Multiscale Lagrangian fluid dynamics simulation for polymeric fluid

We have developed a simulation technique of multiscale Lagrangian fluid dynamics to tackle hierarchical problems relating to historical dependency of polymeric fluid. We investigate flow dynamics of dilute polymeric fluid by using the multiscale simulation approach incorporating Lagrangian particle fluid dynamics technique (the modified smoothed particle hydrodynamics) with stochastic coarse‐grained polymer simulators (the dumbbell model). We have confirmed that our approach is well in agreement with the macroscopic results obtained by a constitutive equation corresponding to the dumbbell model, and observed that microscopic thermal fluctuation appears in macroscopic fluid dynamics as dispersion phenomena. © 2010 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 48: 886–893, 2010     

Existence of solution for a micro-macro model of polymeric fluid: the FENE model

We analyse a non-linear micro-macro model of polymeric fluids in the case of a shear flow. More precisely, we consider the FENE dumbbell model, which models polymers by nonlinear springs, accounting for the finite extensibility of the polymer chain. We prove the existence of a unique solution to the stochastic differential equation which rules the evolution of a representative polymer in the flow and next deduce a local-in-time existence and uniqueness result on the system coupling the stochastic differential equation and the momentum equation on the fluid.     

Brownian configuration fields and variance reduced CONNFFESSIT

Stochastic simulation techniques, such as Brownian dynamics, provide us an extremely powerful tool for solving the usually nonlinear equations describing polymer dynamics in solutions and melts [1]. However, the most challenging problems (e.g. the investigation of the universal behaviour of long polymer chains, or the flow calculation based on stochastic simulation techniques) involve a very large number of degrees of freedom and hence require an enomous amount of computer time. In order to solve such problems on currently available computers it is therefore necessary to develop strategies to drastically suppress the level of the fluctuations in the simulations. The purpose of this note is to show that the recently proposed concept of Brownian configuration fields [2] in viscoelastic flow calculations can be regarded as an extremely powerful extension of variance reduction techniques based on parallel process simulation.