Simplified M-E Approach for the Design of Flexible Pavement Structures

Abaza, Osama · 2007 · Crossref

DOI: 10.35552/anujr.a.21.1.581

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Summary

This paper addresses the limitations of traditional empirical pavement design methods, specifically the AASHTO Guide, which rely on historical data that may not account for modern vehicle characteristics and dynamic loading conditions. The author proposes a simplified mechanistic-empirical (M-E) design procedure for flexible pavement structures. This approach integrates finite element analysis (FEA) with the standard input variables used in AASHTO methodology, aiming to provide a more accurate prediction of pavement performance while remaining accessible to highway engineers. The study utilizes a three-dimensional finite element model developed using SAP 2000 software. The model consists of three layers: an asphaltic concrete surface, a base/subbase layer, and a subgrade layer represented by spring elements. The analysis incorporates typical material properties, including a modulus of elasticity of 4.14 x 10⁶ kN/m² for the asphalt and variable resilient modulus (Mr) values for the subgrade ranging from 1.22 x 10⁶ to 3.66 x 10⁶ kN/m³. Wheel loads were modeled as an equivalent 18-kip single axle load with a contact pressure of 345 kN/m². The research evaluates both static loading and dynamic behavior by incorporating vehicle speed as a variable. Critical failure criteria were defined by the lateral strain at the bottom of the asphalt layer and the vertical strain at the top of the subgrade. The results demonstrate that the proposed FEA-based model yields Structural Number (SN) values that closely align with traditional AASHTO predictions under static conditions. For ESAL repetitions above 1x10⁶, the percentage difference between the two methods ranges from -6% to 7%, with an average difference of 1.3%. However, the dynamic analysis reveals significant deviations; as vehicle speed increases, the tensile strain at the bottom of the asphalt layer decreases due to the time-dependent behavior of asphalt concrete. Consequently, the required SN drops by up to 30% for practical design speeds compared to static calculations. A multiple regression equation was developed to predict SN based on ESAL, subgrade resilient modulus, and vehicle speed, calibrated against AASHTO standards for static cases. The significance of this research lies in its validation of a simplified M-E approach that bridges the gap between complex mechanistic modeling and practical empirical design. By demonstrating that dynamic vehicle speed substantially reduces pavement strain and required thickness, the study highlights the potential for more efficient pavement designs that account for real-world traffic conditions. The proposed method allows engineers to utilize familiar AASHTO input parameters while benefiting from the improved accuracy of finite element analysis, particularly in scenarios involving varying traffic speeds and modern vehicle configurations.

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