Probabilistic calibration of a damage rock mechanics model

Abstract

Current practice in the calibration of damage models requires downscaling the effects of experimental observations from macro/meso to micro. This process introduces uncertainty that is seldom quantified to reflect the expert's confidence in the model predictions. A probabilistic calibration methodology can be introduced to overcome this problem. This paper shows a case study based on a damage rock mechanics model and triaxial experimental data on sandstone, where this approach is implemented to illustrate the impact of varying states of evidence (i.e. model complexity, experimental observations and expert's judgement) on the model predictions. The probabilistic calibration method relies on the use of the Bayesian paradigm to assimilate experimental observations into the probabilistic definition of the model parameters. Results of this approach can be encapsulated into a single probability distribution or posterior, which is later used to assess the model performance. The proposed approach shows the potential to improve current practice in risk analysis since it allows tracing of changes of the model performance for varying evidence conditions in damage-sensitive geostructures such as nuclear waste disposals, landfills, geothermal wells and unconventional oil and gas formations, among others.

Assessment of Spatio-Temporal Kinematic Phenomena Observed along the Boundary of Triaxial Sand Specimens

“…The measurement accuracy was assessed by comparing averaged vertical displacement through DIC data with global readings by linear variable differential transformer (LVDT) transducers, and the difference was found approximately along the vertical direction. Similar accuracy has been observed in the horizontal direction [1,33].…”

Numerical Modeling of an Asteroid Impact on Earth: Matching Field Observations at the Chicxulub Crater Using the Distinct Element Method (DEM)

“…This raised our interest to simulate the impact using PFC, so as to identify likely mechanical responses of the ground during the asteroid's impact, and to explore the potential of PFC to better replicate the crater formation process. Once this simulation is completed, a probabilistic calibration method [39][40][41] will be implemented, to populate all likely combinations of the model parameters that best represent the actual crater's topography and stratigraphy, both during and after impact.…”