ARC Deliverables/Products Presentation and Workshop€¦ · ; Slide No. 2 ARC Deliverables/Products Presentation and Workshop University of Nevada, Reno

www.wrsc.unr.edu ; www.arc.unr.edu Slide No. 1

ARC Deliverables/Products Presentation and Workshop

http://www.arc.unr.edu/

http://www.wrsc.unr.edu/




ARC Deliverables/Products Presentation and WorkshopUniversity of Nevada, Reno




ARC Deliverables/Products Presentation and WorkshopComprehensive Thermal Cracking Analysis Model

for Asphalt Concrete PavementsThermal Cracking Analysis Package (TCAP)




Thermal Cracking AnalysisInfluential Factors• Pavement Structure

Asphalt layer thickness. Interface condition.

• Environmental Conditions Pavement temperatures. Cooling/warming rates.

• Asphalt mixture properties Viscoelastic properties Thermal Volumetric properties Fracture and Crack Initiation Properties

• Asphalt mixture aging Property change with oxidative aging




Thermal Cracking AnalysisExisting Models• Aging of asphalt binder over time is not considered

“viscoelastic, fracture, and volumetric properties of asphalt material constant over time.”

• Thermal coefficient of contraction (CTC) is considered constant with temperature and usually estimated.

• Tensile strength is considered constant with temperature and time.

• Pavement temperature model (currently EICM) can be improved.




Thermal Cracking AnalysisProposed Model

Step 1Pavement Temperature Profile

and History Prediction

Step 2Oxidative Aging Prediction

Step 3Thermal Stress Calculation

Step 4Thermal Cracking Event

Probability

Pavement temperature at depth z (Step 1)

Asphalt binder aging properties• Kinetics (Ea, and APα)• Hardening parameters (HS, m)

Asphalt mixture properties• Air void size• Effective aging zone

Predict Carbonyl (CA) as a function of time and depth

Climatic and meteorological data:• air temperature• solar radiation and• Wind speed

Layer properties:• Pavement layers’ thicknesses• Thermal diffusivity

Surface radiation properties• Albedo, emissivity, absorption coefficients

1-D Heat Diffusion EquationTEMPS Software

Predicted hourly thermal stress • Considering aging effect • temperature dependent CTC

Predicted carbonyl (CA) (Step 2)

Asphalt mixture crack initiation stress (CIS)• Measured using UTSST (i.e., thermal loading)• Age-dependent

Coefficient of thermal contraction• Temperature dependent CTC• Obtained from the thermal strain curve

Compare 𝝈𝝈 𝒕𝒕,𝑪𝑪𝑪𝑪 to % of CISNumbers of events over design life

Predicted pavement temperature (Step 1)(over time and at depth z)

Predicted carbonyl (CA) (Step 2)(over time and at depth z)

Asphalt mixture Relaxation modulus• Directly from the E* complex modulus• based on continuous relaxation spectrum• Age dependent

Coefficient of thermal contraction (CTC)• Temperature dependent CTC• Obtained from the thermal strain curve• Age dependent

1-D Linear viscoelastic model




Thermal Cracking AnalysisPrediction of Field Aging (Numerical solution using FCVM)

Pavement location: Reno, NVAggregate: Northern Nevada Binder type: PG64-28 (SBS mod.)Binder content: 5.22%Air voids: 7%

Ea= 72.53 kJol/molAPα = 4.08 E+8 ln(CA/day)HS = 2.7 (1/CA)m = 9.24 (poise)Air void diameter = 0.5 mmEff. aging zone = 1.0 mm(film thickness)




Thermal Cracking AnalysisThermal Stress Calculation

• 1D linear viscoelastic constitutive equation with oxidative aging effect.

𝜎𝜎𝑇𝑇𝑇 𝑡𝑡,𝐶𝐶𝐶𝐶 = �0

𝑡𝑡𝐸𝐸(𝜉𝜉 𝑡𝑡 − 𝜉𝜉′ 𝑡𝑡 ,𝐶𝐶𝐶𝐶)

𝜕𝜕𝜀𝜀𝑇𝑇𝑇(𝑡𝑡,𝐶𝐶𝐶𝐶)𝜕𝜕𝑡𝑡′

𝑑𝑑𝑡𝑡𝑑

Relaxation ModulusFunction of time,

temperature, and aging

Thermal strain rateFunction of temperature and

age-dependent CTC




Thermal Cracking AnalysisAge-Dependent Relaxation Modulus• Relaxation modulus determined from dynamic complex modulus.

– Continuous relaxation spectrum directly obtained by inverse Laplace Fourier Transform of complex E* (2S2P1D, Olard & Di Benedetto, 2003).

Ideal viscoelastic model




Thermal Cracking AnalysisEvolution of 2S2P1D Coefficient with Aging

Consistent trends were found for the evaluated mixtures!

1

10

100

1,000

0.00 0.20 0.40 0.60

E0 (M

Pa)

CA-CA0

1,000

10,000

100,000

0.00 0.20 0.40 0.60

E∞ (M

Pa)

CA-CA0

0.10

1.00

10.00

0.00 0.20 0.40 0.60

δ

CA-CA0

0.30

0.40

0.50

0.00 0.20 0.40 0.60

k

CA-CA0

0.01

0.10

1.00

0.00 0.20 0.40 0.60

h

CA-CA0

1.0E-04

1.0E-03

1.0E-02

1.0E-01

0.00 0.20 0.40 0.60

T0

CA-CA0

0.005.00

0.00 0.20 0.40 0.60CTCL

(E

05/

°C)

CA CA0NV19I28_5.22_4%_60°C NV19I28_5.22_7%_60°C NV19I28_5.22_11%_60°C

(𝟐𝟐𝟐𝟐𝟐𝟐𝟐𝟐𝟐𝟐𝟐𝟐 𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄)𝒋𝒋 = 𝑪𝑪𝒋𝒋 × 𝒄𝒄𝑩𝑩𝒋𝒋(𝑪𝑪𝑪𝑪−𝑪𝑪𝑪𝑪𝟎𝟎)





2S2P1D coeff. CA Va (%) Abs. (%) LSVTank

(poise)B.C. (%) Retained # 8 Passing # 200

E0 √ √ √ √ √

E∞ √ √ √ √ √ √ √

δ √ √ √ √ √ √

k √ √ √ √

h √ √ √

T0 √ √ √

Mixture variable





y = 0.569x + 20.553R² = 0.770

0

100

200

300

0 100 200 300

Pred

icted

E0 (

MPa)

Measured E0 (MPa)

E0 (MPa) Line of Eguality

y = 0.822x + 3,334.734R² = 0.849

0

10,000

20,000

30,000

40,000

0 10,000 20,000 30,000 40,000Pr

edict

ed E

∞ (M

Pa)

Measured E∞ (MPa)E∞ Line of Eguality

y = 0.851x + 0.163R² = 0.884

0.0

1.0

2.0

3.0

4.0

0.0 1.0 2.0 3.0 4.0

Pred

icted

δ

Measured δ

δ Line of Eguality

y = 0.761x + 0.098R² = 0.775

0.0

0.2

0.4

0.6

0.0 0.2 0.4 0.6

Pred

icted

k

Measured kk Line of Eguality

y = 0.525x + 0.074R² = 0.545

0.0

0.1

0.2

0.3

0.0 0.1 0.2 0.3

Pred

icted

h

Measured hh Line of Eguality

y = 0.553x + 0.002R² = 0.689

0.E+00

5.E-03

1.E-02

2.E-02

2.E-02

0.E+00 5.E-03 1.E-02 2.E-02 2.E-02

Pred

icted

T0

Measured T0

T0 Line of Eguality




Thermal Cracking AnalysisAge-Dependent Properties

• Coefficient of thermal contraction (CTC)

• Crack initiation stress (CIS)

Uniaxial Thermal Stress and Strain Test (UTSST)




Thermal Cracking AnalysisAge-Dependent PropertiesUniaxial Thermal Stress and Strain Test (UTSST)• Samples are cored out of a SGC specimen.

Unrestrained Specimen

Restrained Specimen

Dummy Specimen

170 mm

150 mm 130±5 mm

57 mm




Thermal Cracking AnalysisTemperature and Age-Dependent CTC•

-0.0015

-0.001

-0.0005

0

-50 -40 -30 -20 -10 0 10 20

Ther

mal S

train

(mm/

mm)

Temperature (°C)

CTCl

CTCg

Tg

Unrestrained Specimen

Restrained Specimen

Dummy Specimen

Uniaxial Thermal Stress & Strain Test (UTSST)

𝜀𝜀𝑡𝑡𝑇 =∆𝑙𝑙𝑙𝑙0

= 𝐶𝐶 + 𝐶𝐶𝐶𝐶𝐶𝐶𝑔𝑔 𝐶𝐶 − 𝐶𝐶𝑔𝑔 + 𝑙𝑙𝑙𝑙 1 + 𝑒𝑒(𝑇𝑇−𝑇𝑇𝑔𝑔)

𝑅𝑅

𝑅𝑅(𝐶𝐶𝑇𝑇𝐶𝐶𝑙𝑙−𝐶𝐶𝑇𝑇𝐶𝐶𝑔𝑔)

𝜀𝜀 𝐶𝐶(𝑡𝑡) = �𝑇𝑇0

𝑇𝑇(𝑡𝑡)𝐶𝐶𝐶𝐶𝐶𝐶(𝐶𝐶(𝑡𝑡)) × 𝑑𝑑𝐶𝐶𝑑

𝐶𝐶𝐶𝐶𝐶𝐶 𝐶𝐶 = 𝐶𝐶𝐶𝐶𝐶𝐶𝑔𝑔 +(𝐶𝐶𝐶𝐶𝐶𝐶𝐿𝐿 − 𝐶𝐶𝐶𝐶𝐶𝐶𝑔𝑔) × 𝑒𝑒(

𝑇𝑇−𝑇𝑇𝑔𝑔𝑅𝑅 )

(1 + 𝑒𝑒𝑇𝑇−𝑇𝑇𝑔𝑔𝑅𝑅 )




Thermal Cracking AnalysisAge-Dependent Crack Initiation Stress (CIS)

0

2000

4000

6000

8000

10000

-30 -20 -10 0 10 20

Stiffn

ess (

MPa)

Temperature (°C)

Crack Initiation (CI)

Glassy Hardening

Viscous-Glassy Transition

Viscous SofteningFracture

Crack Initiation Temp. (CIT)





Similar trends were observed for all evaluated mixtures!

𝑪𝑪𝑪𝑪𝟐𝟐 = 𝑬𝑬 × 𝒄𝒄𝑭𝑭(𝑪𝑪𝑪𝑪−𝑪𝑪𝑪𝑪𝟎𝟎)

0.1

1.0

10.0

0.00 0.20 0.40 0.60

Crac

k init

iation

stre

ss (M

Pa)

CA-CA0

-40

-30

-20

-10

0

0.00 0.20 0.40 0.60Crac

k init

iation

temp

eratu

re (°

C)

CA-CA0





CA Va (%) Abs. (%)

LSVTank (poise)

B.C. (%)

Retained # 8

Passing # 200

CIS √ √ √ √ √

CIT √ √ √ √ √ √

Mixture variable

y = 0.98xR² = 0.89

-40

-30

-20

-10

0

10

-40 -30 -20 -10 0 10

Pred

icted

Cra

ck in

i. Tem

p (°C

)

Measured Crack ini. Temp (°C)Crack initiation temperature Line of equality

y = 0.97xR² = 0.72

0

1

2

3

4

5

0 1 2 3 4 5

Pred

icted

Cra

ck in

i stre

ss (M

Pa)

Measured Crack ini stress (MPa)

Crack initiation stress Line of equality




Thermal Cracking AnalysisThermal Cracking Event Probability• The accumulative events during which thermal stress reaches

a defined percentage of the asphalt mixture Crack Initiation Stress (CIS) over the analysis period!

Possible Cracking events




MATLAB Graphical User Interface (GUI)Thermal Cracking Analysis Package (TCAP)




Examples: TCAP Analysis

• Pavement Location– Reno, Nevada

• Asphalt Mixtures: – Polymer-modified PG64-28; 3 air void levels: NV_5.22PG64-28_4%; NV_5.22PG64-28_7%; NV_5.22PG64-28_11%

• Design Period– 20 years




Examples: TCAP analysisEffect of Oxidative Aging on Thermal Stresses

Difference in predicted thermal stresses between aging and no-aging effect analyses.

4% Air Voids

7% Air Voids

11% Air Voids




Examples: TCAP analysisThermal Stress vs. Crack Initiation Stress (CIS)




Examples: TCAP analysis

Effect of Mixtures Air Voids

Cracking likelihoods increase for mixture with higher air voids level….

∼11 yrs

Acc. CI = Weighted average of number of events at which thermal stresses reach different % of CIS.

𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑙𝑙𝐶𝐶 𝐼𝐼𝑙𝑙𝑑𝑑𝑒𝑒𝐼𝐼 =∑𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑙𝑙𝐶𝐶 𝑒𝑒𝑒𝑒𝑒𝑒𝑙𝑙𝑡𝑡𝑖𝑖 %𝐶𝐶𝐶𝐶𝐶𝐶 × 𝐶𝐶%

∑ 𝐶𝐶 % ,

𝐶𝐶 = 100, 80, 70, 60, 50




Examples: TCAP analysisEffect of Modification (Two field projects from Reno, NV)

Un-modifiedPG64-22 (Moana, 2006)

SBS polymer-modified PG64-28 (Sparks, 2008)




TCAP Implementation

Asphalt Mixture(s)(Agg., Binder, Mix Design)

Pavement Structure & Location

Pavement Temperature Prediction

Oxidative Aging Prediction

Materials InputComplex modulus (E*), CTC, CIS

Thermal Cracking Analysis ✔ Pass✖ Fail

• Level 1: Measured kinetics (Mix-aged)• Level 2: Accelerated Aging• Level 3: Database

• Level 1: Measured (Full Testing) • Level 2: Measured (Reduced Testing)• Level 3: Predictive Equations

• Climatic/meteorological data• Material thermal prop.• Surface radiation prop.




Future Research and Improvements

• Field validation of TCAP model.

• Sensitivity analysis of TCAP model.

• Level 3 material input: – Regression models for materials oxidative aging, viscoelastic,

and crack initiation properties.

• Development of a stand-alone TCAP software.




Pavement Temperature Profile PredictionTemperature Estimate Model for Pavement Structures

–– TEMPS ––http://www.arc.unr.edu/Software.html



http://www.arc.unr.edu/Software.html


Pavement Temperature Profile Prediction

Improvement of the Heat Transfer model [Han et al., 2011 (TAMU)] Enhanced boundary conditions. Variable pavement surface radiation properties.

Application of Finite Control Volume method (FCV) with Implicit Scheme [Zia et al., 2014 (UNR)]

Solar Radiation (Albedo)

Incoming (Absorption) and Outgoing (Emissivity) RadiationHeat Convection

(Wind speed)

Heat Diffusion

Heat Transfer Balance Between Pavement Structure & Surrounding Environment




Pavement Temperature Profile PredictionStandalone Software: TEMPS (Alpha Version 0.0.1)

Temperature Estimate Model for Pavement Structures (TEMPS)




Pavement Temperature Profile PredictionTEMPS – Input

•••••




Pavement Temperature Profile PredictionTEMPS – Materials




Pavement Temperature Profile PredictionTEMPS – Climatic Data




Pavement Temperature Profile PredictionTEMPS – Surface Characteristics




Pavement Temperature Profile PredictionTEMPS – Pavement Structure




Pavement Temperature Profile PredictionTEMPS – Mesh Generator




Pavement Temperature Profile PredictionTEMPS – Output Results




Pavement Temperature Profile PredictionTEMPS – Output Summary




Pavement Temperature Profile PredictionTEMPS – Output Summary




Pavement Temperature Profile PredictionTEMPS – Pavement Temperature Distribution




Pavement Temperature Profile PredictionTEMPS – Predicted versus MeasuredGreat Falls, MT at depth of 0.09 m (3.5 inch)

-20-10

01020304050

11/5/2001 12/25/2001 2/13/2002 4/4/2002 5/24/2002 7/13/2002 9/1/2002 10/21/2002 12/10/2002 1/29/2003

Temp

eratu

re (°

C)

Predicted TemperatureMeasured Temperature (LTPP)

-20-10

01020304050

11/5/2001 12/25/2001 2/13/2002 4/4/2002 5/24/2002 7/13/2002 9/1/2002 10/21/2002 12/10/2002 1/29/2003

Temp

eratu

re (°

C)

Calibrated TemperatureMeasured Temperature (LTPP)

Particle Swarm Optimization (PSO) Algorithm: Single yearly surface characteristics




Pavement Temperature Profile PredictionTEMPS – Additional Improvements

• Calibration: Optimize the surface characteristics (Albedo, Emissivity, Absorption) using Particle Swarm Optimization (PSO) Algorithm– Monthly or seasonal values.

• Create/Include input files for LTPP SMP sections.• Provide a summary of pavement cooling/warming rates




Thank You!

Visit our websites at:www.wrsc.unr.eduwww.arc.unr.edu University of Nevada, Reno, www.wrsc.unr.edu








Documents

ARC Deliverables/Products Presentation and Workshop€¦ · ; Slide No. 2 ARC Deliverables/Products Presentation and Workshop University of Nevada, Reno