Evaluating Flexible Pavement Rutting Damage Caused by Heavy Traffic Loads

David Sinkhonde and Ignasio Ngoma
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David Sinkhonde: The Polytechnic – Department of Civil Engineering, University of Malawi
Ignasio Ngoma: The Polytechnic – Department of Civil Engineering, University of Malawi

International Journal of Research and Scientific Innovation, 2020, vol. 7, issue 6, 122-128

Abstract: This research was under taken to evaluate road pavement sections experiencing serious rutting damage induced by heavy traffic vehicles and those experiencing little or no rutting damage. The research on the impact of heavy traffic loads on pavement rutting performance was conducted on HHI to Machinjiri junction (S137) road section using field investigations and surveys. The research incorporated traffic counts for heavy vehicles to confirm levels of heavy vehicle traffic on the road segment and to verify the high numbers of permits issued for truck loading. Field works on identification and quantification of pavement surface distresses by executing visual condition surveys were carried out allowing for the current pavement surface conditions to be rated using pavement condition degrees and severities. The research also utilized Dynamic Cone Penetrometer (DCP) test for rapid in situ measurements of the structural properties of the existing road pavement and therefore it accommodated the evaluation of the in situ properties of the materials in all pavement layers up to the depth of penetration of 800mm. Comprehensive analyses were undertaken on the collected data to evaluate the pavement rutting performance. The utilization of DN values and California Bearing Ratio (CBR) values generated from DCP test results presented a potential methodology for determining the proportion of pavement rutting deterioration attributable to heavy traffic vehicles. Identification and quantification of pavement surface distresses by executing visual condition surveys on a 200m stretch rated the pavement surface conditions as between light and warning, warning, and between warning and severe. The traffic count levels for heavy vehicles obtained for five days indicated an average of 507 heavy vehicles per day and therefore confirming high traffic loads for the road section.

Date: 2020
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