EVALUATION OF CALIBRATION FACTORS FOR RUT DEPTH, FATIGUE CRACKING AND IRI MODELS ON FLEXIBLE PAVEMENT USING MEPDG 2015 METHOD (CASE STUDY: ROAD SECTION FROM BTS. TASIKMALAYA/CIAMIS - ANCOL)

• Main Author: Aprillia Rachmasari, Malinda
• Format: Theses
• Language: Indonesia
• Subjects: Teknik (Rekayasa, enjinering dan kegiatan berkaitan)
• Online Access: https://digilib.itb.ac.id/gdl/view/81815
• Institution: Institut Teknologi Bandung

The BTS road segment. Kab. Tasikmalaya/Ciamis – Ancol is part of the WP Priatim – Pangandaran region, where the economic conditions have not yet developed well, necessitating improvements in physical infrastructure, particularly highways. A highway segment needs to be properly planned and maintained, requiring pavement condition analysis that accurately models the actual conditions. The Mechanical-Empiric Pavement Design Guide (MEPDG) is one of the more complex pavement methods compared to others. Before implementing MEPDG, each region or country must calibrate the model equations to enhance performance calculations that reflect field conditions. This research calibrates the flexible pavement model for rut depth, fatigue cracking, and International Roughness Index (IRI) equations in the MEPDG. The calibration analysis involves coefficients such as ?2r for the HMA layer, fatigue cracking bottom damage coefficient ?2fb, fatigue cracking top damage coefficient ?2ft, and smoothness damage model coefficients C1 and C2. Calibration is conducted on segmented sections based on deflection values and unsegmented sections. The analysis is performed using back-calculation modulus with ELMOD 6 to obtain elastic modulus values and KENPAVE to obtain strain values. These modulus and strain values are then used as input data in the MEPDG model equation solver. The analysis results indicate that damage value determination in global calibration is higher compared to local calibration for each model equation. The use of calibrated coefficient values shows that local calibration can improve pavement damage determination for the upcoming year, based on the reduction in Mean Average Percentage Error (MAPE) from global calibration to local calibration for each model equation, and improves the model determination category based on MAPE values. In conclusion, the calibration of rut depth, fatigue cracking, and IRI models in the MEPDG equations can enhance the determination of pavement damage for the next year, and calibration on segmented sections can improve calculations better than on unsegmented sections.