Process Tomography for

Multiphase Flow Visualization

May 1, 2015, Chiba, Japan

Dr. Masa TAKEI

Prof. of Chiba University, Chiba Japan

Guest Prof. of Xi’an University of Technology,

China

Chiba University

Laboratory on Multiphase

Flow and Visualization

Download web site http://www.em.eng.chiba-u.jp/~takei/ 講義 Doctor course lecture

OUTLINE Multiphase Flow System & CFD-DEM

Necessity of Flow Visualization Techniques

Application of Process Tomography

Plant & Manufacturing Process

Application of Process Tomography

Challenge to Thrombus Detection

Concluding Remarks

Liquid

Gas

Particles

Multiphase Flow Systems

G-L

L-P

G-P

GFFv

ca dt

dm

Tω

dt

dI

Gas phase (Continuum phase ) Solid phase (Discrete phase)

ia,Fuuuu

2)()(

)(egggg

ggp

t

CFD-DEM for System Design in Dense Phase

),( ipiia, uvF g

)8.0(

)1(

4

3

)8.0( 75.1)1(150)1(

7.2

2

2

e

p

D

e

p

Rd

C

Rd

43.0

Re)Re15.01(24 687.0

DC

μ

ρεduv pp Re

Ergun’s equation, 1952

Drag force

m : Mass of the particle, v : Translational velocity, ω : Rotational velocity, p : Pressure,

I : Moment of inertia, Fa : Force acting on particle exerted by surrounding air,

Fc : Contact force, G : Gravitational force, u : Velocity vector of air,

T : Torque caused by the contact force and the moment of inertia of particle,

ε : Volume fraction, ρg : Density of air, μ : Fluid viscosity, μe : Eddy viscosity ,

CD : Drag coefficient for a single particle, dp : Particle diameter, v : Particle velocity

)1000(Re

)1000(Re

Wen and Yu’s equation,

1966

u 0)(

g

g

t

cnctt

tct FFx

xF ftt ifdt

dk

cnct

t

tcnct FF

x

xFF ff if

dt

dk nn

nncn

xxF

Normal contact force

Fig. Models of contact force

Cundall and Strack 1979

Tangential contact force

kn & kt : Spring constant in the normal and tangential direction

ηn & ηt : Coefficient of viscous dissipation in the normal and tangential direction

μf : Friction coefficient

xn & xt : Particle displacement in the normal and tangential direction

Contact Force due to Particles Collision

Particle Particle

24mm

122mm 45mm

Air

Air

Air

Air

Air

FCC

FCC

FCC

FCC

Fig. New designed distributor

New Designed Distributor & Conditions

Powder circulation rate (particle flow rate) Gs [kg/m2s] 349

Center: Side

1:4

Air flow rate of center nozzle Qac [m3/s] 0.094

Total air flow rate of side nozzle Qas [m3/s] 0.378

Table Calculation conditions

T.Zhao, M.Takei, Flow Measurement and Instrumentation, (2007)

T.Zhao, M. Takei, et al., Powder Technology, (2011)

Fig. Fluidized bed test plant

Simulation Conditions

Gas phase Particle phase

Fluid type Air Particle shape spherical

Density(kg/m3) 1.2 Density(kg/m3) 1200

Bed geometry(m) 0.27

(diameter) Particle diameter(mm) 0.3

1.98(height) Number of particles 328400

Superficial velocity (m/s)

20 Spring constant (N/m) 800

Viscosity(kg/ms) 2.0×10-5 Friction coefficient 0.3

Acceleration of gravity (m/s2)

9.8 Time step (s) 10-4

k

dt

n

pp

6

)(

5

23

Time step (Y. Tsuji et al. 1992)

T. Zhao and M.Takei, Advanced Powder Technology, (2008)

T.Zhao and M.Takei, Powder Technology, (2010)

Calculation Domain and Calculation Results Particle

inlet

21

2 122

212 45

270

Particle inlet

270

Air nozzle

(Dimension in mm)

212

122

1980

h=0.33m h=0.99m h=1.65m

Fig. Simulation results of axial position

0.0% 5.0% Powder concentration

Distance from the distributor h [m]

h=300[mm]

h=400[mm]

……

……

……

……

……

……

…

h=1900[mm]

h=0[mm]

Solid

volu

me

fraction [

-]

T.Zhao, M.Takei,. Flow Measurement and Instrumentation, (2010)

T.Zhao, M.Takei, Advanced Powder Technology, (2010)

Distance from center [mm]

Part

icle

volu

me fra

ction [

-]

Calculated Profiles of Axial & Radial Volume Fraction

Fig. Profiles of axial volume fraction

Fig. Profiles of radial volume fraction

Functional particle

Nozzle spray of coating

solvent to nucleus particles

in fluidized bed

Coating Process in Powder Drug Production

Coating process

Coating solvent Nucleus particles

Functional particles

Fig. Functional particles Dry of coating solvent by

hot air

Fig. Coating process

Nucleus particles

Draft tube

Spray nozzle

Hot air supply

Hot air duct

Spray

nozzle

Apertures

plate

Bug

filter

Exhaust duct

Outer

chamber

Draft tube

Operational factors for

uniform coating

CFD-DEM & Noninvasive

monitoring technique to

visualize the uniformity of

particles fluidization

during coating process

M.Takei, et al.,Powder Technology, (2009)

CFD-DEM Simulation for Drug Production

gFFFv

Dwallcollision mdt

dm

collisionF

wallF

：Powder-powder stress

：Powder – wall stress

Powder equations of motion

Fig. Model of Particles Collision

Fig. DEM simulation results

High air velocity

Spring

dashpot

friction slider

DF ：Drag force

OUTLINE Multiphase Flow System & CFD-DEM

Necessity of Flow Visualization Techniques

Application of Process Tomography

Plant & Manufacturing Process

Application of Process Tomography

Challenge to Thrombus Detection

Concluding Remarks

Simulation results look real, but they are not real !!!!!

Academic parameters of particles motion:

Coefficients of spring, dashpot and slider

Drawbacks of simulation: Perfect sphere, Same diameter particles

⇒Coefficients dependency on time & each particle

Industrial parameters of process:

Homogeneous particle concentration

Best nozzle design: Place, Number, Diameter etc.

Proper operation factor: Mass flow rate Q,

Particle supply ratio ξ, Temperature T etc., “in time”

Particle Particle

Gap between Academia and Industry for Best Design

kn & kt : Springs constant

ηn & ηt : Coefficient of viscous dissipation

μf : Friction coefficient

Happy academia: Parameter fitting with experiments

Unhappy industry: How much is the essential parameters for the

best design?

Necessity of Visualization Technique for Best Design

Flow visualization technique for best design to overcome the gap

Non destructive visualization technique

3D + time particle concentration

“What you can see “in real situation” is what you can believe”

Insufficient CFD-DEM for the best design

OUTLINE Multiphase Flow System & CFD-DEM

Necessity of Flow Visualization Techniques

Application of Process Tomography

Plant & Manufacturing Process

Application of Process Tomography

Challenge to Thrombus Detection

Concluding Remarks

Fig. Tomographic image of inside head

by medical CT

Process Tomography

Fig. Overview of PT for particle flow

Pipeline Electrode

Particle

①

②

③

⑫

⑪

⑥

⑧

④ ⑤

⑦

⑨ ⑩

①

②

③

⑫

⑪

⑥

⑧

④ ⑤

⑦

⑨ ⑩

①

②

③

⑫

⑪

⑥

⑧

④ ⑤

⑦

⑨ ⑩

From Hitachi Co Web

Fig. PT(ECT)System

10million US $ Easy handling, Low cost & high seed

10,000 US $

Governing equation of PT(ECT)

Ill posed Inverse Problem

Unknown Number > Expression

Number

Image Reconstruction

Approximate Permittivity E

0)]()([ rr V･　 --(2)

jr

i

c

ji dVV

C rrr ･)()(0,

)12,,1;11,,2,1( iji

--(1)

Ci,,j:Capacitance between i and j electrodes, ε0:Vacuum permittivity, VC : Electrode voltage , r : Position vector,

ε: Relative permittivity, Vi : Potential in cross section, Γi : Area covered with electric force line

Governing Equation in the Electrostatic Field

0)]()([ rr V･　 --(2)0)]()([ rr V･　 --(2)

jr

i

c

ji dVV

C rrr ･)()(0,

)12,,1;11,,2,1( iji

--(1)

Ci,,j:Capacitance between i and j electrodes, ε0:Vacuum permittivity, VC : Electrode voltage , r : Position vector,

ε: Relative permittivity, Vi : Potential in cross section, Γi : Area covered with electric force line

Governing Equation in the Electrostatic Field

32 × 32 Space Resolution

Pipe inner wall

Ｎｘ =32

Ｎｙ =32

x

y

Measured Capacitance C

66 × 1

Sensitivity Matrix S e

66 × 1024

Unknown Permittivity

Distribution E

1024 × 1 C = S e E

1

12

11 10 9

8

7

6

5 4 3

2 Electrode

x

y

Sensitivity [ - ]

32 × 32 Space Resolution

Pipe inner wall

Ｎｘ =32

Ｎｙ =32

x

Ｎｘ =32

Ｎｙ =32

x

y

Measured Capacitance C

66 × 1

Sensitivity Matrix S e

66 × 1024

Unknown Permittivity

Distribution E

1024 × 1 C = S e E

1

12

11 10 9

8

7

6

5 4 3

2 Electrode 1

12

11 10 9

8

7

6

5 4 3

2 Electrode

x

y

Sensitivity [ - ]

M. Takei et al. Measurement Science and Technology (2004, 2006)

1. Two guard electrodes

Concentration of electrical line

2. High Ω Resistance

Protection of stray capacitance

3. Screen electrodes

Noise Absorption

Fig. Guard electrodes

U0=0 U1

Measured electrodes

Guard electrodes

Guard electrodes

Fig. CT sensor

Coaxial cable

Resistance

Earthed electrodes

Guard electrodes

Guard electrodes

Measured electrode

Copper wire

PT(ECT) Sensor

Noise

Fig. Screen electrode

Measured

electrodes

Nois

e a

bsorp

tion

Resistance

Noise protection method

Screen

electrode

M.Takei,et al. International Journal of Applied Electromagnetics and Mechanics, IOS Press, (2002)

M.Takei et al., Particulate Science and Technology, Taylor & Francis, (2002)

0.0 0.2

Reconstructed Images in Fluidized Bed by PT

Air

Low

Sensor position

h=0.33m

h=0.99m

h=1.65m

Case1.1 Case1.2 Case 1.3 Case 1.4

M.Takei et al. Powder Technology (2009)

M.Takei, et al., Experiments in Fluids, Springer, (2008)

Part

icle

volu

me fra

ction [

-]

Axial position h [m]

1:2

1:1

1:4 Air

Air

Air

Particle volume fraction decreased as

axial position goes downstream in both

experiment and simulation.

Low

Middle

High

Axial Volume Fraction Profiles

h=0.33m (Experiment)

h=0.99m (Experiment)

h=1.65m (Experiment)

h=0.33m (Simulation)

h=0.99m (Simulation)

h=1.65m (Simulation)

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0 15 30 45 60 75 90 105 120 135

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0 15 30 45 60 75 90 105 120 135

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0 15 30 45 60 75 90 105 120 135

1:2

1:1

1:4 Air

Air

Air

Low

Middle

High Part

icle

volu

me fra

ction [

-]

Radial position r [mm]

Radial Volume Fraction Profiles

PT Images of Particle Coating

Spray time

0 min

Spray time

10 min

Spray time

20 min

Spray time

30 min

Spray time

40 min Spray time

50 min

0.0 1.0 Concentration

Fig. Instantaneous CT Images at each spray time

The high concentration particle distribution is located near the tube

Nucleus powder Crystalline cellulose Asahi Kasei Corporation Celphia 203

Nucleus powder diameter 150μm

Density of powder 870 kg/m3

Relative permittivity of Air 1.0006

Relative permittivity of Powder 2.1

Atomized coating liquid HPC (Hydroxypropyl Cellulose) Shin-Etsu Chemical Co.

Spray coating time 50 minutes

Sampling time Every 5 minutes for several seconds

Spatial Mean Concentration from Image

y xN

y

N

xoutyx

pNNN

tD1 1

1xytE

The spatial mean particle concentration at a time point

outN : the pixel number outside the pipe

Spray time 0 min

Fig. Spatial mean concentration from CT images.

Spray time 10 min Spray time 20 min

100 200 300 400 500 Time

0.2

0.4

0.6

0.8

1

Range

100 200 300 400 500 Time

0.2

0.4

0.6

0.8

1 Range

100 200 300 400 500 Time

0.2

0.4

0.6

0.8

1 Range

100 200 300 400 500 Time

0.2

0.4

0.6

0.8

1 Range

Sp

atia

l m

ean c

once

ntr

atio

n [

- ]

100 200 300 400 500 Time

0.2

0.4

0.6

0.8

1 Range

Spray time 30 min Spray time 40 min Spray time 50 min

100 200 300 400 500 Time

0.2

0.4

0.6

0.8

1 Range

×Δ t[ms]

×Δ t[ms]

Spat

ial

mea

n c

on

cen

trat

ion

[ - ]

M.Takei, et al.,Powder Technology, (2009)

T. EDA, M.TAKEI et al., Journal of Power and Energy Systems (2013)

Air

Experiments of Trickle Bed Reactor

Pulsing Bubble Trickle

(QL, Q

G)=

(13L/m

in,

70L/m

in)

(QL, Q

G)

=(6

L/m

in, 10L/m

in)

(QL, Q

G)

=(1

3L/m

in,

15L/m

in)

t=4.0

sec

z = 1020 mm,

dp = 5 mm,

x

y

t

3D Reconstructed Images

Flow Patterns in Trickle Bed

(QL, Q

G)=

(13L/m

in,

70L/m

in)

QL

QG

①

② ③

① ② ③

0.0 0.2 Normalized Conductivity [-]

Fig Experimental set up

Measurement

system

• heater

Data acquisition/

Data logger switch

unit

heater

Reference

Ceramics

beaker

Polycarb

onate

particles

Electrodes

0

1

0 1/1

6 2

/16

3/1

6 4

/16

5/1

6 6

/16

7/1

6

• heater

120[sec] 180[sec] 240[sec]

300[sec] 360[sec] 420[sec]

Fig PT temperature images

low

<-Te

mp

era

ture

->h

igh

Temperature Distribution by PT

Fig Temperature distribution by PT

ε :Relative permittivity[F/m],

M :Mol mass[kg/mol],

ρ :Density[kg/m3],

NA : Avogadro Number[-],

T :Temperature[K],

kB : Boltzmann constant[J/K],

μ :Permanent dipole moment[D]

OUTLINE Multiphase Flow System & CFD-DEM

Necessity of Flow Visualization Techniques

Application of Process Tomography

Plant & Manufacturing Process

Application of Process Tomography

Challenge to Thrombus Detection

Concluding Remarks

Artificial

valve

Artificial

heart

Artificial

lung

Artificial

vessel Stent Artificial

kidney

Artificial

liver

2) Unclear Interface multi-physics

between artificial organs and blood

1) Immature thrombus detection

measurement technique

Increase of thrombosis risk

by artificial organs

Thrombus future prediction Thrombus online measurement

Anticoagulant treatment

Anxiety for thrombosis of patient

Possibility of thrombosis prediction(When, Where, How)

However

Japanese COD: 30% Circulatory condition

Cardiac disease: 16％

Cerebrovascular disease: 12%

Others 42％

Cancer: 30％

Figure: Japanese COD

Background of Thrombus Detection

Practical use of artificial organs

COD: Cause of death

Thrombosis in VAD

impeller

Pharmaceutical Approval

of VAD

Business since 2011.4.1

「EVAHEART」「DuraHeart」

(1) Thrombus Insitu detection technique

(2) Thrombus Insilico prediction technique

(3) Thrombus Invitro validation technique

VAD accelerate the formation of thrombus

Complication of Cerebral infarction VAD impeller

Left ventricle

Blood

transmission

Blood

cannula

Aorta ascendens

Return to work &

home healthcare by

implanting VAD

Example of Ventricular Assist Device

Establishment of future prediction technique of thrombus

Our Proposal !!

Research and development of total solution

31

Blood Coagulation Process

Extrinsic reaction

Intrinsic reaction

Tissue factor

VIIa

Ca++

X Xa

IX IXa

XIa XI

XIIa XII

Polymerization

・Gelation reaction in liquid

Prothrombin

Thrombin

XIII XIIIa Ca++

Fibrin clot

Fibrin

Fibrinogen

Fibrinolysis Plasmin (Cross-link)

32

Multi-interface of Thrombus invitro

Artificial interface

Tethering

Biochemistry

factor

Gathering Rolling

G.Matsumiya et al. J Heart Lung Transplant. (2010)

Flow rate

Thrombus

structure

Mu

lti-p

hysic

s

Interface of artificial

surface and elastic

substrate Interface of blood

and endothelium Artificial interface

Interface of blood and

artificial surface

Interface of artificial

surface and

endothelium

Mimic flow

channel

032

1

AW NM

e

B

AW

Tk

NM

332

1 2

0

Polarization

Mw:Number of molecule，NA：Avogadro number，kB：Boltzmann constant，

T：Absolute temperature，ρ：Density

Clausius-Mossotti equation

Debye equation

Dielectric Spectrum Orientation

polarization

Ions polarization: Negligible

Electron

polarization

Microwave f=2.45GHz K.Asami http://www003.upp.so-net.ne.jp/asami/DS.pdf

D：Electrical flux [C/m2],

ε0 ：Vacuum permittivity[F/m] ,

E ：Electrical field[V/m],

P：Polarization[C/m2]，

N: Number of molecule

per unit volume[-],

m: Induced dipole moment [Cm],

F: Effective electric field [V/m],

ε: Relative permittivity[-],

α : Polarizability of molecule [Cm2/V]

μ : Permanent dipole moment[Cm]

●Electrical flux and Polarization

D = ε0E + P P = Nm = NαF

Orientation & Electron

polarizations

(Polar molecule)

34

Electrical Change of RBCs Membrane Cole-Cole Plot

Electrode

R

RBCs

RBCs

R

Plasma

R

RBCs

membrane C

Electrode

R

Electrode

C

Thrombus

Re

acta

nce

[Ω]

Resistance[Ω]

Shift to upper right of

relaxation frequency

Electrode

EDL

Electrode

R

Electrode

C

Electrode

EDL

Membrane

Hemoglobin

Plasma

C

Fibrin

High

frequency

Middle

frequency

Low

frequency

Curr

ent

Curr

ent

Cu

rren

t

CPE CPE

EDL: Electrical Double Layer

0

20

40

60

80

100

120

140

160

180

200

1050 1150 1250 1350 1450

Reacta

nce X

[Ω

]

Resistance R [Ω]

t=0.0min

t=27.0min

t=45.0min

t=72.0min

t=90.0min

f =70kHz

f =1MHz

f =4MHz

Resistance increment for thrombus

formation

VoltageV 1[V]

Measurement frequency f

70kHz～4MHz

Measurement time t 90min

Measurement point 60 Point

Cole-Cole Plot

Shift on upper right

Shift of Cole-Cole plot

20Ω

Electrode

Holder

PC X

Y Z

30mm

Impedance

Analyzer

(Plasma 63%+30%CaCl2)

Reactance Change of RBCs Membrane

Thrombus formation

C Decreased

X Increased

Experimental setup

Bovine

Blood

Calcium

Chloride

Impedance

Analyzer PC

Electrode

20mm

20m

m

Z X

Y

10

mm

Photo of thrombus

formation experiment

Injection current i 4.0[mA]

Sweep AC frequency f 1[kHz]~5[MHz]

Measurement point 201[point](Log)

Calibration Open, Short

Average 5

Measurement condition

Experimental Condition

1. Estimate of RBCs relaxation frequency

2. Measurement of thrombogenic process

Addition of CaCl2

Addition of thrombin

1. Blood+CaCl2

2. Blood+PBS+CaCl2

3. Blood+PBS

4. Blood(Hematocrit change)+CaCl2

Measurement time

3.0mL+1.0mL（0.02M）

3.0mL+0.4mL+0.6mL

3.0mL+1.0mL

3.0mL（H[%]=0, 10, 20, 30）+1.0mL

t =0.0min～60.0min

PBS

PBS+Thrombin

Fibrinogen+PBS

Fibrinogen+Thrombin

4.0mL

3.5mL+0.5mL（1000units/mL）

3.5mL（2500mg/dL）+0.5mL

3.5mL（2500mg/dL）+0.5mL

Blood

Hematocrit

Blood volume

Sodium citrate

Bovine blood（H=36%）

H [%]=0,10,20,30,36,40,50,60

4.0mL

0.4mL（3.2vol%） in 4.0mL 20mm

20

mm

Z

X

Y

10

mm

Bovine

Blood Calcium

Chloride

Calibration Method

Calibration method

Calibration of cell

r0r0p CCε'Cd

Sεε'C

d

SεC 00

Cr=6.93×10-13

C0=8.85×10-14

Gε

Cρ

0

00ωρC

'ε'1

20mm

20

mm

Z

X

Y

10

mm

Relaxation

frequency

Estimate of electrode polarization and RBCs membrane

Stray

capacitance Cr

Cell constant C0

Relative permittivity and Dielectric loss

Relative

permittivity ε’ 0

rp

C

CCε'

Resistivity ρ Dielectric loss ε”

S:Electrode area[m2]

d:Distance between electrode[m]

ε0:Vacuum permittivity[F/m]

ε’: Water permittivity[F/m]

G:Conductance[S]

Cp: Measurement capacitance[F]

ω:Angular frequency[rad/s]

1E+02

1E+03

1E+04

1E+05

1E+06

1E+07

1000 10000 100000 1000000

Rela

tive p

erm

itti

vit

y ε' [-

]

Frequency f [Hz]

H=0% H=10%H=20% H=30%H=36% H=40%H=50% H=60%

0

1000

2000

3000

4000

5000

10000 100000 1000000

Die

lectr

ic l

oss ε

" [

-]

Frequency f [Hz]

H=0% H=10%H=20% H=30%H=36% H=40%H=50% H=60%

Permittivity & Dielectric Loss of RBCs

RBCs relaxation frequency

Electrode relaxation frequency：20kHz

RBCs relaxation frequency：2MHz

RBCs membrane permittivity: 250kHz

Electrode relaxation frequency

f<60kHz : Electrode polarization

60kHz<f<1MHz : RBCs membrane

permittivity

f>1MHz : RBCs dielectric relaxation

Hematocrit change

Electrode polarization

RBCs membrane permittivity

RBCs dielectric relaxation

Electric Influence of Thrombin

0.6

0.61

0.62

0.63

0.64

PBS PBS+Thrombin

Resis

tivit

y ρ

[Ω・m

]

500

520

540

560

PBS PBS+Thrombin

Rela

tive p

erm

itti

vit

y ε' [-

]

decrease

Increase

Resistivity

PBS only

PBS+Thrombin ＞

Relative permittivity

PBS only

PBS+Thrombin ＜

Thrombin decreases

the resistivity

Thrombin increases the

relative permittivity

250kHz

Electrical Influence of Fibrinogen Solution

910

930

950

970

990

1010

Fbg+PBS Fbg+Thrombin

Rela

tive p

erm

itti

vit

y ε' [-

]

0.415

0.42

0.425

0.43

0.435

0.44

0.445

Fbg+PBS Fbg+Thrombin

Resis

tivit

y ρ

[Ω・m

] Resistivity

Fibrinogen+PBS

Fibrinogen+Thrombin

＞

Relative permittivity

Fibrinogen+PBS

Fibrinogen+Thrombin

＜

Increase

Decrease

Fibrin formation

increases the resistivity

250kHz

Fibrin formation decreases

the relative permittivity

2500mg/dL Fibrinogen

Permittivity & Resistivity of Thrombogenic Process

Time [min] 0.0 5.0 10.0 15.0 20.0 25.0 30.0

Visual check － － － ＋ ＋＋ ＋＋＋ ＋＋＋

Time [min] 35.0 40.0 45.0 50.0 55.0 60.0

Visual check ＋＋＋ ＋＋＋ ＋＋＋ ＋＋＋ ＋＋＋ ＋＋＋

(a) －：Non-thrombogenic condition

(b) ＋：Micro thrombus formation

(c) ＋＋：Thrombus over 1mm

(d) ＋＋＋：Huge thrombus

Result of visual check

0.99

1

1.01

1.02

1.03

0.92

0.94

0.96

0.98

1

1.02

0 10 20 30 40 50 60N

orm

alized

resis

tivit

y ρ

* [-

]

No

rmalized

rela

tive

perm

itti

vit

y ε’*

[-]

Time t [min]

fec=20kHz ε' fm=250kHz ε' frc=2MHz ε' fec=20kHz ρ fm=250kHz ρ frc=2MHz ρ

(a) (b) (c)(b) (c) (d)

Relative Permittivity & Resistivity of

Thrombogenic Process of Others Conditions

Non-thrombogenic（PBS 25%） （blood 3.0mL+PBS 1.0mL）

Thrombogenic（CaCl2 15%） （blood 3.0mL+PBS 0.4mL+CaCl2 0.6mL）

The experiments showed the possibility of the real time detection of

thrombosis using the characteristics frequency of red blood cells membrane

0.99

1

1.01

1.02

1.03

1.04

1.05

1.06

0.92

0.94

0.96

0.98

1

0 10 20 30 40 50 60

No

rmalized

resis

tivit

y ρ

* [-

]

No

rmalized

rela

tive

perm

itti

vit

y ε

'* [

-]

Time t [min]

fec=20kHz ε' fm=250kHz ε' frc=2MHz ε' fec=20kHz ρ fm=250kHz ρ frc=2MHz ρ

0.99

1

1.01

1.02

1.03

1.04

0.91

0.93

0.95

0.97

0.99

1.01

0 10 20 30 40 50 60

No

rmalized

resis

tivit

y ρ

* [-

]

No

rmalized

rela

tive

perm

itti

vit

y ε

'* [

-]

Time t [min]

fec=20kHz ε' fm=250kHz ε' frc=2MHz ε' fec=20kHz ρ fm=250kHz ρ frc=2MHz ρ

Relative Permittivity & Resistivity of

Thrombus of Hematocrit Change

Addition of CaCl2

Hematocrit

Measurement time

Blood+CaCl2

H[%]=0, 10, 20, 30

t =0.0min～60.0min

3.0mL+1.0mL（0.02M）

250kHz

Only plasma was not seen of peak

of relative permittivity decrease

The phenomenon was specific to the

thrombosis, and was observed only in

the presence of red blood cells.

0.92

0.94

0.96

0.98

1

1.02

0 10 20 30 40 50 60

No

rmalized

rela

tive

perm

itti

vit

y ε

'* [

-]

Time t [min]

H=0%

H=10%

H=20%

H=30%

Visualization of Thrombogenic Process insitu Detection

Bovine

blood CaCl2

Electrode holder

(PMMA)

Data

Acquisition

System

PC

X

Y Z

30mm

30m

m

Multiplexer 10m

m

5m

m

Cross-section

X

Y

R

Electrode (SUS304)

10mm 3mm

Z

PT visualization image of thrombogenic process

Concluding Remarks

CFD-DEM calculation results in powder technology are

shown in petroleum and pharmaceutical industries.

Flow visualization technique should be played a role of

product design as well as CFD-DEM

Noninvasive PT visualization technique is useful for

pant, manufacturing & blood monitoring.

The concept is “What you can see “in real situation” is

what you can believe”