Accurate predictions of macroscopic multiphase flow properties, such as relative permeability and capillary pressure, are necessary for making key decisions in reservoir engineering. These properties are usually measured experimentally, but pore-scale network modeling has become an efficient alternative for understanding fundamental flow behavior and prediction of macroscopic properties. In many cases network modeling gives excellent agreement with experiment by using models physically representative of real media. Void space within a rock sample can be extracted from high resolution images and converted to a topologically equivalent network of pores and throats. Multiphase fluid transport is then modeled by imposing mass conservation at each pore and implementing the Young-Laplace equation in pore throats; the resulting pressure field and phase distributions are used to extract macroscopic properties. Advancements continue to be made in making network modeling predictive, but one limitation is that artificial (e.g. constant pressure gradient) boundary conditions are usually assumed; they do not reflect the local saturations and pressure distributions that are affected by flow and transport in the surrounding media. In this work we demonstrate that flow behavior at the pore scale, and therefore macroscopic properties, is directly affected by the boundary conditions. Pore-scale drainage is modeled here by direct coupling to other pore-scale models so that the boundary conditions reflect flow behavior in the surrounding media. Saturation couples are used as the mathematical tool to ensure continuity of saturations between adjacent models. Network simulations obtained using the accurate, coupled boundary conditions are compared to traditional approach and the resulting macroscopic petrophysical properties are shown to be largely dependent upon the specified boundary conditions. The predictive ability of network simulations is improved using the novel network coupling scheme. Our results give important insight into upscaling as well as approaches for including pore-scale models directly into reservoir simulators. / text

Dans cette thèse, des simulations PN de séchage sont comparées à des données expérimentales obtenues dans le séchage d´un réseau de micro-fluidique 2D représentatif dans du SiO2 soumis à des conditions thermiques variables dans le but d’identifier les phénomènes physiques à l´échelle des pores qui sont les plus influents. A partir de cette étude, un PN efficace non-isotherme est développé. Ce modèle incorpore i) les phénomènes associés à la dépendendence en température de l´invasion à l´échelle des pores, c´est à dire l´invasion capillaire sous effet thermique et le flux de vapeur ainsi que ii) le transport secondaire induit par d´épais films liquides observé dans les expériences de microfluidique. Cette étude prouve clairement que le comportement macroscopique du séchage est fondamentalement dirigé par le gradient de température imposé sur le PN ainsi que par le transport capillaire secondaire. En accord avec la littérature, les schémas d´invasion que l´on trouve dans l´invasion percolatrice avec l´évaporation progressive d´amas individuels sont observés dans le séchage à variation de température locale négligeable;des gradients où la température diminue à partir de la surface (gradient de température négatif)peut stabiliser le front de séchage, qui évolue entre la phase gazeuse invasive et la phase liquide qui recule, alors qu´une température qui augmente à partir de la surface (gradient de température positif) amène à la déstabilisation de la phase liquide avec une percée prématurée de la branche gazeuse et l’initiation d´un deuxième front de séchage qui migre dans la direction opposé de celle du front de séchage original. Une attention particulière est prêtée aux régimes distincts que l´on trouve dans le second cas (gradient positif) parce qu´ils sont associés à différents procédés d´invasion à l´échelle des pores. Plus précisément, la dépendance en température de la tension de surface établit l´ordre d´invasion tant que la phase liquide est connectée au groupe liquide principal (que l´on trouve généralement pendant la première période de séchage). En revanche,l´étude détaillée des mécanismes de transfert de la vapeur met l´accent sur le fait que la diffusion de la vapeur à travers la région partiellement saturée peut contrôler les distributions des phases gazeuses et liquides à l´échelle des pores pendant la période de séchage lorsque la phase liquide est déconnectée en petits groupes. Cela est aussi lié à la croissance des amas induite par la condensation partielle de la vapeur. Cette thèse montre et discute en détail que cet effet ne dépend pas seulement de la direction et magnitude du gradient de température pour une distribution de tailles de pores donnée mais qu’en plus le taux d´évaporation influence le mécanisme de croissances des amas. Cela indique que la migration du liquide pendant la phase de séchage de milieux poreux peut être contrôlé par l’interaction des gradients thermiques et du taux de séchage. En somme, l´étude du séchage sous effet thermique des réseaux de pores 2D révèle des phénomènes complexes à l´échelle des pores, généralement aussi anticipés dans le séchage des milieux poreux réels. Cela mène au développement d´un modèle mathématique efficace au niveau des pores basés sur des découvertes expérimentales. Cette thèse démontre la manière dont ce modèle peut être appliqué afin de comprendre et développer des procédés de séchage modernes basés sur la simulation du transfert de masse sous effet thermique à l´échelle des pores / In this thesis, PN simulations of drying are compared with experimentally obtained data fromdrying of a representative 2D microfluidic network in SiO2 under varying thermal conditions withthe aim to identify governing physical pore scale effects. Gravity and viscous effects aredisregarded in this thesis. Instead drying with slight local temperature variation and drying withimposed thermal gradients are studied. Based on this investigation, a powerful non-isothermalPNM is developed. This model incorporates i) the phenomena associated with the temperaturedependency of pore scale invasion, namely thermally affected capillary invasion and vapor flow aswell as ii) the secondary effects induced by wetting liquid films of different morphology. This studyclearly evidences that the macroscopic drying behavior is fundamentally dictated by thetemperature gradient imposed on the PN and moreover by the secondary capillary invasion aswell. In agreement with literature, invasion patterns as in invasion percolation with progressiveevaporation of single clusters are observed in drying with negligible local temperature variation;gradients with temperature decreasing from the surface (negative temperature gradient) canstabilize the drying front, evolving between the invading gas phase and the receding liquid phase,whereas temperature increasing from the surface (positive temperature gradient) leads todestabilization of the liquid phase with early breakthrough of a gas branch and initiation of asecond invasion front migrating in opposite direction to the evaporation front receding from theopen surface of the PN. Special attention is paid on the distinct drying regimes found in thesituation of a positive gradient because they are associated with different pore scale invasionprocesses. More precisely, temperature dependency of surface tension dictates the order ofinvasion as long as the liquid phase is connected in a main liquid cluster (usually found during thefirst period of drying). In contrast to this, detailed study of the vapor transfer mechanismsemphasizes that vapor diffusion through the partially saturated region can control the pore leveldistributions of liquid and gas phase during the period of drying when the liquid phase isdisconnected into small clusters. This is also related to the cluster growth induced by partialcondensation of vapor. It is shown and discussed in detail in this thesis that this effect not onlydepends on direction and height of the temperature gradient for a given pore size distribution butthat moreover the overall evaporation rate influences the cluster growth mechanism. This indicatesthat liquid migration during drying of porous media might be controlled by the interplay of thermalgradients and drying rate. In summary, the study of thermally affected drying of the 2-dimensionalPN reveals complex pore scale mechanisms, usually also expected in drying of real porous media.This leads to the development of a strong mathematical pore scale model based on experimentalfindings. It is demonstrated how this model might be applied to understand and develop moderndrying processes based on the simulation of thermally affected pore scale mass transfer

Water quality and river/stream ecosystems are important for all living creatures. To protect human health, aquatic life and the surrounding ecosystem, a considerable amount of time and money has been spent on sampling and monitoring streams and rivers. Water quality monitoring and analysis can help researchers predict and learn from natural processes in the environment and determine human impacts on an ecosystem. Measurements such as temperature, pH, nitrogen concentration, algae and fish count collected along the network are all important factors in water quality analysis. The main purposes of the statistical analysis in this thesis are (1) to assess the relationship between the variable measured in the water (response variable) and other variables that describe either the locations on/along the stream network or certain characteristics at each location (explanatory variable), and (2) to assess the degree of similarity between the response variable values measured at different locations of the stream, i.e. spatial dependence structure. It is commonly accepted that measurements taken at two locations close to each other should have more similarity than locations far away. However, this is not always true for observations from stream networks. Observations from two sites that do not share water flow could be independent of each other even if they are very close in terms of stream distance, especially those observations taken on objects that move passively with the water flow. To model stream network data correctly, it is important to quantify the strength of association between observations from sites that do not share water.

Real-time digital simulation of electrical machines and drives is an efficient approach to evaluate the true behavior of newly designed machines and controllers before applying them in a real system. State-of-the-art real-time digital simulators aim to offer a precise replica for different parts of an electrical drive. By the aid of these powerful simulators and hardware-in-the-loop (HIL) simulation, design engineers are able to test their new controllers or machines against a virtual motor drive which has been previously modeled and tested off-line. Interaction between different parts of the electrical drive, especially under hazardous and abnormal conditions, can then be studied in a cost-effective manner. Although many studies about the optimized models of power electronic drives and digital controllers for real-time simulation have been done, the real-time models of electrical machines are still limited to the lumped parameter electric circuit models. This is mainly due to the complexity of a detailed electrical machine model which makes it computationally expensive. In this thesis geometrical real-time permeance network models (PNMs) of induction machines are developed which can accommodate the local phenomena inside an electric machine such as saturation and slotting. For this purpose, numerical methods inside the model are optimized to reduce the computation time. Novel nonlinear solution algorithms are also developed to address the problem of real-time simulation of nonlinear systems. Next, the proposed model is linked with other parts of an electric drive to develop a PNM-based real-time induction motor drive. A comparison of the results obtained through real-time simulation and experiment shows their agreement. / Power Engineering and Power Electronics

The world population is growing and becoming more connected whereby disease transmission is becoming an increasingly important issue. To learn more about disease spread, honey bees (Apis mellifera) could provide an animal-model system for network transmission. The honey bees have both an individual and a social defense against pathogens, their diseases are well studied and they enable studies on hundreds of individuals. The genetic relatedness is believed to be one of many important factors for disease transmission. A hypothesis is that the more closely related the honey bees are the more interactions will occur. In this study, the genetic relatedness in honey bees was analyzed by the use of microsatellite-DNA primers, in a multiplex PCR. Of the 18 microsatellite-DNA primers that were evaluated, the loci HB-C16-05, A007, AC006, HB-C16-02, AP043 and UN351 showed the highest variation. However, when applied on a larger material, the PCR-products did not yield any chromatograms that were possible to score. Many factors possibly affecting the result are discussed and further efforts will be made to improve the method and thereby determine genetic relatedness.

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This thesis covers a variety of analytical approaches that validate the use of the EvacuatioNZ model on high-rise building analysis. Through performing a number of sensitivity analyses, several model deficiencies as well as functional limitations were improved upon and part of the model developments are continued based on the previous research done by two Master's students at the University of Canterbury. In this thesis, data from three evacuations were considered for different validating aspects. These evacuations were, a hypothetical 21-storey hotel building located in the United States of America, which was previously simulated using Simulex and EXIT89; a trial evacuation that was carried out in a 13-storey office building located in Canada; and a fire drill conducted at a 21-storey office building located in Australia. Overall, the results indicated that the EvacuatioNZ is able to produce reasonable predictions of the total evacuation time regardless of the number of floors involved. The component testing also showed satisfactory outcomes regarding the involvement of disabled occupants, complexity of node configurations, and different pre-movement time distributions. However, the current model still has a number of limitations that need to be verified and tested. These include the preferred route function and the connection problem for long stairs. Further research should also be carried out on the use of the Evacuation model on other types of building structures so as to increase the confidence level of utilizing the EvacuatioNZ model for general applications.

The aim of this thesis is to provide a modelling approach and simulation framework that allows for emergent dynamics in multi-nephron systems to be studied. The ultimate intent of this research is to provide an approach to renal modelling that is capable of predicting whole-kidney function from the dynamics of individual nephrons, and can therefore be of practical use to clinicians. The contributions of this thesis are: / • A modelling approach—hierarchical dynamical networks—which combines complex networks and graph automata into a single modelling framework. This approach explicitly captures the structure and interactions in multi-nephron systems, and decouples the structure and behaviour of the model. This approach allows emergent dynamics to be easily explored and analysed. / • The development of a multi-nephron model that produces valid behaviour and renders the simulation of whole-kidney function from the dynamics of individual nephrons computationally tractable. Using this model, the emergent effects of the couplings and interactions between nephrons can be investigated. / • An investigation into the dynamics of multi-nephron systems that focuses on whole-system and hierarchical properties rather than the dynamics of individual nephrons. As part of this investigation, the dynamics of a 72-nephron system are analysed—a system significantly larger than existing multi-nephron models. / • A study of whole-system stability in response to localised impairments in nephron function. This is the first study of the emergent dynamics of impaired nephron function, and serves as an illustration of how the emergent dynamics produced by renal diseases may be predicted and analysed. The impaired multinephron systems are shown to exhibit very stable behaviour, which we contend is a feature of both the model and the kidney proper. / • The computational cost of the model is shown to be low enough that the simulation of whole-kidney function is feasible for the first time. It is also demonstrated that simulations can be easily distributed across multiple computers, resulting in a significant gain in performance. An implementation of the model that supports parallel and distributed execution is presented, based on the Join Calculus. / • In order to predict whole-kidney function, a whole-kidney model must be constructed. This thesis proposes two approaches for automatically generating such models. / I conclude that the modelling and analysis techniques presented in this thesis allow for emergent dynamics to be studied in large multinephron systems. This work demonstrates that, for the first time, simulation of whole-kidney function from the dynamics of individual nephrons is tractable. Furthermore, the work provides a basis for predicting emergent effects of localised renal disease. With the continued development of this model, we hope that significant insight will be gained into the onset, progression and treatment of renal diseases.

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