Do Models Really Work? Verification and Validation in ... Buttlar.pdf · Verification and Validation in Pavement Engineering Road Materials and ... Model Qualification ... verification

Do Models Really Work? Verification and Validation in Pavement Engineering

Road MaterialsandPavementDesign

Pavements: Materials, design and performance

Lisboa, LNEC, 25 March 2010

William G. Buttlar, PhD, PE

Professor of Civil and Environmental Engineering

University of Illinois at Urbana-Champaign


Pavement Complexity: Closed-Form Solutions do Not Consider:

>Damage

>Propagating Cracks

>Complex Interface Behavior

>Viscoelasticity, Visco-elasto-

Road Pavements: Materials, design and performance


>Viscoelasticity, Visco-elasto-plasticity

>Material Gradients

>Effects of Multiple Wheel Loads for Nonlinear Problems

>Complex Load Spectra


Simulation in Pavement Design and AnalysisSelected Historical Developments

>Layered Elastic Analysis: BISAR, CHEVRON, JULEA, LEAF, ILLIPAVE, MICHPAVE, KENLAYER (1970-1990)

>TCMODEL (SHRP Thermal Cracking Model ~ 1993)



>TCMODEL (SHRP Thermal Cracking Model ~ 1993)

>PCASE, LEDFAA, FAARFIELD (Airfield Pavement Design ~ 1990’s - Present)

>MEPDG (Mechanistic-Empirical Pavement Design Guide) Software (2002 - Present)


Numerical Modeling/Simulation

>Allows for Complexity in Material Properties, Loading Configurations, and Material Response/Distress

>The Time is Now!



>The Time is Now!

� Moore’s Law (double in computing power every 1.5 years)

� IBM Blue Waters at University of Illinois (Petascale computing)


As Engineers, How Can We Handle the Black Box???

Out



???In Out

Phases of Modeling and Simulation

From Oberkampf et al. (Appl. Mech. Rev., vol. 57, no. 5, Sept. 2004)

Phases of modeling and simulations and the role of V&V

Model Qualification

‘‘Determination

of adequacy of the

conceptual model to

provide an

acceptable level of

agreement for the




From Oberkampf et al. (Appl. Mech. Rev., vol. 57, no. 5, Sept. 2004)

agreement for the

domain of intended

application.’’

Model Verification

The process of

determining that a

model implementation

accurately represents

the developer’s

conceptual description

of the model and the

From Oberkampf et al. (Appl. Mech. Rev., vol.

57, no. 5, Sept. 2004)

of the model and the

solution to the model.


LEA Example for Model Verification



Khazanovich and Wang, Trans. Res. Rec., Vol.

2037, pp. 63-75, 2007.

Model ValidationThe process of

determining the

degree to which a

model is an accurate

representation of the

real world from the

perspective of the





57, no. 5, Sept. 2004)

perspective of the

intended uses of the

model.

Validation ProcessHomogeneous Tests

(Direct Tension,

Annular Shear, etc.)

Bench scale, Possibly

Standard Tests

(SE(B), DC(T), SCB, etc.)





57, no. 5, Sept. 2004)

Intermediate Scale/

Structural/ Simulation Tests

(Overlay Tester, Layered

Beam, MMLS, etc.)

APT and Field Sections

(ATLaS, FABAC, HVS, MLS,

Mn/ROAD, LTPP, etc.)


Verification and Validation of Code is Important!!!

Computerized Controls for Braking, Accelerating, Crash Avoidance



Accelerating, Crash Avoidance

Simulation for Pavement Design; What Will be Our Legacy?


Calibration vs. Validation

In Mechanistic – Empirical modeling, which is commonly needed in pavement engineering, we have empirical constants



engineering, we have empirical constants which require calibration. Thus, model calibration is generally needed between verification and validation.

!!! Calibration and Validation are often confused in pavement engineering !!!


MEPDG Example for Model Calibration


Lisboa, LNEC, 25 March 2010From: MEPDG User’s Manual, Chapter 3 (2006).


SHRP Example for Model Validation - TCMODEL

OBSERVED CRACKING

ZERO MED HIGHLOW

ZERO

LOW

PR

ED

ICT

ED

CR

AC

KIN

G16

2


Lisboa, LNEC, 25 March 2010From: SHRP A-357 Final Report (1993).

LOW

MED

HIGH

PR

ED

ICT

ED

CR

AC

KIN

G

4

11

2

2

The statistical ‘PRESS’ procedure was used to independently validate model results when only limited field sections was available.


UIUC Fracture Modeling

Verification, Calibration, and Validation of Cohesive Zone Model

RILEM CAP TG-03



Example #1 – Fracture Modeling

1. Use DCB for Verification

2. DC(T) for Calibration, and

a

H

2δ

P



2. DC(T) for Calibration, and

3. SC(B) for Validation

17

Disk-Shaped Compact Tension, DC(T) Test

>ASTM D7313-07

>Loading Rate:

�CMOD = 1.0-mm/min

>Measurements:

�CMOD

�Load

18

Semi-circular Bend, SC(B) Test

>Loading Rate:

�CMOD = 0.7-mm/min

>Measurements:

�CMOD

�Load

19

Fracture Energy Results (Illinois RILEM Mix)

Peak Loads (CoV shown in parenthesis)

DCT: 2.68 kN (7.5%)

SCB: 6.03 kN (18%)

20

Verification of CZ Modeling Approach using

Double Cantilever Beam Problem

21

a

H

2δ

P


FE Meshes for Fracture Energy Tests



CZ Elements

(~ 0.8 mm)

22

DCT Load-CMOD Curves: Measured vs. Calibrated

Calibration Factors:

DCT CMOD Energy: 0.84

IDT Strength: 1.00

23

Predicted SCB Load-CMOD Curves (Validation)

24

� Friction model

Discrete Element Method (DEM)

nr FF µ=

A

B

sF

sFnr FF µ=

C

D

C

D

sF

nS

SS

B

A

P

nU∆

� Central difference scheme for solving the dynamic problem

Example #2: Discrete Element Modeling

25

SS

* PFC2D 3.0, ITASCA, 2002

fG

σ

maxσ

sepδ δ

Softening

pU

Micro-cracking Macro-cracking

Unloading and Reloading

m1

m2Friction Model

HardeningCohesive Softening Model

E

∑=

−−+=1

/

0)1()(

i

t

i

ieDDtDτ

Where, D(t) = Creep compliance at time t

Di = Material constants

τi = Retardation times

Viscoelastic Contact Model

26

τi = Retardation times

−+−±= ++ tt

k

tttDfu

A

Buu

Cf m)1(

1 11

k

K

C

tKA

21

∆+=

k

K

C

tKB

21

∆−=

mmkC

t

KAC

tC

2

1

2

∆++

∆=

mmkC

t

KAC

tD

2

1

2

∆+−

∆=

Where,

* Contact force f t+1 can be calculated from known values for ut+1, ut, , and f tt

ku

−++=

−

)1(11

)( 1

110

0

τ

ησε

t

KMMe

G

t

Gt

−+=

−−−

)(1

)( 11

1 )(

11

10

ττ

ησε

ttt

KMee

G

tt

10 tt <<

tt <1

: Creep

: Recovery

Verification of Creep Response

27

0.0E+00

2.0E-08

4.0E-08

6.0E-08

8.0E-08

1.0E-07

0 4 8 12 16 20

Time (sec)

Ve

rtic

al S

tra

in (

t)

Analytical Solution

DEM

+=

−−10

1000)(ττε

tK

tM

eGeGAtF

Relaxation

Verification of Relaxation Response

28

0.0E+00

2.0E+05

4.0E+05

6.0E+05

8.0E+05

0 4 8 12 16 20

Time (sec)

Co

nta

ct F

orc

e (

t) (

N)

Analytical Solution

DEM

Verification of Mesh-Independence

The cohesive zone model introduces

a length scale in terms of material

properties such as Young’s modulus,

fracture energy, and material strength

(Rice, 1968).

A fracture process zone where damage

occurs can be estimated as:

29

(a) Comparison of Different Cohesive Particle Sizes

: 0.25mm, 0.5mm, 1.0mm

2218ave

c

c

GEl

συ

π

−=

lc >> Particle (or element) size

The cohesive model results will be

independent of the particle size if it is

much smaller than lc.


Example #3: Size Effect Study



Kim, H., Partl, M.N., Wagoner, M.P., and W.G. Buttlar, “Size Effect Investigation on Fracturing of Asphalt Concrete Using the Cohesive Softening Discrete Element Model,” 7th International RILEM Symposium on Advanced Testing and Characterization of Bituminous Materials, Rhodes, Greece, 2009.


DEM Model Details




Calibration – Intermediate Size




Validation of Size Effect Prediction



Small Specimen

(D=100mm)

Large Specimen

(D=300mm)

Dark Symbols = Model Solid Lines = Experiments


Making Simulations Robust> Recognizing that is often very difficulty to fully verify or validate

a highly complex simulation model, models can be improved by:

� Being thorough in verification…leave no submodel unverified, and

conducting systems-level verification against other codes. Re-

verifying code when changes are made.



verifying code when changes are made.

� Not confusing calibration and validation; Using independent

validation data sets following calibration.

� Validating across entire range of anticipated model use;

documenting un-validated model ‘regions’

� Providing ‘rules of thumb’ and ‘reality checks’ (example h/L ratio for

beams). Providing sample problems and verified solutions.

34


Summary>When Developing or Adopting Numerical Models for

Pavement Analysis and Design, the Models should

be: Qualified, Verified, Calibrated, and Validated



>Consistent Use of These Terms and Properly

Following These Techniques During Model

Development and Adoption are Essential Steps

Towards the Reliable use of Simulation Models in

Pavement Analysis and Design

35


Thanks for your attention!!!



Documents

Do Models Really Work? Verification and Validation in ... Buttlar.pdf · Verification and Validation in Pavement Engineering Road Materials and ... Model Qualification ... verification