Adaptive knowledge-based seismic risk assessment of existing reinforced concrete buildings using the SLaMA method

Abstract

This paper presents and discusses the ongoing developments towards the definition of a multi-knowledge level seismic assessment procedure for large-scale seismic risk applications. The procedure involves the analytical-mechanical SLaMA (Simple Lateral Mechanism Analysis) method and allows for an adaptive and updatable assessment of the seismic performance of buildings accounting for different data acquisition (knowledge) levels. By coupling this approach with vulnerability assessment survey forms, a range/domain of expected capacity curves of a structure can be obtained and used to evaluate the seismic safety and the expected economic losses according to the state-of-the-art procedures in literature. Moreover, the results of the analytical assessment method can be used to develop fragility curves through simplified spectrum-based procedures. Combining the results of the fragility analysis with the hazard analysis, the seismic risk of a structure can be assessed in terms of Mean Annual Frequency (MAF) of collapse, as well as in terms of Expected Annual Losses (EAL). The proposed SLaMA-based approach is illustrated for an existing reinforced concrete building. Results confirm the effectiveness of the methodology for seismic-risk assessment studies at large scale, thus overcoming the issue related to limited building information, yet allowing for a continuous update of the “digital twin” model as further data/information becomes available.