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Main achievements:
· Identification of structural condition indicators suitable to be incorporated in a Bayesian probabilistic network for the quantitative risk assessment (In cooperation with WP1); i.e. clearly measurable and updatable (through inspection) condition indicators suitable to assess structural damage of given building classes.
· Development and validation of updatable analytical or numerical models to predict the behavior of the identified condition indicators during a seismic event.
· Development of a methodology to use residual structural displacements (so far neglected albeit crucial) as a damage indicator.
· Development of a strategy to acquire and extract information relevant to structural damage from aerial and terrestrial photogrammetric field data (In cooperation with WP6).
· Development and validation of a methodology to use photogrammetric field data to update predictive models.
Added value to the research field and society:
· Allow significant reduction of uncertainties due to engineering judgment or expert opinion in the evaluation of structural damage. Structural damage, either directly (e.g. property losses) or indirectly (e.g. casualties, business losses) is the main cause of earthquake related losses.
· Updatable condition indicators clearly measurable before, during and after the earthquake represent a significant improvement to the state-of-the-art of structural damage assessment, where in most of the cases only the pre-event situation is taken into account.
· Provide deep knowledge about residual structural displacements that can be used also in the performance based design of new structures or in the refined assessment of single existing buildings.
· Provide the structural information needed to apply the solid theoretical framework developed in WP1 for the consistent quantitative and rational assessment of seismic risk.
· Provide tools to assess structural performance using photogrammetric field data.
