Mechanical and Civil Engineering Seminar

Ph.D. Thesis Defense

Abstract:

"Basin effects" refer to trapped and reverberating earthquake waves in soft sedimentary deposits overlying convex depressions of the basement bedrock, which significantly alter frequency content, amplitude, and duration of seismic waves. Basin effects have played a major role in past earthquakes and have had catastrophic consequences. While the common practice is to perform a 1D site response analysis, edge effect and the generation of surface waves are among the key contributors to the surface ground motion within a basin.

This thesis studies basin effects to better parameterize the phenomena and suggests a path to appropriately incorporate them in ground motion prediction equations and design codes. In addition, the high-frequency response of a basin in cases with data scarcity is explored. We first perform a systematic study using the Finite element method and dimensional analysis to examine the characteristics of surface ground motion associated with basin effects. After interpreting the impacts of each parameter and ranking them, we train a neural network to estimate surface acceleration time-series given earthquake frequency content, basin geometry, material properties, and location inside a basin. Our results show that at least three parameters are needed to take basin effects into account. Moreover, using statistical methods, we are able to significantly reduce the computational cost of numerical simulations, which is necessary in cases that fast calculation of the response is desirable. Lastly, we study the high-frequency response of a basin when data scarcity is a setback for deterministic modeling. Using a correlated random field to represent basin material, we perform a stochastic analysis using the Monte Carlo technique to quantify the response of a basin.

Please virtually attend this thesis defense:

Zoom link: https://caltech.zoom.us/j/82928141092?pwd=MEdjUXljalFzODRNclg5aEhmWFBKdz09