Toward Accurate Models of Wet Granular Media in Nature
Abstract
The technical objective of the proposed effort is to develop continuum and discrete models for granular media in the slurry and pendular regimes to predict grain motion and the dynamics of the fluid simultaneously. The proposed effort seeks to achieve the stated technical objective through two projects: In Project 1, a 20 and 30 slurry flow continuum model will be developed. This model will be calibrated and validated for a range of geometries through comparison with lattice-Boltzmann method - discrete element method (LBM-DEM) simulations of realistic wet materials. The model and numerical experiments will be used to test the following hypothesis: The granular fabric tensor, a local variable recording contact orientation, is an appropriate independent variable of the anisotropic permeability, with the permeability function informed by the full LBM-DEM. Additionally, the model and numerical experiments will provide insight into the Shields stress concept. In Project 2, a pendular DEM routine that includes fluid content variables, and that integrates appropriate evolution rules to vary water content as grains distribute and exchange water during liquid bridging, will be developed. The open-source LIGGGHTS DEM code will be extended to add a bridge-force calculation that includes the formation-breakage hysteresis of the capillary bridging to the standard DEM particle forces. A simultaneous fluid evolution routine will be used to evolve the fluid distribution in the system. The fluid will be considered to be !n one of two states: within a wetted layer surrounding the particle or participating in a bridge between two particles. Numerical experiments will be performed to acquire information on the rheological behavior of partially wet grains, determine what process governs the formation of sub-regimes affecting stability of wet media, and determine the wetting properties, such as contact angle, of water on natural rocks, gravels, and sands.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 12, 2017
- Source ID
- W911NF1510598
Entities
People
- Ken Kamrin
Organizations
- Army Contracting Command
- Massachusetts Institute of Technology
- United States Army