Long‐Term Performance and Deicing Effect of Sustained‐Release Snow Melting Asphalt Mixture

Abstract

To accelerate snow and ice melting, traditional chloride-based salts are spreaded on asphalt pavement surface, causing serious environmental pollution and infrastructure corrosion. For sustained-release snow melting asphalt mixture, the snow melting agent of Mafilon is directly added to asphalt mixture by replacing partial mineral powder to develop a new type of functional asphalt mixture. In this paper, through the Marshall test, immersion Marshall test, rutting test, trabecular bending test, and Cantabro test, the effects of Mafilon addition on asphalt pavement performance is systematically analysed. Meanwhile, salt precipitation rate is measured by conductimetry to estimate effective deicing period of the pavement. Finally, a new experimental device is designed to quantitatively evaluate snow melting effect of sustained-release snow melting asphalt pavement. The experimental results show that replacing 70% of the mineral powder with Mafilon by volume can achieve satisfactory snow melting effect without affecting usability of asphalt pavement.

Investigation of Long-Term Performance and Deicing Longevity Prediction of Self-Ice-Melting Asphalt Pavement

“…It has been proven that the addition of salt-storage additives reduces pavement performance, particularly in terms of water stability [ 12 , 13 , 14 , 15 ]. Furthermore, the long-term high-temperature performance, low-temperature performance, and water stability of self-ice-melting asphalt pavements deteriorate with the continuous precipitation of salt during soaking treatment [ 12 , 16 , 17 ]. Fortunately, the negative impact of salt-storage additives on the pavement performance of asphalt mixtures can be mitigated by adding 0.3% polyester fiber to mixtures [ 14 , 16 ].…”

“…Furthermore, the long-term high-temperature performance, low-temperature performance, and water stability of self-ice-melting asphalt pavements deteriorate with the continuous precipitation of salt during soaking treatment [ 12 , 16 , 17 ]. Fortunately, the negative impact of salt-storage additives on the pavement performance of asphalt mixtures can be mitigated by adding 0.3% polyester fiber to mixtures [ 14 , 16 ]. The deicing effect of self-ice-melting asphalt pavements depends mainly on the salt precipitation rate, which is mostly influenced by the amount of salt-storage additives [ 18 ].…”

“…For assessment of the deicing longevity of self-ice-melting asphalt pavements, the relationship between salt precipitation and time is obtained mainly by conductivity tests [ 22 ], and a mathematical regression model was developed, given the other influencing factors. Zhou et al [ 16 ] established a simple mathematical model for estimating the effective deicing period using three main factors: the total mass of soluble salt, the rate of salt precipitation, and the average number of local annual precipitation days. Zheng et al [ 23 ] developed an evaluation model by introducing an area conversion coefficient, temperature acceleration coefficient, comprehensive influence coefficient, and climate influence coefficient into the regression model of salt precipitation variation with time.…”

Study on Synthesis and Service Properties of Anticoagulant Ice Microcapsule Coating Material

“…Using the ζ electric potential test method, suitable polymer materials were selected for the interface film to wrap the snow-melting salt and form a microencapsulated structure [30]. After mixing with the emulsified asphalt, the two phases reached thermodynamic equilibrium and formed a stable emulsified asphalt-based snow-melting stock solution [31].…”

Prediction of Anti-Icing Longevity of Asphalt Pavement With Salt-Storage Additive

“…A few studies have reported that the anti-icing longevity of APSSA can be calculated with predictive equations incorporating laboratory experiments (Giuliani et al, 2012;Liu et al, 2014;Ma et al, 2016;Zheng et al, 2016Zheng et al, , 2015Zhong et al, 2018;Zhou et al, 2019). However, these estimations were overly simplified, rough, and inaccurate because of lack of a first-principles-based or mechanistic model.…”