Xiong (Bill) Yu, Ph.D., P.E. Associate Professor, Department of Civil Engineering

Case Western Reserve University

April 26, 2014

Contributors from Former and Current Students:

Zhen (Leo) Liu, Assistant Professor, Michigan Technological University

Chanjuan Han, Graduate Research Assistant

Bin (Ben) Zhang, Michael Baker Jr. Inc.

Multiphysics Simulation and Characterization

In support of Energy Geotechnology

About myself

Ph.D. Purdue University 2003, B.S. and M.S.

Tsinghua University 1997, 2000

Joined CWRU in 2005

Current program affiliation

Civil engineering/Geotechnical engineering/Infrastructure

engineering

EECS, MAE, MSE and other programs

Research program focus/interest

Sustainable geo/infrastructure (design, sensor technology, SHM,

field instrumentation diagnose, etc.)

Durable and multifunctional civil engineering materials

Smart engineering systems

Energy and efficiency

Challenges Facing the Rising Energy Demand

Source: Energy Information Administration Data

Unsaturated uniform soil specimen subjected to surface freezing

Multiphysics: Example

Vertical internal stress

0.00

0.05

0.10

0.15

0.20

0.25 0.30 0.35 0.40 0.45 0.50

0 hour

He

ight (m

)

0.00

0.05

0.10

0.15

0.20

0.25 0.30 0.35 0.40 0.45 0.50

12 hours

He

ight (m

)

0.00

0.05

0.10

0.15

0.20

0.25 0.30 0.35 0.40 0.45 0.50

24 hours

Total volumetric water content

He

ight (m

)

0.00

0.05

0.10

0.15

0.20

0.25 0.30 0.35 0.40 0.45 0.50

50 hours

Total volumetric water content

He

ight (m

)

Distribution of total volumetric water content

Thermal boundary load

Thermo-hydro

Thermo-mechano

Liu and Yu 2012

Understand the Multiphysics Process in

Gas Hydrate Exploration

Gas Hydrate

Definition: Gas hydrates, or clathrate hydrates, is a solid, ice-like form consisting of a host

lattice of water molecules that enclose voids, each of which may contain one molecule of a

guest gas (Selim and Sloan 1985) .

Guest gases: CH4, C2H6, C3H8, i-C4H10, CO2 etc. (Bishnoi 1996, Englezos 1993).

Natural occurring conditions: High Pressures and Low Temperatures (Oceanic Sediments

and Permafrost Regions)

Gas hydrate core sample from 920 m deep

at the Mallik site, Canada (www.sciencewatch.com)

Gas hydrate studied

in the Northern Gulf of Mexico (usgs.gov)

Massive gas hydrates Gas hydrate-bearing sediment

Uniqueness as Energy Source

Huge amounts of methane in a concentrated form

Combustible low molecular weight hydrocarbons such as

methane, ethane, and propane

(Kvenvolden, 1993; Hyndman and Dallimore, 2001)

Organic Carbon

in the Earth

Gas Hydrate Explorations

Challenges:

Limitations in understanding hydrate reservoirs behaviors (Pawar and

Zyvoloski 2005).

Optimal strategy for gas hydrate resource utilization.

Strategies

Simulation studies including analytical and numerical models

coordinated with laboratory studies to address knowledge gaps that are

critical to the prediction of gas production (Moridis et al. 2006).

Field validation

Mechanisms Involved 1. Energy Balance (Thermal Field, T)

2. Mass Transfer (Hydraulic Field, H)

3. Momentum Balance (Mechanical Field, M)

4. Chemical Kinetics (Chemical Field, C)

it is a MULTI-PHYSICAL process.

Trends in Gas Hydrate Simulations Simulation models for gas hydrate

THMC model emerging

Seafloor stability, geohazards prediction

Liu and Yu 2013

THMC

Multiphysics Simulation Structure

2/4/2012

Thermal (T,Ө) Fourier’s eq.

Mechanical (u, T,Ө,h)

Navier’s eq.

Hydraulic (h,T,Ө) Richards’ eq.

Ө

T

u

Ө

h

i i,( , ), ( , )tC

i( , , ),T T

i( , )E

Water Characteristic

th

First Layer Coupling

Third Layer Coupling

Second Layer Coupling

Chemical Field Experimental

(C)

Energy Balance (T)

Mass Balance(H) Moment Balance

(M)

Governing Equations

duu

dt v v q h

j j j j j jd

mdt

v

Tj j j j j j j j

d

dt

vv v F

Tj j j j j j

ee e

t

v

ww w w w w w w wd

mdt

v v

g gg g g g g g g g g g gd d

mdt dt

v v

s 0d

dt

ww w w w w w w w w w w w wg +d

mdt

v

v v i σ F v

gg g g g g g g g g g w w wg +d

mdt

v

v v i σ F v

h h h h h 0g σ F

s s s s s 0g σ F

g gj j j j j

j j j j j j j j j j j j j j j j j j j

T zC T C T H m

t t

v σ v F v v v

hh h

dm

dt

Energy Balance

Momentum Balance

Mass Balance

Model simplifications

w ww w w wg

g

d kp m

dt

i

g g gg g g g ggg

d d kp m

dt dt

i

hh h

dm

dt

s h s h f s s h h' 0p g σ δ i

w,g

ggj j

j

j jj j jjk

pCT

C T T Ht

i

Water Mass (1)

Gas Mass (1)

Hydrate Mass (1)

Solid Momentum (Mechanical,3)

System Energy (1)

Auxiliary Relationships

e A+B expC

Tp

j jσ σw w wp σ δ

g g gp σ δ

f w g1p Sp S p

f' p σ σ δ

sh s h s h f' p σ σ σ σ δ

' :σ C ε

T1

2

ε u u

ww w ww w

gg

kp

v i

gg g gg g

gg

kp

v i

g w 1p p f S

g g

g

M p

RT

w g h s,01 w

w h h h

h

103.55.75 5.75 4.9801

119.5

Mm m m m

M

g

g h h h

h

160.13389

119.5

Mm m m m

M

1

37 3h0

h h f e 23

h

94000.585 10 exp kg m sm p p

T

3 3h h h3h

54200494977.17 W/m

109.5 1054.2 10

mm m

MH

4 2 4 2CH nH O CH +nH O (n = 5.75 in this study)

Implementation

0 4 8 12 16 200.0

0.2

0.4

0.6

0.8

1.0

Satu

ration

Distance from bottom (m)

HydrateResSim

MH21

STARSOIL

STARSSOLID

STOMPHYD

UNIVHOSTON

NewModel

0 4 8 12 16 200.2

0.3

0.4

0.5

0.6

0.7

0.8

Satu

ration

Distance from bottom (m)

HydrateResSim

MH21

STARSOIL

STARSSOLID

STOMPHYD

UNIVHouston

NewModel

1 Day 100 Day

Bottom Top

20 m

USGS-NETL Gas Hydrate Simulation Comparison Project: Case 1 (No Dissociation)

Saturation at different times

Liu and Yu 2013b

Implementation

Bottom Top

20 m

USGS-NETL Gas Hydrate Simulation Comparison Project: Case 2 (Dissociation)

1 Day 100 Day

0 4 8 12 16 200.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

0.60

0.65

HydrateResSim

MH21

STARS

STARSSOLID

STOMPHYD

TOUGHFXHydrate

UnivHouston

NewModel

Sa

tura

tio

n

Distance from bottom (m)

0 4 8 12 16 20

0.2

0.3

0.4

0.5

0.6

0.7

HydrateResSim

MH21

STARS

STARSSOLID

STOMPHYD

TOUGHFXHydrate

UnivHouston

NewModel

Sa

tura

tio

n

Distance from bottom (m)

Saturation at different times

Liu and Yu 2013b

0 10 20 30 40 50 60 70 80 90 100-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Su

bsid

en

ce

(m

)

Time (day)

Subsidence

Hydrate Dissociation Ground Settlement

Profile of a hydrate-bearing zone and

corresponding computational domain

Liu and Yu 2013b

Understand the Multiphysics Process in

Underground Geothermal Heat

Exchanger

Geothermal Heat Exchanger

Summer: cooling mode Winter: heating mode

heat dispersion heat absorption

Prototype House with Geothermal Heat Pump

Prototype

• Geothermal heat pump

system installed under a

three-floor resident

house located in

Cleveland

• Instrumented (Tin,

Tout, flow velocity,

power consumption,

etc.)

Geometry

• U-pipe: D=100mm

• Pipe wall thickness: 5mm

• Length=60m

• Distance between inlet and outlet pipe=0.4m

• Borehole: R=0.4m

Boundary Conditions

• Pipe inlet temperature: Tinlet=7℃

• Flow rate：v=0.1m/s

• Soil temperature: T=15℃ (under depth of 4m)

Material Property

• Fluid: water

• Pipe: HDPE

• Refill material: bentonite

Non-isothermal Pipe

Flow

Physics Process and Simulation Model

soil

borehol

e

pip

e

Heat Transfer in Solid

Coupling

Process

Temperature(degC)

Figure 1 Temperature distribution

on the border of the borehole

and on the transverse section

Figure 2

Temperature

distribution along

the pipe

3-D Stationary Model

• Sensitivity analysis

• Optimize the design

3-D Time-dependent Model

• Compare the simulation and experimental data

• Calibration and optimization

Simulation Design and Schematic Results

Example Results: Sensitivity study

3-D Stationary Model: sensitivity analysis (d=50mm)

7

7.5

8

8.5

9

9.5

10

10.5

11

11.5

12

0.1 0.2 0.3 0.4 0.5 0.6 0.7

Out

let T

empe

ratu

re (℃

)

Flow Velocity (m/s)

10m20m30m40m50m60m70m80m90m100m

16

17

18

19

20

21

22

23

24

25

10 20 30 40 50 60 70 80 90 100

He

at

Exc

ha

ng

e R

ate

(W

/m)

Depth of the pipe (m)

0.1 0.2 0.3 0.4 0.5 0.6 0.7

Flow velocity (m/s)

( ) / Lout inQ cvA t t

0

5

10

15

20

25

30

35

40

45

12

:00

AM

1

:00

AM

2

:00

AM

3

:00

AM

4

:00

AM

5

:00

AM

6

:00

AM

7

:00

AM

8

:00

AM

9

:00

AM

1

0:0

0 A

M

11

:00

AM

1

2:0

0 P

M

1:0

0 P

M

2:0

0 P

M

3:0

0 P

M

4:0

0 P

M

5:0

0 P

M

6:0

0 P

M

7:0

0 P

M

8:0

0 P

M

9:0

0 P

M

10

:00

PM

1

1:0

0 P

M

2012-10-08

T_in(experimental) T_out(simulation)T_out(experimental) BB_low(experimental)BB_high(experimental) 0

5

10

15

20

25

30

35

40

45

12

:00

AM

1

:00

AM

2

:00

AM

3

:00

AM

4

:00

AM

5

:00

AM

6

:00

AM

7

:00

AM

8

:00

AM

9

:00

AM

1

0:0

0 A

M

11

:00

AM

1

2:0

0 P

M

1:0

0 P

M

2:0

0 P

M

3:0

0 P

M

4:0

0 P

M

5:0

0 P

M

6:0

0 P

M

7:0

0 P

M

8:0

0 P

M

9:0

0 P

M

10

:00

PM

1

1:0

0 P

M

2012-10-09

T_in(experimental) T_out(simulation)T_out(experimental) BB_low(experimental)BB_high(experimental)

Example Results: time dependent process

Example Results: time dependent process

0.000

5.000

10.000

15.000

20.000

25.000

2012-11

T_in(experimental) T_out(simulation) T_out(experimental)

Multiphysics Parameters Characterization

Multiphysics Characterization: Thermal-TDR probe:

6 mm

Sensor probe

Thermocouple reading wire

Connect to TDR unit

Combine EM wave and

thermal excitations

Example of thermal pulse response

0 30 60 90 120 15020

25

30

35

40

45

50

Time(s)

Tem

pera

ture

(oC

)

25.6

25.8

26.0

26.2

26.4

Tem

perature(oC

)

Heat Pulse

Thermal Response

EM Wave TDR Signals in Sand and Clay

5.4 5.6 5.8 6.0

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

Re

lative

Vo

lta

ge

(V)

Scaled Distance(m)

Dry Sand

w=4%

w=8%

w=12%

5.4 5.5 5.6 5.7 5.8 5.9 6.0

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

Rel

ativ

e V

olta

ge(V

)

Scaled Distance(m)

Dry Clay

w=5%

w=10%

w=15%

0 10000 20000 30000

-20

-10

0

10

20

30

Tem

pe

ratu

re (

oC

)

Time (s)

Heater

Receiver A

Receiver B

Specimen Center

Environmental Temp

-20 -15 -10 -5 0 5 10 15 20

0.5

1.0

1.5

2.0

2.5

3.0

Thermal Conductivity (W/(m*K))

Temperature (oC)

Characterization of physical and

thermal process during freezing-

thawing

Variation of thermal

conductivity with

temperature

Zhang and Yu 2012

How to advance in this exciting field

Research

Understanding the intrinsic properties relevant to multiphysics

coupling

Innovative characterization tools

Simulation capability (multiscale, multiphysics, nonlinear, time

dependent system)

Education

Interdisciplinary (knowledge base, characterization, etc.)

Modeling

Acknowledgements

Funding Agencies National Science Foundation, The Ohio Department of Transportation/FHWA, TRB/National Research

Council, NCHRP-IDEA, Minnesota Department of Transportation, Cleveland Water Department, Industry

sponsors (GRL/PDI, WPC Inc., Durham Geo Enterprises, MWH Inc., DLZ Ohio Inc., etc)

Graduate Students Past: Xinbao Yu (UT Arlington), Bin Zhang (Mike Baker), Yan Liu (Mount Union Univ), Zhen Liu

(Michigan Tech), Junliang Tao (U. Akron)

Current: Ye Sun (Michigan Tech), Chih-Chien Kung, Guangxi Wu, Jianying Hu, Quan Gao, Yang Yang,

Chanjuan Han, Yuan Guo, Jiale Li

Undergraduate Researchers Pete Simko, John Holman, Yuan Gao, Andrew Bittleman, Pete Simko, Cassandra McFadden, Paul Mangola,

Jingsi Lang, Donald Cartwright, Alex Potter-weight, Randall Beck, Vanessa Penner,Peter Frank, Ben Ma,

Rebecca Ciciretti, Joseph Brenner, Javanni Gonzalez, Vanessa Penner, Grant Mott, et al.)

Department engineer: Jim Berrila

Thank you