Sensitivity Study of Iowa Flexible Pavements Using Mechanistic-Empirical Pavement Design Guide
Hali̇l Ceylan, Sunghwan Kim, Michael Heitzman, Kasthurirangan Gopalakrishnan
Abstract
Hali̇l Ceylan, Sunghwan Kim, Michael Heitzman, Kasthurirangan Gopalakrishnan
Abstract
In the newly released Mechanistic-Empirical Pavement Design Guide (MEPDG) (1), the coefficients of the distress prediction models were determined through national calibration efforts using the Long-Term Pavement Performance (LTPP). But the LTPP database used to develop the calibrated distress models did not include test sections from Iowa. Thus, there is a need to recalibrate the models, if required, to use them for pavement design and rehabilitation in Iowa. As a first step in this direction, a preliminary sensitivity study was undertaken to assess the comparative effect of design input parameters pertaining to material properties, traffic and climate on performance of two existing flexible pavements in Iowa with relatively thick Asphalt Concrete (AC) layers. A total of 20 individual inputs were evaluated by studying the effect of each input on five different performance measures (longitudinal cracking, alligator cracking, transverse cracking, rutting, and roughness) for each pavement structure resulting in about 200 simulations using the MEPDG. A limited set of runs were also conducted to study the two-way interaction among the input variables (e.g., effect of traffic distribution on performance for varying AC surface thicknesses). The results showed that the predicted longitudinal cracking was influenced by most input parameters. Alligator cracking, roughness, and rutting in unbound layers remained insensitive to most input parameters. There is no input parameter that is sensitive to all the performance measures. Future research will focus on comparing the predicted measures against the recorded pavement distresses in the Iowa DOT’s Pavement Management Information System (PMIS) database.
OpenAlex reports 6 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
In the newly released Mechanistic-Empirical Pavement Design Guide (MEPDG) (1), the coefficients of the distress prediction models were determined through national calibration efforts using the Long-Term Pavement Performance (LTPP). But the LTPP database used to develop the calibrated distress models did not include test sections from Iowa. Thus, there is a need to recalibrate the models, if required, to use them for pavement design and rehabilitation in Iowa. As a first step in this direction, a preliminary sensitivity study was undertaken to assess the comparative effect of design input parameters pertaining to material properties, traffic and climate on performance of two existing flexible pavements in Iowa with relatively thick Asphalt Concrete (AC) layers. A total of 20 individual inputs were evaluated by studying the effect of each input on five different performance measures (longitudinal cracking, alligator cracking, transverse cracking, rutting, and roughness) for each pavement structure resulting in about 200 simulations using the MEPDG. A limited set of runs were also conducted to study the two-way interaction among the input variables (e.g., effect of traffic distribution on performance for varying AC surface thicknesses). The results showed that the predicted longitudinal cracking was influenced by most input parameters. Alligator cracking, roughness, and rutting in unbound layers remained insensitive to most input parameters. There is no input parameter that is sensitive to all the performance measures. Future research will focus on comparing the predicted measures against the recorded pavement distresses in the Iowa DOT’s Pavement Management Information System (PMIS) database.
Key concepts: Rut, Cracking, International Roughness Index, Pavement engineering, Asphalt, Engineering, Asphalt concrete, Pavement management