Optimal Timing Of Preventive Maintenance Action Based On Performance Index Model For Rigid Pavements

Preventive maintenance is an active maintenance, which can meet better the needs of maintenance work in our country comparing with the traditional maintenance ways. Therefore, preventive maintenance is much accounted of transportation departments. Much research aimed at preventive maintenance, especially for asphalt pavements, and a lot of research achievments were gained. But research on preventive maintenance for rigid pavements in particularly optimal timing of preventive maintenance, was relatively fewer.This thesis researched on optimal timing of preventive maintenance action for rigid pavements on the basis of domestic and foreign findings.Firstly, the thesis set forth preventive maintenance treatments, benefits of preventive maintenance and issues in integrating pavement management into preventive maintenance for rigid pavements. Secondly, the thesis analysed the methods and models of performance prediction, and a prediction model on the basis of the pavement condition index was established for rigid pavments. Thirdly, based on the main hypothesis that an increase in roughness of rigid pavements leads to higher dynamic axle loads, and this amplification of load magnitude can lead to a tangible acceleration of pavement distress, the thesis used respectively the ride quality index (RQI) and distress index (DI) as measures of pavement surface roughness and distress, defined the DI value while the remaining service life for pavement was zero as the maximal of DI, developed a general pavement performance model which can exactly describe the pavement distress related to dynamic loading with progress of pavement roughness. Finally, equations used to calculate the corresponding RQI threshold-value and DI value were determined when acceleration in pavement distress related to dynamic load reaches the peak, thus the optimal timing of preventive maintenance action to improve the riding quality for pavments is addressed.