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Water Damage Resistance of Tuff Asphalt Mixtures with Admixtures Based on Surface Energy Theory

Author(s):





Medium: journal article
Language(s): English
Published in: Buildings, , n. 12, v. 13
Page(s): 3105
DOI: 10.3390/buildings13123105
Abstract:

At present, tuff aggregates as asphalt pavement mixtures have insufficient water damage resistance; hence, modifying and evaluating the related properties of tuff asphalt mixtures are necessary. In this study, cement and a liquid antistripping agent were selected as admixtures, and tuff and limestone mixtures without admixtures were selected as control. The surface energy for the SBS-modified asphalt polymers and aggregates in the mixtures was evaluated by using surface energy theory. The adhesion work and the spalling work of the polymer–aggregate interface was calculated, and a factor k was proposed to predict the water damage resistance of the tuff mixture with admixtures. The prediction values were compared with those of the macroscopic water stability test for the mixture. The results of this research showed that the factor k after adding admixtures was improved, and the increase range was from 7.14% to 47.62%. The admixture scheme with the best improvement was that with 2% cement content, in which the k value increased by 21.57% and 47.62% compared with that of the limestone and tuff mixtures without admixtures, respectively. The tested water stability indexes and the predicted factor k under different admixture schemes exhibited a good positive correlation, and the correlation equations were obtained by linear fitting. Thus, it was feasible to use the factor k characterizing the water damage resistance of tuff mixtures using surface energy theory.

Copyright: © 2023 by the authors; licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10753797
  • Published on:
    14/01/2024
  • Last updated on:
    07/02/2024
 
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