My name is Elif Oral. I'm a scientist working on geohazard problems as a postdoctoral researcher at Caltech.
Here I share the numerical tools that I developed and/or contributed to, mostly relevant to earthquake source mechanics, engineering mechanics, wave propagation, earthquake engineering, and observational seismology.
My scripts for data analysis are mostly python libraries/class and Jupyter notebooks; my softwares for large-scale computational mechanics are generally hybrid with the core parts written once upon a time in Fortran, and the relatively new parts that adopt the spirit of its time and conditions, such as CUDA for GPU use in high performance computing.
The world is evolving so are my research interests. Thanks for looking, and stay tuned for more open science ++
| Name | Description |
|---|---|
| 1D3CSEM | Prediction of seismic response of liquefiable sites |
| IWANelem | Modeling experimental soil behaviour under dynamic loading |
| Name | Description |
|---|---|
| specfem3d | Initial stress heterogeneity for dynamic rupture modeling and applications to SoCal & Ridgecrest |
| specfem3d | Seismic site response of complex sedimentary basins |
| sem2dpack | Modeling site effects in linear and nonlinear media |
| sem2dpack | Python class and Jupyter notebooks for mesh preparation (Cubit/Trelis) and post-processing |
| RIKsrf | Kinematic source modeling for ground motion prediction in Martinique |
| Name | Description |
|---|---|
| SCEC benchmark | Dataframes and notebooks for our models in SCEC DRV benchmark |
| Palu slow supershear | Dynamic rupture modeling for damaged medium of 2018 Palu, Indonesia earthquake & Python scripts for post-processing |
| Zagreb | Notebook trials for MUSIC backprojection, seismic data processing, and data clustering for 2020 Zagreb, Crotia earthquake |
| Convertisseur | Python scripts to convert RIKsrf outputs to source input for 3D wave propagation codes |
| How-to-obspy | Beginner's Jupyter notebooks on downloading seismic data and obspy use |
| How-to-machine-learning | My notebooks from Caltech workshop on Machine Learning |
For more details on examples/tutorials, click here
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