Analysis of CBR design value selection methods on flexible pavement design: Colombia case study

  • Authors

    • Otto Mora L. Universidad de la costa
    • Michel Murillo A. Universidad de la costa
    • Tiana Rosania A. Universidad de la costa
    • Abraham Castañeda A.
    • Rosa Pinto C. Universidad de la costa
    • Andrea Padilla M. Universidad de la costa
    2020-05-07
    https://doi.org/10.14419/ijet.v9i2.30628
  • Asphalt, CBR, Design, Flexible Pavement, Pavement Design.
  • A comparative analysis was carried out to observe the variation of a flexible pavement structural thickness, due to the use of different meth-ods to calculate the CBR design value, as an essential variable to estimate the Subgrade Resilient Modulus (Mr) through an empirical corre-lation. The Asphalt Institute Method and the Mean Criterion Method were applied to calculate de Design CBR value of a homogeneous roadway division from a representative track section located in the Bolivar Department, Colombia. As a result, the Design Percentiles of the CBR design unit were expanded for the Asphalt Institute method, thus, allowing the approach of more reliable and safe designs, considering that this method limits the selection percentiles to three traffic levels.

     

     

  • References

    1. [1] Castillo, C. (2014), Revisión de los métodos de diseño de pavimentos flexibles "AASHTO93" y el "MODELO ELASTICO LINEAL", mediante el modelo viscoelastico propuesto por la "ME PDG NCHRP 1-37A (3D-MOVE)". Bogotá.

      [2] AASHTO 93. (s.f.). AASHTO guide for design of pavement structure, American Association of State and Highway Transportation Officials.

      [3] Sánchez, F. (2016), Diseño de Pavimentos Asfalticos para calles y carreteras.

      [4] Sas, W., Gluchowski, A., & Szymanski, A. (2012), Determination of the Resilient modulus MR for the lime stabilized clay obtained from the repeated loading CBR tests. https://doi.org/10.2478/v10060-011-0070-0.

      [5] Esfahani, M.A., & Goli, A. (2018), Effects of Aggregate Gradation on Resilient Modulus and CBR in Unbound Granular Materials. DOI:10.22119/ijte.2018.49727

      [6] Sas, W., Gluchowski, A., Gabrys, K., Soból, E., & Szymanski, A. (2018), Resilient modulus testing with application of cyclic CBR test for road subgrade materials. ResearchGate. https://doi.org/10.1002/cepa.763.

      [7] Asphalt Institute Method: http://www.asphaltinstitute.org/engineering/design/

      [8] Higuera, C. H. (2011), Nociones sobre métodos de diseño de estructuras de pavimentos para carreteras. Tunja: Universidad Pedagógica y Tecnológica de Colombia.

      [9] Instituto Nacional de Vías INVÃAS – Colombia: https://www.invias.gov.co/index.php/documentos-tecnicos

      [10] Goenaga, B., Fuentes, L., & Mora, O. (2018), A Practical Approach to Incorporate Roughness-Induced Dynamic Load in Pavement Design and Performance Prediction. ResearchGate. https://doi.org/10.1007/s13369-018-3414-9.

      [11] Montejo, A. (2002), Ingeniería de Pavimentos para Carreteras. Bogotá.

      [12] Dione, A., Fall, M., Berthaud, Y., Benboudjama, F., & Michou, A. (2014). Implementation of Resilient Modulus–CBR relationship in Mechanistic Pavement Design. Sciences Appliquées et de l'Ingénieur, 1(2), 65-71.

      [13] Erlingsson, S. (2007). On forecasting the resilient modulus from the CBR value of granular bases. Road materials and pavement design, 8(4), 783-797. https://doi.org/10.1080/14680629.2007.9690099.

      [14] Cafiso, S., & Di Graziano, A. (2012). Definition of homogenous sections in road pavement measurements. Procedia-Social and Behavioral Sciences, 53, 1069-1079. https://doi.org/10.1016/j.sbspro.2012.09.956.

      [15] Misra, R., & Das, A. (2003). Identification of homogeneous sections from road data. International Journal of Pavement Engineering, 4(4), 229-233. https://doi.org/10.1080/10298430410001672237.

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  • How to Cite

    Mora L., O., Murillo A., M., Rosania A., T., Castañeda A., A., Pinto C., R., & Padilla M., A. (2020). Analysis of CBR design value selection methods on flexible pavement design: Colombia case study. International Journal of Engineering & Technology, 9(2), 509-514. https://doi.org/10.14419/ijet.v9i2.30628