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Parallel DSMC Simulation of Micro/Nano Structured Cavity Flow

Dr. Ehsan Roohi

Collaborators:

Alireza Mohammadzaeh

Dr. Hamid Niazmand

Outline

Overview of micro/nano fluidics systems

DSMC algorithm

Parallel implementation

Physical aspect of flow field

Micro-Nano fluidics Systems

Nano Channels

Nano Nozzles Micro-nozzles

Micro-channel

4

Micro-Nano fluidics Systems The ink-jet printer: an example of micro-fluidics in action

Thermal ink-jet operation

Micro-beam

Micro-

propulsion

system

5

Micro-Nano fluidics Systems

Micro/Nano Lid-driven Cavity

Isothermal cavity

B

A

C

D

Argon flow

0.005 < Kn < 0.1

300wallT K

Kn=0.05, Re=10

L=1E-6 m

100 /U m s

Knudsen Regime for Rarefied Flows

Continuum

regime

Slip

regime

Transition

regime

Free molecular

regime

0 0.001 0.1 10

Knudsen number

Traditional

NS equations

NS equations

accompanied by

velocity slip and

temperature jump

boundary

conditions

Molecular approach

DSMC technique

Kn=l/L

Direct Simulation Monte Carlo

(DSMC ) Algorithm

Initialize system with particles

Loop over time steps

Create particles at open

boundaries

Move all the particles

Process any interactions of

particle & boundaries

Sort particles into cells

Select and execute random

collisions

Sample statistical values

Example: Flow past a sphere

Parallel DSMC Processing

Load balanced domain decomposition Perform a simulation with much less number of particles for a short period

Domain Decomposition

N=500,000 particle

Kn=0.05

Number of Processors

S

1 2 3 4

1

2

3

4 OPDSMC

Ideal

Parallel Processing Speed up

N=500,000 particle

Kn=0.05

s

p

TS=

T

OpenMP MPI

2 processor 1.99 1.94

4 processor 3.74 3.45

OpenMP: Schwartzentruber et al.

Number of Processor

No

n-d

imen

sio

nal

ized

Tim

e

0 1 2 3 4 5

5

10

15

20

25

30

Move

Index

Sample

Collision

Number of Processor

Nu

mb

ero

fM

ole

cule

s

0 1 2 3 4 5

125000

130000

135000

140000

DSMC Steps Occupied Time

N=500,000 particle

Kn=0.05

DSMC Results Validation

Kn=0.1

Re=1.5

Kn=1.0

Re=0.5

p/p

0

1

1.1

Current study DSMC

Mizzi et al. [16] DSMC

A B C D A

a)

X/L

u/UWall

v/U

Wa

ll

Y/L

0 0.2 0.4 0.6 0.8 1

0 0.1 0.2 0.3 0.4

-0.1

-0.05

0

0.05

0.1

0

0.2

0.4

0.6

0.8

1

Current study

John et al. [20]

Horizontal centerline

Verical centerline

b)

Horizontal Velocity Contour

Kn=0.05

Kn=0.005 Kn=0.1 Kn=0.05

Heat Flux Distribution

Entropy

( )BoltzS k Ln

, , , ,( ) ( )bins x y z x y zf cLn Ln f

, , ,x y z x y zf f f

DSMC

/s S

Velocity Distribution Functions

Vz

VD

F-1000 0 1000

0

0.0005

0.001

0.0015f

z

fMaxwellian

,x yfzf

Kn=0.05

Top left Corner

Cy-2000-1000

01000

2000

Y

Z

X

Entropy Distribution

Kn=0.005 Kn=0.1 Kn=0.05

Entropy Density

Kn=0.005 Kn=0.1 Kn=0.05

DSMC

Concluding Remarks

• Considerable speed up in parallel DSMC in comparison with

the serial DSMC

• Dependencies of heat flux vectors on the additional terms

besides the temperature gradient

• Development of the unconventional cold-to-hot heat flux

process in the direction of increasing entropy

• Entropy density a tool to specify the degrees of rarefaction