Development and validation for in situ asphalt mixture density prediction models

Zhen Leng, Imad L. Al-Qadi, Samer Lahouar

Research output: Contribution to journalArticlepeer-review


In situ asphalt mixture density is an important quality property of flexible pavements. A previous study introduced the potential of ground penetrating radar (GPR) to estimate in situ asphalt mixture density continuously, rapidly, and nondestructively. Three density prediction models were developed based on the relationship between the asphaltic mixture volumetric characteristics and the components dielectric constants. In this study, a full-scale test site was carefully designed and constructed for the model validation. Five different mixes were placed in the test site, and each was compacted at four density levels. Both GPR data and cores were collected from the test site to validate the performance of the density models developed in the previous study. The validation results indicated that all three models provided reasonably accurate predictions with errors in the range of 2.22.8%, and the modified Bottcher model (Al-Qadi, Lahouar and Leng (ALL) model) performed the best. In addition, the authors provided the appropriate algorithm for predicting in situ asphalt mixture density through a GPR survey.

Original languageEnglish (US)
Pages (from-to)369-375
Number of pages7
JournalNDT and E International
Issue number4
StatePublished - Jul 2011


  • Asphalt mixture
  • Density
  • Density prediction model
  • Ground penetrating radar

ASJC Scopus subject areas

  • General Materials Science
  • Condensed Matter Physics
  • Mechanical Engineering


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