foodsmaio.blogg.se

Ghorbani B, Arulrajah A, Narsilio G et al (2020) Development of genetic-based models for predicting the resilient modulus of cohesive pavement subgrade soils. George KP (2004) Prediction of resilient modulus from soil index properties. CĮlias MB, Titi HH (2006) Evaluation of resilient modulus model parameters for mechanistic-empirical pavement design. American Association of State Highway and Transportation Officials. Washington, D.CĪASHTO (2003) AASHTO T307, Determining the Resilient Modulus of Soils and Aggregate Materials, Standard Specifications for Transportation Materials and Methods of Sampling and Testing. Washington, D.CĪASHTO (2002) Standard specifications for transportation materials and methods of sampling and testing. Washington, D.CĪASHTO (1993) AASHTO Guide for Design of Pavement Structures. The proposed model could potentially be a good alternative to the existing constitutive models if methods for the determination of the k-coefficients could be developed.ĪASHTO (1986) AASHTO Pavement Design.

The results of the proposed model were also compared with the bulk stress model and the universal model, which is currently used by the mechanistic-empirical pavement design guide (MEPDG), and obtained to be generally better than both models. The results showed that the model has a very good fit to the data with coefficient of determination, root mean square error and mean absolute error values of 0.94, 2.20 and 1.76, respectively. A multi-variable nonlinear curve fitting was done using the SciPy library. The performance of the model was tested by fitting it to an M R test data obtained from the long-term pavement performance database. The proposed model relates M R with the bulk stress, confining pressure and deviatoric stress of the soil using four coefficients. The general form of three-parameter model which is common in many constitutive equations for M R was extended here to have four parameters. A new constitutive model for the resilient modulus (M R) of subgrade soils was developed in this study based on existing models.