Algoritmo genético aplicado à seleção multicritérios de isolantes térmicos em edificações

• Ano de defesa: 2018
• Autor(a) principal: Stamoulis, Michel Nikolaos
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Tecnológica Federal do Paraná; Ponta Grossa; Brasil; Programa de Pós-Graduação em Engenharia Mecânica; UTFPR
• Palavras-chave em Português: Algorítmos genéticos; Materiais isolantes; Conforto humano; Eficiência industrial; Processo decisório por critério múltiplo; Genetic algorithms; Insulating materials; Human comfort; Efficiency, Industrial; Multiple criteria decision making; CNPQ::ENGENHARIAS::ENGENHARIA MECANICA; Engenharia Mecânica
• Link de acesso: http://repositorio.utfpr.edu.br/jspui/handle/1/3777

The global necessity of energy consumption reduction, in front of the economic and environment impacts issues due the electricity energy generation is responsible to motivate researches to improving the energy efficiency of buildings. Among the strategies used to improve this energy efficiency, stands out the application of optimized thermal insulation on buildings walls. Thus, in order to contribute to the improvement of the cost x benefit relation, this study aims to provide an optimization tooling for insulation selection choice applied on industrial shed building roof. Beyond the thermal comfort and high cost considered on selection process, some hygrothermic properties also has been analysed to obtain the best insulation layer option. To implement this optimization technique, a several thermo-energetic simulations of the environment were performed using the DOMUS® software applying 4 types of insulation material (Polyurethane, Expanded Polystyrene, Rockwool and Glass Wool) combining 10 thickness ranging from 0.5 cm to 5 cm, with purpose of obtaining different thermal comfort indexes (PPD - Predicted Percentage of Dissatisfied) and thermal load. Posteriorly, was executed the best insulation ranking from the weights assigned to the parameters in the objective function, using the technique of the genetic algorithm (AG) applied to the multicriteria selection, being implemented in MATLAB® software. The optimization results showed that the polyurethane (PU) insulation, applied with a thickness of 1 cm, is the best installation option on the roof, considering the building functional parameters, occupant metabolic activity, clothes index and contour conditions in which it affects the thermal comfort index. Taking into account the NBR 15220 standard that establishes a global coefficient of 2 W / m²K for the insulated roof, the Rock Wool with 2 cm thickness proved to be the best choice of insulation layer material. In this way, it was observed that the optimum selection of the thermal insulation could vary according to the objective function applied and the methodology for decision-making analysis. In addition, the use of DOMUS® combined with optimization algorithms proved to be an assertive tool in the selection of materials, promoting cost reduction and increased energy efficiency in buildings.