PREDICTION OF REMAINING SERVICES LIFE AND FAILURE LOCATION OF FLEXIBLE PAVEMENT USING INDONESIAN ROAD MANAGEMENT SYSTEM (IRMS) V.3 AND AASHTO 1993 METHOD(CASE STUDY : BTS. PROV. JAMBI - PENINGGALAN ROAD)

• Main Author: Urmila, Dea
• Format: Theses
• Language: Indonesia
• Subjects: Teknik (Rekayasa, enjinering dan kegiatan berkaitan)
• Online Access: https://digilib.itb.ac.id/gdl/view/73096
• Institution: Institut Teknologi Bandung

An increase in traffic load per year is one of the factors causing a decrease in pavement performance, so it is important to evaluate the pavement structure by predicting the Remaining Service Life (RSL) of the pavement and identifying the failure location of the pavement’s layering system. Indonesia has implemented the Indonesian Road Management System (IRMS) V.3 program as a tool in road programming where there is an approach to predict RSL values based on structural and functional conditions (if structural data is not available) in IRMS V.3. Another method that can be used as a guide in predicting RSL values is AASHTO 1993 so this research aims to compare the RSL values of several methods on road maintenance requirements. By predicting the RSL value, Road Users will not experience road failure beforehand so that the RSL can be a parameter in making decisions related to road preservation which is also related to maintenance costs. In the structural evaluation of pavements, it is important to identify the failure location of the pavement’s layering system. Emile Horak developed a method by utilizing the deflection bowl parameters in determining the structural conditions of flexible pavements. With this method, the failure location in the pavement layer system can be identified thereby increasing the accuracy of road maintenance in Indonesia. The results showed that the predicted remaining services life based on functional data resulted in the most pessimistic and smaller remaining life compared to predictions using structural data. This is caused by the roughness parameter which is more describes surface conditions without really knowing the conditions in the pavement structure. Prediction of the remaining services life using the IRMS V.3 method based on structural data resulted in the most optimistic and higher remaining life compared to the AASHTO 1993 method. This is due to the prediction of the remaining services life using the IRMS V.3 method does not consider subgrade parameters while subgrade soil is the main factor for the bearing capacity of the pavement structure. The IRMS V.3 method based on structural data and the AASHTO 1993 method are not sensitive to road surface irregularities so that the two methods cannot trigger pavement surface maintenance. The AASHTO 1993 method is the most optimal method for use in flexible pavement maintenance decision trees. This is due to decision making starting with the roughness value so that the shortcomings of the AASHTO 1993 method, which is not sensitive to surface roughness are resolved with a decision tree. According to Emile Horak's method, the failure location in the pavement’s layer system mostly occurs in the subgrade. On the road segment under review, the subgrade that is excluded in the calculation of the prediction of the remaining services life of the pavement using the IRMS V.3 method will gives the better results if it include the subgrade characteristics in predicting the remaining services life. A high RSL value in a segment does not necessarily mean lower maintenance costs. The decision-making method for the type of maintenance of flexible pavement in IRMS V.3 is not only based on the RSL value, but also considers the IRI value. RSL as one of the factors in making decisions on the flexible pavement maintenance in IRMS V.3 only applies to roads with an IRI value of < 12 m/km or roads with sound to warning conditions. Roads with an IRI value of ? 12 m/km or roads with severe conditions will undergo maintenance in the form of reconstruction without considering the RSL value.