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Emergence of collective dynamics in active biological systems -- Swimming micro-organisms -- Norihiro Oyama John J. Molina Ryoichi Yamamoto* Department of Chemical Engineering, Kyoto University 1 12/08/2015, YITP, Kyoto

Emergence of collective dynamics in active biological systems

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Page 1: Emergence of collective dynamics in active biological systems

Emergence of collective dynamics in active biological systems

-- Swimming micro-organisms --

Norihiro OyamaJohn J. Molina

Ryoichi Yamamoto*

Department of Chemical Engineering, Kyoto University

1

12/08/2015, YITP, Kyoto

Page 2: Emergence of collective dynamics in active biological systems

Outline

1. Introduction:

– DNS for particles moving through Fluids

Stokes friction, Oseen (RPY), … are not the end of the story -> Need DNS to go beyond

2. DNS of swimming (active) particles:

– Self motions of swimming particles

– Collective motions of swimming particles

2

Page 3: Emergence of collective dynamics in active biological systems

Particles moving through fluids

3

G

Gravity:Sedimentation

in colloidal disp.

Gravity:A falling objectat high Re=103

Page 4: Emergence of collective dynamics in active biological systems

• FEM: sharp solid/fluid interface on irregular lattice→ extremely slow…

Basic equations for DNS

exchangemomentum

Navier-Stokes(Fluid)

Newton-Euler(Particles)

21, 0pp

t

fu u u u

, ,i i ii i ii i

d d dm

dt dt dt

R V ΩFV I N

• FPD/SPM: smeared out interface on fixed square lattice → much faster!!

4

ξa

Page 5: Emergence of collective dynamics in active biological systems

FPD and SPM

5

SS

SPM (2005)Nakayama, RY

Define body force to enforce fluid/particle boundary conditions

(colloid, swimmer, etc.)

body force

P

S

P S

FPD (2000)Tanaka, Araki

1( , )n tu x*( , )tu x

( , )n tu x

1( , )n tu x

Page 6: Emergence of collective dynamics in active biological systems

Implementation of no-slip b.c. , , ,n n n n

i i iR V u r

Step 1

Step 2

Step 3

1n n

PRE 2005

Momentum conservation 6

Page 7: Emergence of collective dynamics in active biological systems

This choice can reproducethe collect Stokes drag forcewithin 5% error.

Numerical test: Drag force (1)

EPJE 2008

Mobility coefficient of spheres at Re=1

7

Mo

bili

ty c

oef

fici

ent

Page 8: Emergence of collective dynamics in active biological systems

Numerical test: Drag force (2)

JCP 2013

Drag coefficient of non-spherical rigid bodies at Re=1

Any shaped rigid bodies can be formed by assembling spheres

8

Simulation vs. Stokes theory

Page 9: Emergence of collective dynamics in active biological systems

Numerical test: Drag force (3)Drag coefficient of a sphere CD at Re<200

9

(D=8Δ)

Re=10

RSC Advances 2014

Page 10: Emergence of collective dynamics in active biological systems

Numerical test: Lubrication force

10

Two particles are approaching with velocity V under a constant force F. V tends to decrease with decreasing the separation h due to the lubrication force.

h

F

Stokesian Dynamics (Brady)

RPY

SPM

Lubrication (2-body)

SPM can reproduce lubrication force very correctly until the particle separation becomes comparable to x (= grid size)

EPJE 2008

V1 V2

Approaching velocity of a pair of spheres at Re=0 under a constant F

Page 11: Emergence of collective dynamics in active biological systems

Outline

1. Introduction:

– DNS for particles moving through Fluids

2. DNS of swimming (active) particles:

– Self motions of swimming particles

– Collective motions of swimming particles

11

Page 12: Emergence of collective dynamics in active biological systems

Implementation of surface flow

Total momentum is conserved

tangential surface flow

2x

aa

propulsion

SM 2013

12

Page 13: Emergence of collective dynamics in active biological systems

r

z

x

y

θ

e

r

A model micro-swimmer: Squirmer

13

J. R. Blake (1971)

Polynomial expansion of surface slip velocity. Only component is treated here.

neglecting n>2

φ

Propulsion

θ

( )

1 2ˆsin sin 2s B B u θ

( )su

Page 14: Emergence of collective dynamics in active biological systems

A spherical model: Squirmer

Ishikawa & Pedley (2006-)

propelling velocity stress against shear flow

( )

1ˆsin sin 2s B u θSurface flow

velocity

down

up

14

J. R. Blake (1971)

Page 15: Emergence of collective dynamics in active biological systems

A spherical model: Squirmer

0

Bacteria chlamydomonas

Pusher Puller

Micro-organism

Squirmer

0 0

15

extension contraction

Page 16: Emergence of collective dynamics in active biological systems

SD

Ishikawa, Pedley, … (2006-)Swan, Brady, … (2011-)

.

.

.

DNS

LBM:Llopis, Pagonabarraga, … (2006-)

MPC / SRD:Dowton, Stark (2009-)

Götze, Gompper (2010-)

Navier-Stokes:Molina, Yamamoto, … (2013-)

.

.

.

Sim. methods for squirmers

16

16

Page 17: Emergence of collective dynamics in active biological systems

A single swimmer

0

Neutral swimmerExternally driven colloid(gravity, tweezers, etc…)

Box: 64 x 64 x 64 with PBC, Particle radius: a=6, φ=0.002Re=0.01, Pe=∞, Ma=0

SM 2013

1( ) | |u r r3( ) | |u r r

17

Page 18: Emergence of collective dynamics in active biological systems

A single swimmer

2 0 2

NeutralPusher Puller

Box: 64 x 64 x 64 with PBC, Particle radius: a=6, φ=0.002Re=0.01, Pe=∞, Ma=0

SM 2013

2( ) | |u r r3( ) | |u r r

2( ) | |u r r

18

Page 19: Emergence of collective dynamics in active biological systems

A single swimmerStream lines

19

2 Puller

( )u r

SM 2013

Page 20: Emergence of collective dynamics in active biological systems

20

Swimmer dispersion

2

neutral

puller

0

pusher

2

0.01 0.05 0.10 0.124

, SM 2013

20

Page 21: Emergence of collective dynamics in active biological systems

Velocity auto correlation

21

SM 2013

s

1( )l U

Short-time Long-time

weak dependency on ,

2

2

(, ) ~ ~

)( l

c

UD U

r

↑collision radius

Analogous to low density gas

(mean-free-path)

2( ) exp ex

, ,p

s l

t tC t U U

Page 22: Emergence of collective dynamics in active biological systems

Collision radius of swimmers

22

SM 2013

1/2

2 2c lr U

cr

PullerPusher

( 5)cr a

increases with increasing ||

Nearly symmetric for puller (0)

and pusher (0)

cr

Page 23: Emergence of collective dynamics in active biological systems

Outline

1. Introduction:

– DNS for particles moving through Fluids

2. DNS of swimming (active) particles:

– Self motions of swimming particles

– Collective motions of swimming particles

23

Page 24: Emergence of collective dynamics in active biological systems

Collective motion: flock of birds

24

Interactions:

• Hydrodynamic

• Communication

Re ~ 103~5

Ex. Vicsek model

Page 25: Emergence of collective dynamics in active biological systems

Collective motion: E-coli bacteria

25

Interactions:

• Hydrodynamic

• Steric (rod-rod)

Re ~ 10-3~-5

Ex. Active LC model

Page 26: Emergence of collective dynamics in active biological systems

Question

Can any non-trivial collective motions take place in a system composed of spherical swimming particles which only hydrodynamically interacting to each other?

DNS is an ideal tool to answer this question.

26

Page 27: Emergence of collective dynamics in active biological systems

Collective motion of squirmersconfined between hard walls (at a volume fraction = 0.13)

puller with = +0.5 27

unpublished

pusher with = -0.5

Page 28: Emergence of collective dynamics in active biological systems

Dynamic structure factorSummary for bulk liquids

Rayleigh mode(thermal diffusion)

Brillouin mode(phonon)

dispersion relation with speed of sound: cs

sω kc

28

s

1c

T

T

bDa

22 k

T

22D k

Page 29: Emergence of collective dynamics in active biological systems

Dynamic structure factorof bulk squirmers

dispersion relation with speed of wave: cs

sω kc

(puller with =+0.5)

ω

Brillouin mode(phonon-like?)

29

unpublished

Page 30: Emergence of collective dynamics in active biological systems

Dynamic structure factorof bulk squirmers (pusher with =-0.5)

ω

Similar to the previous puller case (=+0.5),but the intensity of the wave is much suppressed.

30

unpublished

Page 31: Emergence of collective dynamics in active biological systems

Dynamic structure factorDispersion relation

31

unpublished

sω kc

Page 32: Emergence of collective dynamics in active biological systems

Open questions

• Dependencies of the phenomena on

• Mechanism of density wave

• Corresponding experiments

32

unpublished

, , L

naive guess …

for pullers

contraction