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The master's thesis focuses on creating a numerical model of a polymeric heat sink with emphasis on its significant thermal conductivity anisotropy. This anisotropy is caused by highly thermally conductive graphite filler. Its final orientation is given by the melt flow inside the mould cavity during injection molding. The numerical model is created on the basis of a heat sink prototype subjected to experimental measurements, whose physical conditions are reliably replicated by the model. The determination of anisotropy is divided into two parts. The qualitative part is based on the fracture analysis of the heat sink prototype and determines the principal directions of the conductivity tensor in individual sections of the geometry. The computation of principal conductivities falls into the quantitative part, in which this task is formulated as an inverse heat conduction problem. The input data for the proposed task are experimentally obtained temperatures at different places of the geometry. The values of principal conductivities are optimized to minimize the difference between the measured and simulated temperatures.

It is very important to develop efficient but still accurate and stable numerical methods for solving heat and mass transfer processes in many industrial applications. The thesis deals with an inverse heat conduction problem which is used to compute boundary conditions (temperatures, heat flux or heat transfer coefficient). Nowadays, two approaches are often used for inverse task - sequential estimation and whole domain estimation. The main goal of this work is to develop a new approach, the so-called sub-domain method, which emphasizes advantages just as reduce disadvantages of both methods mentioned above. This approach is then tested on generated prototypic data and on data from real experiments. All methods are compared with respect to accuracy of results as well as to computational efficiency.

Numerical simulations of thermal processes are based on known geometry, material properties, initial and boundaries conditions. The massive use of these simulations in the metallurgical industry (for example for simulation of heat treatment of steel) is limited by the knowledge of precise boundary conditions, which are not easy to determine in compare to other input parameters. Empirical formulas are not sufficiently accurate for most non-trivial processes. Therefore, it is necessary to obtain the boundary conditions by experimental way. Boundary conditions can not be measured directly. The boundary conditions are determined by solving inverse heat conduction problem based on the measured temperature records. This doctoral thesis focuses on two types of the inverse heat conduction problems, which are poorly solved by existing methods. The first type are tasks that contains sharp increase/decrease in the values of the boundary conditions. Two new approaches are proposed and compared in this thesis for this type of tasks. The second type are tasks with non-stationary and non-homogeneous cooling. Three new methods were developed for this case. They are applied for the case of water cooling of vertical aluminum sample. The base characteristics of the current task is inhomogeneous cooling. One part of the surface is cooled intensively by flowing water in contrast to the other part of surface which is cooled only with low intensity since it is protected from direct contact with water by the vapor layer (Leidenfrost effect). The positions of these two part of surface are not stationary (they change during the experiment). The newly developed methods are compared to each other.

A têmpera dos aços envolve a austenitização de uma peça seguida por um resfriamento rápido para promover a formação de microestrutura martensítica. É necessário avaliar os meios de têmpera para manter o processo de têmpera sob controle. Os parâmetros mais importantes no processo de resfriamento são o coeficiente de transferência de calor e/ou o fluxo de calor entre o meio de têmpera e a peça a ser resfriada. Um dos métodos de se avaliar os meios de têmpera (meios de resfriamento) e saber o que está acontecendo dentro da peça durante o resfriamento do ponto de vista térmico é o problema inverso de condução de calor. O problema inverso de condução de calor consiste na determinação de parâmetros como fluxo de calor, taxa de resfriamento e temperatura em qualquer posição através da peça, assim como o coeficiente de transferência de calor. Esses parâmetros são obtidos a partir de medições de temperatura em um ou mais pontos dentro da peça. O escopo deste trabalho foi desenvolver um software baseado no problema inverso condução de calor para avaliar meios de resfriamento para têmpera. A validação deste código foi feita usando água, óleo de soja, óleo mineral e solução aquosa de NaNO3. / Steels quenching involves part austenitization followed by a fast cooling to promote martensitic microstructure formation. It is necessary to evaluate quenchants in order to keep the quenching process under control. The most important cooling process parameters are the heat transfer coefficient and/or the heat flux between the quenchant and the part to be cooled. One of the methods to evaluate quenchants (cooling media) and to know what is happening inside the part during the cooling in the thermal point of view is the inverse heat conduction problem. The inverse heat conduction problem consists in the determination of parameters like heat flux, cooling rate and temperature in any position across the part, as well as the heat transfer coefficient. These parameters are obtained from temperature measurements in one or more points inside the part. The scope of this work was to develop a software based in the inverse heat conduction problem in order to evaluate quenchants for quenching. The validation of this code was made using water, soybean oil, mineral oil and NaNO3 aqueous solution.

A têmpera dos aços envolve a austenitização de uma peça seguida por um resfriamento rápido para promover a formação de microestrutura martensítica. É necessário avaliar os meios de têmpera para manter o processo de têmpera sob controle. Os parâmetros mais importantes no processo de resfriamento são o coeficiente de transferência de calor e/ou o fluxo de calor entre o meio de têmpera e a peça a ser resfriada. Um dos métodos de se avaliar os meios de têmpera (meios de resfriamento) e saber o que está acontecendo dentro da peça durante o resfriamento do ponto de vista térmico é o problema inverso de condução de calor. O problema inverso de condução de calor consiste na determinação de parâmetros como fluxo de calor, taxa de resfriamento e temperatura em qualquer posição através da peça, assim como o coeficiente de transferência de calor. Esses parâmetros são obtidos a partir de medições de temperatura em um ou mais pontos dentro da peça. O escopo deste trabalho foi desenvolver um software baseado no problema inverso condução de calor para avaliar meios de resfriamento para têmpera. A validação deste código foi feita usando água, óleo de soja, óleo mineral e solução aquosa de NaNO3. / Steels quenching involves part austenitization followed by a fast cooling to promote martensitic microstructure formation. It is necessary to evaluate quenchants in order to keep the quenching process under control. The most important cooling process parameters are the heat transfer coefficient and/or the heat flux between the quenchant and the part to be cooled. One of the methods to evaluate quenchants (cooling media) and to know what is happening inside the part during the cooling in the thermal point of view is the inverse heat conduction problem. The inverse heat conduction problem consists in the determination of parameters like heat flux, cooling rate and temperature in any position across the part, as well as the heat transfer coefficient. These parameters are obtained from temperature measurements in one or more points inside the part. The scope of this work was to develop a software based in the inverse heat conduction problem in order to evaluate quenchants for quenching. The validation of this code was made using water, soybean oil, mineral oil and NaNO3 aqueous solution.