0000000000940167
AUTHOR
Yaser Afshar
A new algorithm for simulating flows of conducting fluids in the presence of electric fields
Abstract We propose an algorithm based on dissipative particle dynamics (DPD) for simulations of conducting fluids in the presence of an electric field. In this model, the electrostatic equations are solved in each DPD time step to determine the charge density at the fluid surfaces. These surface charges are distributed on a thin layer of fluid particles near the interface, and the corresponding interfacial electric forces are added to other DPD forces. The algorithm is applied to the electrospinning process at the Taylor cone formation stage. It is shown that, when the applied voltage is sufficiently high, the algorithm captures the formation of a Taylor cone with analytical apex angle 98.…
Exploiting seeding of random number generators for efficient domain decomposition parallelization of dissipative particle dynamics
Abstract Dissipative particle dynamics (DPD) is a new promising method commonly used in coarse-grained simulations of soft matter and biomolecular systems at constant temperature. The DPD thermostat involves the evaluation of stochastic or random forces between pairs of neighboring particles in every time step. In a parallel computing environment, the transfer of these forces from node to node can be very time consuming. In this paper we describe the implementation of a seeded random number generator with three input seeds at each step which enables the complete generation of the pairwise stochastic forces in parallel DPD simulations with minimal communication between nodes.