Developing Correlation between pavement functional and structural parameters for Pavement Evaluation

Articles in Press

Document Type : Research Paper

Authors

1 University of Engineering and Technology, Lahore, Pakistan

2 Department of Transportation Engineering & Management, University of Engineering and Technology, Lahore, Pakistan.

3 Department of Transportation Engineering and Management, University of Engineering and Technology, 54000, Lahore, Pakistan,

Abstract

The research aims at developing a model to predict the deflection of flexible pavements using IRI values to optimize maintenance activities without conducting deflection testing. 62 km of Multan- Lodhran south bound section, a part of N-5 is selected as study area, from km 929+000 to km 867+000. The data had been collected from the database of Road Asset Management Division (RAMD), National Highway Authority, Islamabad, Pakistan on basis of data availability and reliability. Collected data includes International Roughness Index (IRI) values measured by profilometer and deflection data measured by Falling Weight Deflectometer (FWD). Existing pavement structure data was collected from NHA Regional office. Linear and Logarithmic Regression analysis methodology using SPSS Statistical Analysis Software was used to develop correlation between pavement functional and structural parameters. Also, Microsoft Excel was used for data analysis and validation purpose. The developed regression model showed significant relationships between deflection and IRI. Additionally, AASHTO Back calculation method was also used for determining the effective structure number (SNeff) using deflection results from FWD to determine correlation of IRI with another structural parameter. Considering this, a significant correlation was found between SNeff and IRI. However, it was found that other parameters i.e., subgrade resilient modulus (Mr) and pavement elastic modulous (Ep) did not show any significant relation. The result showed that if pavement IRI values are known, deflection and SNeff can be predicted providing feasibility for transportation agencies that do not have the capabilities as deflection tests are costly and require sophistication for its data handling.

Keywords

International Journal of Transportation Engineering

Articles in Press, Accepted Manuscript
Available Online from 20 February 2024

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