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.

ALVES, C. A. A study concerning homeostasis and population development of collagen fibers. 2017. 88 f. Tese (Doutorado em Física) – Centro de Ciências, Universidade Federal do Ceará, Fortaleza, 2017. / Submitted by Pós-Graduação em Física (posgrad@fisica.ufc.br) on 2017-11-21T16:35:18Z No. of bitstreams: 1 2017_tese_caalves.pdf: 8939939 bytes, checksum: 5cbf75fd845e26cdee776ee15fc2cfbf (MD5) / Approved for entry into archive by Giordana Silva (giordana.nascimento@gmail.com) on 2017-11-22T18:55:25Z (GMT) No. of bitstreams: 1 2017_tese_caalves.pdf: 8939939 bytes, checksum: 5cbf75fd845e26cdee776ee15fc2cfbf (MD5) / Made available in DSpace on 2017-11-22T18:55:25Z (GMT). No. of bitstreams: 1 2017_tese_caalves.pdf: 8939939 bytes, checksum: 5cbf75fd845e26cdee776ee15fc2cfbf (MD5) Previous issue date: 2017 / Collagen is a generic name for the group of the most common proteins in mammals. It confers mechanical stability, strength and toughness to the tissues, in a large number of species. In this work we investigate two properties of collagen that explain in part the choice by natural selection of this substance as an essential building material. In the first study the property under investigation is the homeostasis of a single fiber, i.e., the maintenance of its elastic properties under the action of collagen monomers that contribute to its stiffening and enzymes that digest it. The model used for this purpose is a onedimensional chain of linearly elastic springs in series coupled with layers of sites. Particles representing monomers and enzymes can diffuse along these layers and interact with the springs according to specified rules. The predicted lognormal distribution for the local stiffness is compared to experimental data from electronic microscopy images and a good concordance is found. The second part of this work deals with the distribution of sizes among multiple collagen fibers, which is found to be bimodal, hypothetically because it leads to a compromise between stiffness and toughness of the bundle of fibers. We propose a mechanism for the evolution of the fiber population which includes growth, fusion and birth of fibers and write a Population Balance Equation for that. By performing a parameter estimation over a set of Monte Carlo simulations, we determine the parameters that best fit the available data. / Collagen is a generic name for the group of the most common proteins in mammals. It confers mechanical stability, strength and toughness to the tissues, in a large number of species. In this work we investigate two properties of collagen that explain in part the choice by natural selection of this substance as an essential building material. In the first study the property under investigation is the homeostasis of a single fiber, i.e., the maintenance of its elastic properties under the action of collagen monomers that contribute to its stiffening and enzymes that digest it. The model used for this purpose is a onedimensional chain of linearly elastic springs in series coupled with layers of sites. Particles representing monomers and enzymes can diffuse along these layers and interact with the springs according to specified rules. The predicted lognormal distribution for the local stiffness is compared to experimental data from electronic microscopy images and a good concordance is found. The second part of this work deals with the distribution of sizes among multiple collagen fibers, which is found to be bimodal, hypothetically because it leads to a compromise between stiffness and toughness of the bundle of fibers. We propose a mechanism for the evolution of the fiber population which includes growth, fusion and birth of fibers and write a Population Balance Equation for that. By performing a parameter estimation over a set of Monte Carlo simulations, we determine the parameters that best fit the available data.

Calculations on stress, strain and deformation are typically made using finite element methods (FEM). An alternative to this is a rigid bodydynamics approach also called lumped element method (LEM). LEM implements deformation by replacing single rigid bodies with multiple subbodies, which are in turn connected with joints (also called constraints) that allow movement between the sub-bodies. If instead of FEM, a lumped element method is used to simulate deformable objects, sufficient accuracy can be obtained at a much lower cost, complexity-wise. A lumped element method-approach could for example achieve real-time simulationspeed. The purpose of this thesis is to expand upon previous work into LEM, analyzing how the rigid bodies and constraints should be configured to produce accurate results for a wider range of objects. Specifically, beams of varying cross section and curved beam axis, as well as other test cases. The simulated values are compared with the analytic predictions given by Euler-Bernoulli beam theory. These simulations are implemented using the AGX Dynamics physics engine from Algoryx Simulation AB. One intended application area of LEM is crane arms. This motivates the focus on analyzing how LEM behaves when simulating beams, as they represent the most basic version of crane arms. Simulation and testing of full crane objects was unfortunately not accomplished, partly due to a lack of convenient testing data. Further work is needed to confirm that LEM behaves well for these expanded cases as well. In addition to the analysis section above, the purpose is also to implement a pipeline for automatic conversion of a CAD-model to a lumped element version in AGX. Specifically, a CAD-model given in the 3D-modeling software SpaceClaim.

Indiana University-Purdue University Indianapolis (IUPUI) / While computed tomographic angiography (CTA) has emerged as a powerful noninvasive option that allows for direct visualization of arterial stenosis(AS), it cant assess the hemodynamic abnormality caused by an AS. Alternatively, trans-stenotic pressure gradient (TSPG) and fractional flow reserve (FFR) are well-validated hemodynamic indices to assess the ischemic severity of an AS. However, they have significant restriction in practice due to invasiveness and high cost. To fill the gap, a new computational modality, called InVascular has been developed for non-invasive quantification TSPG and/or FFR based on patient's CTA, aiming to quantify the hemodynamic abnormality of the stenosis and help to assess the therapeutic/surgical benefits of treatment for the patient. Such a new capability gives rise to a potential of computation aided diagnostics and therapeutics in a patient-specific environment for ASs, which is expected to contribute to precision planning for cardiovascular disease treatment. InVascular integrates a computational modeling of diseases arteries based on CTA and Doppler ultrasonography data, with cutting-edge Graphic Processing Unit (GPU) parallel-computing technology. Revolutionary fast computing speed enables noninvasive quantification of TSPG and/or FFR for an AS within a clinic permissible time frame. In this work, we focus on the implementation of inlet and outlet boundary condition (BC) based on physiological image date and and 3-element Windkessel model as well as lumped parameter network in volumetric lattice Boltzmann method. The application study in real human coronary and renal arterial system demonstrates the reliability of the in vivo pressure quantification through the comparisons of pressure waves between noninvasive computational and invasive measurement. In addition, parametrization of worsening renal arterial stenosis (RAS) and coronary arterial stenosis (CAS) characterized by volumetric lumen reduction (S) enables establishing the correlation between TSPG/FFR and S, from which the ischemic severity of the AS (mild, moderate, or severe) can be identified. In this study, we quantify TSPG and/or FFR for five patient cases with visualized stenosis in coronary and renal arteries and compare the non-invasive computational results with invasive measurement through catheterization. The ischemic severity of each AS is predicted. The results of this study demonstrate the reliability and clinical applicability of InVascular.

Cardiovascular disease, including coronary artery disease and aortic valve stenosis, impacts tens of millions of people annually and carries a massive global economic burden. Advances in medical imaging, hardware and software are leading to an increased interest in the field of cardiovascular computational modelling to help combat the devastating impact of cardiovascular disease. Lumped parameter modelling (a branch of computational modelling) holds the potential of aiding in the early diagnosis of these diseases, assisting clinicians in determining personalized and optimal treatments and offering a unique in-silico setting to study cardiac and circulatory diseases due to its rapid computation time, ease of automation and relative simplicity. In this thesis, cardiovascular lumped parameter modelling is presented in detail and a patient-specific framework capable of simulating blood flow waveforms and hemodynamic data in the heart and coronary arteries was developed. The framework used only non-invasive clinical data and images (Computed Tomography images, echocardiography data and cuff blood pressure) as inputs. The novel model was then applied to 19 patients with aortic stenosis who underwent transcatheter aortic valve replacement. The diastolic coronary flow waveforms in the left anterior descending artery, left circumflex artery and right coronary artery were validated against a previously developed patient-specific 3D fluid-structure interaction model for all 19 subjects (pre and post intervention). There were strong qualitative and quantitative agreements between the two models. After the procedure, aortic valve area and net pressure gradient across the aortic valve improved for almost all the subjects. As for the hemodynamic data, according to the model, there was substantial variability in terms of the increase or decrease post intervention. On average, left ventricle workload and maximum left ventricle pressure decreased by 4.5% and 13.0% while cardiac output, mean arterial pressure and resting heart rate increased by 9.9%, 6.9% and 1.9% respectively. There were also subject specific changes in coronary blood flow (37% had increased flow in all three coronary arteries, 32% had decreased flow in all coronary arteries, and 31% had both increased and decreased flow in different coronary arteries). All in all, a proof-of-concept cardiac and coronary lumped parameter framework was developed, validated, and applied in this thesis. / Thesis / Master of Applied Science (MASc) / The heart is a vital part of the cardiovascular system, which helps deliver and regulate blood flow through the entire human body. The coronary arteries are a crucial part of this system since they deliver blood directly to heart muscles. For numerous reasons, the cardiovascular system can become diseased over time and require clinical treatment. Coronary artery disease and aortic valve stenosis are among the most prevalent cardiovascular diseases globally. While medical imaging on its own is a crucial part of the disease management and treatment process, advanced computational models can further enhance the process and provide clinics with data and predictions they might otherwise miss. In this thesis, a patient specific computational framework capable of simulating blood flow waveforms and cardiovascular data in the heart and coronary arteries using only non-invasive clinical data and images was developed and validated. The novel model was applied to a series of patients with aortic stenosis who underwent heart valve replacement with the aim of studying the impact on coronary blood flow and global cardiovascular metrics.

This master thesis addresses the development of an automatic numerical tool for thermal analysis, focusing on thermal systems comprising a printed circuit board assembly and cooling case structure. The project, conducted in collaboration with Unibap, aims to enhance the design process of space computer modules by automating middle steps between design software and thermal analysis results. The numerical tool employs the lumped parameter method, implemented in Python, as an alternative to traditional finite element analysis to efficiently generate thermal results. Informed decisions can be made using the tool regarding case-cooling and the selection of components requiring cooling, thus optimizing manufacturing costs and design complexity. The project results in the successful development of the automatic numerical tool. A unique method to derive values for thermal resistance within the case structure is also utilized. Though experimental test results for verification are pending, the functionality of the tool is presented along with results from a thermal analysis where it is used.

A mathematical model of blood flow in infants with hypoplastic left heart syndrome (HLHS) was improved by adding cerebral autoregulation. This is the process by which blood vessels constrict or dilate to keep blood flow steady in certain organs during pressure changes. The original lumped parameter model transformed the fluid flow into an electrical circuit. Its behavior is described using a system of thirty-three coupled differential equations that are solved numerically using a fourth-order Runge-Kutta method implemented in MATLAB. A literature review that includes a discussion of autoregulation mechanisms and approaches to modeling them is followed by a description of the model created for this paper. The model is based on the baroreceptor or neurogenic theory of autoregulation. According to this theory, nerves in certain places within the cardiovascular system detect changes in blood pressure. The brain then compensates by sending a signal to blood vessels to constrict or dilate. The model of the control system responded fairly well to a pressure drop with a steady state error of about two percent. Running the model with or without the control system activated had little effect on other parameters, notably cardiac output. A more complete model of blood flow control would include autonomic regulation. This would vary more parameters than local autoregulation, including heart rate and contractility. This is suggested as a topic of further research.

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Yes / In this work a simulation of detailed steady state model of an industrial fluid catalytic cracking (FCC) unit with a newly proposed six-lumped kinetic model which cracks gas oil into diesel, gasoline, liquefied petroleum gas (LPG), dry gas and coke. Frequency factors, activation energies and heats of reaction for the catalytic cracking kinetics and a number of model parameters were estimated using a model based parameter estimation technique along with data from an industrial FCC unit in Sudan. The estimated parameters were used to predict the major riser fractions; diesel as 0.1842 kg-lump/kg-feed with a 0.81% error while gasoline as 0.4863 kg-lump/kg-feed with a 2.71% error compared with the plant data. Thus, with good confidence, the developed kinetic model is able to simulate any type of FCC riser with six-lump model as catalyst-to-oil (C/O) ratios were varied and the results predicted the typical riser profiles.

Two methods using lumped element (lumped parameter) methods to model flexible bodies have been presented. The methods are based on the concept of using a Guyan reduced stiffness matrix to describe the elasticity of a body. The component to be modeled has been divided into two parts using FE software and the mass and inertia tensor for the respective part of the component have been retrieved. The first method has been based on including the elements from the stiffness matrix in compliant constraints. The compliant constraints have been derived and a prototype has been implemented in MATLAB. It has been shown that using compliant constraints and stiffness parameters from a Guyan reduced stiffness matrix it is possible, with highly accurate results, to describe the deformation of a flexible body in multibody simulations. The second method is based on springs and dampers and has been implemented in the simulation environment Dymola. The springs and dampers have been constructed to include coupling elements from a Guyan reduced stiffness matrix. It has been shown that using the proposed method it is possible, with highly accurate results, to describe the static deformation of a flexible body. Further, using dynamic simulations of a full robot manipulator model, it has been shown that it is possible to use the spring-damper model to capture the deformation of the links of a manipulator in dynamic simulations with large translations and rotations.