Building Risk Assessment Model after Earthquake Using Rapid Assessment Method

Abstract

This study proposes a seismic risk assessment model for reinforced concrete buildings following an earthquake by applying the Rapid Visual Screening (RVS) method, adapted to suit Thailand’s urban and geotechnical context. The assessment process combines standardized scoring from FEMA P-154 with field-surveyed physical indicators such as building height, number of stories, plan irregularities, presence of shear walls, and visible damage. These factors are converted into a Final RVS Score through basic scoring and adjustment factors (Score Modifiers). A logistic regression model is then employed to estimate the collapse probability based on the Final RVS Score. Field surveys were conducted on five buildings located in Bangkok, an area characterized by soft soil and moderate seismic risk. The analysis revealed a moderate negative correlation between building height and RVS score (ρ = -0.625), and a moderate positive correlation between building height and collapse probability (ρ = +0.675). One of the case study buildings, a 15-story structure with structural deterioration and irregular features, showed a high collapse probability of 73.11%. The adapted model demonstrated its effectiveness for rapid, cost-efficient screening without requiring detailed structural drawings or in-depth engineering analysis. It allows for prioritized decision-making in post-earthquake building inspections, potentially reducing unnecessary demolitions and supporting sustainable urban resilience. However, further enhancement incorporating dynamic structural behavior and digital inspection tools such as point cloud data is recommended to improve accuracy.