Recently there has been a great deal of attention, from researchers both in academia and in industry, focused on the rheological properties of solutions of viscoelastic wormlike micelles formed by surfactants. It is particularly vital to understand the properties of these solutions with regard to their flow in porous media, given their application to the recovery of hydrocarbons from subterranean formations. In this study a realistic mesoscopic Brownian dynamics model has been utilized to investigate the flow of viscoelastic surfactant (VES) fluid through individual pores with sizes of around one micron. In particular the influence of micelle size, pore geometry and flow rate on the ability of worms to pass through the pores was studied. The ways in which these parameters influence the conformational properties of the worms and the spatial distribution of micelles inside the simulation cell was also investigated. Despite the observation that the density and length distributions became non-uniform at higher scission energy, the distribution of breaking and fusion events remained spatially uniform.

We describe in detail how to implement a coarse-grained hybrid molecular dynamics and stochastic rotation dynamics simulation technique that captures the combined effects of Brownian and hydrodynamic forces in colloidal suspensions. The importance of carefully tuning the simulation parameters to correctly resolve the multiple time and length scales of this problem is emphasized. We systematically analyze how our coarse-graining scheme resolves dimensionless hydrodynamic numbers such as the Reynolds number Re, which indicates the importance of inertial effects, the Schmidt number Sc, which indicates whether momentum transport is liquidlike or gaslike, the Mach number, which measures compressibility effects, the Knudsen number, which describes the importance of noncontinuum molecular effects, and the Peclet number, which describes the relative effects of convective and diffusive transport. With these dimensionless numbers in the correct regime the many Brownian and hydrodynamic time scales can be telescoped together to maximize computational efficiency while still correctly resolving the physically relevant processes. We also show how to control a number of numerical artifacts, such as finite-size effects and solvent-induced attractive depletion interactions. When all these considerations are properly taken into account, the measured colloidal velocity autocorrelation functions and related self-diffusion and friction coefficients compare quantitatively with theoretical calculations. By contrast, these calculations demonstrate that, notwithstanding its seductive simplicity, the basic Langevin equation does a remarkably poor job of capturing the decay rate of the velocity autocorrelation function in the colloidal regime, strongly underestimating it at short times and strongly overestimating it at long times. Finally, we discuss in detail how to map the parameters of our method onto physical systems and from this extract more general lessons-keeping in mind that there is no such thing as a free lunch-that may be relevant for other coarse-graining schemes such as lattice Boltzmann or dissipative particle dynamics.

The interplay between hydrodynamic and Brownian fluctuations during steady-state sedimentation of hard sphere particles for Peclet numbers (Pe) ranging from 0.1-15 was studied using a mesoscopic computer simulation. A stochastic rotation dynamics (SRD) to the problem of sedimenting HS was adapted to perform the simulations. It was shown that the hydrodynamic interactions (HI) induce backflow effects that dominate the reduction of the average sedimentation velocity with increasing particle packing fraction, even when the they were an order of magnitude weaker than Brownian forces. It was observed that the velocity fluctuations begin to show nonequilibrium hydrodynamic character for Pe>1.

A coarse-grained simulation model was used to investigate the transient and steady-state nonlinear flow properties of unentangled and moderately entangled polyethylene melts. It was found that the model's predictions agree very well with various rheological experiments for shearing flow. This enabled to test the stress-optical rule and it was observed that it was valid, but only for low and moderate shear rates.

Molecular dynamics (MD) simulations of a polyethylene melt were performed to investigate the validity of the Rouse model predictions for a comprehensive set of correlation functions. It was found that the chains behave like Rouse theory predicts, but only on length scales larger than the segment length.

A soft-sphere discrete particle model was used to simulate mixing behavior of solid substrate particles in a slow rotating drum for solid-state fermentation. In this approach, forces acting on and subsequent motion of individual particles can be predicted. The (2D) simulations were qualitatively and quantitatively validated by mixing experiments using video and image analysis techniques. It was found that the simulations successfully predicted the mixing progress as a function of the degree of filling and size of the drum. It is shown that only relatively large, straight baffles perpendicular to the drum wall (67% of the drum radius) increase the mixing performance of the rotating drum. Considering the different aspects of mixing dealt with in this work, it is concluded that the soft sphere discrete particle model can serve as a valuable tool for investigating mixing of solid substrate particles. Finally, it is expected that this model may evolve into a potential tool for design and scale-up of mixed solid-state fermenters.