原文传递
Iowa Calibration of MEPDG Performance Prediction Models, June 2013.
| 题名： | Iowa Calibration of MEPDG Performance Prediction Models, June 2013. |
| 作者： | Ceylan, H.; Gopalakrishnan, K.; Kim, S.; Ma, D. |
| 关键词： | Calibration; Construction Materials; Design; Flexible Pavements; Iowa; Mechanistic-empirical Pavement Design Guide(mepdg); Pavement; Performance Evaluation; Research Projects Design |
| 摘要： | This study aims to improve the accuracy of AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) pavement performance predictions for Iowa pavement systems through local calibration of MEPDG prediction models. A total of 130 representative pavement sites across Iowa were selected. The selected pavement sites represent flexible, rigid, and composite pavement systems throughout Iowa. The required MEPDG inputs and the historical performance data for the selected sites were extracted from a variety of sources. The accuracy of the nationally-calibrated MEPDG prediction models for Iowa conditions was evaluated. The local calibration factors of MEPDG performance prediction models were identified to improve the accuracy of model predictions. The identified local calibration coefficients are presented with other significant findings and recommendations for use in MEPDG/DARWin- ME for Iowa pavement systems. |
| 报告类型： | 科技报告 |
相关文献
- Iowa Calibration of MEPDG Performance Prediction Models, June 2013. Technical Transfer Summary.
- MEPDG Work Plan Task No. 8: Validation of Pavement Performance Curves for the Mechanistic-Empirical Pavement Design Guide.
- Implementation Plan for the New Mechanistic-Empirical Pavement Design Guide.
- Calibration of Rutting Models for Structural and Mix Design. National Cooperative Highway Research Program (NCHRP) Report 719.
- Calibration of Rutting Models for Structural and Mix Design. National Cooperative Highway Research Program (NCHRP) Report 719
- Mechanistic-Empirical Pavement Design Guide Flexible Pavement Performance Prediction Models for Montana. Volume 1. Executive Research Summary.
检索历史
应用推荐
