Hydrodynamics in Espresso. Kai Grass 1

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1 Hydrodynamics in Espresso Kai Grass 1

Hydrodynamics in Espresso Explicit solvent: Lennard-Jones liquid at constant energy Dissipative Particle Dynamics (DPD): thermostated particle fluid Lattice

2 Hydrodynamics in Espresso Explicit solvent: Lennard-Jones liquid at constant energy Dissipative Particle Dynamics (DPD): thermostated particle fluid Lattice Boltzmann (LB): thermostated lattice fluid Stochastic Rotation Dynamics (SRD): thermostated particle gas currently under development Mesoscopic fluid models 2

3 ESPResSo does not offer atomistic water models (TIP3,...)... instantaneous hydrodynamics (Rotne- Prager-Oseen tensor)... But extensibility of ESPResSo allows for integrating these methods if needed 3

Comparison Explicit (LJ) solvent easy to model no special algorithm needed BUT 10-20 times slower than mesoscopic fluid

4 Comparison Explicit (LJ) solvent easy to model no special algorithm needed BUT times slower than mesoscopic fluid models DPD easy to approach and model complex thermostat input parameters have to be maped tohydrodynamic properties of the fluid 4

5 Comparison LB abstract lattice fluid with complex internal dynamics easy coupling to the MD particles hydrodynamic properties of the fluid are well described by input parameters SRD abstract particle gas based on stochastics different coupling schemes 5

6 Lattice Boltzmann theory Lattice Boltzmann equation streaming and collision discrete set of velocity populations hydrodynamic fields from populations Frictional coupling of MD particles to LB fluid Stokesian drag momentum transfer total momentum conserved [ ] F = Γ V u( R, t) [1] P. Ahlrichs and B. Dünweg. International Journal of Modern Physics C, 9: ,

7 Lattice Boltzmann usage 4 # d e f i n e the c e l l s y s t e m 5 cellsystem domain decomposition n o v e r l e t l i s t 6 7 i f {! ( $continue ) } { 8 # s e t s i m u l a t i o n box 9 setmd box l $length $length $length 0 setmd p e r i o d i c setmd s k i n $ skin 2 setmd t i m e s t e p $timestep 3 } 4 5 puts System s i z e : [ setmd box l ]. # s t o p a l l p a r t i c l e s b e f o r e e n t e r i n g l b stop particles thermostat o f f thermostat l b $temp lbfluid dens $lbdens v i s c $ v i s c a g r i d $ a grid tau $ l b t i m e s t e p lbfluid f r i c t i o n $lbgamma puts [ thermostat ] 7

Lattice Boltzmann problems Particle sizes: only one friction parameter Boundaries: only plane walls (see Marcellos document) lbboundaries bounce_back.

8 Lattice Boltzmann problems Particle sizes: only one friction parameter Boundaries: only plane walls (see Marcellos document) lbboundaries bounce_back. constraint wall normal dist [ expr $wallposlow ] type $walls constraint wall normal dist [ expr -1.*($wallposhigh) ] type $walls 8

9 DPD theory F i = i j ( F C ij + F D ij + F R ij ), F C ij = a ij (r c r ij ) ˆr ij for r ij < r c 0 for r ij r c, F D ij = ω D (r ij )ζ(ˆr ij u ij )ˆr ij, F R ij = ω R (r ij ) 2ζk B T γ ij tˆr ij, 9

10 DPD usage Syntax thermostat dpd temperature gamma r cut [ WF wf tgamma tr cut TWF twf ] Interaction DPD thermostat The DPD thermostat can also be set up as a normal interaction to make friction between different particle types different. Syntax thermostat inter_dpd temperature Description and Syntax inter type1 type2 inter_dpd gamma r cut [ WF wf tgamma tr cut TWF twf ] 10

DPD problems Fluid properties are not defined by DPD parameters and have to be matched (see http://arxiv.

11 DPD problems Fluid properties are not defined by DPD parameters and have to be matched (see Different boundary conditions: stick / slip are available by means of viscous layer 11

The Lattice Boltzmann Method in ESPResSo: Polymer Diffusion and Electroosmotic Flow

ESPResSo Tutorial The Lattice Boltzmann Method in ESPResSo: Polymer Diffusion and Electroosmotic Flow Stefan Kesselheim Georg Rempfer June 14, 2016 Institute for Computational Physics, Stuttgart University