integration of wave-based sensing into engineering decisions

Integration of Wave-Based Sensing into

Engineering Decisions

Present at Purdue Geotechnical Society Workshop in Honor of Vince

May 1st, 2010

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

Engineering and Computer Science, Case Western Reserve University, OH, USA, 216-368-6247, [email protected]

About Myself

Purdue University� Ph.D. Civil Engineering, 2003� M.S. Electrical and Computer Engineering, 2002

Tsinghua University, China� M.S. Civil Engineering (Geotechnical Engineering), 2000

� B.S. Civil Engineering (Hydraulic Structural Engineering), 1997

� B.S. Computer Science, 1997

Research Interest

� Current program affiliation

� Geotechnical engineering

� Infrastructure engineering

� EECS

� Current research focus

� Design and analyses of civil infrastructures

� Civil engineering materials

� Sensor technology and field instrumentation

� Sustainability (green design, risk assessment, environmental geotechnology, etc)

Instrument Assisted Criteria for

Freezing Damage of Concrete

Introduction

� Freeze-thaw damage of pavement in cold region

� Pavement structure

� Thermal crack

� Debonding

� Subgrade properties

� Stiffness

� Strength

� Drainage

� Thermal expansion (earth pressure..)

Preventing Freezing Damages of

Early Stage Concrete

� Important for concrete pouring in cold weather

� Significant cost added for heat curing or construction delay

� Highly empirical at this moment� ODOT mandate 5-day thermal curing

Mechanism of Freezing Damages

� Volume of water expand while freezing

� Migration of moisture in micro-pores

� Mechanical criteria for preventing freezing damage� Phase criteria: Vair>10%Vfree water

� Strength criteria: fc,t>pice crystal

Summary of Concrete Materials

Investigated

Name Design 28 day strength

Slump Water-cement ratio

Actual w-c ratio

Ordinary 4000 psi 4 inch 0.53 0.648

High strength

8000 psi 2 inch (6 inch actual)

0.26 0.552

Self-consolidating

6000 psi 6 inch 0.31 0.33

Laboratory Tests

� Experimental program� Specimen preparation simulate

actual production process

� Subject to different curing conditions

� Both 4 inch and 6 inch molds prepared,2000 lbs concrete within 1 hour

� 60 4 inch

� 30 6 inch

10

Finished specimen with sensors Monitoring system: Serial or USB

� Monitor under controlled curing conditions

� Air void content during curing process: ordinary concrete without air entry admix

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0 1 2 3 4 5 6 7 8

Day

Wa

ter

Co

nte

nt

0.0%

0.2%

0.4%

0.6%

0.8%

1.0%

1.2%

1.4%

1.6%

1.8%

Vo

lum

e o

f A

ir V

oid

Water Content

Volume of Air Void

Estimation of air content

� Air void content during curing process: high strength concrete with air entry admix

0

0.02

0.04

0.06

0.08

0.1

0.12

0 1 2 3 4 5 6 7 8

Day

Wate

r C

on

ten

t

5.0%

5.2%

5.4%

5.6%

5.8%

6.0%

6.2%

6.4%

Vo

lum

e o

f A

ir V

oid

Water Content

Volume of Air Void


� Early freezing damage assessment: Concrete mix with no air entry admix

� Water content

� Air void content

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

0.050.070.090.110.130.15water contentwater contentwater contentwater content

Vol

ume

Exp

ansi

on b

y V

olum

e E

xpan

sion

by

Vol

ume

Exp

ansi

on b

y V

olum

e E

xpan

sion

by

Wat

erW

ater

Wat

erW

ater

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

Vol

ume

of A

ir V

oid

Vol

ume

of A

ir V

oid

Vol

ume

of A

ir V

oid

Vol

ume

of A

ir V

oid

Volume Expansion by WaterVolume of Air Void


waterfreeporeempty VV ,, %10≥

Yan Liu, Case Western Reserve University 330-475-5792, [email protected]

� Concrete mix with air entry admix

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

0.050.070.090.110.130.15water contentwater contentwater contentwater content

Vol

ume

Exp

ansi

on b

y V

olum

e E

xpan

sion

by

Vol

ume

Exp

ansi

on b

y V

olum

e E

xpan

sion

by

Wat

erW

ater

Wat

erW

ater

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%V

olum

e of

Air

Voi

dV

olum

e of

Air

Voi

dV

olum

e of

Air

Voi

dV

olum

e of

Air

Voi

d

Volume Expansion by WaterVolume of Air Void

Estimation of air content waterfreeporeempty VV ,, %10≥

Assistance in the Spring Load

Restrictions

Spring Load Restrictions

Pavement Load Reduction During Thaw(%)

Expected Increase in Pavement Life

(%)

20 62

30 78

40 88

50 95

Isotal 1993

� Commonly used for pavement preservation

� Around 20 states and foreign regions

Implementation of SLR

Country Start of SLR End of SLR Restriction Technology forDeterminingRestriction

France n/a n/a 2.5- 4-, 6-, 8- ton forsingle dual tireaxles

Frost depthmeasurements

Finland April May Gross weights”

4-, 8-, 12-, 18 ton;total shutdown

FWD, experience

Iceland 30 cm of thaw n/a Depends on vehicletype and axleconfiguration

Frost depthmeasurements

Sweden April May 4-,6-,8-ton per axle FWD, frost depthmeasurements,experience

Norway 5-15 cm ofthaw

Min 90% of summerbearing capacity

Change yearly FWD, frost depthmeasurements

Prediction 4-8 weeks afterimposing

As needed

Practice in U.S.

State Start of SLR(around)

End of SLR(around)

Restriction Technology forDeterminingRestriction

NorthDakota

March 15 June 1 Differs between trunkhighways andcounty roads

Deflection measurement andexperience

SouthDakota

February 28 April 27 6-,7- ton per axle Deflection measurement andexperience

Iowa March 1 May 1 No overloads Road Rater and experience

Wisconsin March 10 May 10 No overloads Deflection measurement andexperience

Michigan Every March Late May 70% of gross weightfor HMA roads

experience

Minnesota March May 5-,7-, 9-ton per axle Design testing andexperience

Freeze-Thaw Measurements

� Frost tubes (plastic fluorescent dye tubes)

� Manual, subjective, slow responses

� Resistivity probe

� Subjective

� Thermal method

� No discretion of freeze-thaw status

� Affected by salt and pressure

Implementation Challenges

� Technology for freeze-thaw status

� Mechanistic relationships

� Sound load restriction practice

� Level

� Duration

Dielectric Constant of Phases

� Air: 1

� Soil solids: ~ 3-7

� Water: 81

� Ice: ~ 3

� TDR for freeze-thaw measurement?

1st sponage 2nd sponage Moisture tin

Figure TDR signal for bare strip sensor and that with moisture spot along it

Distributive Sensing

� Example of Sensor Responses

Comparison with Existing Probes� Mobility

� Installation

� Cable

� Labor

a) b)

c) d)

Field Installation

Freezing Process

0 5 10 15 20 25 30 35 40-1

-0.5

0

0.5

1

Rela

tive V

ola

ge

12/15/200712/26/20071/15/2008

1/30/20082/15/2008Installation (11/1/07)

signal responses of

ground freezing process

0 5 10 15 20 25 30 35 40 45-1

-0.5

0

0.5

1

Length(m)

Rela

tive V

oltage

3/14/08

2/15/08

2/29/08

3/29/08

4/15/08 and after

SLR can be lifted around one month earlier?

Schematic Presentation

55 60 65 70 75 80 85 90-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

Days from Start of Year 2008

Thaw

Sta

tus Indic

ato

r (T

SI) a

t 2:0

0P

M o

f each d

ay

freezing

freezing

55 60 65 70 75 80 85 90-10

0

10

20

30

40

50

Days from the beginning of 2008

Tem

pera

ture

(F)

Temperature at 14:00PM

Average daily temperature

28

TDR PVC Sensor

3.0 3.5 4.0 4.5 5.0 5.5 6.0

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Air

Soil-Water content 9%



Water

Vo

ltage

(mV

)

Scaled Distance(m)

SensorWaveforms of different materials

Validation of measurements of the sensor

29

Unconfined Compression TestSoil Specimen being frozen and monitored

0

2

4

6

8

10

12

14

0% 20% 40% 60% 80% 100% 120%

Degree of Freeze

Initi

al M

odulu

s (

MP

a)

Initial modus versus degree of freeze

� Initial modulus of frozen specimen

Mechanical Behaviors Based on

Degree of Freeze/thaw

31

0.5

0.7

0.9

1.1

1.3

1.5

1.7

1.9

2.1

2.3

2.5

0% 20% 40% 60% 80% 100% 120%

Degree of Thaw

Pe

ak s

tre

ng

th r

atio

(th

aw

/na

ture

)� Peak strength of thawed specimen

Ratio of peak strength between specimens at different

thawing stage and that of the virgin sample

Mechanical Behaviors Based on

Degree of Freeze/thaw

PC

USB Scope

Substrate

Sensor

Waves Go Beyond and Support

Traditional Civil Engineering

ECG EEG

detecting sensor

Prototype

electronic board

Tao et al. 2010

Sun et al. 2010

Conclusion

� EM Wave Technologies have great potential in infrastructure applications

� Understanding the principles and explore innovations is the key

� Requires interdisciplinary collaborations and close integration with professionals in engineering practice

Acknowledgements� Dr. Vince P. Drnevich and Ph.D. Committee Members at Purdue

� Dr. Marika Santagata, Dr. Bob Nowack, Dr. Chin-lin Chen

� Janet Lowell and fellow students

� Colleagues at CWRU

� Graduate Students (Xinbao Yu, Bin Zhang, Yan Liu, Zhen Liu, JunliangTao, Ye Sun)

� Undergraduate Researchers (Pete Simko, 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, etc)

� Department engineer Jim Berrila

Funding Agencies and Collaborators

� National Science Foundation

� The Ohio Department of Transportation/FHWA

� Minnesota Department of Transportation

� Cleveland Water Department

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

Thank you!

integration of wave-based sensing into engineering decisions

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