Speaker
Mustaque Hossain
(Kansas State University, Manhattan, KS 66506, USA)
Description
Abstract. The AASHTOWare mechanistic-empirical pavement design (PMED) is a state-of-the-art new and rehabilitation project design proce-dure that accounts for local environmental conditions, highway materials, and actual highway traffic distribution using axle load spectra. The distress prediction models must be calibrated for a particular state or region to apply this procedure precisely. However, generating input data for calibration is one of the most challenging aspects of the calibration process. This paper describes the input data collection process for PMED calibration for reha-bilitated pavements in Kansas, a midwestern state in the United States.
Co-authors
Nat Velasquez
(Kansas Department of Transportation, Topeka, KS 66611, USA)
Shuvo Islam
(AgileAssets, Austin, TX 78746, USA)
