Abstract
The new Mechanistic-Empirical Pavement Design Guide (MEPDG) requires a large number of design input parameters. For a design agency, it is rational to focus on data collection of input parameters that are more influential to the design output. Sensitivity analyses help to identify these important input parameters. In the past, both local and global sensitivity analyses have been carried out. Different significance indicators have been used to rank the importance of the design input parameters. However, both local and global sensitivity analyses have limitations. In this study, an example of a regional sensitivity analysis (RSA) conducted on the new MEPDG design software (DARWin-ME) using the Monte Carlo filtering (MCF) method was presented. As demonstrated in this example, the presented RSA method is advantageous in identifying input parameters that are most influential to the designed pavement thickness using the MEPDG.
Original language | American English |
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Title of host publication | Proceedings of the Airfield and Highway Pavement Conference |
DOIs | |
State | Published - Jul 9 2013 |
Disciplines
- Construction Engineering
- Civil Engineering
Keywords
- Filtering method
- M-E flexible pavement design
- Monte Carlo
- Regional sensitivity analysis