Flexible Pavement Maintenance Based on Calibrated Performance Curve.

Ahmed, Essam; Mahdy, Hassan Abd-elzaher; Mohamed, Hamdy Elsayed

doi:10.21608/bfemu.2021.169620

Flexible Pavement Maintenance Based on Calibrated Performance Curve.

Document Type : Research Studies

Authors

¹ M.sc Student, Civil Engineering, Public Works Department, Faculty of Engineering, Ain Shams University, Egypt.

² Professor of Highway and Airport Engineering, Public Works Department, Faculty of Engineering, Ain Shams University, Egypt.

10.21608/bfemu.2021.169620

Abstract

In this paper, a performance curve is used to optimize flexible pavement maintenance. The main aim of this study is to develop a performance model based on Benkelman Beam (BB) results by using prediction models derived from the data for Pavement Condition Index (PCI) that was obtained from three districts belonging to the General Authority for Roads, Bridges and Land Transport (GARBLT) which consist of about Central district (26sections), Middle-Delta (22 sections), and East-Delta (14 sections) with a total length of 124 Kilometers. The proposed model was validated by comparing the predicted values with actual (PCI) with a coefficient of determination R^2 () equals 0.87. Structural evaluation of in-service pavements is a key activity for both the project and network-level pavement management systems. Benkelman Beam was used for measuring the deflection. Test points were taken at a distance of 1.5 m from the edge of the pavement. Since the deflections measured by the Benkelman Beam are influenced by the pavement temperature and seasonal variations in climate, therefore, pavement was recorded temperature for making subsequent corrections to the deflection values. Since the Structure Number (SN) evaluation of in-service pavements is a key component for both the Structural Condition Index (SCI), the resulting deflections from (BB) were converted to structural number (SN) using a model and the validity has been checked by taking samples from the pavement layers, which revealed a strong correlation between them with a coefficient of determination (R^2) of 0.62. The structure number in 2018 is predicted from the proposed model and then compared with actual field measurements for the same year. A conclusion is made regarding the validity of the proposed prediction model with a coefficient of determination (R^2) equals 0.91. Since (BB) reading is important to determine Pavement Condition Index (PCI) value.

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