Arbitrary flow boundary conditions in smoothed dissipative particle dynamics: A generalized virtual rheometer

Abstract

In this work a methodology to perform rheological studies on Smoothed Dissipative Particle Dynamics under arbitrary flow configurations is introduced. To evaluate the accuracy and flexibility of the proposed methodology viscometric studies for Newtonian fluids under pure shear, pure extension, and arbitrary flows in bulk or near walls are introduced. The applicability of this methodology to obtain viscoelastic properties of non-Newtonian fluids, such as polymer solutions is also presented. The new computational approach offer relevant advantages in a variety of applications ranging from multiscale simulations to rheological characterization of complex flows.

Mesoscopic simulations of inertial drag enhancement and polymer migration in viscoelastic solutions flowing around a confined array of cylinders

“…) is a normalized kernel function of finite support r c . Following previous work using SDPD particles we have adopted Lucy kernel [31]:…”

“…where p 0 , ρ 0 and γ parameters are chosen to minimize density variations (< 5%) by choosing a sufficiently large speed of sound c s = p 0 γ/ρ 0 . A background pressure pb = 0.7 ensures positive pressure across the domain for the range of deformation rates studied, which provides numerical stability [31]. For all our simulations with choose a time step ∆t = 0.003 given by the shorter time scale in the Courant-Friedrich-Lewy condition δt c = dx/32c s and δt η = dx 2 /16η [33,34].…”

Non-affine motion and selection of slip coefficient in constitutive modeling of polymeric solutions using a mixed derivative

“…A background dimensionless pressure contribution ε = 0.7 ensures positive pressure across the domain for the range of deformation rates studied, which provides numerical stability. 33 In Eq. ( 25), a i j = 5η/3 − ζ and b i j = 5(ζ + η/3) are friction coefficients given by the shear η and bulk ζ viscosities.…”

“…Substitution of ( 37), ( 38) into (36) renders the continuum Eqn. (33) 36) presents some problems due to the need of differentiating the evolution of u α in time, which is error prone. However, Eq.…”

Computational Mesoscale Framework for Biological Clustering and Fractal Aggregation

“…To address the limitations of current methods in modeling relevant spatial-temporal scales, we employ the smoothed dissipative particle dynamics (SDPD) method [31, 32, 33, 34, 35]. The SDPD method discretizes the fluctuating Navier-Stokes equations and consistently satisfies the First and Second Laws of Thermodynamics and the Fluctuation-Dissipation Theorem [32, 34, 36, 37]. It has been used to study complex fluids, colloid-solvent interactions, colloid-colloid interactions, and blood flow [35, 38, 39, 40].…”