Enhancing the Prediction of Subgrade Stiffness Modulus and CBR using FWD for Flexible Pavements
Gary Chai, Sanaul Huq Chowdhury, Sittam P. Manoharan
Abstract
Gary Chai, Sanaul Huq Chowdhury, Sittam P. Manoharan
Abstract
Deflection based model developed by Queensland Department of Transportation and Main Roads (TMR) is commonly used for predicting the subgrade CBR of asphalt pavements. The model utilises Falling Weight Deflectometer (FWD) deflection D900 recorded at 900 mm from the impact load. The principal aim of the study is to enhance the prediction of in-situ subgrade stiffness modulus and CBR using FWD for asphalt pavements with thin surfacing layers. The scope of the study included the comparison of subgrade CBR predictions from the deflection model and the predictions were verified using the in-situ CBR values derived from Dynamic Cone Penetrometer (DCP) from eleven pavement test sites. The approach for computing the degree of nonlinearity of subgrade was discussed. The study shows that the deflection model over predicts the subgrade CBR because the deflections recorded at sensor D900 are consistently small due to the nonlinearity of the subgrade material. Subsequently, a modified TMR model was developed, by considering subgrade nonlinearity in the model. As a result, the CBR prediction was significantly enhanced.
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Deflection based model developed by Queensland Department of Transportation and Main Roads (TMR) is commonly used for predicting the subgrade CBR of asphalt pavements. The model utilises Falling Weight Deflectometer (FWD) deflection D900 recorded at 900 mm from the impact load. The principal aim of the study is to enhance the prediction of in-situ subgrade stiffness modulus and CBR using FWD for asphalt pavements with thin surfacing layers. The scope of the study included the comparison of subgrade CBR predictions from the deflection model and the predictions were verified using the in-situ CBR values derived from Dynamic Cone Penetrometer (DCP) from eleven pavement test sites. The approach for computing the degree of nonlinearity of subgrade was discussed. The study shows that the deflection model over predicts the subgrade CBR because the deflections recorded at sensor D900 are consistently small due to the nonlinearity of the subgrade material. Subsequently, a modified TMR model was developed, by considering subgrade nonlinearity in the model. As a result, the CBR prediction was significantly enhanced.
Key concepts: Subgrade, Falling weight deflectometer, Deflection (physics), Geotechnical engineering, Penetrometer, Stiffness, Asphalt, Asphalt concrete