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Modelling of friction and convective coefficients in a dry transformer

Authors: Sousa, Catarina Corte-Real Côncio;

Modelling of friction and convective coefficients in a dry transformer

Abstract

Esta dissertação baseia-se no estudo, axi-simétrico 2D, de transferência de calor por convecção, em condutas de refrigeração de transformadores secos, por meio de simulações de CFD (ANSYS Fluent). O objetivo foi a definição de um modelo matemático descritivo dos coeficientes médios de transferência de calor por convecção e de fricção, em relação à convecção natural e forçada, num canal cilíndrico vertical anular, sob condições de fluxo de calor uniforme nas paredes. O fluido de refrigeração neste tipo de transformador é o ar, por convecção natural e um sistema AC é assumido na base do transformador para convecção forçada. Todas as condições do sistema e propriedades do fluido foram construídas e definidas no programa Fluent. Foram realizados vários testes prévios, principalmente para selecionar adequadamente a malha de estudo e o modelo fluido-dinâmico. O estudo paramétrico foi construído tendo em conta 45 geometrias, 8 fluxos de calor na parede, 4 velocidades para simulações de convecção forçada, enquanto para convecção natural foi criada e assumida uma correlação linear de velocidade de fluxo de calor. Isto corresponde a 1800 simulações. Após análise e tratamento dos dados, foi realizada uma regressão não linear no MATLAB, visando as funções descritivas dos coeficientes referidos. Obteve-se um ajuste adequado através de redes neurais artificiais (RNA), fornecendo previsões do coeficiente de convecção de erros relativos inferiores a 12% para aproximadamente 80% dos casos e inferior a 15% para aproximadamente 70% dos casos de coeficiente de atrito, relativamente aos resultados obtidos das simulações. Concluiu-se uma precisão superada das previsões de RNA, comparada com o modelo mais adequado de literatura considerado, para o coeficiente de transferência de calor por convecção.

This thesis stands for a 2D axisymmetric study of convection heat transfer, within cooler ducts of dry type transformers, by means of CFD simulations (ANSYS Fluent). The purpose was the definition of descriptive functions for the mean heat transfer and friction coefficients, regarding free and forced convection, within a vertical cylindrical annular duct, under isoflux conditions (uniform wall heat flux). Dry-transformer type uses air as cooling system by natural convection and an AC system is assumed at the base of the transformer for forced convection. All system conditions and fluid properties were constructed and defined at Fluent program. Several pre-tests were performed, mainly in order to properly select the studied mesh and fluid-dynamic model. The parametric study was assembled accounting for 45 geometry’s designs, 8 values for wall heat flux, 4 velocities for forced convection simulations, while for natural convection a linear correlation heat flux-velocity was assumed. This corresponds to 1800 simulations. After data analysis and treatment, a non-linear regression was performed in MATLAB, aiming for the descriptive functions of convection heat transfer and friction coefficients, obtained thru CFD. A successful fitting was obtained through artificial neural networks (ANN), providing predictions for convective coefficient of relative errors inferior to 12% for approximately 80% of cases and inferior to 15% for approximately 70% of cases for friction coefficient. It was concluded an overcome accuracy of the ANN’s predictions shown, compared to the most fitted literature’s model considered, for convective heat transfer coefficient.

Mestrado em Engenharia Química

Country
Portugal
Related Organizations
Keywords

Convection Heat Transfer, Thermal Modelling, Dry Transformers, CFD analysis

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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