Utilization of physics-based simulated earthquake ground motions for performance assessment of tall buildings – validation, collapse safety, and machine learning tools for regional risk evaluation

Limited data on strong earthquakes and their effects on structures poses one of the main challenges of making reliable risk assessments of tall buildings. For instance, while the collapse safety of tall buildings is likely controlled by large magnitude earthquakes with long durations and high low-frequency content, there are few available recorded ground motions to evaluate these issues. The influence of geologic basins on amplifying ground motion effects raises additional questions. Absent recorded motions from past large magnitude earthquakes, physics-based ground motion simulations provide an attractive alternative. This talk will focus on utilization of simulated ground motions for performance assessment of tall buildings with the following overall goals: (1) developing confidence in the use of simulated ground motions through comparative assessments of recorded and simulated motions; (2) identifying important characteristics of extreme ground motions for collapse safety of tall buildings; (3) exploring areas where simulated ground motions provide significant advantages over recorded motions for performance-based engineering. First, we will examine an effort to validate the use of physics-based simulations in engineering applications by using ground motions simulated with Southern California Earthquake Center’s (SCEC) Broadband Platform (BBP). Next, collapse risk of tall buildings in the Los Angeles basin will be investigated by contrasting conventional risk assessments with assessments obtained utilizing the SCEC CyberShake simulations. Finally, we will quantify the influence of basin effects on seismic collapse risk and present machine learning approaches for identification of efficient intensity measures and development of reliable collapse classification algorithms. Opportunities for future work will be discussed.

Bio:
Nenad Bijelić is currently a postdoctoral scholar at the Unit of Applied Mechanics, University of Innsbruck, Austria. He obtained his Ph.D. (2018) and M.S. (2014) from Stanford University, USA, and B.S. (2010) from University of Zagreb, Croatia all in civil engineering. In 2012 he received the Fulbright Science and Technology award to study earthquake engineering in the USA. His research is in the area of structural and earthquake engineering focusing on dynamics of nonlinear systems and application of statistical and machine learning tools. Focus of his recent research was on reliable risk assessment of tall buildings located in sedimentary basins through high-performance computing and utilization of emergent technologies in earthquake simulations. He is a reviewer for Natural Hazards Review and served as a reviewer for the 11^th U.S. National Conference on Earthquake Engineering.