Otimização de pavimentos de lajes lisas maciças protendidas

• Ano de defesa: 2022
• Autor(a) principal: Toscano, Caroline Galvão
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Laje de concreto; Concreto protendido; Otimização estrutural; Algoritmos genéticos
• Link de acesso: http://www.repositorio.ufc.br/handle/riufc/70913

The structural solution chosen for the slabs of a building is a very important factor, as it represents a very significant cost at the end of the work. The use of prestressing, and in particular nonadherent prestressing, has become increasingly popular, as well as its application to flat slabs for allowing greater spans, greater architectural flexibility and agility in execution and a lower cost of labor. These factors have made prestressed flat slabs attractive solutions in some cases. Even presenting a higher consumption of concrete in relation to the ribbed slabs, these have a simpler formwork system. For a prestressed flat slab to present a competitive cost, considering the defined topology of the columns, it is necessary to pay attention to the choice of the slab height, the quantity and the cable layout. In this sense, the use of optimization techniques are great tools to obtain an optimal detailing of a flat slab floor. Normally, optimization models considering a complete floor have been used, but the applications have been reduced to isolated slabs. The objective of this work is to develop an optimization model for prestressed flat slab floors according to the recommendations of NBR 6118/2014, seeking to minimize material and labor costs. The design variables are the slab thickness and parameters associated with the number of cables and their vertical profiles in both directions, all of the discrete type. The grid analogy model is used in the structural analysis, with the prestressing effect modeled as an equivalent load, to evaluate displacements and stresses to verify constraints related to the ultimate and service limit states. The optimization problem was solved by adapting an open source genetic algorithm, which has been successfully applied to discrete structural optimization problems. The solutions obtained were attractive in terms of generating a preliminary solution that can help the designer to define the initial project.