1,041
Views
63
CrossRef citations to date
0
Altmetric
Articles

Development of ANN-GA program for backcalculation of pavement moduli under FWD testing with viscoelastic and nonlinear parameters

&
Pages 490-498 | Received 26 Jan 2017, Accepted 08 Mar 2017, Published online: 09 Apr 2017

References

  • ABAQUS . 2010. ABAQUS analysis user’s manual, version 6.10. Pawtucket, RI: Habbit, Karlsson & Sorenson Inc.
  • Alkasawneh, W. , 2007. Backcalculation of pavement moduli using genetic algorithms. Dissertation [PhD]. The University of Akron.
  • Al-Qadi, I.L. , Wang, H. , and Tutumluer, E. , 2010. Dynamic analysis of thin asphalt pavements by using cross-anisotropic stress-dependent properties for granular layer. Transportation Research Record, No. 2154. Washington, DC: TRB, National Research Council, 156–163.10.3141/2154-16
  • ARA, Inc. ERES Division , 2004. Guide for mechanistic-empirical design of new and rehabilitated pavement structures, Washington, DC: TRB, NCHRP 1-37A Final Report.
  • Bathe, K.J. , 1982. Finite element procedures in engineering analysis. Upper Saddle River, NJ: Prentice-Hall.
  • Beale, M.H. , Hagan, M.T. , and Demuth, H.B. , 2015. Neural network toolbox™ user’s guide. The MathWorks, Inc. Available from: www.mathworks.com.
  • Ceylan, H. , Gopalakrishnan, K. , and Guclu, A. , 2007. Advanced approaches to characterizing nonlinear pavement system responses. Transportation Research Record, No. 2005. Washington, DC: TRB, National Research Council, 86–94.
  • Chatti, K. , Ji, Y. , and Harichandran, R. , 2004. Dynamic time domain backcalculation of layer moduli, damping, and thicknesses in flexible pavements. Transportation Research Record, No. 1869. Washington, DC: TRB, National Research Council, 106–116.
  • Chatti, K. , et al. , 2017. Enhanced analysis of falling weight deflectometer data for use with mechanistic-empirical flexible pavement design and analysis and recommendations for improvements to falling weight deflectometer. McLean, VA: Federal Highway Administration (FHWA) , Publication No. FHWA-HRT-15-063.
  • FHWA , 2000. Temperature predictions and adjustment factors for asphalt pavement. McLean, VA: Federal Highway Administration (FHWA), Publication No. FHWA-RD-98-085.
  • FHWA , 2016. LTPP InfoPave. Available from: https://infopave.fhwa.dot.gov/.
  • Fwa, T.F. , Tan, C.Y. , and Chan, W.T. , 1997. Backcalculation analysis of pavement-layer moduli using genetic algorithms. Transportation Research Record, No. 1570. Washington, DC: TRB, National Research Council, 134–142.
  • George, K.P. , 2004. Prediction of resilient modulus from soil index properties. Jackson, MS: Mississippi Department of Transportation Research Division, Final Report to Federal Highway Administration.
  • Goldberg, D.E. , 1989. Genetic algorithms in search, optimization, and machine learning. Reading, MA: Addison-Wesley Pub. Co.
  • Gopalakrishnan, K. , et al. , 2014. Development of asphalt dynamic modulus master curve using falling weight deflectometer measurements. Ames, IA: Iowa Department of Transportation, Final Report to Iowa Highway Research Board.
  • Huang, Y.H. , 1993. Pavement analysis and design. 1st ed. Upper Saddle River, NJ: Prentice Hall.
  • Izevbekhai, B. and Pederson, N. , 2010. Investigation of deflection and vibration dynamics of concrete and bituminous pavements constructed over geofoam. St. Paul, MN: Minnesota Department of Transportation, Final Report to MnDOT.
  • Kim, Y.R. , et al. , 2011. LTPP computed parameter: dynamic modulus. McLean, VA: FHWA, FHWA-HRT-10-035 Final Report.
  • Kutay, M.E. , Chatti, K. , and Lei, L. , 2011. Backcalculation of dynamic modulus mastercurve from FWD surface deflections. Transportation Research Record, No. 2227. Washington, DC: TRB, National Research Council, 87–96.
  • Lee, Y. , Kim, Y. , and Ranjithan, S. , 1998. Dynamic analysis-based approach to determine flexible pavement layer moduli using deflection basin parameters. Transportation Research Record, No. 1639. Washington, DC: TRB, National Research Council, 36–42.
  • Mateos, A. and Snyder, M.B. , 2002. Validation of flexible pavement structural response models with data from the minnesota road research project. Transportation Research Record, No. 1806. Washington, DC: TRB, National Research Council, 19–29.
  • Meier, R.W. , 1995. Backcalculation of flexible pavement moduli from falling weight deflectometer data using artificial neural networks. Washington, DC: Army Corps of Engineers, Final Report to U.S.
  • Mun, S. and Kim, Y.R. , 2009. Backcalculation of subgrade stiffness under rubblised PCC slabs using multilevel FWD loads. International Journal of Pavement Engineering, 10 (1), 9–18.10.1080/10298430701827650
  • Park, S.W. and Schapery, R.A. , 1999. Methods of interconversion between linear viscoelastic material functions. Part I-a numerical method based on Prony series. International Journal of Solids and Structures, 36, 1653–1675.
  • Park, D.Y. , Buch, N. , and Chatti, K. , 2001. Effective layer temperature prediction model and temperature correction via falling-weight deflectometer deflections. Transportation Research Record, No. 1764. Washington, DC: TRB, National Research Council, 97–111.
  • Romanoschi, S.A. and Metcalf, J.B. , 2001. Effects of interface condition and horizontal wheel loads on the life of flexible pavement structures. Transportation Research Record, No. 1778. Washington, DC: TRB, National Research Council, 123–131.
  • Tarefder, R.A. , et al. , 2014. Finite element model of pavement response under load considering cross-anisotropy in unbound layers. Advances in Civil Engineering Materials, 3 (1), 57–75.
  • Tutumluer, E. and Thompson, M.R. , 1997. Anisotropic modeling of granular bases in flexible pavement. Transportation Research Record, No. 1577. Washington, DC: TRB, National Research Council, 18–26.
  • Tutumluer, E. , Pekcan, O. , and Ghaboussi, J. , 2009. Nondestructive pavement evaluation using finite element analysis based soft computing models. West Lafayette, IN: Final Report to USDOT Region V Regional University Transportation Center.
  • Varma, S. and Kutay, E. , 2016. Backcalculation of viscoelastic and nonlinear flexible pavement layer properties from falling weight deflections. International Journal of Pavement Engineering, 17, 388–402.10.1080/10298436.2014.993196
  • Wang, H. and Li, M.Y. , 2015. Evaluation of effects of variations in aggregate base layer properties on flexible pavement performance. Transportation Research Record, No. 2524. Washington, DC: TRB, National Research Council, 119–129.
  • Wang, H. and Li, M.Y. , 2016. Comparative study of asphalt pavement responses under FWD loading and moving vehicular loading. Journal of Transportation Engineering, 142 (12), 04016069.10.1061/(ASCE)TE.1943-5436.0000902
  • Xiao, Y.J. and Tutumluer, E. , 2012. Best value granular material for road foundations. Saint Paul, MN: Minnesota Department of Transportation , Final report to Minnesota DOT.
  • Zaabar, I. , et al. , 2014. Backcalculation of asphalt concrete modulus master curve form field-measured falling weight reflectometer data: using a new time domain viscoelastic dynamic solution and genetic algorithm. Transportation Research Record, No. 2457. Washington, DC: TRB, National Research Council, 80–92.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.