A framework to quantify uncertainty in critical slip distance in rate and state friction model for earthquakes
| Autor: | Karthik Reddy Lyathakula, Given Names Deactivated Family Name Deactivated |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
engrXiv|Engineering|Risk Analysis
bepress|Engineering|Risk Analysis engrXiv|Engineering bepress|Engineering|Computational Engineering bepress|Engineering|Civil and Environmental Engineering bepress|Engineering engrXiv|Engineering|Computational Engineering engrXiv|Engineering|Civil and Environmental Engineering |
| DOI: | 10.31224/osf.io/9bf4m |
| Popis: | This work presents a framework to inversely quantify uncertainty in the model parameters of the friction model using earthquake data via the Bayesian inference. The forward model is the popular rate- and state- friction (RSF) model along with the spring slider damper idealization. The inverse model is to determine the model parameters using the earthquake data as the response of the RSF model. The conventional solution to the inverse problem is the deterministic parameter values, which may not represent the true value, and quantifying uncertainty in the model parameters increases confidence in the estimation. The uncertainty in the model parameters is estimated by the posterior distribution obtained through the Bayesian inversion. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|