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SUMMARY:Utilization of physics-based simulated earthquake ground motions f
 or performance assessment of tall buildings – validation\, collapse safe
 ty\, and machine learning tools for regional risk evaluation
DTSTART:20181130T121500
DTEND:20181130T130000
DTSTAMP:20260407T115140Z
UID:9aa92fc264dff38424411bf4e3300e3cc72a879c12bf0865aa0414bf
CATEGORIES:Conferences - Seminars
DESCRIPTION:Dr. Nenad Bijelić\, postdoctoral scholar at the Unit of Appl
 ied Mechanics\, University of Innsbruck\, Austria\nLimited data on strong 
 earthquakes and their effects on structures poses one of the main challeng
 es of making reliable risk assessments of tall buildings. For instance\, w
 hile the collapse safety of tall buildings is likely controlled by large m
 agnitude 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 raise
 s additional questions. Absent recorded motions from past large magnitude 
 earthquakes\, physics-based ground motion simulations provide an attractiv
 e alternative. This talk will focus on utilization of simulated ground mot
 ions for performance assessment of tall buildings with the following overa
 ll goals: (1) developing confidence in the use of simulated ground motions
  through comparative assessments of recorded and simulated motions\; (2) i
 dentifying important characteristics of extreme ground motions for collaps
 e safety of tall buildings\; (3) exploring areas where simulated ground mo
 tions 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 m
 otions simulated with Southern California Earthquake Center’s (SCEC) Bro
 adband Platform (BBP). Next\, collapse risk of tall buildings in the Los A
 ngeles basin will be investigated by contrasting conventional risk assessm
 ents with assessments obtained utilizing the SCEC CyberShake simulations. 
 Finally\, we will quantify the influence of basin effects on seismic colla
 pse risk and present machine learning approaches for identification of eff
 icient intensity measures and development of reliable collapse classificat
 ion algorithms. Opportunities for future work will be discussed.\n\nBio:\n
 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 Un
 iversity of Zagreb\, Croatia all in civil engineering. In 2012 he received
  the Fulbright Science and Technology award to study earthquake engineerin
 g in the USA. His research is in the area of structural and earthquake eng
 ineering focusing on dynamics of nonlinear systems and application of stat
 istical and machine learning tools. Focus of his recent research was on re
 liable risk assessment of tall buildings located in sedimentary basins thr
 ough high-performance computing and utilization of emergent technologies i
 n earthquake simulations. He is a reviewer for Natural Hazards Review and 
 served as a reviewer for the 11th U.S. National Conference on Earthquake E
 ngineering.
LOCATION:GC B1 10 https://plan.epfl.ch/?room=GCB110
STATUS:CANCELLED
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