- Title
- Calibration of micromechanical parameters for DEM simulations by using the particle filter
- Creator
- Cheng, Hongyang; Shuku, Takayuki; Thoeni, Klaus; Yamamoto, Haruyuki
- Relation
- 8th International Conference on Micromechanics on Granular Media. Powders and Grains 2017 - 8th International Conference on Micromechanics on Granular Media [presented in EPJ Web of Conferences, Vol. 140] (Montpellier, France 3-7 July, 2017)
- Publisher Link
- http://dx.doi.org/10.1051/epjconf/201714012011
- Publisher
- EDP Sciences
- Resource Type
- conference paper
- Date
- 2017
- Description
- The calibration of DEM models is typically accomplished by trail and error. However, the procedure lacks of objectivity and has several uncertainties. To deal with these issues, the particle filter is employed as a novel approach to calibrate DEM models of granular soils. The posterior probability distribution of the microparameters that give numerical results in good agreement with the experimental response of a Toyoura sand specimen is approximated by independent model trajectories, referred as 'particles', based on Monte Carlo sampling. The soil specimen is modeled by polydisperse packings with different numbers of spherical grains. Prepared in 'stress-free' states, the packings are subjected to triaxial quasistatic loading. Given the experimental data, the posterior probability distribution is incrementally updated, until convergence is reached. The resulting 'particles' with higher weights are identified as the calibration results. The evolutions of the weighted averages and posterior probability distribution of the micro-parameters are plotted to show the advantage of using a particle filter, i.e., multiple solutions are identified for each parameter with known probabilities of reproducing the experimental response.
- Subject
- DEM models; particle filter; granular soils; Monte Carlo sampling
- Identifier
- http://hdl.handle.net/1959.13/1387816
- Identifier
- uon:32670
- Identifier
- ISSN:2100-014X
- Rights
- © The Authors, published by EDP Sciences, 2017. This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- Language
- eng
- Full Text
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