Feasibility of the Use of Existing Analytical Models and Experimental Data to Assess Current Design Methods for Pavement Geogrid-Reinforced Base Layers

https://doi.org/10.21949/15181981995PDFTech ReportMT94-08116MT94-08116GeogridsBase course (Pavements)MontanaMontana. Department of TransportationPerkins, Steven W.Montana State University (Bozeman, Mont.). Department of Civil EngineeringMontana. Dept. of TransportationUnited States. Federal Highway AdministrationIn recent years polymer geogrids have been proposed and used to improve the performance of paved roadways and/or to reduce base course thickness. Performance improvements have been demonstrated for design conditions where relatively large rut depths are acceptable and where relatively weak pavement sections have been used. This work was undertaken to examine existing literature concerning laboratory and field experimental studies, and analytical studies pertaining to the inclusion of geogrid polymer materials in roadway pavement sections for the purpose of improving performance or to allow for a reduction in the constructed section thicknesses. The original goal of this study was to examine the feasibility of using existing data from laboratory or field studies and existing finite element models to validate and calibrate the model and then use the model to predict the response of pavement sections not included in the experimental studies. This study has indicated that this approach is feasible and has been accomplished by a previous project. Furthermore, the literature reviewed in this study has shown conflicting results pertaining to the level of improvement that is realized by inclusion of a geogrid in the base course layer of a pavement section. While additional laboratory and analytical studies may aid in resolving these conflicts it is concluded that the most productive approach at this point is to construct well-instrumented, full-scale field sections to assess improvement levels. These sections should be designed and constructed to include variables identified in previous studies as having the greatest impact on pavement performance.88