Mechanistic Design Framework for Evaluating the Potential for Concrete Pavement Growth and Blowup
Publication: Journal of Transportation Engineering, Part B: Pavements
Volume 150, Issue 3
Abstract
Pavement growth (PG) refers to the expansion of the integrated slab length when all the contraction joints of the concrete pavement are close within the expansion joint (EJ). It results from the complex interactions of numerous factors, such as climatic conditions (extremely high temperature and moisture levels), material, and the quantity of incompressible particles infiltrating the pavement joints structure. Currently, the methods and guidelines available for evaluating the annual PG and predictions of concrete pavement blowup are considerably limited. In this study, a mechanistic design framework was developed for estimating the PG and predicting pavement blowup potential. Moreover, a computer tool called Pavement Growth and Blowup Analysis (PGBA) was developed using MATLAB. This tool considers factors such as the pavement configuration, climatic conditions, configuration of EJs, and design reliability. It was used to evaluate the effectiveness of EJs and predict the blowup occurrence times for concrete pavements. To evaluate the PGBA tool, PG data from field measurements conducted by the Maryland DOT were compared with the results obtained using the PGBA tool. The PG predicted by the PGBA tool shows good agreement with the field measurements. However, because concrete pavement blowup data corresponding to PG measurement were not available, a comparison of the PGBA blowup results was not possible. The PGBA tool can be used to predict the service life of EJs and the blowup occurrence time according to the climatic data, pavement structure and materials, joint design, base friction characteristics, and engineering judgment.
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Data Availability Statement
Some of the data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request: specifically, the input and algorithm for coding that generate the results of the proposed methodology.
Acknowledgments
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2021R1A6A1A03044326) and Institute for Disaster Prevention of Gangneung-Wonju National University.
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Information
Published In
Journal of Transportation Engineering, Part B: Pavements
Volume 150 • Issue 3 • September 2024
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Jan 11, 2022
Accepted: Jan 24, 2024
Published online: May 6, 2024
Published in print: Sep 1, 2024
Discussion open until: Oct 6, 2024
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