scholarly journals Inviscid simulations of expansion waves propagating into structured particle beds at low volume fractions

2018 ◽  
Vol 3 (9) ◽  
Author(s):  
Goran Marjanovic ◽  
Jason Hackl ◽  
Mrugesh Shringarpure ◽  
Subramanian Annamalai ◽  
Thomas L. Jackson ◽  
...  
2018 ◽  
Vol 90 (6) ◽  
pp. 1085-1098 ◽  
Author(s):  
Isha Malhotra ◽  
Sujin B. Babu

Abstract In the present study we are performing simulation of simple model of two patch colloidal particles undergoing irreversible diffusion limited cluster aggregation using patchy Brownian cluster dynamics. In addition to the irreversible aggregation of patches, the spheres are coupled with isotropic reversible aggregation through the Kern–Frenkel potential. Due to the presence of anisotropic and isotropic potential we have also defined three different kinds of clusters formed due to anisotropic potential and isotropic potential only as well as both the potentials together. We have investigated the effect of patch size on self-assembly under different solvent qualities for various volume fractions. We will show that at low volume fractions during aggregation process, we end up in a chain conformation for smaller patch size while in a globular conformation for bigger patch size. We also observed a chain to bundle transformation depending on the attractive interaction strength between the chains or in other words depending on the quality of the solvent. We will also show that bundling process is very similar to nucleation and growth phenomena observed in colloidal system with short range attraction. We have also studied the bond angle distribution for this system, where for small patches only two angles are more probable indicating chain formation, while for bundling at very low volume fraction a tail is developed in the distribution. While for the case of higher patch angle this distribution is broad compared to the case of low patch angles showing we have a more globular conformation. We are also proposing a model for the formation of bundles which are similar to amyloid fibers using two patch colloidal particles.


2011 ◽  
Vol 10 (4) ◽  
pp. 1027-1043 ◽  
Author(s):  
Jun Huang ◽  
Ole Jørgen Nydal

AbstractThe classical discrete element approach (DEM) based on Newtonian dynamics can be divided into two major groups, event-driven methods (EDM) and time-driven methods (TDM). Generally speaking, TDM simulations are suited for cases with high volume fractions where there are collisions between multiple objects. EDM simulations are suited for cases with low volume fractions from the viewpoint of CPU time. A method combining EDM and TDM called Hybrid Algorithm of event-driven and time-driven methods (HAET) is presented in this paper. The HAET method employs TDM for the areas with high volume fractions and EDM for the remaining areas with low volume fractions. It can decrease the CPU time for simulating granular flows with strongly non-uniform volume fractions. In addition, a modified EDM algorithm using a constant time as the lower time step limit is presented. Finally, an example is presented to demonstrate the hybrid algorithm.


2012 ◽  
Vol 09 (01) ◽  
pp. 1240010 ◽  
Author(s):  
JUN HUANG ◽  
ANGELA DE LEEBEECK ◽  
OLE JØRGEN NYDAL

Event-driven method (EDM) and the time-driven method (TDM) are two main branches of discrete element methods (DEM) for the simulations of granular materials. A new algorithm is introduced in this paper where different models are used for different local volume fractions. TDM time step is used for the cases with high volume fractions and EDM time step is used for the cases with low volume fractions. Whether the local volume fraction is low or high is determined by the number of neighbors in the Verlet table. While the time step updating the Verlet table is the same as the time step for those particles without neighbors in the Verlet table.


1992 ◽  
Vol 26 (10) ◽  
pp. 1565-1570 ◽  
Author(s):  
Angela Szaruga ◽  
Lisa Rothenflue ◽  
Raghavan Srinivasan ◽  
Harry A. Lipsitt

Sign in / Sign up

Export Citation Format

Share Document