This paper proposes a rational strategy for retrofitting Reinforced Concrete (RC) frame structures, based on combing member- and structure-level techniques, in order to achieve optimal design objectives within the framework of a potentially Multi-Criteria Performance-Based approach. Composite materials, with emphasis on Fiber-Reinforced Polymers (FRP), can be employed in local strengthening interventions, such as confinement of columns, hence representing a viable member-level technique. Therefore, this paper presents the key features of a novel numerical procedure that implements a genetic algorithm capable of selecting the “fittest” solution among the technically feasible ones consisting of alternative configurations of steel bracing systems (as structure-level technique) and FRP-based member-level interventions. The paper reports the main assumptions about the representations of “individuals” as part of this genetic algorithm procedure, along with some details on the algorithm operations (i.e. selection, crossover and mutation). Finally, a preliminary application is proposed.

Composite materials as part of an optimal strategy for seismic retrofitting of RC frames

FALCONE, ROBERTO;LIMA, CARMINE;FAELLA, Ciro;MARTINELLI, Enzo
2016

Abstract

This paper proposes a rational strategy for retrofitting Reinforced Concrete (RC) frame structures, based on combing member- and structure-level techniques, in order to achieve optimal design objectives within the framework of a potentially Multi-Criteria Performance-Based approach. Composite materials, with emphasis on Fiber-Reinforced Polymers (FRP), can be employed in local strengthening interventions, such as confinement of columns, hence representing a viable member-level technique. Therefore, this paper presents the key features of a novel numerical procedure that implements a genetic algorithm capable of selecting the “fittest” solution among the technically feasible ones consisting of alternative configurations of steel bracing systems (as structure-level technique) and FRP-based member-level interventions. The paper reports the main assumptions about the representations of “individuals” as part of this genetic algorithm procedure, along with some details on the algorithm operations (i.e. selection, crossover and mutation). Finally, a preliminary application is proposed.
978-988-14480-26
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11386/4678386
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