Implementation of Mechanistic-Empirical Pavement Design Guide against Indonesian Conditions using Arizona Calibration

3.1. Existing Pavement Analysis

The existing pavement in this research consists of a 30 cm thickness of asphalt layer and a 15 cm grade-A granular aggregate layer. The modulus default values of the road materials for a 30 cm thick asphalt layer are 600 MPa and the Poisson's ratio of 0.35. As for the 15 cm granular layer, the modulus value is 150 MPa with a Poisson ratio of 0.35. Finally, the subgrade has a modulus of 60 MPa and a Poisson ratio of 0.45.

3.2. Traffic Analysis

In this study, the traffic growth factor considered is 4.8%, referred to in the Indonesian Road Pavement Design Manual (2017) [19]. The calculation of vehicle growth is separated into two-periods groups: the 2020 period uses factual loading, whilst the 2021 to 2029 period uses normal predicted loading. This classification is decided based on the government's regulation that no vehicles would exceed the standard vehicle weight or be overloaded by the end of 2020. However, due to data constraints, notably regarding the distribution of axle load per type of axle on each vehicle category, the value of ESA 4 was utilized for traffic loading in the MEPDG approach. Consequently, substituting the number of axle load spectra with ESA will reduce the accuracy of the MEPDG computations, as it only employs a dual-wheel single-axle model. The following Table 1 is the calculation of ESA 4 and ESA 5 from the traffic data in both directions for a design life of ten years.

3.3. Climate Analysis

Climate analysis is performed to identify the Weighted Mean Annual Pavement Temperature (WMAPT). The WMAPT parameter is necessary to correct the FWD deflection data with the annual average pavement temperature (AAPT). Table 2 shows the result of the climate analysis.

3.4. Deflection Analysis

The deflection analysis of the FWD measurement consists of three steps: (1) deflection correction to temperature, (2) division of segments, and (3) back-calculation examination of each part. Initially, to correct the deflection results according to temperature, it is required to calculate fT or compare the asphalt temperature during the test to the WMAPT. The outcomes of the fT calculation were then plotted in a graph to generate the deflection correction factor. In the Road Pavement Design Manual [18], the deflection correction factor is obtained from a table based on the fT value and asphalt thickness. Subsequently, the deflection data is segmented, and one representative deflection is taken from each segment for the back-calculation process (Table 3).

As a result of the back-calculation process in the BAKFAA software, the smallest RMS values were obtained, respectively, 11% for the N (normal) direction segment 1 and 7% for the O (opposite) direction segment 1. Therefore, asphalt and granular modulus values are close to the seed modulus but quite far for the subgrade case. Also, the resulting RMS value ranges from 7% to 16%, which indicates that the back-calculation output is still not precise as it is outside the rule range of 1% to 2%. Hence, the modulus of the existing pavement used in the subsequent analysis is the default value of the pavements listed in the Indonesian Road Pavement Design Manual [19]. Then, all four segments will be merged into one.

6.1. Permanent Deformation Model

In the 2015 MEPDG, permanent deformation is the sum of deformations in asphalt, unbound base, and soil subgrade. This indicates that all layers of the pavement are reviewed. Therefore, executing the permanent deformation damage model using the 2015 MEPDG in Indonesia has good potential, considering many issues on the permanent deformation of the asphalt surface that cannot be controlled. At present, the only pavement evaluation methods accessible in Indonesia are those that detect permanent deformations in the subgrade layer.

The permanent deformation of asphalt in the 2015 MEPDG has a composition where the strain is inversely proportional to the load repetitions, which were calculated by dividing the permanent deformation value by the allowable strain. Moreover, there are supplementary variables in the form of correction of layer thickness and asphalt temperature, which also global and local calibration of load repetitions, layer thickness, and temperature. Otherwise, in the empirical model of permanent soil deformation, the number of load repetitions on the 2015 MEPDG is an exponential function, influenced by the material properties indicators: β and ρ. Furthermore, there are additional variables in the form of correction of layer thickness and material properties, as well as global and local calibration of thickness, depending on the type of material, i.e., granular layer or subgrade.

6.2. Fatigue Cracking Model

The MEPDG categorizes fatigue cracking into alligator, longitudinal, and reflective cracks [23]. The strain and modulus are inversely proportional to the number of load repetitions; contrarily, the asphalt content is directly proportional. This method also has additional variables, including layer thickness correction, damage type (alligator or longitudinal), air void percentage, and global or local calibration of layer thickness, resulting strain, and modulus. However, the reflection cracking model has not yet been globally calibrated by the 2015 MEPDG. In contrast, the most widely used damage percentage model is calculated by dividing 100% of the predicted damage by the design life (t) and the asphalt overlay thickness (a, b), with the addition of calibration parameters (c, d). In the Indonesian case, the road pavement design procedure considers only alligator cracking; therefore, the 2015 MEPDG damage model is more comprehensive to be applied.

6.3. IRI Model

The International Roughness Index (IRI) model, presently being developed in Indonesia, was created by William D.O. Paterson in 1987 according to the Highway Development and Management (HDM) III, as seen in Equation (1). The model has variables in the form of initial IRI, Structural Number (SN), cumulative ESA4, and pavement life. The SN value represents the strength of a pavement structure required for a combination of soil bearing capacity (Mr), cumulative load (ESAL), the Present Serviceability Index (PSI), and the environment. In addition, the SN value used in the AASHTO (1993) [ 24 ] method to determine the pavement layer thickness was based on the layer and drainage coefficients.

(1)

With:

RI ( t ): IRI value at time t (m/km)

RI ₀ : initial IRI value (m/km)

SNC : structural number

NE ₄ ( t ): cumulative ESA4 at time t (million ESA4)

t : pavement age (year)

Comparing the IRI models of the 2015 MEPDG with the Paterson model reveals that the initial IRI value was derived from the new pavement or new overlay. This value is then corrected to the MEDPG damage model and cumulative load or the structural number for the Paterson model. Regarding pavement life, the 2015 MEPDG expressed it as a safety factor (SF). In the Paterson model (1987) [25], however, pavement life is represented by an exponential function. Additionally, the variables employed are more diversified, especially concerning environmental aspects.

7.1. Data Requirements

The most crucial traffic data in this research is the WIM (Weight-in-Motion) data per axle type for each vehicle in Indonesia, which was adapted from the “Supplement to Road Pavement Design Manual” issued by the Indonesia Ministry of Public Works and Housing (2020) [26]. Likewise, the proportion of heavy vehicles belonging to each class within a certain period is also mandatory to identify its distribution. In the 2015 MEPDG, traffic data input is divided into three distinct levels depending on the completeness of the data possessed, as described in the Methodology section. This manual covers default values related to WIM data, heavy vehicle distribution, and axle types for each kind of vehicle. These indicators are also entered when using the AASHTOWare software, which incorporates both fatigue and thermal cracking [27]. Moreover, to adapt the MEPDG procedure to Indonesia, it is necessary to discover the default value of traffic data, as listed in Fig. (2).

In Indonesia, pavement material properties have been regulated in the General Specifications (2018) [28] issued by the Directorate of Highways, Ministry of Public Works and Housing. However, several essential parameters in applying the MEPDG method have not been defined yet but need to be determined. Hence, the standard for asphalt material properties must be evolved, especially the Dynamic Modulus values of the asphalt layer at different loading times and temperature periods. The material properties of the asphalt layer in the 2015 MEPDG are classified into several matters, including volumetric data, and mechanical and thermal properties. In contrast, the granular and subgrade layers are divided into strength or modulus, along with the thermal, gradation, and engineering properties. The Federal Highway Administration (FHWA) database, which includes hourly climate details from year to year for each weather station, is utilized for implementing the MEPDG method. Not only does it contain complete data, but it is also easy to access. However, in the case of Indonesia, climate data must be collected from the National Meteorology, Climatology, and Geophysics Agency. Unfortunately, the information available is merely in the form of daily climate and rainfall, while the comprehensive data on groundwater levels for Indonesia has not yet been known.

7.2. Damage Model Adjustment

To be applied in Indonesia, the empirical model and performance criteria of the 2015 MEPDG should be adapted to local circumstances. Hence, the first step is to modify the input of the empirical model in order to match the units used in Indonesia before calibrating the formulas and adjusting the pavement damage that exists in the area under review. Furthermore, as winter does not occur in Indonesia, the variables related to freezing temperature were omitted. Some formulas are described as follows:

• Asphalt permanent deformation model:

(2)

With:

∆_p(HMA): permanent deformation on HMA layer (mm)

Ɛ_r(HMA): resilient or elastic strain at the center of HMA

n: number of load repetitions

T: pavement temperature (°C)

kz: depth correction, which is formulated as follows:

(3)

(4)

(5)

With:

D: depth below the surface (mm)

H_HMA: total HMA thickness (mm)

• Soil Permanent Deformation Model:

(6)

With:

∆p(soil): permanent deformation of the soil layer (mm)

n: number of load repetitions

ε₀: the intercept of permanent deformation repetitive load

tests in the laboratory (in/in)

ε_r: resilient strain of the laboratory test to determine properties ε₀, β, ρ (in/in)

ε_v: average vertical strain in the layer

h_soil: soil layer thickness (mm)

(7)

(8)

(9)

(10)

With:

W_c: water content (%)

M_r: resilient modulus (psi)

a_1,9: regression constraints: a₁ = 0.15 dan a₉ = 20.0

b_1,9: regression constraints: b₁ = 0.0 dan b₉ = 0.0

• Fatigue cracking model:

(11)

with:

N_f-HMA: a number of load repetitions

ε_t: tensile strain at a critical location

E_HMA: dynamic modulus HMA (psi)

Where:

(12)

(13)

with:

V_be: effective asphalt content by volume (%)

V_a: air void percentage in the HMA mixture (%)

C_h: thickness correction (depending on the crack type)

• C_H of Alligator Cracking:

(14)

• C_H of Longitudinal Cracking:

(15)

With:

H_HMA: a total of HMA thickness (mm)

• Alligator Cracking Area:

(16)

(17)

(18)

With:

FC_bottom: alligator crack area at the bottom of HMA (%)

Dl_bottom: cumulative damage index at the bottom of HMA

• Longitudinal Cracking Area:

(19)

with:

FC_top: the length of the longitudinal crack at the top of HMA (m/km)

Dl_top: cumulative damage index at the top of HMA

The alligator cracking width in the MEPDG model is 12 ft (3.67 m) with a length of 500 ft (152.40 m). When applied to Indonesia, the area's dimension refer to the national road standards, which is 3.6 m (11,81 ft) wide and 150 m (492.13 ft) long. This measure results in a total area of 5,812.5 ft². On the other side, the length of the longitudinal cracking considered in the MEPDG is 500 ft (152.40 m). Thus, the size reviewed for the Indonesian case can be converted to 150 m (492.13 ft) long.

• The IRI model:

(20)

with:

IRI₀: IRI after overlay (m/km)

SF: site factor

FCtotal: fatigue cracking area (alligator, longitudinal, reflection) (%)

RD: average rut depth (mm)

(21)

with:

Age: pavement life (year)

PI: soil index plastic percentage

R: average annual rainfall (mm)

P₀₂: percent passing 0.02 mm

P₂₀₀: percent passing 0.075 mm

7.3. Definition of Performance Criteria

The arrangement of performance criteria aims to guarantee that the constructed road is able to serve the traffic loads during its design life while still preserving the comfort of road users and road functionality. The design performance criteria for Indonesian conditions were determined following the regulation of the Directorate of Highways concerning “Guidelines for Selection of Preventive Maintenance Technology for Road Pavement” [29] for road damage models, as well as rules by Indonesia's Ministry of Public Works and Housing on “Road Maintenance and Surveillance Procedures” [30] for the IRI model. Moreover, more studies are demanded since the determination of the first IRI value is contingent on the contractor's ability to work on the road surface layer.

7.4. Local and Global Calibration

In this instance, global calibration findings from the National Cooperative Highway Research Program (NCHRP) in 2004 [31] may be used in conjunction with initial calibration values derived from the most recent American global calibration. As for local calibration, it may be adopted from one of the states in America, such as Arizona, or by following the instructions in the “Guide for the Local Calibration of the Mechanistic-Empirical Pavement Design Guide”, which is released by AASHTO [32, 33].