Impact of Subgrade and Granular Layer Material Properties on Rutting

Material properties play avital role to determine the structural and functional performance of pavement layers during its service life. Pavement deformation or rutting is one of the key distress that affects the pavement performance. The strength parameters of subgrade and granular layer are correlated with the permanent deformations characteristics. Theindividualeffect in addition to combined effectof various combinations are considered to estimate rutting using multi linear regression (MLR) and artificial neural network (ANN) techniques. The data was collected in staggered position at every kilometer of a national highway stretch. The characteristic deflection, field dry density, modified liquid limit, California bearing ratio (CBR) were correlated individually with the rutting measurement and sensitivity analysis also performed. The impact of fines and dynamic behavior of soil response are considered in four possible combinations and correlated with rutting. The result shows that characteristic deflection, field dry density, modified liquid limit and modulus of elasticity of subgrade, and granular layer individually consists good relation with rutting except liquid limit. A good correlation was obtained supporting the validity of R2 values of ANN for subgrade and granular layer 0.84 and 0.86 respectively for combinations of parameters. Likewise, results of R2 values for MLR models obtained are 0.70 and 0.79, for the given layers subsequently comparing the R2 values of MLR and ANN it is concluded that ANN models are more efficient than MLR.