Stock-constrained optimization of diagrid exoskeletons using reclaimed steel for seismic retrofit of RC buildings

The reuse of structural steel is gaining increasing attention due to its sustainability benefits and the inherent durability of the material. However, this practice requires a reversal of the conventional design process, as the structural elements are defined a priori. Moreover, in Italy, a large portion of the existing reinforced concrete (RC) buildings constructed between the 1960s and 1980s exhibits high seismic vulnerability, making seismic retrofitting interventions necessary. This research aims to address both issues by applying steel reuse to the seismic retrofit of existing RC structures through the adoption of external diagrid-type systems incorporating reused steel elements. A Python-based algorithm is developed and implemented within a workflow created in the Rhino/Grasshopper environment and managed through a genetic algorithm. At each step of the optimization process, the diagrid structure—whose design variables correspond to nodal coordinates—is initially generated using new steel elements, which are subsequently replaced, with reused elements while satisfying structural and geometric constraints. In Italy, most steel suitable for reuse originates from industrial buildings or electrical transmission towers and mainly consists of L -shaped sections. For this reason, the algorithm includes the capability to manage such profiles by coupling them in pairs or in groups of four, enabling a broader range of section configurations. This approach increases the probability of achieving an optimal match between reused and new elements. The proposed methodology enables the exploitation of Italian steel reuse datasets and provides a framework for extending the service life of both steel components and existing RC structures.