Description
The seismic upgrading of existing RC structures has become a timely challenge that often civil engineers are meant to deal with. Although this particular design problem can be solved adopting an appropriate combination of member-level and structure-level techniques, it is really hard to find any design rule for supporting engineers in a similar choice. Thus, if such decision process is seen as an optimization problem, Genetic Algorithms (GAs) could be employed to search for the “fittest” upgrading solution, with respect to one predefined optimization criterion. The present paper outlines the latest advances in the implementation of a recently-formulated GA-based optimization procedure for the seismic upgrading of existing Reinforced Concrete (RC) structures, selecting a feasible and code compliant solution, obtained by combining FRP jacketing of RC columns (as member-level technique) with the introduction of steel braces (as structure-level technique). Recently, novel optimization criteria have been adopted, not only accounting for the initial intervention costs, but also for the environmental costs, accounting for Life-Cycle-Assessment (LCA) of all the operations required for of both member- and structure-level interventions. At each procedure iteration, the feasibility of a “population” of potential upgrading solutions is evaluated with respect to a previously-defined objective function and, then, some “genetic operators” are handled to generate new potential upgrading solutions with the aim of gradually increasing their cost-effectiveness. The paper focuses on the comparison between the “optimal” seismic upgrading solutions for an ideal RC existing building, suggested by the GA-based procedure, adopting different optimization objectives, accounting for both economic and environmental costs.
