Critical care is provided to patients who require intensive monitoring and often the support of failing organs. Cardiovascular and circulatory diseases and dysfunctions are extremely common in this group of patients. However, cardiac disease states are highly patient-specific and every patient has a unique expression of the disease or underlying dysfunction. Clinical staff must consider many combinations of different disease scenarios based on frequently conflicting or confusing measured data on a patient’s condition. Successful diagnosis and treatment therefore often rely on the experience and intuition of clinical staff, increasing the likelihood for clinical errors. A cardiovascular (CVS) computerized model that uniquely represents the patient and underlying dysfunction or disease is developed. The CVS model is extended to account for the known physiologic mechanisms during spontaneous breathing and mechanical ventilation, thus increasing the model’s accuracy of representing a critically ill patient in the intensive care unit (ICU). The extended CVS model is validated by correctly simulating several well known circulatory mechanisms and interactions. An integral-based system parameter identification method is refined and extended to account for much smaller subsets of available input data, as usually seen in critical care units. For example, instead of requiring the continuous ventricle pressure and volume waveforms, only the end-systolic (ESV) and end-diastolic (EDV) volume values are needed, which can be even further reduced to only using the global end-diastolic volume (GEDV) and estimating the ventricle volumes. These changes make the CVS model and its application to monitoring more pplicable to a clinical environment. The CVS model and integral-based parameter identification approach are validated on data from porcine experiments of pulmonary embolism (PE), positive end-expiratory pressure (PEEP) titrations at different volemic levels, and 2 different studies of induced endotoxic (septic) shock. They are also validated on 3 adrenaline dosing data sets obtained from published studies in humans. Overall, these studies are used to show how the model and realistic clinical measurements may be used to provide a clear clinical picture in real-time. A wide range of clinically measured hemodynamics were successfully captured over time. The integral-based method identified all model parameters, typically with less than 10% error versus clinically measured pressure and volume signals. Moreover, patient-specific parameter relationships were formulated allowing the forward prediction of the patient’s response towards clinical interventions, such as administering a fluid bolus or changing the dose of an inotrope. Hence, the model and methods are able to provide diagnostic information and therapeutic decision support. In particular, tracking the model parameter changes over time can assist clinical staff in finding the right diagnosis, for example an increase in pulmonary vascular resistance indicates a developing constriction in the pulmonary artery caused by an embolus. Furthermore, using the predictive ability of the model and developed methods, different treatment choices and their effect on the patient can be simulated. Thus, the best individual treatment for each patient can be developed and chosen, and unnecessary or even harmful interventions avoided. This research thus increases confidence in the clinical applicability and validity of this overall diagnostic monitoring and therapy guidance approach. It accomplishes this goal using a novel physiological model of the heart and circulation. The integral-based parameter identification methods take dense, numerical data from diverse measurements and aggregate them into a clearer physiological picture of CVS status. Hence, the broader accomplishment of this thesis is the transformation, using computation and models, of diverse and often confusing measured data into a patient-specific physiological picture - a new model-based therapeutic.

Diffuse liver disease is a growing problem and a major cause of death worldwide. In the final stages the treatment often involves liver resection or transplant and in deciding what course of action is to be taken it is crucial to have a correct assessment of the function of the liver. The current “gold standard” for this assessment is to take a liver biopsy which has a number of disadvantages. As an alternative, a method involving magnetic resonance imaging and mechanistic modeling of the liver has been developed at Linköping University. One of the obstacles for this method to overcome in order to reach clinical implementation is the speed of the parameter estimation. In this project the methodology of metamodeling is tested as a possible solution to this speed problem. Metamodeling involve making models of models using extensive model simulations and mathematical tools. With the use of regression methods, clustering algorithms, and optimization, different methods for parameter estimation have been evaluated. The results show that several, but not all, of the parameters could be accurately estimated using metamodeling and that metamodeling could be a highly useful tool when modeling biological systems. With further development, metamodeling could bring this non-invasive method for estimation of liver function a major step closer to application in the clinic.

Graduate / 0485

Thermal modelling is of great importance in all electric machines but especially in permanent magnet synchronous machines (PMSMs). The thermally fragile permanent magnets (PMs) can more easily be demagnetized at high temperatures. When high speed machines are considered, heat extraction surfaces are small due to the higher energy density. This thesis focuses on the thermal modelling of a high speed slotless PMSM using analytical techniques. From literature it is clear that analytical distributed models have not reached its full potential in thermal modelling of electric machines. Thermal experiments on high speed electric machine, including rotor PM temperature measurements are not commonly found in literature. The thermal behaviour of each component of the machine is influenced by the overall temperature distribution. The widely used lumped parameter (LP) cylindrical component model derived by Mellor et al. is used to derive a LP model of the entire machine. A two dimensional (2-D) analytical distributed model is derived for the rotor PM using the separation of variables method. Three of the boundaries are assumed to be of the convection type and the fourth of constant heat flow type. Different convection coefficients are assumed to exist in the radial and axial directions. The distributed model is verified using COMSOL R and good correlation is shown. The distributed model is used to determine the temperature distribution in the PM and the convection heat flow in the axial direction. Loss calculation is an integral part of thermal modelling. Temperature changes in an electric machine is due to the interaction between the heat generation (losses) and heat removal. The losses found in a high speed slotless PMSM are investigated. A 2-D analytical magnetic model is used to determine the stator lamination loss as well as the stator winding eddy current loss. A simple LP model is derived for the rotor eddy current loss. Due to the relatively large resistivity of the shielding cylinder and PM material, the rotor eddy current loss is a significant part of the total machine loss. The tangential current width is determined empirically in this thesis but a 3-D distributed model which includes end space effects and skin depth could also be used. A large part of thermal modelling is empirically based. The convection and interface resistances are determined through a set of experiments in this thesis. The measured and calculated convection coefficients correlated well for both forced and natural convection cooling. A large temperature increase found during the no-load test can be attributed to large bearing loss, possibly due to axial loading. The LP model is modified to include the phenomena found during the experiments. The thermal model is used to predict the temperatures of a high speed PMSM at rated load and speed. Although the PM is not heated above the Curie temperature, demagnetization is still possible. According to the model, the machine will not be able to operate at full load and speed for extensive periods due to mechanical stress limits being exceeded. The temperature distribution of the PM could not be verified since the temperatures in the air gap and end space could not be measured. It is expected that axial heat flow will be larger than what is currently predicted by the distributed model. A sensitivity analysis was used to investigate the influence of the thermal resistances and losses on the machine temperatures. Methods for reducing the rotor eddy current loss and interface resistances are also discussed. The first contribution of this thesis is the 2-D analytical distributed model for the PM of a high speed PMSM. Hot spots and 2-D heat flow can be analysed using this model. Combining the LP and 2-D analytical distributed models is another contribution. This combines the simplicity and fast solution times of the LP model with the 2-D thermal distribution of the analytical distributed model. The systematic experimental investigation of the thermal behaviour of a high speed PMSM is a further contribution. / Thesis (Ph.D. (Electrical Engineering))--North-West University, Potchefstroom Campus, 2011.

Thermal modelling is of great importance in all electric machines but especially in permanent magnet synchronous machines (PMSMs). The thermally fragile permanent magnets (PMs) can more easily be demagnetized at high temperatures. When high speed machines are considered, heat extraction surfaces are small due to the higher energy density. This thesis focuses on the thermal modelling of a high speed slotless PMSM using analytical techniques. From literature it is clear that analytical distributed models have not reached its full potential in thermal modelling of electric machines. Thermal experiments on high speed electric machine, including rotor PM temperature measurements are not commonly found in literature. The thermal behaviour of each component of the machine is influenced by the overall temperature distribution. The widely used lumped parameter (LP) cylindrical component model derived by Mellor et al. is used to derive a LP model of the entire machine. A two dimensional (2-D) analytical distributed model is derived for the rotor PM using the separation of variables method. Three of the boundaries are assumed to be of the convection type and the fourth of constant heat flow type. Different convection coefficients are assumed to exist in the radial and axial directions. The distributed model is verified using COMSOL R and good correlation is shown. The distributed model is used to determine the temperature distribution in the PM and the convection heat flow in the axial direction. Loss calculation is an integral part of thermal modelling. Temperature changes in an electric machine is due to the interaction between the heat generation (losses) and heat removal. The losses found in a high speed slotless PMSM are investigated. A 2-D analytical magnetic model is used to determine the stator lamination loss as well as the stator winding eddy current loss. A simple LP model is derived for the rotor eddy current loss. Due to the relatively large resistivity of the shielding cylinder and PM material, the rotor eddy current loss is a significant part of the total machine loss. The tangential current width is determined empirically in this thesis but a 3-D distributed model which includes end space effects and skin depth could also be used. A large part of thermal modelling is empirically based. The convection and interface resistances are determined through a set of experiments in this thesis. The measured and calculated convection coefficients correlated well for both forced and natural convection cooling. A large temperature increase found during the no-load test can be attributed to large bearing loss, possibly due to axial loading. The LP model is modified to include the phenomena found during the experiments. The thermal model is used to predict the temperatures of a high speed PMSM at rated load and speed. Although the PM is not heated above the Curie temperature, demagnetization is still possible. According to the model, the machine will not be able to operate at full load and speed for extensive periods due to mechanical stress limits being exceeded. The temperature distribution of the PM could not be verified since the temperatures in the air gap and end space could not be measured. It is expected that axial heat flow will be larger than what is currently predicted by the distributed model. A sensitivity analysis was used to investigate the influence of the thermal resistances and losses on the machine temperatures. Methods for reducing the rotor eddy current loss and interface resistances are also discussed. The first contribution of this thesis is the 2-D analytical distributed model for the PM of a high speed PMSM. Hot spots and 2-D heat flow can be analysed using this model. Combining the LP and 2-D analytical distributed models is another contribution. This combines the simplicity and fast solution times of the LP model with the 2-D thermal distribution of the analytical distributed model. The systematic experimental investigation of the thermal behaviour of a high speed PMSM is a further contribution. / Thesis (Ph.D. (Electrical Engineering))--North-West University, Potchefstroom Campus, 2011.

Graduate / 0485

No description available.

We develop a new approach to the analysis of pseudodifferential operators with small parameter 'epsilon' in (0,1] on a compact smooth manifold X. The standard approach assumes action of operators in Sobolev spaces whose norms depend on 'epsilon'. Instead we consider the cylinder [0,1] x X over X and study pseudodifferential operators on the cylinder which act, by the very nature, on functions depending on 'epsilon' as well. The action in 'epsilon' reduces to multiplication by functions of this variable and does not include any differentiation. As but one result we mention asymptotic of solutions to singular perturbation problems for small values of 'epsilon'.

No description available.

In this research, a recent version of the Boreal Ecosystem Productivity Simulator (BEPS), called BEPS-TerrainLab, was adapted to northern peatlands and evaluated using observations made at the Mer Bleue bog located near Ottawa, Ontario, and the Sandhill fen located near Prince Albert, Saskatchewan. The code was extended and modified with a major focus on the adequate representation of northern peatlands' multi-layer canopy and the associated processes related to energy, water vapour and carbon dioxide fluxes through remotely-sensed leaf area index (LAI) maps. An important prerequisite for the successful mapping of LAI based on remote sensing imagery is the accurate measurement of LAI in the field with a standard technique such as the LAI-2000 plant canopy analyzer. As part of this research, a quick and reliable method to determine shrub LAI with the LAI-2000 instrument was developed. This method was used to collect a large number of LAI data at the Mer Bleue bog for the development of a new remote sensing-based methodology using multiple endmember spectral unmixing that allows for separate tree and shrub LAI mapping in ombrotrophic peatlands. A slight modification of this methodology allows for its application to minerotrophic peatlands and their surrounding landscapes. These LAI maps were used to explicitly represent the tree and shrub layers of the Mer Bleue bog and the tree and shrub/sedge layers of the Sandill fen within BEPS-TerrainLab. The adapted version of BEPS-TerrainLab was used to investigate the in fluence of mescoscale topography (Mer Bleue bog) and macro- and mesoscale topography (Sandhill fen) on wetness, evapotranspiration, and gross primary productivity during the snow-free period of 2004. This research suggests that future peatland ecosystem modelling efforts at regional and continental scales should include a peatland type-specific differentiation of macro- and mesoscale topographic effects on hydrology, to allow for a more realistic simulation of peatlands' soil water balance. This is an important prerequisite for the reduction of currently existing uncertainties in wetlands' contribution to North America's carbon dioxide and methane annual fluxes from an ecosystem modelling perspective.