Site response analysis and microzonation of Anchorage, Alaska, USA, using strong-motion data from recent earthquakes

Student thesis: Doctoral Thesis

Abstract

Anchorage, Alaska, is located in one of the most active tectonic settings in the world. The city and region were significantly impacted by the MW9.2 Great Alaska Earthquake in 1964, and they were recently shaken by a MW7.1 event in 2018. The city was developed in an area underlain by complex soil deposits of varied geological origins and stiffnesses, with the deposits’ thicknesses increasing east to west. Situated at the edge of the North American Plate, with the actively subducting Pacific Plate below, Anchorage is susceptible to both intraslab and interface earthquakes, along with crustal earthquakes. Strong-motion stations were installed across the city in an attempt to capture the variability in site response. Strong-motion recordings from 35 stations over the years of 2004 to 2019 were collected, processed, and prepared for analysis of that variability. The Generalized Inversion Technique (GIT) was used to calculate the Fourier spectral amplification at each strong-motion station and the variability of amplification at 1 Hz and 5 Hz were mapped for Anchorage. The 2018 MW7.1 strong-motion recordings were compared to the lower-magnitude events in the database to evaluate the differences at strong-motion stations related to linear and nonlinear site response. The horizontal to vertical spectral ratio (HVSR) was calculated for each strong-motion station and regional relationships between fpeak and the time-averaged shear wave velocity in the upper 30m (VS30) were developed. A contour map estimating seismic site class across Anchorage was developed using 70 VS30 estimates and measurements at other locations. A methodology is also developed using Fourier spectral amplification and Random Vibration Theory (RVT) to estimate engineering site response spectra at strong-motion stations. An approach to address nonlinear site response is applied to the methodology because the database is predominantly composed of linear site response recordings.
Date of Award25 Oct 2021
Original languageEnglish
Awarding Institution
  • University Of Strathclyde
SupervisorJohn Douglas (Supervisor) & Stella Pytharouli (Supervisor)

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