Multi-Objective Optimization of FRP Jackets for Improving the Seismic Response of Reinforced Concrete Frames

Abstract

Abstract:In this study, a multi-objective Genetic Algorithm (GA) optimization procedure is proposed for the seismic retrofitting of Reinforced Concrete (RC) building frames via Fiber-Reinforced Polymer (FRP) jackets. The optimization problem is solved via numerically efficient but accurate Finite-Element (FE) models able to take into account the strengthening and ductility increase contribution for a given FRP jacketing configuration. Based on a reference RC frame case study, an optimization approach aimed to maximize the frame ductility and minimize the FRP volume/cost is proposed, by taking into account different FRP jackets thicknesses for the internal and external columns and well as for each separate frame floor. In doing so, careful consideration is paid also to the expected collapse mechanism for the frame and the approach to embed a further objective able to control the collapse mechanism into the procedure is described. The results show the potential of the approach, which not only provides the entire Pareto Front of the multi-objective optimization problem, but also allows for general considerations about the influence of the design variables on the response of a given RC building.

Optimal FRP Jacket Placement in RC Frame Structures Towards a Resilient Seismic Design

“…where N is the number of columns' plastic hinges (i.e., twice the number of columns in an RC frame), and COV original is related to R i values before implementation of the seismic retrofitting, and is used as a scale factor in Equation (16). For optimization of the objective function, two meta-heuristic algorithms were applied: (1) genetic algorithm (GA), and (2) particle swarm optimization (PSO).…”

“…The first objective function was the amount of FRP and the second one was a measure of the seismic performance of the frame in a way that the spectral acceleration corresponding to the collapse prevention performance level was maximized through incremental dynamic analysis (IDA). Last but not least, Chisari and Bedon [16] and Chisari and Bedon [17] proposed a multi-objective genetic algorithm procedure for the seismic retrofitting of RC buildings. The objective aimed at finding the most competitive solution in terms of cost and performance, while satisfying the performance-based design (serviceability and ultimate) damage levels.…”

Reinforced Concrete Slab Optimization with Simulated Annealing

“…• Evolution Strategies (ES) [5]; • Evolutionary Programming (EP) [6]; • Genetic Algorithms (GAs) [7]; and…”

Editorial for the "FRP Structures" Special Issue

“…Their paper presents an adaptive procedure for the kinematic limit analysis of FRP reinforced masonry vaults through applications. As in the case of (Chisari and Bedon, 2016), an optimization problem is presented, but an approach that relies on a new Genetic Algorithm NURBS-based general framework-recently presented by the same authors-is taken into account. The basic idea consists into exploiting the NURBS structure of a CAD geometric 3D model for a given reinforced masonry vault, in order to define an adaptive rigid body assembly on which an (upper bound) limit analysis can be performed.…”

“…While it is well-known that a strength and ductility enhancement can be expected from the use of FRP strips and jackets compared to a given bare reinforced concrete frame, recent studies only focused on the optimization of the FRP jackets themselves, in the form of cost, weight and structural benefits. In the paper from Chisari and Bedon (2016), this open topic is further assessed by means of a genetic algorithm optimization problem. A key aspect, in that study, is given by the multiobjective optimization approach, as well as by the possible control-via a local reinforcement technique-of the global collapse mechanism for a given concrete structure.…”