in-situ validation of three-dimensional pavement finite...

In-Situ Validation of Three-DimensionalPavement Finite Element Models

Osman Erman Gungor, Imad L. Al-Qadi, Angeli Gamezand Jaime A. Hernandez

Abstract Mechanistic-based pavement design guides gained popularity in the lastdecade. Accurate computation of stress, strain, and the deformation field withinpavement, which are used in pavement design guides, is important to realisticallypredict pavement performance over the design life. The layered elastic theory andfinite element method (FEM) are commonly used to compute the critical responsesof pavement structure. Although the layered elastic theory analysis is relativelyfaster and easier to implement, it hinders real loading and pavement materialcharacterization. Therefore, FEM has become more attractive to pavementresearchers for investigating pavement behavior under tire loading since the last twodecades. Although several studies have been conducted for developing FE modelfor pavement, limited work has been done to validate the finite element (FE) modelsusing in-situ pavement responses. This study presents an advancedthree-dimensional (3-D) pavement FE model validated using four pavement sec-tions. Good agreement was noted between the FE analysis results and pavementfield instrument responses to loading, especially for vertical pressures and hori-zontal tensile strains in the transverse direction. When using proper materialcharacterization parameters and accurate tire loading, the FE model is capable ofrealistically simulating tire-pavement interaction in the field.

Keywords Finite element analysis � Validation � Flexible pavement �Mechanisticpavement design approach

O.E. Gungor (&) � I.L. Al-Qadi � A. Gamez � J.A. HernandezDepartment of Civil and Environmental Engineering,University of Illinois at Urbana-Champaign, 205 North Mathews,Urbana, IL 61801, USAe-mail: [email protected]

© Springer International Publishing Switzerland 2016J.P. Aguiar-Moya et al. (eds.), The Roles of Accelerated Pavement Testingin Pavement Sustainability, DOI 10.1007/978-3-319-42797-3_10

145

1 Introduction

Mechanistic-empirical based pavement design guides that link mechanistic pave-ment responses to pavement distress prediction gained popularity in the last decade.Accurate computation of stress, strain, and deformation fields within pavementplays a crucial role in realistically predicting pavement performance over the designlife. The layered elastic theory (LET), originally developed by Burmister et al.(1944), is the traditional approach to compute pavement response to vehicularloading. Although LET is relatively faster and easier to implement, it hinders realloading conditions and material characterization in pavement analysis.

Finite element method (FEM), on the other hand, considers variables that areomitted in LET simulations, such as linear viscoelastic characterization of asphaltconcrete (AC), anisotropic stress-dependent material characterization for granularlayers, realistic model for simulating interaction between pavement layers, 3-Dnon-uniform contact stresses, in addition to simulating continuously moving tireloads. Considering those variables in pavement analysis not only results in accuratecomputation of pavement responses but also helps researchers get better under-standing of complex pavement behavior under tire loading. Therefore, FEMbecame more attractive to pavement researchers in the past two decades.

A significant number of studies using FEM for analyzing pavement structurehave been conducted. FEM is applied in several ways in pavements, including thefollowing: Comparing the effect of using wide-base tire and dual-tire assembly(DTA) on pavement performance (Al-Qadi et al. 2005; Gungor et al. 2014),understanding the importance of nonlinear characterization of granular material inpavement response (Kim et al. 2009), characterization of rutting within pavementstructure (Fang et al. 2004), understanding crack initiation and propagation with AC(Ameri et al. 2011; Underwood et al. 2009) are examples of the main applicationsof FEM on pavement analysis.

Although several studies have been conducted to develop pavement FE modelfor a variety of purposes as listed above, limited research has been initiated tovalidate FE models using in-situ pavement responses. This study presents andvalidates an advanced 3-D pavement FE model using four pavement sections. Thefollowing section introduces the developed pavement FE model and explains itsimportant features. Then, the validation results for each section are provided anddiscussed. Finally, the last section presents the conclusion of the paper.

2 Finite Element Model

Realistic simulation of flexible pavement structure under tire load is quite a chal-lenging task. Other than its geometry, every component of the simulation, such asloading conditions and material characterization, is complicated. The tire appliesnon-uniform, 3-D contact stress on pavement. AC exhibits viscoelastic behavior,

146 O.E. Gungor et al.

meaning that stiffness is time, temperature, and frequency of loading dependent andshould be properly modelled in the simulation. Moreover, granular material showsanisotropic stress-dependent nonlinear behavior. Not only the material’s stiffnessdepends on the stress level it is exposed to, but also it behaves differently in eachprincipal direction (anisotropy). Additionally, modelling interaction between dif-ferent pavement layers further complicates the behavior of pavement structure. Theliterature clarifies the significant effect of these conditions on pavement responses.Therefore, it is important to capture them while simulating pavement behaviorunder tire loading to compute pavement responses accurately.

LET is the current analysis approach used in mechanistic-empirical guides toobtain pavement responses mostly because of its computational efficiency.However, unrealistic simplifications and assumptions are associated therewith.Linear elastic characterization of AC and base materials, spring model assumptionfor layer interface, two-dimensional (2-D) uniform tire pressure, and circular con-tact area are only some examples of the simplifications and assumptions of LET.

FEM, on the other hand, is a promising numerical method that can overcome thedifficulties and challenges in flexible pavement simulation. It has the ability toconsider non-uniformity in loading conditions and complex nonlinear materialcharacterizations. Since there are a number inputs required for 3-D pavement FEMthat cannot be considered in LET (e.g., temperature, speed) these two pavementanalysis approaches are not comparable. However, comparison of FEM withMechanistic-Empirical Pavement Design Guide (AASHTO 2008) that incorporatesLET within its framework is studied as part of another study (Al-Qadi et al. InReview).

The pavement FE model presented in this paper is the ultimate version of overten years of on-going research by Al-Qadi and his coworkers (Wang and Al-Qadi2010; Elseifi et al. 2006; Yoo et al. 2007; Al-Qadi and Yoo 2007). The key featuresof the developed FE model can be categorized into five different groups: geometryand boundary conditions, loading conditions, material characterization, analysismethod, and interface interaction model. A brief explanation for each key feature isgiven in the following sections.

2.1 Finite Element Model and Boundary Conditions

The FE model of flexible pavement structure that was developed in commercial FEsoftware, ABAQUS, is given in Fig. 1. Three main issues that need to be addressedwhen developing pavement FE model: element size, i.e., mesh size (i), depth of themodel (ii) and lateral size of the model (iii). In traditional pavement analysisapproaches, such as LET, the subgrade is assumed to have infinite depth. However,a finite depth needs to be assigned to subgrade in the FE model. In addition tofinding subgrade depth, the element size should be optimized. FE elements generatemore accurate results as the size of the element gets smaller. On the other hand,computational time increases as the number of elements in the model increases.

In-Situ Validation of Three-Dimensional Pavement … 147

Therefore, optimum element size and subgrade thickness are determined by meshsensitivity analysis. In order to perform mesh sensitivity analysis, an elastic FEmodel was compared to an LET software, known as Bisar, for five different criticalpavement responses: maximum transverse tensile strain at the bottom of AC;maximum compressive strain within subgrade; and maximum vertical shear strainwithin AC, base, and subgrade. The mesh was refined until the difference betweenthe FE model and Bisar was equal to or less than 5 %.

The pavement response yields haversine like pulse duration as demonstrated inFig. 2. As a result of trying different wheel path lengths (1000 and 2000 mm), itwas observed that a path length longer than 2000 mm was required to capture theentire pulse duration. On the other hand, it was observed that there is no significantdifference in the maximum magnitude of pavement responses obtained from 1000and 2000 mm of wheel path. Therefore, the wheel path was decided to be keptaround 1000 mm, which is long enough to capture maximum pavement response.

2.2 Loading Conditions

LET assumes 2-D uniform static vertical pressures with circular load. On the otherhand, the tire applies 3-D non-uniform contact stress, measured in the experimentalong with the realistic contact area. FEM considers these true measured contactstresses and contact areas in the simulations. Details about tire contact measure-ments can be found elsewhere (Hernandez et al. 2013). In addition to the

Fig. 1 3-D finite element model


non-uniform contact stress, simulating the tire as a continuous moving load, ratherthan a static steady load, is another important realistic consideration in the devel-oped model.

2.3 Material Characterization

It is clearly stated in the literature that AC should be characterized as viscoelasticmaterial whose stiffness depends on the frequency of loading, time, and tempera-ture. Time, temperature, and loading frequency dependencies can be captured byvarious experiments that produce a plot called “master curve”. ABAQUS considersshear and bulk moduli for viscoelastic young modulus through Prony coefficientsthat are obtained from fitting to the master curve (Eqs. 1, 2). Afterwards, bulk andshear modulus are calculated by assuming a constant Poisson’s ratio. Wlliams–Landell–Ferry function was used to model time-temperature superposition of AC,as shown in Eq. 3:

G tð Þ ¼ G0 1�Xni¼1

Gi 1� e�tsi

� � !ð1Þ

K tð Þ ¼ K0 1�Xni¼1

Ki 1� e�tsi

� � !ð2Þ

Fig. 2 Pulse duration results for the two wheel paths


whereG = shear modulus,K = bulk modulust = reduced relaxation timeG0 and K0 = instantenous shear and volumetric modulusGi, Ki and τi = Prony series parameters

log atð Þ ¼ �C1 T� Trð ÞC2 þ T� Trð Þ ð3Þ

whereαt = shift factorC1, C2 = regression coefficientsT = analysis temperatureTr = reference temperature

In conventional pavement analysis approaches, both base and subgrade materialsare characterized as linear elastic material. However, it has been shown that stiffnessof the granular materials changes depending on the stress level they are exposed to.Moreover, they behave differently in each principal direction. Therefore, they aremodelled as anisotropic stress-dependent nonlinear material using MEPDG model(NCHRP 2004), as shown in Eqs. 4–6. It should be noted that effect of consideringnon-linearity in material characterization is negligible for thick pavement, whereload is mostly carried by AC. Therefore, only granular material in thin pavement ismodelled as stress-dependent anisotropic material to decrease computational cost.

Mrv ¼ k1hpo

� �k2 rd

po

� �k3

ð4Þ

Mrh ¼ k4hpo

� �k5 rd

po

� �k6

ð5Þ

Mrs ¼ k7hpo

� �k8 rd

po

� �k9

ð6Þ

whereMrv, Mrh, Mrs = vertical, horizontal and shear resilient modulush ¼ r1 þr2 þr3 = bulk stressespo = unit reference pressurek1, k2, k3, k4, k5, k6 = regression coefficients


2.4 Analysis Method

There are three commonly used methods for pavement analysis: static, quasi-static,and dynamic analysis. Static analysis assumes that the tire is not moving.Quasi-static analysis models the tire as a moving load, but fails to capture theinertial/damping effect and frequency-dependent material properties. Therefore,dynamic analysis was used in this study to properly simulate moving tire loads withnonlinear material characterization. The dynamic equation solved in ABAQUS isgiven in Eq. 7. This equation can be solved using the implicit or explicit directintegration method. In this study, the implicit direct integration method was selectedbecause it is more efficient for the level of frequencies observed in pavementsimulations.

M½ � €U� �þ C½ � _U

� �þ K½ � Uf g ¼ Pf g ð7Þ

where[M] = mass matrix[C] = damping matrix[K] = stiffness matrix{P} = external force vector{Ü} = acceleration vector{U ̇} = displacement vector.

2.5 Interface Model

The model used for defining how two pavement layers interact with each other isanother key parameter for pavement simulation. All AC layers are assumed to befully bonded to each other in the developed model. On the other hand, AC-base andbase-subgrade interaction were simulated using a Coulomb model. In this model,resistance of the movement is assumed to be proportional to normal stress at theinterface. In addition, a tolerance limit was set for shear strength above which twolayers start sliding relative to each other. In case of relative sliding, frictional stresswould be assumed constant.

3 Results and Discussion

Validation of FE model of flexible pavement was conducted for four differentpavement sections: Illinois Center of Transportation, Florida, Smart Road, and UCDavis sections. The validation results and discussions are given below for eachsection.


3.1 Illinois Center for Transportation Section

The first attempt to validate pavement FE model was performed on a pavementsection built at the Illinois Center of Transportation testing facility. The pavementsection, called “Section C” (Al-Qadi et al. 2008), was selected for validation. Thelayer properties of this section are given in Table 1.

This section with 3 in of AC thickness is considered as thin section. The Pronycoefficients used for viscoelastic characterization of AC are given in Table 2. Thebase material should be modelled as anisotropic stress-dependent material toachieve more realistic pavement simulations. The nonlinear model parameters(Eqs. 4–6) are given in Table 3.

The selected loading conditions for validation were 35.6 kN axle load and690 kPa tire inflation pressure for DTA. A comparison between FEM and field datawas performed by using two pavement responses: vertical pressure at the bottom ofbase and transverse strain at the bottom of AC (Table 4). The relative differencebetween FEM and field data are computed as 9.7 and 24.8 %, respectively. Thevariation of transverse strain at the bottom of AC could be attributed to bending ofthe strain gauge in the field due to weak supporting platform for AC. In this case,strain gauges report higher values since they possibly report summation of axialtensile strain and bending tensile strain.

Table 1 Illinois Center for Transportation section input parameters

Layer Thickness(mm)

Instantaneous/linearmodulus (MPa)

Poisson’sratio

Density(×10−6)

Rayleighdampingparameters(α)

Rayleighdampingparameters(β)

AC 127 9840 0.35 2.30 N/A N/A

Base 305 Nonlinear 0.35 2.10 3.1416 0.000795

Subgrade – 45 0.4 1.56 3.1416 0.000795

Table 2 Prony coefficientsof AC layer

i Gi (MPa) Ki (MPa) τi1 6209.04 6209.04 0.0206

2 2469.84 2469.84 0.173

3 833.448 833.448 1.29

4 261.744 261.744 5.35

5 64.944 64.944 106

Table 3 Nonlinear modelparameters for base layer

k1(kPa)

1010 k4(kPa)

227 k7(kPa)

321

k2 0.791 k5 1.071 k8 0.857

k3 −0.478 k6 −1.332 k9 −6.681


3.2 Florida Section

Results of the Accelerated Pavement Test conducted at Florida Department ofTransportation facility were used to validate FEM pavement model. The test lanesmeasured 92 m long and 3.7 m wide. The “Test pit” section was selected for FEMvalidation. The pavement structure properties of this section and the other inputsparameters for FEM are given in Table 5.

The AC layer is characterized as linear viscoelastic material by Prony series,shown in Table 6. The pavement is considered as “thin pavement”, hence, the base

Table 4 Validation results for Illinois Center for Transportation section

Depth(mm)

Locationdefinition

Pavementresponse

Simulationresults

Fieldmeasurement

Difference(%)

432 Top ofsubgrade

Verticalpressure (kPa)

16.8 15.2 10.9

188 Bottom of AC(BM-25)

Transversalstrain (με)

53.3 70.9 24.8

Table 5 Florida section input parameters

Layer Thickness(mm)


Poisson’sratio

Density(×10−6)



AC 76.2 15,420 0.35 2.3 N/A N/A

Base 266.7 Nonlinear 0.4 2.1 3.1416 0.000795

Subbase 304.8 140 0.4 1.5 3.1416 0.000795

Subgrade 131 0.4 1.5 3.1416 0.000795

Table 6 Prony coefficientsof AC layer

i Gi (MPa) Ki (MPa) τi1 6859.929 6859.929 8.06E+00

2 5938.446 5938.446 7.89E+01

3 7098.832 7098.832 6.75E+02

4 5085.221 5085.221 6.49E+03

5 3890.706 3890.706 5.72E+04

6 1419.7664 1419.7664 8.16E+05

7 2969.223 2969.223 2.07E+06

8 219.44947 219.44947 7.61E+07

9 385.6577 385.6577 5.00E+08

10 246.07009 246.07009 2.88E+09

11 22.52514 22.52514 1.31E+10


was modelled as stress-dependent anisotropic material to have more realistic sim-ulations. The Uzan parameters for the base is given in Table 7.

The loading conditions were defined with a half-axle load of 26.7 kN and tirepressure of 552 kPa for DTA. Four critical responses, including vertical pressures atbottom of AC and bottom of base and transverse and longitudinal strains at bottomAC, were used for validation, as shown in Table 8. Four pressure cells are installedin this section, two of them are located at the bottom of AC and the other two at thebottom of the base layer. The relative difference between FEM and field arereported as 1.2 and 16.1 %. On the other hand, a total of six strain gauges wereinstalled at the bottom of the AC layer: three in traffic direction and three in thetransverse direction. The relative differences between FEM and field data for theseresponses were 11.9 and 52 % for traffic and transverse directions, respectively(Table 9).

Table 7 Nonlinear model parameters for base layer

k1 (kPa) 1038.7 k3 (kPa) 1038.7 k7 (kPa) 1038.7

k2 0.67 k5 0.67 k8 0.67

k3 −0.302 k6 −0.302 k9 −0.302

Because of lack of data, base layer is assumed to be isotropic material

Table 8 Validation results for Florida section

Depth(mm)

Locationdefinition

Pavementresponse

Simulationresults

Fieldmeasurement

Difference(%)

76.2 Top of base Vertical pressure(kPa)

166.9 168.9 1.18

342.9 Top ofsubgrade

Vertical pressure(kPa)

26.89 31 13.26

76.2 Bottom of AC Transversal strain(με)

18.5 21.1 12.32

76.2 Bottom of AC Longitudinalstrain (με)

43 98 56.12

Table 9 Smart Road section input parameters

Layer Thickness(mm)


Poisson’sratio

Density(×10−6)



AC 38 4230.9 0.35 2.30 N/A N/A

AC 150 4750.49 0.4 2.30 3.1416 0.000795

OGDL 75 2415 0.4 2.10 3.1416 0.000795

CTB 150 10342.14 0.4 2.10 3.1416 0.000795

Subbase 175 310.26 0.4 1.5 3.1416 0.000795

Subgrade – 262.00 0.4 1.5 3.1416 0.000795

OGDL open-graded drainage layer, CTB cement-treated base


FEM results are in agreement for the vertical pressures and tensile strains in thetransverse direction (around 10 %). However, the prediction of the strain in trafficdirection is off by a factor of 2. The reason for this discrepancy can be explained asfollows: the base material is characterized as stress-dependent anisotropic nonlinearmaterial to simulate the behavior of the base layer. However, since the resilientmodulus test was conducted only using vertical deviatoric load, it was not possibleto obtain nonlinear material characterization parameters for all three dimensions.Therefore, the base material was assumed isotropic; hence, FEM may have resultedin underestimated tensile strains in the traffic direction.

3.3 Smart Road Section

Section B, which is considered a “thick” section, of the Smart Road project wasused to validate the FE model in this study. The section has the following inputparameters (Al-Qadi et al. 2004).

AC layers are characterized as viscoelastic and were defined using the Pronyseries. Al-Qadi et al. (2008) shifted the Prony series to 25 °C and, therefore, theWilliam–Landel–Ferry coefficients are omitted (Table 10). In this scenario, the twolayers are assumed to be subjected to uniform temperature condition of 25 °C.Additionally, since the pavement is considered as thick pavement, the base layer isassumed to be linear elastic material to decrease computational cost.

Moreover, the loading condition was defined with a half-axle load of 35 kN and720 kPa for the DTA. Given all presented input parameters, three critical responseswere determined from the FE model and compared with field data (Table 11).Based on the resulting differences, the vertical pressure on top of the subgrade andtransversal and longitudinal strain underneath the AC layers varied by 2.4, 12.1,and 2.1 %, respectively. For this section, FEM delivered quite accurate approxi-mation for field pavement responses.

Table 10 Prony coefficients of AC layer

i Gi (MPa) Ki (MPa) τi Gi (MPa) Ki (MPa) τi1 3277.4667 3277.4667 1.00 × 10−2 3085.7378 3085.7378 1.00 × 10−2

2 698.01388 698.01388 1.00 × 10−1 1069.5918 1069.5918 1.00 × 10−1

3 168.3602 168.3602 1.00 405.53936 405.53936 1.00

4 58.509116 58.509116 1.00 × 101 117.09055 117.09055 1.00 × 101

5 11.577435 11.577435 1.00 × 102 50.973233 50.973233 1.00 × 102

6 7.2373775 7.2373775 1.00 × 103 70927.191 70927.191 1.00 × 103

7 8.6331515 8.6331515 1.00 × 104 3.4551549 3.4551549 1.00 × 104

8 0.0699114 0.0699114 1.00 × 105 – – –

9 0.0288996 0.0288996 1.00 × 106 – – –


3.4 UC Davis Section

The last section used for FEM validation was built at the University of CaliforniaPavement Research Center facility in Davis, California. The section, called“671HC”, was selected for FEM validation. This section has two AC layers, each60 mm thick. The top layer is warm mixed asphalt and the bottom is AC.Underneath the two AC layers, a recycled base and a subbase layers exit having 250and 270 mm layer thicknesses, respectively (Table 12).

The Prony coefficient for viscoelastic characterization of AC is given inTable 13. For this section, it was important to assume a linear elastic behavior forthe base layer because resilient modulus data for this section was not available. Thebase layer was assumed to have 60 MPa, which was obtained from the conepenetration test.

The load case was selected as 26 kN axle load and 552 kPa tire pressure forDTA. FEM was compared with field data for four pavement responses: verticalpressures at the top of base and subgrade and tensile strain at the bottom of each liftof AC layer. Comparison results are given in Table 14.

FEM prediction for vertical pressure at the top and bottom of the base layer wasmuch lower than field responses. The base material was characterized as linearelastic material due to the lack of resilient modulus data. As reported in the liter-ature (Kim et al. 2009), linear elastic characterization of base results is accepted instiffer behavior in pavement simulation. The effect gets even more significant forpavement with thinner AC layer as in this section.

Table 11 Validation results for Smart Road section

Depth(mm)

Locationdefinition

Pavementresponse

Simulationresults

Fieldmeasurement

Difference(%)

588 Top ofsubgrade

Verticalpressure (MPa)

40 40.9 2.44

188 Bottom ofAC

Transversalstrain (με)

103.79 92.62 12.06

188 Bottom ofAC

Longitudinalstrain (με)

116.11 118.65 2.14

Table 12 UC Davis section input parameters

Layer Thickness(mm)


Poisson’sratio

Density(×10−6)

Rayleighdampingparameters (α)

Rayleighdampingparameters (β)

AC 60 25,070.5 0.35 2.30 × 10−6 N/A N/A

AC 60 20,200.2 0.4 2.30 × 10−5 3.1416 0.000795

Base 250 300 0.4 2.10 × 10−6 3.1416 0.000795

Subbase 270 300 0.4 2.10 × 10−7 3.1416 0.000795

Subgrade – 60 0.4 1.5 × 10−6 3.1416 0.000795


4 Conclusion

This paper presents a study about in-situ validation of flexible pavement FEmodelling. The validation was conducted on four different sections. Three sectionsare classified as “thin pavement”, where anisotropic stress-dependent base char-acterization plays a critical role in the realistic simulation of pavement behaviorunder tire loading. In all cases, AC was modelled as viscoelastic material to captureits dependency on the frequency of loading and temperature. Moreover, the tire wassimulated as moving load to capture the dynamic effect on pavement, and realistictemperature gradient was imposed on pavement.

Validation was performed for pavement responses of vertical pressure at layerinterfaces and transverse strains at the bottom of AC. In general, good agreementwas noted between FEM calculated and pavement field instrument responses. Therelative differences were computed around 10–15 % which is acceptable, consid-ering the high variability in field data. The importance of proper characterization ofbase layer for accurate prediction of pavement responses is also highlighted in thispaper. In conclusion, this study proves that FEM is a promising technique forsimulating tire-pavement interaction in the field when proper material characteri-zation parameters and accurate tire loading are considered.

Table 13 Prony coefficients of AC layer

i Gi (MPa) Ki (MPa) τi Gi (MPa) Ki (MPa) τi

1 8991.5622 8991.5622 6.43E+00 4303.1373 4303.1373 7.97E+00

2 4362.6974 4362.6974 7.44E+02 5422.6967 5422.6967 6.55E+01

3 4693.0468 4693.0468 5.99E+03 1115.6559 1115.6559 8.94E+02

4 1761.065 1761.065 7.70E+04 3151.1575 3151.1575 6.61E+03

5 3019.8724 3019.8724 4.21E+05 240.59757 240.59757 9.67E+04

6 728.78796 728.78796 6.57E+06 3450.7857 3450.7857 4.44E+05

7 142.43435 142.43435 9.09E+07 1169.9032 1169.9032 5.19E+06

8 586.31793 586.31793 6.19E+08 453.44754 453.44754 6.50E+07

9 673.50101 673.50101 4.87E+09 56.296935 56.296935 9.50E+08

10 65.073848 65.073848 1.09E+10 574.7684 574.7684 3.05E+09

Table 14 Validation results for UC Davis section

Depth(mm)

Locationdefinition

Pavementresponse

Simulationresults

Fieldmeasurement

Difference(%)

120 Top of base Vertical pressure(kPa)

8.6 12.3 30.08

370 Top ofsubgrade

Vertical pressure(kPa)

4.5 5.8 22.41

120 Bottom of AC Transversal strain(με)

11.57 16.9 31.54


Acknowledgments This paper is based on the results of project DTFH61-11-C-00025, TheImpact of Wide-Base Tires on Pavement—A National Study. Project DTFH61-11-C-00025 isconducted in cooperation with the Illinois Center for Transportation; the U.S. Department ofTransportation, Federal Highway Administration; Rubber Manufacturers Association, and thefollowing state departments of transportation: Florida, Illinois, Minnesota, Montana, New York,Ohio, Oklahoma, South Dakota, Texas, and Virginia. The authors would like to acknowledge theassistance provided by many individuals including Hasan Ozer, Mojtaba Ziyadi, BouzidChoubane, Jamie Green of FLDO, John Harvey of UC Davis, Erol Tutumluer of UIUC.

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in-situ validation of three-dimensional pavement finite...

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