Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Development of a Regional Pavement Performance Database for the AASHTO (American Association of State Highway and Transportation Officials) Mechnistic-Empirical Pavement Design Guide. Part 2. Validations and Local Calibration
This project identified two important calibration factors for a Midwest implementation of the Mechanistic-Empirical Pavement Design Guide (M-E PDG). The calibration factors are for the fatigue damage model in flexible pavements in Wisconsin. Pavement performance data was collected from Michigan, Ohio, Iowa and Wisconsin state transportation agencies using uniform data structures as spreadsheet templates specifically designed to manage the calibration data. Spreadsheets were developed for both flexible and rigid pavements. Calibration factors were derived by minimizing differences between observed and predicted pavement performance. The gathering of data required for calibration is labor intensive because the data resides in various and incongruent data sets. Furthermore, some pavement performance observations include temporary effects of maintenance and those observations must be removed through a tedious data cleaning process. The scope of calibration factors are limited by these data impediments. For each state, the observed and predicted performances are compared for both flexible and rigid pavements. The predicted performance is computed using default and derived calibration factors. The project includes a case study design as an example for quantifying the benefits of the M-E PDG.
Development of a Regional Pavement Performance Database for the AASHTO (American Association of State Highway and Transportation Officials) Mechnistic-Empirical Pavement Design Guide. Part 2. Validations and Local Calibration
This project identified two important calibration factors for a Midwest implementation of the Mechanistic-Empirical Pavement Design Guide (M-E PDG). The calibration factors are for the fatigue damage model in flexible pavements in Wisconsin. Pavement performance data was collected from Michigan, Ohio, Iowa and Wisconsin state transportation agencies using uniform data structures as spreadsheet templates specifically designed to manage the calibration data. Spreadsheets were developed for both flexible and rigid pavements. Calibration factors were derived by minimizing differences between observed and predicted pavement performance. The gathering of data required for calibration is labor intensive because the data resides in various and incongruent data sets. Furthermore, some pavement performance observations include temporary effects of maintenance and those observations must be removed through a tedious data cleaning process. The scope of calibration factors are limited by these data impediments. For each state, the observed and predicted performances are compared for both flexible and rigid pavements. The predicted performance is computed using default and derived calibration factors. The project includes a case study design as an example for quantifying the benefits of the M-E PDG.
Development of a Regional Pavement Performance Database for the AASHTO (American Association of State Highway and Transportation Officials) Mechnistic-Empirical Pavement Design Guide. Part 2. Validations and Local Calibration
M. Kang (Autor:in) / T. M. Adams (Autor:in) / H. Bahia (Autor:in)
2007
89 pages
Report
Keine Angabe
Englisch
Construction Equipment, Materials, & Supplies , Development , Validation , Flexible pavements , Rigid pavements , Benefits , Data collection , Literature review , Case studies , Data sources , Regional pavement performance database , AASHTO mechnistic-empirical pavement design guide , Local calibration , WisPAVE pavement design outputs , Prediction factors , M-E PDG procedure