61th Sogo Bosai seminar

  • Date : 25 Aug. 2022 15:00 - 16:30
  • Seminar
Date 25 Aug. 2022 15:00 - 16:30
Place S-519D of Uji campus or ONLINE via zoom
Target Researcher, Student, General

We are pleased to announce the 61st Sogo Bosai Seminar (Aug 25) as follows. We look forward to your kind participation.
Seminar will be delivered in English.
 
[Title]
Modeling of the Effects of Surface Geology on Earthquake-Induced Ground Shaking: Play the Cards We Are Dealt
(表層地質が地震動に及ぼす影響のモデル化:手持ちのカードで何ができるか?)

 
[Speaker]

Dr. Chuanbin Zhu

Program-Specific Assistant Professor, Sophisticated Earthquake Risk Evaluation (Hanshin Consultants) Division, DPRI, Kyoto University

 
[Date]
August 25 (Thur), 15:00 – 16:30
 
[Venue & Registration]
The seminar will be held in a hybrid manner both via Zoom and onsite. The venue is room S-519D of Uji campus, Kyoto University.
 
Please register here by August 23.
https://forms.gle/YivR75RtuoXqb1rL8
 
[Abstract]
When an earthquake occurs, a part of the energy stored in the Earth is released in the form of seismic waves that originate from the source, and the seismic waves pass through the earth. When they reach the Earth’s surface, the ground shakes. The intensity of ground shaking at a location is dependent on the surface and subsurface geological/physical/geotechnical conditions at the observation site. The impact of these geo-conditions on ground motions is referred to as “site effects”, “site amplification” or “site response”. The accurate characterization of site effects is crucial in the estimation of ground shaking from future earthquakes which our buildings or infrastructures of interest is designed to resist.
How well can we model site effects? This depends on the quantity and quality of information available. Often, due to time or budgetary constraints, we have to “play the cards we are dealt”, namely using the information we have in order to characterize site effects. Then it boils down to the question how well we can capitalize on the various information at hand, using physics-based modelling, machine learning, and classic parametric models? I dedicate this talk to addressing this question, especially the methods based on the machine learning where up-to-date techniques are applied to the densely-observed strong-motion data in Japan.
 
[Short bio]
Dr. Chuanbin Zhu is a Program-Specific Assistant Professor, DPRI, Kyoto University. Prior to joining DPRI, he worked as a Research Fellow and then Senior Research Fellow at the Helmholtz Center Potsdam – GFZ German Research Centre for Geosciences, Germany. Dr. Zhu obtained his Ph.D. degree in earthquake engineering at Queensland University of Technology, Australia, after his undergraduate and graduate studies in China. Dr. Zhu has delivered more than 20 journal articles in GJI, BSSA, Earthq. Spectra, BEE, SDEE, JEE, etc. He has won the “Outstanding Ph.D. Thesis Award”, and served as a leading session convener and co-convener at the Seismological Society of America Annual Meetings in 2021 and 2022, and the 38th General Assembly of the European Seismological Commission, as well as the Leading Topic Editor of ESCI journal Frontiers in Built Environment.