Multiph Mu tiphysics ysics Simu mulation lation and d Cha - - PowerPoint PPT Presentation

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.

Mu Multiph tiphysics ysics Simu mulation lation and d Cha haract racteriza erization tion In su supp pport t of En Energ ergy y Ge Geotechnolog echnology

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

Height (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

Height (m)

0.20

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,

( , ), ( , )

t

C     

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

 

du u dt



         v v q h

   

j j j j j j

d m dt        v

   

T j j j j j j j j

d dt        v v v F

   

T j j j j j j

e e e t        v

 

w w w w w w w w w

d m dt              v v

 

g g g g g g g g g g g g g

d d m dt dt                     v v

s

d dt    

w w w w w w w w w w w w w w

g + d m dt              v v v i σ F v

 

g g g g g g g g g g g w w w

g + d m dt              v v v i σ F v

 

h h h h h

g        σ F

 

s s s s s

g        σ F

 

   

g g

j j j j j

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

T z C T C T H m t t          



                 

           

    

v σ v F v v v

h h h

d m dt   

Energy Balance Momentum Balance Mass Balance

Model simplifications

 

w w w w w w

g g d k p m dt               i

 

g g g g g g g g

g g d d k p m dt dt                  i

h h h

d m dt   

     

s h s h f s s h h

' p g                        σ δ i

 

 

w,g

g g

j j

j j j

j j j

jk

p

C T C T T H t



  



             

 

      

 

i

Water Mass (1) Gas Mass (1) Hydrate Mass (1) Solid Momentum (Mechanical,3) System Energy (1)

Auxiliary Relationships

e

A+B exp C T p        

j j

  σ σ

w w w

p    σ δ

g g g

p    σ δ

 

f w g

1 p Sp S p   

f

' p   σ σ δ

 

sh s h s h f

' p        σ σ σ σ δ

' :  σ C ε

 

T

1 2         ε u u

 

w w w w w w

g g k p        v i

 

g g g g g g

g g k p        v i

 

g w 1

p p f S  

g g g

M p RT  

w g h s,0

1        

w w h h h h

103.5 5.75 5.75 4.9801 119.5 M m m m m M      

g g h h h h

16 0.13389 119.5 M m m m m M        

 

 

13 7 3 h0 h h f e 23 h

9400 0.585 10 exp kg m s m p p T               

 

3

3 h h h 3 h

54200 494977.17 W/m 109.5 10

54.2 10 m

m m M

H



  

 

4 2 4 2

CH nH O CH +nH O     

(n = 5.75 in this study)

Implementation

4 8 12 16 20 0.0 0.2 0.4 0.6 0.8 1.0

Saturation Distance from bottom (m)

HydrateResSim MH21 STARSOIL STARSSOLID STOMPHYD UNIVHOSTON NewModel 4 8 12 16 20 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Saturation

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

4 8 12 16 20 0.20 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

Saturation Distance from bottom (m)

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

Saturation Distance from bottom (m)

Saturation at different times Liu and Yu 2013b

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

Subsidence (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

• n 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 Outlet Temperature (℃) Flow Velocity (m/s) 10m 20m 30m 40m 50m 60m 70m 80m 90m 100m

16 17 18 19 20 21 22 23 24 25 10 20 30 40 50 60 70 80 90 100

Heat Exchange Rate (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)

( ) / L

• ut

in

Q cvA t t   

5 10 15 20 25 30 35 40 45

00 AM 00 AM 00 AM 00 AM 00 AM 00 AM 00 AM 00 AM 00 AM 00 AM 00 AM 00 AM :00 PM :00 PM :00 PM :00 PM :00 PM :00 PM :00 PM :00 PM :00 PM :00 PM :00 PM :00 PM

2012-10-08

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

5 10 15 20 25 30 35 40 45

:00 AM :00 AM :00 AM :00 AM :00 AM :00 AM :00 AM :00 AM :00 AM :00 AM :00 AM :00 AM :00 PM :00 PM :00 PM :00 PM :00 PM :00 PM :00 PM :00 PM :00 PM :00 PM :00 PM :00 PM

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

30 60 90 120 150

20 25 30 35 40 45 50

Time(s) Temperature(

• C)

25.6 25.8 26.0 26.2 26.4

Temperature(

• C)

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 Relative Voltage(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 Relative Voltage(V) Scaled Distance(m)

Dry Clay w=5% w=10% w=15%

10000 20000 30000

• 20
• 10

10 20 30 Temperature (

• C)

Time (s)

Heater Receiver A Receiver B Specimen Center Environmental Temp

• 20
• 15
• 10
• 5

5 10 15 20 0.5 1.0 1.5 2.0 2.5 3.0 Thermal Conductivity (W/(m*K)) Temperature (

• C)

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