The main focus of this thesis is to effectively estimate levels of peak ground acceleration (PGA) during a seismic event for a given site. This will be achieved by applying regression analysis via a mixed model methodology to data collected from previously recorded seismic events collected from the PEER Strong Motion Database using a program written in MATLAB. The basic mixed model combines both fixed and random effect terms. Two models are analyzed and compared based on varying combinations of predictor variables, such as magnitude, distance, shear wave velocity, and site class. While the primary objective of this thesis solely examines the modeling of PGA, the same methodology can be applied in predicting other ground motion intensity parameters such as Peak Ground Velocity (PGV) or the spectral ordinate at a given vibration period.
| Identifer | oai:union.ndltd.org:siu.edu/oai:opensiuc.lib.siu.edu:theses-2875 |
| Date | 01 May 2016 |
| Creators | Betancourt, Michelle Renee |
| Publisher | OpenSIUC |
| Source Sets | Southern Illinois University Carbondale |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses |
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