Projects per year
Abstract
This work develops a procedure that involves the use of Bayesian approach to quantify data scatterness, estimates the optimal values of model parameters, and selects the most appropriate model for the construction of normalized modulus reduction curves of soils. The proposed procedure is then demonstrated using real observation data based on a set of comprehensive resonant column tests on coarse-grained soils conducted in the study.
| Original language | English |
|---|---|
| Pages (from-to) | 305–333 |
| Journal | Journal of Earthquake Engineering |
| Volume | 23 |
| Issue number | 2 |
| Online published | 19 May 2017 |
| DOIs | |
| Publication status | Published - 2019 |
Research Keywords
- Bayesian Approach
- Hyperbolic Model
- Model Selection
- Normalized Modulus Reduction Curves
- Parameter Identification
- Resonant Column Test
Fingerprint
Dive into the research topics of 'Bayesian Parameter Identification and Model Selection for Normalized Modulus Reduction Curves of Soils'. Together they form a unique fingerprint.Projects
- 2 Finished
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GRF: Quantifying Site-specific Geotechnical Variability by Markov Chain Monte Carlo Simulation
WANG, Y. (Principal Investigator / Project Coordinator) & LEE, S.-W. (Co-Investigator)
1/07/15 → 26/03/19
Project: Research
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GRF: Transitional Behaviour in Tailings
WANG, Y. (Principal Investigator / Project Coordinator), COOP, M. R. (Co-Investigator), Hu, W. (Co-Investigator), SCHNAID, F. (Co-Investigator), SENETAKIS, K. (Co-Investigator) & SITHARAM, T. G. (Co-Investigator)
1/01/14 → 11/06/18
Project: Research