from training data. A dynamical model learnt in this manner can also be a source of useful information in its own right, and a set of dynamical models can provide discriminatory power for use in classification problems. Methods exist to perform such learning, but are limited in that they assume the availability of 'ground truth' data. In a visual tracking system, this is rarely the case. A learning system must work from visual data alone, and this thesis develops methods for learning dynamical models while explicitly taking account of the nature of the training data --- they are noisy measurements. The algorithms are developed within two tracking frameworks. The Kalman filter is a simple and fast approach, applicable where the visual clutter is limited. The recently-developed Condensation algorithm is capable of tracking in more demanding situations, and can also employ a wider range of dynamical models than the Kalman filter, for instance multi-mode models. The success of the learning algorithms is demonstrated experimentally. When using a Kalman filter, the dynamical models learnt using the algorithms presented here produce better tracking when compared with those learnt using current methods. Learning directly from training data gathered using Condensation is an entirely new technique, and experiments show that many aspects of a multi-mode system can be successfully identified using very little prior information. Significant computational effort is required by the implementation of the methods, and there is scope for improvement in this regard. Other possibilities for future work include investigation of the strong links this work has with learning problems in other areas. Most notable is the study of the 'graphical models' commonly used in expert systems, where the ideas presented here promise to give insight and perhaps lead to new techniques.

BACKGROUND: Little is known of the effects of obesity, body size and body composition, and blood pressure (BP) in childhood on hypertension (HBP) and cardiac structure and function in adulthood due to the lack of long-term serial data on these parameters from childhood into adulthood. In the present study, we are poised to analyze these serial data from the Fels Longitudinal Study (FLS) to evaluate the extent to which body size during childhood determines HBP and cardiac structure and function in the same individuals in adulthood through mathematical modeling. METHODS: The data were from 412 males and 403 females in the FLS. Stature and BMI parameters were estimated using the Preeze-Baines model and the third degree polynomial model to describe the timing, velocity and duration of these measure from 2 to 25 years of age. The biological parameters were related to adult BP and echocardiographic (Echo-) measurements using Generalized Linear Models (GLM). RESULTS: The parameters of stature and BMI were compared between male and female to their overall goodness of fit and their capabilities to quantify the timing, rate of increase, and duration of the growth events. For stature parameters, the age at onset and peak velocity was earlier for girls; but the peak velocity was greater in boys; the velocity at onset was about the same for boys and girls; and stature at onset, peak velocity and adult was greater for boys. For BMI parameters, boys tended to have larger BMI values than girls, but the rates of change in BMI were almost the same; there was no sex difference in the timing of BMI rebound, but there was for the age of the peak velocity of BMI and maximum BMI, both of which were earlier in girls than in boys. CONCLUSIONS: Changes in childhood stature and BMI parameters were related to adult BP and Echo-measurements more so in females than males. Also the relationship of the adult BP measurements with corresponding childhood biological parameters was stronger than the relationship for adult Echo-measurements.

An intracranial aneurysm (IA) is a balloon-like focal lesion on the cerebral arterial wall. IAs are poorly understood, but are commonly considered to be a disease caused by multiple factors. Current interventional treatments are accompanied with risks. Given the low incidence of rupture, it would be ideal to only treat aneurysms identified with rupture risk. Numerical models of aneurysm development may provide insight into the disease mechanisms, and contribute to the prediction of disease progression. Better understanding of the disease aetiology will also guide clinical decision making. Different hypotheses have been proposed on the influence of haemodynamic stimuli on IA inception. We investigate this influence by examining the haemodynamic stimuli of the 'pre-aneurysmal' vasculature in the locations of IA formation in 22 clinical cases. The 'pre aneurysmal' geometries are obtained by applying a novel numerical vessel reconstruction method on the aneurysmal geometries. This automated reconstruction method propagates a closed curve along the vessel skeleton using the local Frenet frames to smoothly morph the upstream boundary into the downstream boundary. We observe that locally elevated wall shear stress (WSS) and gradient oscillatory number (GON) are highly correlated with regions susceptible to sidewall IA formation, whilst haemodynamic indices associated with the oscillation of the WSS vectors have much lower correlations. A common assumption made in the literature on arterial growth and remodelling (G&R) is that the 'state of stretch' (denoted as the attachment stretch) at which collagen fibres are configured in the extracellular matrix (ECM) is assumed to be constant. This will lead to an unrealistically thickened arterial wall in modelling aneurysm evolution. We propose a novel 1D mathematical model of collagen microstructural adaption during IA evolution. We assume new collagen fibres are configured into the ECM in a state of attachment stretch distribution which can be temporally adaptive. We explicitly define the functional form of this distribution and model its temporal adaption during IA evolution. This model is then implemented into two 3D models of IA evolution: a solid structural model and Fluid-Solid-Growth (FSG) model. In the solid structural model, the artery is modelled as a two-layer, nonlinear elastic cylindrical membrane using a physiologically realistic constitutive model. The development of the aneurysm is considered as a consequence of the growth and remodelling of its material constituents: elastinous constituents are prescribed to degrade in a localised circular patch; collagen concentration and recruitment variables enable the growth and remodelling of collagen fabric to be simulated; adaption of the attachment stretch distribution is confined locally within the region of aneurysm evolution. The sophisticated solid model predicts stabilised saccular IAs with realistic sizes and wall thicknesses. The FSG model simulates the IA development on patient-specific vasculature: the updated 3D solid structural model is integrated into a patient-specific geometry of the vasculature and the growth and remodelling of the constituents is now linked to the local haemodynamic stimuli obtained from a rigid-wall computational fluid dynamics analysis. Adaption of the attachment stretch distribution is also confined locally in the region where the constituents degrade. An illustrative case of IA development on patient specific geometry is provided. Based on our study, we conclude that incorporating the adaption of attachment stretch distribution is necessary to simulate IA evolution with physiological evolving wall thicknesses. However, how vascular cells confine this adaption heterogeneously needs further investigation. Improved understanding and modelling of the biology of the arterial wall is needed for more sophisticated models of aneurysm evolution. It will in turn assist in understanding the aetiology of IA formation. Ultimately we hope to have a patient-specific growth model that could have the potential be used to assist diagnostic decisions.

En réponse à une stimulation sonore, la cellule ciliée interne libère du glutamate qui va activer des récepteurs distribués sur le bouton post-synaptique. Les courants post-synaptiques vont ensuite dépolariser la terminaison périphérique des neurones auditifs primaires, et initier le déclenchement d'un potentiel d'action. Tandis que la connaissance des mécanismes pré-synaptiques a considérablement progressé ces 10 dernières années, les mécanismes responsables de l'initiation des potentiels d'action sont encore méconnus. Dans cette étude, nous avons déterminé les conductances ioniques nécessaires au déclenchement des potentiels d'action.Les paramètres biophysiques des conductances (Na+ et K+) ont été identifiés (algorithme d'identification trace entière) à partir d'enregistrements de patch clamp acquis sur les corps cellulaires. Un modèle mathématique de nœud de Ranvier a ensuite été développé en faisant l'hypothèse que les canaux présents sur le corps cellulaire et sur un nœud de Ranvier étaient de même nature mais en densité différente. Les paramètres de ce modèle ont été identifiés pour reproduire les potentiels d'action extracellulaire au moyen d'un algorithme de descente du gradient.Nous avons identifié : i) un courant Na+ entrant rapide (GNa activation: V1/2=-33 mV, tau_act< 0.5 ms; inactivation: V1/2=-61 mV, tau_inact < 2 ms) et deux courants K+ sortants, un rectifiant retardé activé à haut seuil (GKH, activation: V1/2=-41 mV; tau_act < 2.5 ms) et un activé à bas seuil (GKL, activation: V1/2=-56 mV; tau_act < 5 ms). Le modèle de nœud de Ranvier génère des potentiels d'action extracellulaire similaires à ceux enregistrés in vivo. La différence de durée du potentiel d'action observée le long de l'axe tonotopique (i.e. 450 µs de durée pic à pic à 1 kHz contre 250 µs à 20 kHz) s'explique parfaitement par un gradient de densité en canaux ioniques le long de la cochlée (GNa ~78 nS, GKL ~9 nS, GKH ~3 nS à 1 kHz contre GNa ~90 nS, GKL ~12 nS, GKH ~6 nS à 20 kHz).Cette étude a permis d'identifier les conductances ioniques et les densités de canaux responsables de l'initiation des potentiels d'action dans les neurones auditifs primaires. Elle suggère que la coopération entre le courant Na+ et des 2 courants K+ est probablement à l'origine de la haute fréquence de décharge de ces neurones. Le modèle de nœud de Ranvier permet en outre de tester de nouvelles stratégies de stimulation électrique dans le contexte de l'implant cochléaire. / In response to sound stimulation, inner hair cell triggers glutamate release onto the dendrite-like processes of primary auditory neurons and drives action potentials, which are convey to the central nervous system. Whereas knowledge of the transfer function at the ribbon synapse has considerably progress, little is known about the voltage-gated ionic channels which shape the action potential. Here, we provide a comprehensive computational model bridging the gap between the voltage-dependent currents measured in vitro on fresh isolated primary auditory neurons and spikes (extracellular action potentials) recorded in vivo from guinea pig auditory nerve fibers.Voltage-dependent currents (Na+ and K+) of SGNs somata patch-clamp recordings were fitted by a Hodgkin-Huxley model with a full trace identification algorithm. Node of Ranvier model was designed from the hypothesis that channel expressed on soma were identical, but differ in density. Simulated spikes were adjusted in order to match in vivo single-unit recordings with gradient-descent algorithm. Computation of the data allows to the identification of: i) one fast inward Na current (GNa activation: V1/2=-33 mV, τact< 0.5 ms; inactivation: V1/2=-61 mV, τinact < 2 ms); and ii) two K conductances, a high voltage-activated delayed-rectifier component (GKH, activation: V1/2=-41 mV; τact < 2.5 ms) and a low voltage-activated component (GKL, activation: V1/2=-56 mV; τact < 5 ms). Node of Ranvier model generate spikes that fit with in vivo recordings. Interestingly, the different spike durations along the tonotopic axis measured in vivo (i.e. 450 µs peak-to-peak duration versus 250 µs for 1 to 20 kHz, respectively) was explain by a gradual change in Na and K channel densities along the cochlea (GNa ~78 nS, GKL ~9 nS, GKH ~3 nS at 1 kHz versus GNa ~90 nS, GKL ~12 nS, GKH ~6 nS at 20 kHz).This study identifies the ionic conductances and densities, which shape the action potential waveform of auditory nerve fibers and suggests that the interplay of fast inward Na+ current and the two K+ enables the auditory nerve fibers to sustain high firing rates. In addition, this node of Ranvier model provides a valuable tool to design new electrical stimulation strategies for cochlear implants.

[pt] Este trabalho apresenta os resultados de um modelo matemático proposto para a carbocloração de pentóxido de nióbio com uma corrente de cloro gasoso em presença de carbono sólido como agente redutor. O modelo é baseado na equação de conservação de massa unidimensional em regime transitório. Soluções desta equação, acompanhada das condições de contorno e inicial, foram obtidas através do método de diferenças finitas. Uma análise estatística por distribuição t-student, dos valores obtidos utilizando o modelo de otimização Nelder e Mead, foi empregado neste estudo. O modelo representa resultados obtidos experimentalmente em um estudo anterior, referentes à conversão do pentóxido de nióbio em pentacloreto de nióbio gasoso por meio de um programa computacional para PC utilizando a linguagem Visual Basic for Applications (VBA). Os resultados experimentais apresentam uma boa concordância com os obtidos com o modelo e permitem representar de forma satisfatória o mecanismo reacional observado, incorporando os efeitos das variáveis envolvidas. Foram ainda determinadas a constante cinética e a difusividade efetiva para as diferentes variações de teor de carbono e porosidade nas temperaturas de 700 graus Celsius e 800 graus Celsius, para um fluxo de gás e altura da amostra constante. Observou-se que a melhor conversão do pentóxido de nióbio (96,5 por cento) obtém-se para 800 graus Celsius, 28 por cento de porosidade e 9 por cento de carbono. O tipo de controle é por difusão. / [en] This study presents the results of a mathematical model proposed for carbochlorination of niobium pentoxide under a stream of chlorine gas in the presence of solid carbon as reducing agent. The model is based on one-dimensional unsteady state regime considering kinetic, diffusion and mass conservation. Solutions for this equation, associated with initial and boundary conditions were obtained using the method of finite differences. In this study, the Nelder and Mead optimization model was used and t-Student’s statistics was applied for goodness of fit analysis. The data obtained experimentally in a previous study, concerning the conversion of niobium pentoxide into niobium pentachloride gas, was processed using a computer software written for an Excel platform on Visual Basic for Applications (VBA). It was found that the experimental results were in accordance with the models outputs, allowing satisfactory representation of the observed reaction mechanism, incorporating the effects of the intervening variables. It was also determined the kinetic constant and the effective diffusivity for the different levels of carbon content and porosity, at temperatures of 700 Celsius degrees and 800 Celsius degrees for a specified gas flow and sample height. It was observed that the best conversion of the niobium pentoxide (96.5 per cent) is obtained at 800 Celsius degrees for 28 per cent porosity and 9 per cent carbon, for diffusion control.

Difusores podem ser empregados para extração de sacarose da cana de açúcar e da beterraba, para a extração de tanino da casca de acácia negra e para extração de óleos vegetais de plantas oleaginosas. Apesar de operarem de forma simples do ponto de vista mecânico e químico, problemas que ocorrem na sua operação comprometem a eficiência de extração. A modelagem, simulação e otimização de difusores de biomassa mostra-se essencial para melhor compreender tais problemas e propor estratégias otimizadas de projeto e operação. Nesse contexto, a tese aqui proposta tem como objetivo principal modelar e simular a operação de um difusor de biomassa de 10 estágios (Biomassa entra pelo estágio 1 e sai do difusor pelo estágio 10. A água de embebição faz o trajeto em contracorrente, i.e. entra pelo estágio 10 e sai pelo estágio 1) para, posteriormente, otimizá-lo mono e multi-objetivamente considerando a possibilidade de conexão entre todos os estágios de extração. No caso da otimização mono-objetivo, no qual uma vazão de embebição de líquido fixa é considerada, o principal objetivo da otimização consiste em maximizar a concentração de soluto no líquido que deixa o difusor a partir de mudanças aleatórias nos coeficientes de conectividade do difusor. Já para a otimização multi-objetivo, a vazão de embebição de líquido que entra no difusor é considerada variável. Sendo assim, a otimização do sistema requer a maximização de dois objetivos simultaneamente (a maximização da concentração de soluto no líquido e minimização da concentração final de soluto na biomassa) a partir de mudanças aleatórias nos coeficientes de conectividade do difusor. Além disso, visto que a minimização de problemas operacionais está relacionada com a monitoração da altura de nível de líquido no leito de fibra, diferentes sinais para detecção de presença de líquido no leito de fibras em um estágio de extração experimental foram testados. Dos resultados de simulação e otimização obtidos, podemos concluir que novas conexões entre os estágios do difusor podem otimizar o processo de extração o que contraria o senso comum segundo o qual as conexões devem ser sequenciais. No caso da otimização mono-objetivo, 82 a 89% do fluido é direcionado para o estágio seguinte ao longo dos estágios de extração (exceto para o estágio 6, no qual esse valor é de 100%). A recirculação do fluido para o mesmo estágio é mais acentuada nos estágios finais (estágios 1 a 4), apresentando o difusor otimizado 14 a 18% de recirculação do fluido para o mesmo estágio nesses estágios enquanto para os demais estágios a recirculação varia entre 0 e 11%. Já para os estágios iniciais (estágios 5, 7, 8 e 9), a recirculação do fluido para o estágio anterior apresenta maior destaque, variando de 6 a 16% enquanto para os demais estágios é de apenas 0 a 2%. O estágio 6, por sua vez, é o único que se conecta exclusivamente com o estágio seguinte. Para a otimização multi-objetivo, resultados similares foram encontrados, sendo que a probabilidade de que 85 a 100% do fluido seja circulada para o estágio seguinte está entre 93 e 99%. Em relação a recirculação para o mesmo estágio, a probabilidade de que de 0 a 15% do fluido seja recirculado varia de 58 a 79% para os estágios 1 a 4, de 49 a 55% para os estágios medianos 5, 6 e 7 e de 60 a 90% para os três últimos estágios (estágios 8, 9 e 10). Para a conexão com o estágio imediatamente anterior, a probabilidade de que de 0 a 15% do fluido seja direcionado para o estágio anterior é maior nos estágios 1, 2, 8 e 9, variando entre 31 e 38%. Para a detecção da presença de líquido no leito de fibras em um estágio de extração, dois tipos de sinais diferentes, condutividade elétrica e radiação infravermelha, foram testados. Os testes foram realizados, em um estágio de extração experimental, primeiramente apenas com água e, em seguida, com bagaço de cana. Os medidores de condutividade mostraram-se estáveis e com repetitividade quando testados com água. Já nos testes realizados com bagaço de cana, o sinal de condutividade mostrou-se insuficiente para a detecção de líquido. Para os medidores de infravermelho testados com água, os mesmos apresentaram alguns sintomas de instabilidade e variabilidade. Quando testados com cana, os medidores de infravermelho também apresentam instabilidade e variâncias distintas que dependem da posição do medidor no difusor e, consequentemente, da compactação do leito de fibra. Infere-se então que um aumento da variância do sinal pode ser um indicativo de um aumento da compactação do leito e, consequentemente, de diminuição da sua permeabilidade. / Diffusers can be used to extract sucrose from sugarcane and sugarbeet, to extract tannin from black acacia bark and to extract oil from oleaginous plants. Although they operate simply from a mechanical and chemical point of view, problems that occur in their operation can compromise the extraction efficiency. The modeling, simulation and optimization of biomass diffusers is essential to better understand such problems and propose optimized strategies for their project and operation. In this context, the main objective of the proposed thesis is to model and simulate the operation of a ten- stage biomass diffuser to later optimize it mono and multi-objectively considering the possibility of connection among all extraction stages. In the case of the mono-objective optimization, in which a fixed liquid imbibition flow rate is considered, the main objective of the optimization is to maximize the concentration of solute in the liquid that leaves the diffuser from random changes in the connectivity coefficients of the diffuser. For the multi-objective optimization, the liquid imbibition flow rate entering the diffuser is considered variable. Therefore, the optimization of the system requires the maximization of two objectives simultaneously (the maximization of the solute concentration in the liquid and minimization of the final solute concentration in the biomass) from random changes in the diffuser connectivity coefficients. In addition, since the minimization of operational problems is related to the monitoring of liquid level height in the fiber bed, different types of signals for level measurement were tested on an experimental extraction stage. From the simulation and optimization results, we can conclude that new connections among the stages of the diffuser can optimize the extraction process which runs counter to common sense that connections must be sequential. In the case of the mono-objective optimization, 82 to 89% of the fluid is directed to the next stage along the extraction stages (except for stage 6, in which this value is 100%). The recirculation of the fluid to the same stage is more pronounced in the final stages (stages 1 to 4), with the optimized diffuser having 14 to 18% of fluid recirculation for the same stage in these stages while for the remaining stages the recirculation varies between 0 and 11%. For the initial stages (stages 5, 7, 8 and 9), fluid recirculation to the previous stage is more prominent, varying from 6 to 16% while for the remaining stages it is only 0 to 2%. Stage 6, in turn, is the only one that connects only to the next stage. For the multi-objective optimization, similar results were found, with the probability of 85 to 100% of the fluid being circulated to the next stage being between 93 and 99%. Regarding recirculation to the same stage, the probability of 0 to 15% of the fluid being recirculated varies from 58 to 79% for stages 1 to 4, from 49 to 55% for the medium stages 5, 6 and 7 and from 60 to 90% for the last three stages (stages 8, 9 and 10). For the connection to the immediately preceding stage, the probability that 0 to 15% of the fluid being directed to the previous stage is greater in stages 1, 2, 8 and 9, ranging from 31 to 38%. For liquid level measurement, two different types of signals, electrical conductivity and infrared radiation were tested. The tests were first carried out only with water and then with sugarcane bagasse. Conductivity meters were stable and repeatable when tested with water. In the tests performed with sugarcane bagasse, the conductivity signal was insufficient for level measurement. For water-tested infrared meters, they have shown some instability symptoms and variability. When tested with cane, the infrared meters exhibit instability and distinct variances that depend on the position of the meter in the diffuser and, consequently, bed compactation. It can be then inferred that an increase in the signal variance can be also an indicative of increased bed compactation and, consequently, decreased bed permeability.