New calibration approach to improve Pavement ME Design thermal cracking prediction: mixture-specific coefficients – the Michigan case study

Abstract

Local calibration of the TCMODEL implemented in the Pavement ME Design software has been challenging for many States. This is primarily due to the nature of its mathematical formulation, which is extremely sensitive to the fracture parameter n and the Performance Grade (PG) of the asphalt binder. By simply changing the low PG by one grade, the TCMODEL can predict from zero cracking to the maximum amount of cracking possible. However, this level of sensitivity is not observed in the field. Since the model itself cannot be modified in the Pavement ME Design software, its sensitivity may be adjusted by using mixture-specific local calibration coefficient (k). This approach seems to overcome the problem of the high sensitivity of the TCMODEL and provides very good predictions. However, estimation of mixture-specific k at the design stage of a road can be difficult. To overcome this difficulty, a practical equation was developed using the Multi-Gene Genetic Programming technique so that mixture-specific k-values can be estimated from the asphalt mixture volumetrics as well as other inputs used in the Pavement ME Design software (e.g. |E*| and Indirect Tensile Strength at −10°C). While the equation itself may only be applicable to Michigan mixtures, the general form of the equation is a good starting point for others to develop similar equations in different regions.

Keywords:

• thermal cracking
• AASHTOWare Pavement ME Design software
• local calibration
• pavement design
• mixture-specific coefficient

Acknowledgements

The Authors would like to thank the Michigan Department of Transportation (MDOT) for the financial support of this study, especially the research advisory panel members including Michael Eacker, Justin Schenkel, Adnan Iftikhar, and Andre Clover for providing necessary data and valuable comments throughout the research study. This publication is disseminated in the interest of information exchange. The Michigan Department of Transportation (hereinafter referred to as MDOT) expressly disclaims any liability, of any kind, or for any reason, that might otherwise arise out of any use of this publication or the information or data provided in the publication. MDOT further disclaims any responsibility for typographical errors or accuracy of the information provided or contained within this information. MDOT makes no warranties or representations whatsoever regarding the quality, content, completeness, suitability, adequacy, sequence, accuracy or timeliness of the information and data provided, or that the contents represent standards, specifications, or regulations.

Additional information

Funding

This work was supported by Michigan Department of Transportation [grant number 2013-0066 Z9].