ETD RECORD
Development of predictive model to determine the dynamic modulus for hot mix asphalt
Citation
Abu Abdo, Ahmed.. (2008). Development of predictive model to determine the dynamic modulus for hot mix asphalt. Theses and Dissertations Collection, University of Idaho Library Digital Collections. https://www.lib.uidaho.edu/digital/etd/items/etd_333.html
- Title:
- Development of predictive model to determine the dynamic modulus for hot mix asphalt
- Author:
- Abu Abdo, Ahmed.
- Date:
- 2008
- Keywords:
- Asphalt--Mixing Asphalt--Mixing--Computer simulation
- Program:
- Civil Engineering
- Abstract:
- The release of the AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) increased the importance of the dynamic modulus (E*) of asphalt mixes. However, E* evaluation methods such as Super Performance Tester (SPT) were found to be overly sophisticated for mix design and quality control stages. This research addresses the development of a simple and effective prediction model of E*.;To achieve this goal, a wide range of commonly used mixes in the State of Idaho was evaluated, a total of seventeen mixes. Seven additional different field mixes were selected for model validation. Dimensional analysis was used to determine the proposed model general form. Using 408 test data points, a prediction model was developed with a correlation coefficient R{esc}p2{esc}s of 0.962. The model was later verified using the seven additional field mixes. In addition, the proposed model results were compared to the two well-known Witczak's revised 1996 and 2006 models; it was found that the proposed model had better predictions, especially when used in MEPDG as Level-1 input. As a last step of validation, reliability simulation was conducted utilizing the MEPDG permanent deformation prediction models. The reliability of using the proposed model instead measured E* in MEPDG was found to be 95%.;In conclusion, the predicted E* values had a very high correlation with measured E* values. Hence, the model can be utilized in design stage when running MEPDG as Level-1 input instead of laboratory E* data, to eliminate any low performance mixes before conducting sophisticated tests.
- Description:
- Thesis (Ph. D., Civil Engineering)--University of Idaho, November 2008.
- Major Professor:
- Fouod M. Bayomy.
- Defense Date:
- November 2008.
- Type:
- Text
- Format Original:
- xii, 122 leaves :col. ill. ;29 cm.
- Format:
- record
Rights
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- In Copyright - Educational Use Permitted. For more information, please contact University of Idaho Library Special Collections and Archives Department at libspec@uidaho.edu.
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