Modification of the Hirsch dynamic modulus prediction model for asphalt mixtures

Cheng Zhang, Shihui Shen, Xiaoyun Jia

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

The dynamic modulus of an asphalt mixture plays a crucial role in pavement design and performance prediction of asphalt pavement. Among many predictive models, the semiempirical Hirsch model is one of the most popularly used dynamic modulus prediction models. However, the current Hirsch model uses several model constants that were determined based on a number of assumptions and simplifications for conventional asphalt mixtures. Considering the trend of using new types of asphalt mixtures and the potential application of the modulus properties in fundamental pavement performance analysis, those constants may not be appropriate any longer. This paper aims to modify the current Hirsch model by generalizing the model parameters based on the rule of mixtures and the theory of elasticity and viscoelasticity. Twenty-six asphalt mixtures, which contain different percentages of reclaimed asphalt pavement (RAP), sourced from China and the United States were used in this study to evaluate the predictive quality of the modified Hirsch model compared with other models. The modified Hirsch model produced the best predictive quality among three models. In addition, the modified model was suitable for predicting the dynamic modulus of high RAP mixtures. Future work was recommended to validate the proposed model using a larger database.

Original languageEnglish (US)
Article number04017241
JournalJournal of Materials in Civil Engineering
Volume29
Issue number12
DOIs
StatePublished - Dec 1 2017

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Building and Construction
  • Materials Science(all)
  • Mechanics of Materials

Fingerprint Dive into the research topics of 'Modification of the Hirsch dynamic modulus prediction model for asphalt mixtures'. Together they form a unique fingerprint.

  • Cite this