1. Introduction
Warm-mixing technology allows asphalt to reach the viscosity needed for mixing at lower temperatures and, therefore, is able to reduce the mixing temperature by 30–40 °C during the asphalt mixture production, resulting in less energy consumption, better construction convenience, and less aging of the asphalt [
1,
2,
3,
4,
5]. However, problems also arise in that the moisture susceptibility may deteriorate as a consequence of lower mixing and compacting temperatures [
6,
7,
8].
Relative studies have pointed out that the moisture damage of a mixture is attributed to the adhesion failure between asphalt and aggregate and, therefore, researchers have introduced various methods and indicators to characterize the adhesion properties [
9,
10,
11,
12]. Currently, many methods haven been brought out to estimate the moisture susceptibility of asphalt mixtures. For instance, the boiling method indicates the moisture susceptibility by comparing the stripping of the mixed aggregates before and after suffering boiling, but the process takes a long time and is subjective [
13]. Photoelectric colorimetry uses the relationship between the concentration of a substance at a determined wavelength and the absorption effect of light to determine the absorbance of a solution and then calculate the concentration, but the operation is very complex [
14]. Atomic force microscopy (AFM) is able to characterize the adhesive property between asphalt and aggregate in nanoscale, but the sample preparation is demanding [
15]. As for surface free energy (SFE), there is no need for specimen compaction and the adhesive between the asphalt and aggregates can be simply calculated by testing the SFE parameters. Therefore, SFE obtains more attention in present studies on the moisture resistance of asphalt mixtures [
16].
Elphingstone introduced SFE to asphalt mixture research for the first time to study the interfacial cracking prediction in hot-mix asphalt (HMA) mixtures [
17]. Cheng measured the SFE indexes of different asphalts and aggregates and calculated the cohesion work of asphalt and the adhesion work of the asphalt–aggregate interface. A comparison between the SFE test and conventional moisture susceptibility tests confirmed the feasibility of SFE indicators to evaluate the moisture susceptibility [
18]. Zhang et al. compared the SFE test result with adhesion grade and TSR obtained from a laboratory test of six different WMAs, and the relevance among them was studied [
19]. Xiao et al. utilized an SFE test on asphalt with different aging degrees and found that the aging process had an adverse influence on moisture susceptibility based on SFE indicators, but also pointed out the limitation of the SFE method in characterizing the impact of the penetrating of asphalt into pores on aggregates [
20]. Alvarez et al. utilized SFE to determine the optimal dose of WMA additives for achieving the best asphalt–aggregate adhesion [
21]. Ali et al. combined both SFE and laboratory tests to investigate the effect of additives as well as aging on the moisture resistance of asphalt mixtures [
22]. Yang et al. analyzed the mechanism of a certain warm-mix additive using an SFE test [
23]. Habal et al. compared the water resistance of a mixture with different warm-mix additives and aggregate–asphalt combinations using SFE and laboratory tests, finding a good relationship between the SFE indicators and performance test results. Furthermore, a threshold was established based on SFE whose accuracy is a favorable 90% [
24,
25].
There are more factors impacting the moisture susceptibility of WMA compared with HMA [
7]. In addition to the commonly accepted factors of HMA, the involvement of warm-mixing additives and the mixing procedure applied also attracted the attention of researchers in terms of their impact on the moisture susceptibility of WMA. Hurley et al. found that the influence of different warm-mixing additives on different aggregates is distinct [
26,
27,
28]. Zaumanis noted that the poor adhesion between asphalt and aggregates may occur due to unevaporated water remaining during some warm-mixing process, thus leading to the negative performance of WMA [
29].
Current research has carried out remarkable investigations into SFE theory and the influencing factors on the moisture susceptibility of WMA. It can still be noticed that few studies concern the influence of moisture content and the mixing process and are therefore unable to precisely estimate the moisture susceptibility of WMA, especially with dry-mix additives. In this research, on the basis of SFE theory, a novel indicator for evaluating the asphalt–aggregate adhesive property with different moisture contents is proposed. Moreover, a three-phase model of aggregate–asphalt-warm mixing additives is introduced and enhanced from the conventional two-phase model by taking the process of dry mixing into consideration. The influence of several factors on the moisture susceptibility is analyzed using the advanced indicator and model put forward in this paper and the freeze–thaw splitting test is applied for the verification of the SFE test.
4. Results and Discussion
The factors affecting the moisture susceptibility of WMA, which are complicated, can be studied by using SFE theory. The characteristics of raw materials, the mixture design, and the mixing temperature will all make a difference [
35]. In this paper, the influence of aggregate type, aggregate moisture content, warm-mix additives, asphalt type, and mixing method on the water stability of WMA are studied utilizing SFE theory.
4.1. Surface Free Energy Components
The test samples and the testing procedures are shown in
Figure 7. The parameters based on surface free energy were calculated after contact angles were measured, and the results are shown in
Table 6.
4.2. The Effect of Aggregate Type
In order to explore the effect of aggregate type on the water stability of WMA, the adhesion parameters of basalt, granite, and limestone with agent A modified base asphalt were calculated and are shown in
Figure 8. The TSR test values of corresponding mixtures were prepared and tested for verification. The mixture gradation was AC-20. Results are shown in
Table 7.
It can be seen from the viewpoint of adhesion indicators that the type of aggregate had a significant influence on the asphalt–aggregate adhesion. The ranking result was limestone > basalt > granite ordered by Was, Wasw, as well as ER. The ranking of TSR results shows favorable consistency with the adhesion indicators.
4.3. The Effect of Aggregate Moisture Content
None of the existing adhesion indicators consider the effect of aggregate moisture content. Calculation models of adhesion work, with and without moisture, respectively, simulate conditions of no water and adequate water. In this paper, the effective adhesion work is proposed based on the moisture content of aggregate in the mixtures. The physical meaning of effective adhesion is the value of the surface energy change on a unit area of the aggregate after adhesion among water, asphalt, and aggregate. The value is positively correlated with asphalt content and adhesion work without moisture, and negatively correlated with moisture content and adhesion work with moisture, as shown in Equation (13). The larger the effective adhesion work, the better the adhesion between asphalt and aggregate.
where
is the effective adhesion work, mJ/m
2; ω and P
a represent the aggregate moisture content and asphalt content, respectively, %.
The adhesion work with and without moisture between warm-mixing agent A modified asphalt and different aggregates were calculated, as shown in
Table 8. Analysis of the results shows that for all combinations of asphalts and aggregates, W
asw was less than W
as, meaning that water was more prone to achieve adhesion to aggregate than asphalt. This indicates that the presence of water influenced the adhesion between asphalt and aggregate, thus creating weakened adhesion areas at the interface of asphalt and aggregates, which can result in easier water invasion into the asphalt–aggregate interface and moisture damage.
Meanwhile, specimens using warm-mixing additive agent A and limestone with moisture contents of 0%, 0.01%, 0.4%, and 1.5%, respectively, were prepared for the freeze–thaw splitting test. The mixing temperature was 135 °C, the gradation was AC-13, and the asphalt content was 5.0%. The TSR results and effective adhesion work of mixtures with different moisture contents were summarized and then subjected to linear regression analysis, as shown in
Figure 9.
From the figure, it can be seen that the effective adhesion work decreased significantly as the moisture content of aggregate increased, indicating that the presence of water in the aggregate significantly degraded the adhesion of the asphalt to the aggregate. The TSR values verified this phenomenon. As the moisture content of the aggregate increased, the splitting strength without freeze–thaw cycles decreased slightly, while that with freeze–thaw conditioning decreased sharply, leading to a dramatic decline in TSR.
Linear regression analysis shows that the correlation coefficient between TSR and Was,eff calculated reached 0.95, which means strong correlation. This proves the validity of the effective adhesion work in evaluating the water stability of the WMA.
4.4. The Effect of Warm-Mixing Agent Type
It has been researched that warm-mixing agents have an important effect on the performance of WMA. In this section, the adhesion indicators of different warm-mixing modified base asphalts to limestone are calculated. The results are shown in
Table 9 and
Figure 10.
The ranking based on the calculation of the three adhesion indicators was different. The results ranked by the Was were A > E > D > B > C, while those by the Wasw and ER were D > B > E > A > C. The difference emerged due to the consideration of the effect of moisture. When lacking the consideration of water, agents A and D were able to promote the adhesion as the value announced, while all the agents deteriorated the adhesion when moisture was taken into account as and ER, with oil-based warm-mixing agent D having the least effect.
To verify the above findings, WMA samples using warm-mixing agents A, D, and E were compacted and the TSR test was conducted. The mixture gradation was AC-20, and the aggregate was limestone. Results are shown in
Table 10.
From the view of TSR, all the warm-mixing agents degraded the moisture susceptibility, among which the mixture with agent D was the least affected. The ranking by TSR test result was consistent with the calculation of Wasw and ER. The reason may be the possible introduction of moisture brought by agents A and E. Agent A was a kind of water-soluble solid and, thus, can easily absorb water, while agent E was in the form of an emulsion containing water. Agent D was oil-based, and thus hydrophilic, and would not be a cause for the introduction of water. Overall, all the indicators except came to the consensus that the water stability of WMA with an oil-based warm-mixing agent was better.
4.5. The Effect of Asphalt Type
To investigate the effect of asphalt type on the moisture stability of WMA, the adhesion indicators were calculated based on the SFE parameters of base asphalt, SBS modified asphalt, and limestone aggregates, and the result is shown in
Figure 11. The freeze–thaw splitting test was conducted for verification on the hot mix and warm mix simultaneously with limestone and base asphalt or SBS modified. The warm-mix additive was agent C and the mixing temperature was 30 °C lower than that for HMA. The test result is shown in
Table 11.
It can be inferred from the results that when different warm-mix additives were applied to different asphalts, the adhesion properties between asphalt and aggregate were distinct. In other words, there was compatibility between asphalt and warm-mix agents. From the calculation result of ER, agent D was the best among the five agents for base asphalt, while agent C was the best for SBS modified asphalt. The choice of asphalt can determine the application of warm-mix agents and, therefore, result in distinct performances of WMA mixtures.
In the meantime, when applying different asphalts to warm mixing, the effect on the moisture susceptibility is distinct. To take the combination of asphalt + agent C as an example, the introduction of agent C resulted in an extreme decrease in ER for base asphalt, while the ER for SBS modified asphalt was almost equivalent to that of original asphalt and was much higher than agent C modified base asphalt. This was verified by the TSR result. Also, it is worth noticing that the TSR result for the base asphalt mixture was consistent with ER value, which both showed a sharp decrease, while that of SBS modified asphalt showed a slight enhancement and was not consistent with ER. There may be other more sophisticated mechanisms for the interaction between polymer modified asphalt and warm-mix agent that compensate for the slight decline in SFE parameters.
4.6. The Effect of the Mixing Process
As interpreted above, the conventional two-phase asphalt–aggregate adhesion model is suitable for the wet-mixing method, in which the warm-mixing additives are added into asphalt to modified asphalt first and then mixed with aggregates. When confronted with additives needing the dry-mixing method, the adhesion of asphalt, aggregate, and warm-mixing agent should be characterized using the three-phase model proposed in previous sections. In this article, the adhesion indicator ER of agent E with base asphalt based on two- and three-phase model was calculated and is shown in
Figure 12. Dry-mixing and wet-mixing WMA mixture specimens using AC-13 gradation for the TSR test were prepared with agent E, limestone, and base asphalt for validation. The mixing temperature was 135 °C. The freeze–thaw splitting test results are shown in
Table 12.
For different types of aggregates, the ER values of the three-phase model were greater than those of the two-phase model, indicating better adhesion prepared using the dry-mixing method. The TSR result demonstrated the theoretical calculation, with mixtures prepared using the dry-mixing method superior to those using the wet-mixing method. This consistency also indicates that the three-phase model proposed in this paper is effective for predicting the water stability of the WMA prepared with the dry-mixing method.