Memory as a Common Asset. Algorithmic Generative Representations for the Reconstruction of the Community Identity after the Earthquake

After a calamity, a community wonders about which common assets to found the reconstruction and therefore its future identity. The study introduces an innovative generative simulation protocol that draws typological and parametric representations of reconstruction scenarios according to the masterplan and the recommendations for color, materials, and architectural lexicon, and also socio-economic issues. The working strategy starts from the morphological tuning between the building and living in respect of maintaining the place character. The townscape is the result of generative algorithmic representations for the city of Amatrice; the protocol proposes reconstruction models according to the architectural and environmental town pattern book. The graphic document typologically summarizes the key elements of the environmental character; it is possible to parameterize these data and build a tool for the generation of urban digital models to fix the block reconstruction. The need for this operational tool arises considering the numerous failures of reconstruction practices after recent earthquakes and rebuilding the city not only as a technical and technological response but also as a social responsibility to include commons and therefore memory and landscape.