TECHNICAL PAPERS
Mar 1, 2007

Computational Constitutive Model for Predicting Nonlinear Viscoelastic Damage and Fracture Failure of Asphalt Concrete Mixtures

Publication: International Journal of Geomechanics
Volume 7, Issue 2

Abstract

A computational constitutive model was developed to predict damage and fracture failure of asphalt concrete mixtures. Complex heterogeneity and inelastic mechanical behavior are addressed by the model by using finite-element methods and elastic–viscoelastic constitutive relations. Damage evolution due to progressive cracking is represented by randomly oriented interface fracture, which is governed by a newly developed nonlinear viscoelastic cohesive zone model. Computational simulations demonstrate that damage evolution and failure of asphalt concrete mixtures is dependent on the mechanical properties of the mixture. This approach is suitable for the relative evaluation of asphalt concrete mixtures by simply employing material properties and fracture properties of mixture components rather than by performing expensive laboratory tests recursively, which are typically required for continuum damage mechanics modeling.

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Acknowledgments

The writers would like to acknowledge and are grateful for the asphalt concrete testing data provided by Dr. H. Lee at Sejong University in Korea.

References

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Published In

Go to International Journal of Geomechanics
International Journal of Geomechanics
Volume 7Issue 2March 2007
Pages: 102 - 110

History

Received: Jun 6, 2006
Accepted: Jun 9, 2006
Published online: Mar 1, 2007
Published in print: Mar 2007

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Authors

Affiliations

Yong-Rak Kim, M.ASCE
Assistant Professor, Dept. of Civil Engineering, W351 Nebraska Hall, Univ. of Nebraska, Lincoln, NE 68588-0531 (corresponding author). E-mail: [email protected]
D. H. Allen
Professor, Dept. of Engineering Mechanics, 114 Othmer Hall, Univ. of Nebraska, Lincoln, NE 68588-0642. E-mail: [email protected]
D. N. Little, F.ASCE
Professor, Dept. of Civil Engineering, 601 CE/TTI Building, Texas A&M Univ., College Station, TX 77843-3135. E-mail: [email protected]

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