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Sofia Maria Carrato DinizSidnea Eliane Campos RibeiroJose Marcio Fonseca CalixtoSebastiao Salvador Real PereiraElayne Marques Silva2019-08-13T07:57:48Z2019-08-13T07:57:48Z2017-08-29http://hdl.handle.net/1843/BUOS-AUWM62Reinforced concrete (RC) structures are often subjected to deicing salts or in a marine environment; as such, a major problem in the durability of these structures is the corrosion of reinforcing steel. In this light, Fiber Reinforced Polymers (FRP), as noncorrosive materials, provide a promising prospect for use as reinforcement in concrete construction. FRP reinforcement may offer not only greater durability but also higher resistance and, consequently, potential gains throughout the lifecycle of the structure. Although the use of FRP bars as structural reinforcement shows great promise in terms of durability, the characteristics of this material led to new challenges in the design of FRP-RC components.Due to differences between the mechanical properties of steel and FRP, the reliability of FRPreinforced concrete (RC) beams shall be assessed. While a reasonable body of knowledge has been gathered regarding the reliability of FRP-RC beams with respect to ultimate limit states, the same is not true for serviceability of such beams. Since FRP is characterized by higher values of strength and lower Youngs modulus compared to steel, this implies that the design of FRP-RC structures will be influenced almost exclusively by serviceability limit states. In this study, a contribution to the development of semiprobabilistic design recommendations for FRP-RC beams, with respect to the serviceability limit state, is reported. Numerous equations have been proposed for computing the effective moment of inertia of FRP-RC members. Thisresearch also aims to select an equation for the calculation of the effective moment of inertia for FRP-RC beams assessed in this study. Since most of the variables involved in the problem (mechanical properties of concrete and FRP, geometric characteristics, model error, loads, etc.) are random, serviceability is established in probabilistic terms. In this context, Monte Carlo simulation is used in the probabilistic description of beam deflections, and in the computation of the probability of failure of designed beams with respect to the limit state of excessive deflections. Large probabilities of failure are found for this serviceability limit state according to current design recommendations. Suggestions are presented on simple, but effective ways to circumvent this limitation.Reinforced concrete (RC) structures are often subjected to deicing salts or in a marine environment; as such, a major problem in the durability of these structures is the corrosion of reinforcing steel. In this light, Fiber Reinforced Polymers (FRP), as noncorrosive materials, provide a promising prospect for use as reinforcement in concrete construction. FRP reinforcement may offer not only greater durability but also higher resistance and, consequently, potential gains throughout the lifecycle of the structure. Although the use of FRP bars as structural reinforcement shows great promise in terms of durability, the characteristics of this material led to new challenges in the design of FRP-RC components.Due to differences between the mechanical properties of steel and FRP, the reliability of FRPreinforced concrete (RC) beams shall be assessed. While a reasonable body of knowledge has been gathered regarding the reliability of FRP-RC beams with respect to ultimate limit states, the same is not true for serviceability of such beams. Since FRP is characterized by higher values of strength and lower Youngs modulus compared to steel, this implies that the design of FRP-RC structures will be influenced almost exclusively by serviceability limit states. In this study, a contribution to the development of semiprobabilistic design recommendations for FRP-RC beams, with respect to the serviceability limit state, is reported. Numerous equations have been proposed for computing the effective moment of inertia of FRP-RC members. Thisresearch also aims to select an equation for the calculation of the effective moment of inertia for FRP-RC beams assessed in this study. Since most of the variables involved in the problem (mechanical properties of concrete and FRP, geometric characteristics, model error, loads, etc.) are random, serviceability is established in probabilistic terms. In this context, Monte Carlo simulation is used in the probabilistic description of beam deflections, and in the computation of the probability of failure of designed beams with respect to the limit state of excessive deflections. Large probabilities of failure are found for this serviceability limit state according to current design recommendations. Suggestions are presented on simple, but effective ways to circumvent this limitation.Universidade Federal de Minas GeraisUFMGMétodo de Monte CarloEngenharia de estruturasConfiabilidade (Engenharia)Momentos de inérciaEffective moment of inertiaFRPBeamsDesign codesProbabilityDurabilityReliabilityFRP-reinforced structuresServiceability limit stateMonte Carlo simulationDeflectionsProbabilistic assessment of serviceability of FRP-reinforced concretebeamsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/openAccessporreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMGORIGINALdisserta__o_elayne_marques_rev_final.pdfapplication/pdf2052447https://repositorio.ufmg.br/bitstream/1843/BUOS-AUWM62/1/disserta__o_elayne_marques_rev_final.pdf93b1e9fe9f15c6717ae1888601bbc038MD51TEXTdisserta__o_elayne_marques_rev_final.pdf.txtdisserta__o_elayne_marques_rev_final.pdf.txtExtracted texttext/plain172973https://repositorio.ufmg.br/bitstream/1843/BUOS-AUWM62/2/disserta__o_elayne_marques_rev_final.pdf.txt3cec7e4bc665f61d0e0c539cb3d564caMD521843/BUOS-AUWM622019-11-14 22:05:18.563oai:repositorio.ufmg.br:1843/BUOS-AUWM62Repositório InstitucionalPUBhttps://repositorio.ufmg.br/oaiopendoar:2019-11-15T01:05:18Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false
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