Resilient Modulus of Siliciclastic Unbound Granular Materials under Repeated Wheel Loading

Abstract

The Resilient Modulus (Mr) is a fundamental material property input in modern Mechanistic-Empirical (M-E) pavements structural design. Empirical pavement design methods have been in use over a long period during which large databases of fourdays-soaked California Bearing Ratio (CBR) values at or near the Maximum Dry Density have been generated in the strength assessments for Unbound Granular Materials (UGMs). In the adoption of the M-E design approach researchers have so far attempted with various degrees of success to develop models to derive resilient modulus from the conventional CBR-based databases. This study provides an extensive laboratory experimental study to investigate the resilient modulus of siliciclastic unbound granular materials under cyclic loading. The study involved samples collected from twelve active roads construction borrow areas in Iringa Region in Tanzania. The materials were fully characterised at Tanzania National Roads Agency Central Materials Laboratory (TANROADS CML) to enable classification of the materials in the empirical approach to which a range of materials of CBR Grades 25 to 80 were defined. Further, the mineralogy of the samples was assessed by X-Ray Diffraction (XRD) using inXitu Bench top XRD 231 analyser at University of Dar es Salaam Geology Department. A servo-hydraulic Universal Testing Machine-130 at TANROADS CML was used to simulate Repeated Load Test on the multiple samples from which resilient modulus of the UGMs were determined. A soaked CBR - Mr prediction model was then developed which showed strong non-linear relationship and correlated well with existing databases. Based on this study, the developed model has shown better performance compared to other studies and gives a good estimate of Mr values without performing the Repeated Load Triaxial (RLT) test for Mr determination. In addition, estimates of Mr values for each class of siliciclastic UGMs has been achieved and tabulated using the developed model.