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Asphalt and Asphalt Mixtures

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Civil Engineering".

Deadline for manuscript submissions: closed (30 November 2023) | Viewed by 3114

Special Issue Editor


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Guest Editor
Highway College, Chang’an University, Xi’an, China
Interests: asphalt; modified bitumen; asphalt mixture; mixture design
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue focuses on the basic characteristics, mi- design methods, performance testing and evaluation of asphalt binder and asphalt mixture. In recent years, with the rapid development of expressways, asphalt pavement is used increasingly widely. With the innovation of new materials and the emergence of new technology, traditional asphalt mixture has been injected with new vitality. People not only pay attention to how to use it, but also pay more attention to its mechanism of action and how to increase its durability. Focusing on advanced new materials and their applications, we accept relevant academic articles from the aspects of technical performance evaluation, mix design, testing techniques and performance evaluation, micro- and macro-analysis, numerical simulation, etc., hoping to promote the development of asphalt and asphalt mixture technology, focusing on its long-term durability and functional characteristics.

Prof. Dr. Peiwen Hao
Guest Editor

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Keywords

  • asphalt binder
  • asphalt mixture
  • performance
  • mixture design methods
  • modified asphalt
  • microscopic analysis
  • modification mechanism
  • test methods
  • numerical simulation
  • MD simulation
  • durability
  • function

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Published Papers (2 papers)

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Research

14 pages, 3097 KiB  
Article
Decay Characteristics of Mechanical Properties of Asphalt Mixtures under Sizeable Wet Temperature Cycle
by Yi-Liang Li, Jian-Guo Wei, Qi-Lin Fu, Li-Duan Zhang and Fan Liu
Appl. Sci. 2023, 13(20), 11210; https://doi.org/10.3390/app132011210 - 12 Oct 2023
Viewed by 973
Abstract
Asphalt mixtures will inevitably be affected by rainwater and the effect of the wet temperature cycle during a pavement’s life span. Especially in coastal areas such as Guangdong and Hainan in China, asphalt pavement is particularly susceptible to the sizeable wet temperature cycle [...] Read more.
Asphalt mixtures will inevitably be affected by rainwater and the effect of the wet temperature cycle during a pavement’s life span. Especially in coastal areas such as Guangdong and Hainan in China, asphalt pavement is particularly susceptible to the sizeable wet temperature cycle formed by the high temperature and sudden temperature drop of rainstorms in summer. For this study, we used a homemade sizeable wet temperature cycle environment simulation device to analyze the decay characteristics and the mechanical properties of asphalt pavements in this environment; modified bending and tensile strength and shear strength tests were used to study the decay patterns of shear strength, bending, and tensile strength, and the stiffness modulus of asphalt mixtures with different air voids and different pavement depths under the action of a sizeable wet temperature cycle. In addition, the Grey correlation method was used to analyze the significance of each influencing factor on the decay of mechanical properties, and mathematical fitting was used to establish the prediction equation of the mechanical properties of asphalt mixtures. The results show that with the increase in the number of sizeable wet temperature cycles, the asphalt mixture’s shear strength, flexural tensile strength, and flexural tensile modulus decrease, the degree of decay increases, and the rate of decay gradually slows down. In the case of the same number of sizeable wet temperature cycles, the degree of decay of the asphalt mixtures gradually decreases with increasing depth or decreasing void ratio. After 100 sizeable wet temperature cycles, the maximum values of the decay of shear strength, modulus of strength, and flexural tensile strength were 22.30%, 23.29%, and 32.01%. The importance of the influence of each factor on the decay of the mechanical properties is as follows: the number of sizeable wet temperature cycles > void rate > depth. The prediction equations of the established mechanical properties have a good prediction effect, and the correlation between predicted values and actual values can be up to 0.925. The prediction equations can effectively predict the mechanical properties of asphalt mixtures with different air voids and depths under the action of sizeable wet temperature cycles. Full article
(This article belongs to the Special Issue Asphalt and Asphalt Mixtures)
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22 pages, 6299 KiB  
Article
Experimental and Machine Learning Approach to Investigate the Mechanical Performance of Asphalt Mixtures with Silica Fume Filler
by Nitin Tiwari, Fabio Rondinella, Neelima Satyam and Nicola Baldo
Appl. Sci. 2023, 13(11), 6664; https://doi.org/10.3390/app13116664 - 30 May 2023
Cited by 1 | Viewed by 1730
Abstract
This study explores the potential in substituting ordinary Portland cement (OPC) with industrial waste silica fume (SF) as a mineral filler in asphalt mixtures (AM) for flexible road pavements. The Marshall and indirect tensile strength tests were used to evaluate the mechanical resistance [...] Read more.
This study explores the potential in substituting ordinary Portland cement (OPC) with industrial waste silica fume (SF) as a mineral filler in asphalt mixtures (AM) for flexible road pavements. The Marshall and indirect tensile strength tests were used to evaluate the mechanical resistance and durability of the AMs for different SF and OPC ratios. To develop predictive models of the key mechanical and volumetric parameters, the experimental data were analyzed using artificial neural networks (ANN) with three different activation functions and leave-one-out cross-validation as a resampling method. The addition of SF resulted in a performance comparable to, or slightly better than, OPC-based mixtures, with a maximum indirect tensile strength of 1044.45 kPa at 5% bitumen content. The ANN modeling was highly successful, partly due to an interpolation-based data augmentation strategy, with a correlation coefficient RCV of 0.9988. Full article
(This article belongs to the Special Issue Asphalt and Asphalt Mixtures)
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