Multi-physical coupling
|
|
Direct numerical simulation of wave propagation in saturated granular media using coupled LBM-DEM
|
Poroelasticity theory predicts wave velocities in a saturated porous medium through a coupling between the bulk deformation of the solid skeleton and porous fluid flow. The challenge emerges below the characteristic wavelengths at which hydrodynamic interactions between grains and pore fluid become important. We investigate the pressure and volume fraction dependence of compressional- and shear-wave velocities in fluid-saturated, random, isotropic, frictional granular packings. The lattice Boltzmann method (LBM) and discrete element method (DEM) are two-way coupled to capture the particle-pore fluid interactions; an acoustic source is implemented to insert a traveling wave from the fluid reservoir to the saturated medium. We extract wave velocities from the acoustic branches in the wavenumber-frequency space, for a range of confining pressures and volume fractions. For random isotropic granular media the pressure-wave velocity data collapse on a single curve when scaled properly by the volume fraction.
|
|
|
Space-time domain response of particle velocity in the longitudinal direction
|
|
The role of viscosity on virgin and recycled particles in polymer sintering
Sintering of powder materials has received critical attention, due to the increasing use of powder-based additive manufacturing processes. Simulation techniques like the discrete particle method can be used to better understand the process, but require calibrated models of the neck-growth kinetics.
This work provides a detailed microscopic description of the viscoelastic coalescence of polymer particles. Three stages are identified, in which different sintering mechanisms dominate. This description leads to a model for neck-growth kinetics that has three particle-scale parameters that need to be calibrated: the sintering rate, material fluidity and cohesive separation distance. The experimental data confirms the existence of three distinct sintering stage. Then, GrainLearning, an open-source Bayesian calibration tool, is utilized to calibrate and validate these parameters, using experimental data from sintering pairs of PA12 particles. Finally, we include a degradation factor to model the effect of using degraded (recycled) powder, which has been heated previously beyond the glass temperature.
This work provides a detailed microscopic description of the viscoelastic coalescence of polymer particles. Three stages are identified, in which different sintering mechanisms dominate. This description leads to a model for neck-growth kinetics that has three particle-scale parameters that need to be calibrated: the sintering rate, material fluidity and cohesive separation distance. The experimental data confirms the existence of three distinct sintering stage. Then, GrainLearning, an open-source Bayesian calibration tool, is utilized to calibrate and validate these parameters, using experimental data from sintering pairs of PA12 particles. Finally, we include a degradation factor to model the effect of using degraded (recycled) powder, which has been heated previously beyond the glass temperature.
