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Preparation for implementation of the mechanistic-empirical pavement design guide in Michigan, part 3 : local calibration and validation of the pavement-ME performance models.

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  • Abstract:
    The main objective of Part 3 was to locally calibrate and validate the mechanistic-empirical pavement

    design guide (Pavement-ME) performance models to Michigan conditions. The local calibration of the

    performance models in the Pavement-ME is a challenging task, especially due to data limitations. A total

    of 108 and 20 reconstruct flexible and rigid pavement candidate projects, respectively, were selected.

    Similarly, a total of 33 and 8 rehabilitated pavement projects for flexible and rigid pavements, respectively

    were selected for the local calibration. The selection process considered pavement type, age,

    geographical location, and number of condition data collection cycles. The selected set of pavement

    section met the following data requirements (a) adequate number of sections for each performance

    model, (b) a wide range of inputs related to traffic, climate, design and material characterization, (c) a

    reasonable extent and occurrence of observed condition data over time. The national calibrated

    performance models were evaluated by using the data for the selected pavement sections. The results

    showed that the global models in the Pavement-ME don’t adequately predict pavement performance for

    Michigan conditions. Therefore, local calibration of the models is essential. The local calibrations for all

    performance prediction models for flexible and rigid pavements were performed for multiple datasets

    (reconstruct, rehabilitation and a combination of both) and using robust statistical techniques (e.g.

    repeated split sampling and bootstrapping). The results of local calibration and validation of various

    models show that the locally calibrated model significantly improve the performance predictions for

    Michigan conditions. The local calibration coefficients for all performance models are documented in the

    report. The report also includes the recommendations on the most appropriate calibration coefficients for

    each of the performance models in Michigan along with the future guidelines and data needs.

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