Date of Award

Spring 4-2-2024

Access Type

Thesis - Open Access

Degree Name

Master of Science in Civil Engineering


Civil Engineering

Committee Chair

Ghada Ellithy

First Committee Member

Ashok Gurjar

Second Committee Member

Siddharth Shiladitya Parida

College Dean

Jim Gregory


Geogrids have been used for decades to improve the performance in both paved and unpaved road construction. This research focuses on quantifying the performance and optimizing the design of unpaved roadways using the results from an extensive cyclic triaxial testing program. Twenty-seven cyclic triaxial tests were performed, consisting of unreinforced (control) and reinforced samples using two types of 3D geogrids: Grid1 and Grid2. The samples measured 150 mm in diameter and a height of 300 mm. The tests were run under different loading sequences ranging from 41 kPa to 55 psi (6 psi to 8 psi of confining stress and deviatoric stress from 13.7 kPa to 124 kPa (2 psi to 18 psi). The used frequency of the load cycles was 1 Hz or one per 1 second, where the maximum applied stress occurred in the first 0.2 seconds of the loading cycle, while the contact stress was applied during the following 0.8 seconds. A flexible pavement structure typically consists of an asphalt layer overlying a base course layer placed on top of the natural subgrade. The samples used in the testing program consisted of a lower layer of bentonite clay and sand mix, representing the subgrade material, overlain by an upper layer of aggregate material simulating the base layer. In the reinforced samples, a geogrid layer was positioned between the upper and lower layers to evaluate its impact on the mechanical properties of the pavement structure and its performance. Three California Bearing Ratios (CBR) of the subgrade were tested: 1%, 2%, and 4%; for each CBR value, three base thicknesses were tested: 50 mm, 100 mm, and 200 mm. The effectiveness of geogrid reinforcement in roadway performance improvement was assessed by examining the Resilient Modulus (MR), plastic strain (p) and elastic strain (e) and comparing durability and rutting between reinforced and unreinforced sections. The results showed that reinforced samples experienced up to a 20% increase in resilient modulus (MR over unreinforced ones, indicating enhanced load capacity and resilience. In addition, reinforced samples showed up to 60% lower plastic strain (p), underscoring the role of geogrids in reducing deformation and improving durability. The benefits of reinforcement varied with subgrade strength (CBR values) and base thickness, the lower the CBR and base thickness, the more notable improvements were. Aiming for performance optimization and longevity and using the results from the testing program, Matlab and Python codes were developed to establish a performance-based model for designing unpaved roadways with and without geogrid reinforcement. Validation of the control section design showed consistency of predicted strains between the formulated cyclic composite model and existing methods. The test results were also used to support using geogrids in flexible pavement road design using the AASHTO 93 pavement method by introducing the Reinforcement Improvement Ratio (RIR) and the Layer Coefficient Ratio (LCR). RIR is the ratio between reinforced and unreinforced number of passes in Equivalent Standard Axial Loads (ESALs) at the same stress, and LCR is the layer coefficient of the geogrid-reinforced base layer, which quantifies the geogrid reinforcement's impact on extending pavement life and reducing initial and maintenance cost.