| About this Abstract |
| Meeting |
2020 TMS Annual Meeting & Exhibition
|
| Symposium
|
Algorithm Development in Materials Science and Engineering
|
| Presentation Title |
Functional Uncertainty Propagation with Bayesian Ensembles in Molecular Dynamics |
| Author(s) |
Saaketh Desai, Sam Reeve, Alejandro Strachan |
| On-Site Speaker (Planned) |
Saaketh Desai |
| Abstract Scope |
Functional uncertainty quantification (FunUQ) is a method to quantify uncertainties in materials models stemming from input functions, as opposed to input parameters. FunUQ has been previously used within multi-fidelity molecular dynamics (MD) simulations, correcting quantities of interest (QoIs) originating from one interatomic model to yield the QoIs for a new functional form without additional simulation. We now use FunUQ to propagate uncertainties originating from interatomic potentials in MD. Starting with an ensemble of potentials obtained via Bayesian calibration, we run a small number of direct MD simulations across the distribution, calculate sensitivity to local changes in the function via FunUQ (the functional derivative), and predict the QoIs for each parameter set in the ensemble. This is the first computationally tractable MD simulation with quantified uncertainties directly from the interatomic model, the main source of uncertainty. All FunUQ codes and examples are available for online simulation in nanoHUB: https://nanohub.org/tools/funuq.
This work was performed in part under the auspices of the U.S. DOE by LLNL under contract DE-AC52-07NA27344. |
| Proceedings Inclusion? |
Planned: Supplemental Proceedings volume |