# Application of Mechanistic Empirical Pavement Design Guide Software in Saudi Arabia
## 3 Methodology  
The research methodology adopted, shown in Figure 5, for the project was very specific and organized to achieve all the research objectives determined initially. The output intended from the project is to develop generic regional guidelines for pavement structure to satisfy existing conditions in KSA in terms of the traffic, climate, and material characterization. The current licensed software provides access to various climatic files available on the AASHTOware website. The process on how to select different location and download the climate files is elaborated in the manual for the software. There is an option to select the desired location online and download the updated climate data base files for the particular location through the website from Modern-Era Retrospective Analysis for Research and Applications (MERRA) for MEPDG Inputs. Hence, MERRA data covers the entire globe, climate data for the four regions in KSA, which can be readily selected from the software for design. Based on the literature review and data collected from Ministry of Transport (MOT), MEPDG Software was used to predict pavement distresses in terms of pavement rutting, fatigue cracking, and International Roughness Index (IRI) for the local conditions. Figure 5 shows the flow-chart for the methodology which was implemented to progress work according to the plan. Figure 4: Example of fatigue and thermal cracking in flexible pavement. To adopt the mechanistic-empirical design method to develop structural pavement deign in KSA, there is a need to consider the influence of site conditions (different climatic regions), traffic loading and asphalt mixture characteristics including binder properties. The MEPDG allows engineers to predict pavement performance (i.e., development of distresses such as rutting and alligator cracking over the design period) because the software incorporates more fundamental material characteristics (such as the dynamic modulus (1E*1) master curve), climate data, axle-load spectra, and other advances. The overall pavement design framework of the MEPDG is shown in Figure 6.  
Due to the complexity of material inputs required, a hierarchical input data scheme has been implemented in the AASHTO MEPDG Software. Level 1 inputs are site-specific and considered the most accurate as they are determined from actual measurements of the materials used in a specific project. Level 2 inputs are used when the designer has a modest understanding of the input parameters for the software. This level is used when limited resources and data are available. Level 3 inputs are used when the designer has insufficient materials data for the project and is forced to use default values. In summary, Level 1 is considered the most accurate and normally involves comprehensive laboratory and field testing. In contrast, Level 3 is the simplest and considered the least accurate, as it requires estimate of input vales based on experience with no testing. Inputs at Level 2 are estimated through correlation with other material properties that are measured in the laboratory or field, which is the method that was used in this study. The selection of the locations for the project are dependent on various parameters, mainly the temperature zoning map of Saudi Arabia as shown in Figure 7. The team restricted the site conditions at four regions in KSA. These were: Central Region (Riyadh); Eastern Region (Al-Ahsa); Western Region (Jeddah); and Northern Region (Arar) shown with dots in Figure 7. It has well been established and known that these four regions encompass different environmental zones. Figure 5: Flow-chart for the activities. The Federal Highway Administration (FHWA) in the USA classifies vehicles into thirteen different classes, 4 through 13 are accounted for in MEPDG using the vehicle class distribution (VCD) as shown in Table 1. The VCD is calculated by dividing the annual average daily truck traffic for each truck class (AADTT) by the annual average daily truck traffic (AADTT) for all trucks as listed below [35]:  
1.