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Journal Article

AI-based optimization framework for the design of seismic retrofitting of reinforced concrete frame structures based on direct costs and EAL

Di Trapani Fabio, Sberna A.P., Giuseppe C. Marano
Computers and Structures — August 2022
PDF DOI
AI-based optimization framework for the design of seismic retrofitting of reinforced concrete frame structures based on direct costs and EAL

Abstract

This paper proposes a novel framework for the optimized seismic retrofitting design of reinforced concrete frame structures, to minimize retrofitting-related costs and simultaneously controlling the expected annual loss (EAL). The framework makes use of artificial intelligence techniques, adopting a genetic algorithm-based optimization algorithm.

structural optimizationexisting structuresseismic retrofittingExpected Annual Lossesgenetic algorithmsconcrete structuresFRPsteel bracesOpenSees

Highlights

  • A novel AI-based framework for the seismic retrofitting cost optimization of RC buildings is proposed.
  • The framework also controls service life cost through the evaluation of the expected annual loss (EAL).
  • The method can provide multiple topological and sizing optimization of the reinforcement.
  • The optimization process is based on a genetic algorithm handling a fiber-section model realized in OpenSees.