Thermal analysis of massive concrete foundations at early ages

• Ano de defesa: 2024
• Autor(a) principal: Machado, Amanda Moreira Lima
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Palavras-chave em Português: Análise térmica; Concreto massa; Elementos finitos; Fundações de torres eólicas; Formação de etringita tardia; Fissuração térmica; Thermal analysis; Mass concrete; Finite element simulation; Delayed ettringite formation; Thermal cracking; CNPQ::ENGENHARIAS::ENGENHARIA CIVIL
• Link de acesso: http://repositorio.ufc.br/handle/riufc/78927

The power generation from wind has been showing high rates of production growth, especially in the Northeast region of Brazil. To produce this type of energy, it is necessary to build tall towers that are supported on bulky concrete foundations. In addition, the increasing verticalization of urban centers in concentrated areas is intertwined with the need for measures to ensure the structural stability of tall buildings, such as the use of mass concrete foundation blocks. For the construction of these types of structures, measures are needed both to optimize the concreting process, which involves previous planning and experience of the labor involved, and to avoid the appearance of pathological manifestations, such as cracks and delayed ettringite formation, due to the changes in the thermomechanical behavior of these concrete structures caused by the exothermic reactions of cement hydration. Thus, this dissertation aimed to evaluate the thermal behavior of mass concrete structures by performing computational predictions in two software (Ansys and b4cast) and applying a case study in the field. The influence of some input parameter variation on the results obtained and the reliability of the prediction models were verified. The analysis showed that the main difference identified between the results obtained in the two software was concerning the time to reach the internal temperature peaks. In general, the b4cast software presented higher temperature results than Ansys and was closer to the field measurements. The influence caused by the variation of the specific heat of concrete was the most significant among the parameters evaluated, causing a closer approximation of the predictive models with the measured data, especially about the values of maximum temperatures. Finally, the case study was fundamental to implement, in the field, the casting plan developed for the structure and to identify the main challenges, improvements, and care during the process of prediction, casting, and monitoring of mass concrete structures.