The global Pavement-mechanistic-empirical (ME) transfer functions have been calibrated using the long-term pavement performance (LTPP) pavement sections at the national level. These functions may need calibration for local conditions for reliable performance predictions. Several calibration studies have been conducted for local conditions, but limited research is available on the impact of calibration on pavement design. This study calibrates and validates the Pavement-ME transfer functions using version 2.6 for Michigan. A total of 256 flexible and 113 rigid sections have been selected based on the performance and availability of Pavement-ME inputs. The authors obtained the Pavement-ME inputs using construction records, plans, job mix formula (JMF), and material testing results. In contrast, the performance data was obtained from the Michigan Department of Transportation (MDOT) pavement management system (PMS) database. The calibrated models were then used for pavement design to estimate the impact of calibration and for comparison with AASHTO93 designs. The paper identifies the controlling distresses for pavement design. A total of 44 new flexible and rigid sections were designed based on the newly calibrated coefficients. The results show a significant improvement in performance prediction after local calibration. A comparison between AASHTO93 and Pavement-ME designs showed a reduction in hot-mix asphalt (HMA) and plain cement concrete (PCC) slab thicknesses for the latter approach. On average, the surface thicknesses using locally calibrated coefficients were thinner by 0.22 in. (0.56 cm) and 0.44 in. (1.12 cm) for flexible and rigid pavements, respectively. Critical design distresses for flexible pavements include bottom-up and thermal cracking. Conversely, transverse cracking and international roughness index (IRI) control the designs for rigid sections. Evaluating the impact of locally calibrated models on pavement designs is essential to obtaining practical and cost-effective design thickness.
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Singh et al. (2024) studied this question.
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