Authors:
Syed Asif Imran
1
;
Sesh Commuri
2
and
Musharraf Zaman
2
Affiliations:
1
University of Oklahoma, United States
;
2
The University of Oklahoma, United States
Keyword(s):
Intelligent Compaction, Vibration Analysis, Asphalt Pavements, Roller Dynamics, Construction Engineering.
Related
Ontology
Subjects/Areas/Topics:
Engineering Applications
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Robotics and Automation
;
Signal Processing, Sensors, Systems Modeling and Control
;
System Modeling
Abstract:
The quality and longevity of an asphalt pavement is influenced by several factors including, the design of the mix and environmental factors at the time of compaction. These factors are difficult to control during the construction process and often result in inadequate compaction of the pavement. Intelligent Compaction (IC) technologies address this issue by providing continuous real-time estimation of the compaction level achieved during construction. This information can then be used to address quality issues during construction and improve the overall quality of the pavement. One of the goals of IC is the dynamic adjustment of the compaction effort of the vibratory roller in order to achieve uniform density and stiffness of the pavement. However, complex dynamics of the compaction process and lack of computationally tractable dynamical models hamper the development of such controllers of vibratory rollers. In this study, the interaction between the vibratory roller and the underly
ing pavement is studied. A two-dimensional lumped element model that can replicate the compaction in the field is developed and its parameters are determined using the visco-elastic plastic properties and the shear deformation properties of the asphalt mix. Numerical simulation results show that the model is capable of capturing the coupled vibration dynamics of the asphalt-roller system in both the vertical and longitudinal direction. Comparison of numerical studies with the field compaction data also indicates that the model can be helpful in the development of control algorithms to improve the quality of pavements during their construction.
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