A comparative vulnerability assessment of reinforced concrete buildings using rapid visual screening methods and pushover analysis

One of the critical research areas of engineering science is the assessment of existing buildings' seismic vulnerability. Since the existing building stock is made up of structures that were built before design codes were developed, taking into account low or moderate design codes may make them vulnerable to an upcoming earthquake. To this end, rapid visual screening (RVS) methods can be used to identify building vulnerability before or after an earthquake. A number of RVS methods have been developed; however, it's critical to assess their accuracy in terms of their ability to reliably classify the state of building vulnerability. Therefore, this study offers an application of conventional RVS methods (FEMA P-154, RISK-UE Project, JBDPA), as well as a comparison of the results of the building safety level classification of 20 existing reinforced concrete buildings from Győr, Hungary. Pushover analysis was used as a detailed vulnerability assessment technique in addition to the RVS methods to evaluate one more reinforced concrete building. The findings of pushover analysis and RVS methods are contrasted to demonstrate how effectively RVS methods can be utilized to determine building vulnerability. Additionally, the findings of this study can be used to select an RVS method for commencing a pre-earthquake building assessment of the existing reinforced concrete building stock in the investigation area.

Keywords: earthquake; existing buildings; vulnerability assessment; rapid visual screening; machine learning; building damage state