A Study on Evaluation and Application of Snowmelt Performance of Anti-Icing Asphalt Pavement

applied sciences

Article A Study on Evaluation and Application of Snowmelt Performance of Anti-Icing Asphalt Pavement

Mulian Zheng 1,*, Shujuan Wu 1,2, Chongtao Wang 3, Yifeng Li 4, Zonghui Ma 5 and Lei Peng 6

1 Key Laboratory for Special Area Highway Engineering of Ministry of Education, Chang’an University, Xi’an 710064, China; [email protected] 2 Lanzhou University of Technology, Lanzhou 730050, China 3 First Highway Consultants Co., Ltd., 63 Kejier Road Hi-Tech Industries Development Zone, Xi’an 710075, China; [email protected] 4 Highway Administration Bureau of Rizhao City, 7 Yantai Road, Rizhao 276826, China; [email protected] 5 Highway Administration Bureau of Dezhou City, 1255 Mid Dongfeng Road Decheng District, Dezhou 253006, China; [email protected] 6 Hubei Urban Construction Design Institute Co. Ltd., 1 Longxiang Street, Hanyang District, Wuhan 430051, China; [email protected] * Correspondence: [email protected]; Tel.: +86-29-8233-4846

Academic Editor: Zhanping You Received: 14 April 2017; Accepted: 31 May 2017; Published: 5 June 2017

Abstract: This paper presents a quantitative estimation of anti-icing asphalt mixture snow-melting performance and provides the application guidance for the mixture under study. The regression model of snowmelt quality evolution was established and experimentally verified for different values of snowfall intensity, temperature and blending content of anti-icing filler. The deicing performance of anti-icing asphalt mixtures was evaluated via the impact load tests. The results obtained indicate that the application temperatures of the anti-icing asphalt mixture should exceed −10 ◦C for moderate or light snow conditions and exceed 0 ◦C for heavy or blizzard snow conditions. A linear dependence between the snowmelt quality of anti-icing asphalt mixture and time is observed for all tested values of snowfall intensity and temperature. On the other hand, under the same snowfall intensity conditions, a two- to threefold increase of the melting rate with temperature is observed. The available records for the last 30 years in different regions under study concerning variation ranges of three meteorological factors (namely, the extremely minimum temperature, snowfall intensity and the coldest month’s average temperature), the most suitable temperature for application of anti-icing asphalt pavement was identified for each particular region.

Keywords: anti-icing asphalt pavement; self-snow-melting performance; deicing performance; linear dependence; climate zone

1. Introduction For the past years, the natural environment has experienced a severe deterioration worldwide, with frequent occurrence of extreme weather events, including snow appearance in unusual seasons and locations. Consequently, ice formed by melted and refrozen snow on roads deteriorates their skid resistance, i.e., the force developed when a tire that is prevented from rotating slides along the pavement surface, which makes the motion of vehicles very unsteady, especially during braking or maneuvering [1]. Given this, anti-icing asphalt mixtures have been applied in Switzerland, Austria, the United States, and some other countries for the construction of snow- and ice-melting roads, which are also referred to as self-ice-melting pavements [2–6]. The engineering experience in the United States, Japan, Germany, and some other countries has shown that the trafﬁc accident rate related to

Appl. Sci. 2017, 7, 583; doi:10.3390/app7060583 www.mdpi.com/journal/applsci Appl. Sci. 2017, 7, 583 2 of 22 pavement icing or snowing in winter can be reduced by 91.4% in the case of pavement mixing with the proposed anti-icing filler [7,8]. Thus, snow- and ice-induced traffic congestion can be effectively alleviated to ensure a safer and smoother ride of vehicles. According to the “Evaluation Test Method Manual” sponsored by the US Strategic Highway Research Program, three methods were introduced for testing the deicing performance—ice melting test, ice penetration test and ice undercutting test [9–11]—and these tests have already been improved by some researchers [12–14]. Although the shear, disbandment, and scraping tests have been developed, and these tests have shown a realistic representation of field parameters, their results are not yet standardized [15–18]. Many researchers evaluate the ice-breaking effect of the self-ice-melting pavements by measuring the numerical value of swing, also referred to as British Pendulum Number (BPN), which is widely used for skid resistance assessment [5,19]. When exploring the salt dissolving-out progression in the anti-icing asphalt mixtures, the conductivity test is applied [20]. Japanese scholars developed an experimental vehicle with built-in drums, which can be used to evaluate the effect of tires with different textures and anti-freezing agent on snow- and ice-frozen roads [21]. The Pavement Research Center of Chang’an University, Xi’an, China, has developed a pavement ice-melting simulation tester, which can simulate the ice-melting performance of the snow-melting pavement [22]. Scholars from Harbin Institute of Technology, Harbin, China, developed an adhesion force measurement system, which allows measuring the adhesion between ice and asphalt pavement [23]. In general, some ice-melting tests fail to separate the entire melted portion from the remaining ice. In the studies of salt dissolution, certain problems with the variation range identification arose when the salt dissolving-out amount reached a certain high value. Some experimental tools being applicable only to particular areas, the respective results are reduced to indirect qualitative evaluation of the snow-melting ability. There are scarce data on the climatic zones of anti-icing asphalt mixture application. The respective evaluation techniques either involve the direct observation methods to evaluate the ice-breaking effect or evaluate the melting of self-ice-melting pavements visually and indirectly. The modified ice penetration test, which is used for measuring deicer performance based on the penetration capacity as a function of time, fails to measure the theoretical or extended time of ice penetration capability [24]. Furthermore, the modified ice undercutting test measures the deicer performance based on the undercut area but fails to measure the ice undercutting capability for the theoretical or extended time instants [25]. Given the above, the developed experimental instruments should be able to separate the melted portion from remaining snow and determine the melting quality more accurately, evaluating the relationship between melting quality and time. The anti-freezing performance of anti-icing asphalt mixture can be evaluated by measuring the loading times. Based on the analysis of qualitative changes of snow on the road invoked by the effects of road loads, snow intensity, filler dosage and temperature, this study advances a regression model of the melting quality evolution, verifies the regression model, evaluates the snowmelt performance, identifies the climate zones and provides recommendations on application of self-ice-melting pavements.

2. Materials and Experiment

2.1. Materials

2.1.1. Asphalt and Aggregate Anti-icing asphalt mixtures are primarily used in low-temperature regions, which require a good stability at a low temperature. Hence, Styrene Butadiene Styrene Block Polymer (SBS) modiﬁed asphalt was used in this study, as the main parameters listed in Table1. Appl. Sci. 2017, 7, 583 3 of 22

Table 1. Styrene Butadiene Styrene Block Polymer (SBS) modiﬁed asphalt technology index.

Technical Indicators Measured Values Standard Values Test Method [26] Penetration 25 ◦C (0.1 mm) 57 40–60 T0604 Penetration Index PI 0.125 ≥0 T0604 ◦ Softening point TR&B ( C) 85 ≥60 T0606 Ductility (5 ◦C, 5 cm/min)/cm 23.3 ≥20 T0605 Kinematic viscosity 135 ◦C (Pa·s) 1.12 ≤3 T0625 Flashing point (◦C) 326 ≥230 T0611 Solubility (%) 99.6 ≥99 T0607 Elastic recovery 25 ◦C (%) 88 ≥75 T0662 48 h Thermal storage softening 1.8 ≤2.5 T0661 point difference (◦C) Density (g·cm−3) 1.023 Measured T0603 Quality change (%) 0.04 ≤1.0 T0609 Penetration ratio 25 ◦C (%) 75.9 ≥65 T0604

Chloride ions, the anti-icing ﬁller, will accelerate the peeling of asphalt. To ensure the mixture’s adhesion and the pavement’s performance, the adhesion of asphalt and aggregate is up to level 5 and water absorption of aggregate is less than 1%. The coarse aggregates were the diorites from Shangzhou City in Shaanxi Province, China and the ﬁne aggregates were limestones from Pucheng City in Shaanxi Province, China. The mineral powders were ground limestones provided by Jinghe Stone Factory in Beijing, China. Technical details are shown in Tables2–4.

Table 2. Coarse aggregate test results.

Technical Indicators Measured Values Standard Values Test Method [27] Crushing value (%) 11.9 ≤26 T0316 Abrasion value (%) 10.5 ≤28 T0317 Clay content (%) 0.75 ≤3 T0314 Adhesivity with asphalt Level 5 Above level 4 T0616 9.5–16 mm 2.924 Apparent density (g·cm−3) ≥2.6 T0304 4.75–9.5 mm 2.927 9.5–16 mm 2.898 Gross bulk density (g·cm−3) - T0304 4.75–9.5 mm 2.887 ≥9.5 mm 4.23 ≤15.0 Needle ﬂake content (%) T0312 <9.5 mm 6.40 ≤20.0 9.5–16 mm 0.47 Bibulous rate (%) ≤2.0 T0304 4.75–9.5 mm 0.73

Table 3. Fine aggregate test results.

Technical Indicators Measured Values Standard Values Test Method [27] 2.36–4.75 mm 2.729 Apparent density (g·cm−3) ≥ 2.5 T0328 0–2.36 mm 2.722 2.36–4.75 mm 2.667 Gross bulk density (g·cm−3) - T0304 0–2.36 mm 2.661 Sand equivalent 97 ≥60 T0334 Clay content 1.3 ≤3.0 T0333 Bibulous rate 0.85 - T0330 Appl. Sci. 2017, 7, 583 4 of 22

Table 4. Mineral powder test results. Appl. Sci. 2017, 7, 583 4 of 22

Technical IndicatorsTable 4. Measured Mineral powder Values test results. Standard Values Test Method [27] Apparent relative density (g·cm−3) 2.468 - T0352 Technical Indicators Measured Values Standard Values Test Method [27] Apparent relative density (g·cm0.6 mm−3) 2.468 100.00 - 100 T0352 0.60.3 mm mm 100.00 99.75 100 90–100 Size range (mm) T0351 0.30.15 mm mm 99.75 93.00 90–100 90–100 Size range (mm) T0351 0.150.075 mm mm 93.00 83.50 90–100 75–100 Appearance0.075 mm 83.50 Qualiﬁed 75–100 Non-caking - Appearance Qualified Non-caking - HydrophilicHydrophilic coefficient coefﬁcient 0.74 0.74 <1 <1 T0353 T0353

2.1.2.2.1.2. Anti-Icing Anti-Icing Filler Filler V-260V-260 is the is productthe product of of Switzeand Switzeand Verglimit Verglimit Anti-Icing Road Road Surface Surface Limited Limited Company, Company, Geneva, Geneva, SwitzerlandSwitzerland and Iceguardand Iceguard (IGD) (IGD) is anti-icing is anti-icing developed developed by Chang’anby Chang’an University University of China.of China. The The melting melting points are◦ both 260 °C the major constituent is CaCl2, the salinity contents of IGD and V-260 points are both 260 C the major constituent is CaCl2, the salinity contents of IGD and V-260 are 58.8% are 58.8% and 94.6% respectively, the cost of IGD is 60% as that of V-260, the appearances are both and 94.6% respectively, the cost of IGD is 60% as that of V-260, the appearances are both white granules, white granules, as shown in Figure 1. The specific physical performance indicators are shown in Table as shown5. in Figure1. The speciﬁc physical performance indicators are shown in Table5.

(a) IGD (b) V-260 Figure 1. The particle form of the anti-icing material. Figure 1. The particle form of the anti-icing material. Table 5. Physical performance index. Table 5. Physical performance index. Technical Indicators V-260 IGD Test Method [27] Proportion (g·mL−1) 1.8 2.07 Technical Indicators V-260 IGD Test Method [27] Particle diameter (mm) 0.1–5 0.1–4 −1 ProportionMelting (g·mL point) (°C) 1.8 260 260 2.07 Data from manufacturer ParticleSolution diameter PH (mm) value 0.1–5 11–12 10–11 0.1–4 Melting point (◦C) 260 260 Salt content (%) 94.6 58.8 Data from manufacturer Solution PH value 11–12 10–11 −1 Salt contentApparent (%) density (g·mL ) 94.60.84 0.94 58.8 Apparent density (g·mL−1) <0.6 mm 0.84 72.6 0.944.1 Passing percentage (%) <2.36 mm 2.1 47.7 T0327 <0.6 mm 72.6 4.1 Passing percentage (%) <4.75 mm 100 100 <2.36 mm 2.1 47.7 T0327 2.2. Anti-Icing Asphalt Mixture <4.75 mm 100 100

2.2. Anti-Icing2.2.1. Design Asphalt of Ingredient Mixture Conventional asphalt mixture used AC-13, which is widely used as the wearing course in China, 2.2.1.and Design satisfied of Ingredient the specifications set forth by Chinese Ministry of Transportation (MOT), as shown in ConventionalFigure 2. asphalt mixture used AC-13, which is widely used as the wearing course in China, and satisﬁed the speciﬁcations set forth by Chinese Ministry of Transportation (MOT), as shown in Figure 2. Appl. Sci. 2017, 7, 583 5 of 22

100 graded upper limit gradation median 80 Graded lower limit Synthetic gradation

40 Passing rate/% Passing

0 16 13.2 9.5 4.75 2.36 1.18 0.6 0.3 0.15 0.075 Mesh size/mm Figure 2. Aggregate gradation ﬁgure. Figure 2. Aggregate gradation figure.

With the method of Marshall Marshall design, design, the the void void volume volume was was 3%–6% 3–6% andand thethe physico-mechanicalphysico-mechanical index waswas calculated.calculated. ThroughThrough optimization, optimization, the the asphalt–aggregate asphalt–aggregate ratio ratio was was 4.8% 4.8% and and the the amount amount of mineralof mineral powder powder was was 5 wt 5 %. wt V-260 %. V-260 and IGD and wereIGD addedwere added as additive as additive to conventional to conventional asphalt mixtureasphalt tomixture increase to increase its density, its accountingdensity, accounting for 5 wt %for of 5 thewt asphalt% of the mixture, asphalt andmixtur othere, and parameters other parameters were the samewere asthe those same of as conventional those of conventional asphalt mixture. asphalt The mi experimentalxture. The experimental results are depictedresults are in Tabledepicted6 and in theTable pavement 6 and the performances pavement performa are describednces are in described Table7. in Table 7.

Table 6. Marshall testing results of asphalt mixturemixture added.added.

Void Void Voids in Mineral AggregateAggregate Voids Voids MarshallMarshall Asphalt-AggregateAsphalt-Aggregate Volume Voids in Mineral FlowFlow Value Value Volume Aggregate FilledFilled with with Asphalt StabilityStability RatioRatio (%) (%) （VV） Aggregate (VMA)/% (FL)/mm(FL)/mm (VV)/% (VMA)/% Asphalt(VFA)/% (VFA)/% (MS)/KN(MS)/KN /% Anti-icing asphalt Anti-icing asphalt 4.8 3.0 13.3 77.0 15.48 3.8 mixture with V-260 4.8 3.0 13.3 77.0 15.48 3.8 mixture with V-260 Anti-icingAnti-icing asphalt asphalt 4.8 4.83.0 3.013.4 13.4 80.1 80.1 14.23 14.23 3.4 3.4 mixturemixture with with IGD IGD ConventionalConventional asphalt asphalt 4.8 4.83.1 3.113.5 13.5 73.4 73.4 16.15 16.15 3.6 3.6 mixturemixture StandardStandard values values [28] [28 ] - - 3–6 3–6 >12.5 >12.5 65–75 65–75 ≥8≥8 2–42–4 TestTest method method [26] [26 ] ------T0709 T0709 T0709 T0709

Table 7. Test results of asphalt mixture performance. Table 7. Test results of asphalt mixture performance. Freeze-Thaw Maximum Residual Dynamic Standard Flooding Technical Residual Freeze-ThawSplitting Dynamic MaximumFlexural- Standard Flooding Stability Stability Flying Loss Flying Loss TechnicalIndicators Indicators Stability SplittingStrength StrengthRatio Stability Flexural-TensileTensile Strain Flying Loss Flying Loss (%) (times/mm) (%) (%) (%) Ratio(%) (%) (times/mm) Strain(µε ()µε ) (%) (%) anti-icing asphalt anti-icing asphalt 89.7 87.2 8579 4834 1.6 2.51 mixturemixture with with V- V-260 89.7 87.2 8579 4834 1.6 2.51 anti-icing260 asphalt 90.14 87.8 7969 4257 1.8 2.72 anti-icingmixture asphalt with IGD 90.14 87.8 7969 4257 1.8 2.72 mixtureConventional with IGD asphalt 96.5 92.6 6997 4531 1.69 1.73 Conventionalmixture 96.5 92.6 6997 4531 1.69 1.73 asphaltStandard mixture values [28] 85 80 2800 2500 15 15 Standard values Test method [26]85 T0709 T072980 T07192800 T07152500 T073315 T073315 [28] Test method [26] T0709 T0729 T0719 T0715 T0733 T0733

Appl. Sci. 2017, 7, 583 6 of 22

Asphalt mixture type and asphalt-aggregate ratio are measured as test variables in this section. Many characteristic parameters were measured, such as void volume, aggregate voids filled with asphalt, voids in mineral aggregate, Marshall stability, flow value, residual stability, freeze-thaw splitting strength, dynamic stability, maximum flexural-tensile strain and so on. There are 81 specimens in total. Table7 compares with the water stability, high-temperature stability and low-temperature crack resistance between conventional asphalt mixture and the anti-icing asphalt mixture. It can be observed that the addition of anti-icing filter reduced the mixture’s residual stability and tensile strength ratio and simultaneously enhanced the maximum flexural-tensile strain. The residual stability and freeze-thaw splitting strength ratio of anti-icing asphalt mixture with IGD are slightly larger than anti-icing asphalt mixture with V-260. The reason is that the salt content of IGD is lower than that of V-260, and the salt is soaked in water, the change of void volume of anti-icing asphalt mixture with IGD is relatively small, and it is denser than anti-icing asphalt mixture with V-260.

2.2.2. Determination of Anti-Icing Filler Distribution The asphalt mixture specimens containing 5% of V-260 were made according to the gradation in Section 2.2.1. The cross-sectional image of anti-icing asphalt mixture specimens were obtained by CT scanning technology and then processed by digital image processing technique [29,30]. The anti-icing filler was separated from the asphalt mixture. Taking the Marshall specimen as an example, the images were firstly extracted along both longitudinal and transverse directions, and then equally divided into 12 pieces with equal areas; the number of anti-icing filler points in each piece was counted. The variance of the number was calculated. The uniformity of anti-icing filler distribution in the image can be characterized by Equations (1) and (2):

U = − log(S) (1)

2 ∑12 (x − x) S = i=1 i (2) 12 where U is distribution uniformity value, S is variance, xi is number of anti-icing filler points, and x is average of the number of anti-icing filler points. The calculated distribution uniformity value (U) in Equation (1) represents the uniformity of anti-icing filler distributed in the entire image. A greater value of U reflects more favorable uniformity of the distribution of characteristic points. If U is greater than or equal to −2, the uniformity is good; otherwise, the uniformity is poor [31].

2.2.3. Longitudinal Distribution Evaluation In the course of scanning the Marshall specimen, nine images were evenly extracted in the longitudinal direction at an interval of 10.15 mm. Each image was further divided into 12 equal segments from four directions (vertical, horizontal, 45◦ and 135◦, respectively), and these segments were then referred to as directional image blocks. The anti-icing ﬁller points were labeled in Photoshop CS6. Then, the coordinates were added after image segmentation. Figures3 and4 show the processed results of Image 2 which is the second image in the longitudinal direction. Appl. Sci. 2017, 7, 583 7 of 22 Appl. Sci. 2017, 7, 583 7 of 22 Appl. Sci. 2017, 7, 583 7 of 22

Before image processing After image processing ((a)) Before image processing ((b)) After image processing Figure 3. Image partition. FigureFigure 3. Image 3. Image partition. partition.

9 1 2 5 10 7 6 3 6 11 4 4 8 8 12 Figure 4. Extract scatter. Figure 4. Extract scatter. Figure 4. Extract scatter. InIn FigureFigure 4,4, thethe numbersnumbers ofof anti-icianti-icing filler points in the 12 blocks are 12, 12, 9, 14, 9, 14, 14, 11, 11, 13, 18,In Figureand 5.4 The, the variance numbers S of isis anti-icing 9.81.9.81. TheThe ﬁller U valuevalue points isis equalequal in the toto 12 − blocks0.99 (more are 12, than 12, − 9,2), 14, representing 9, 14, 14, 11, a 11, great13, uniformity 18, and 5. The in the variance longitudinalS is 9.81. direction. The U value is equal to −0.99 (more than −2), representing a great uniformityThe statistical in the results longitudinal of the remainin direction.g images are described in Table 8. The statistical results of the remaining images are described in Table8. Table 8. Calculation results of longitudinal uniformity. Table 8. Calculation results of longitudinal uniformity. Table 8. Calculation results ofRegion longitudinal uniformity. Number Region Number 1 2 3 4 5 6 7 8 9 10 11 12 Variance Uniformity 1 2 3 4 5 6 7 8 9 10 11 12 Variance Uniformity 1 7 6 6 6 1 10 9 5 Region 3 10 8 4 7.02 −0.85 Number1 7 6 6 6 1 10 9 5 3 10 8 4 7.02 −0.85 3 1 23 22 2 16 3 17 4 27 513 618 7 19 8 29 919 1010 1120 12 26.58 Variance − Uniformity1.42 3 23 22 16 17 27 13 18 19 29 19 10 20 26.58 −1.42 4 21 23 15 16 28 16 14 16 25 21 16 12 22.08 −1.34 41 721 23 6 15 6 16 6 28 116 1014 9 16 5 25 321 1016 812 4 22.08 7.02 −1.34− 0.85 5 23 23 17 18 24 21 18 18 21 25 16 19 8.19 −0.91 53 23 23 2223 17 16 18 17 24 27 21 1318 18 18 19 21 2925 1916 1019 20 8.19 26.58 −0.91− 1.42 6 22 23 18 17 17 24 19 20 21 22 21 16 6.17 −0.79 64 21 22 23 18 15 17 16 17 28 24 1619 14 20 16 21 2522 2121 1616 12 6.17 22.08 −0.79− 1.34 75 23 21 2322 18 17 17 18 25 24 15 2117 18 21 18 26 21 19 2513 1620 19 13.42 8.19 −1.13−0.91 7 21 22 18 17 25 15 17 21 26 19 13 20 13.42 −1.13 86 22 17 2315 11 18 17 17 16 17 17 2412 19 15 20 18 21 11 2213 2118 16 6.33 6.17 −0.80−0.79 8 17 15 11 17 16 17 12 15 18 11 13 18 6.33 −0.80 97 21 14 228 18 8 11 17 12 25 6 1511 17 12 21 13 26 11 197 1310 20 5.69 13.42 −0.75−1.13 98 17 14 158 118 11 17 12 16 6 1711 12 12 15 13 1811 117 1310 18 5.69 6.33 −0.75− 0.80 9 14 8 8 11 12 6 11 12 13 11 7 10 5.69 −0.75 2.2.4. Transverse Distribution Evaluation 2.2.4.Likewise, Transverse in the Distribution transverse Evaluationdirection, the specimen was scanned with Computed Tomography (CT) at an interval of 13.5 mm. Each image was divided into 12 segments for the evaluation of (CT) at Likewise,an interval in theof transverse13.5 mm. direction,Each image the was specimen divided was into scanned 12 segments with Computed for theTomography evaluation of (CT) distribution uniformity. After Image 1 was segmented,ted, anti-icinganti-icing fillerfiller popointsints werewere marked,marked, asas illustratedat an interval in Figures of 13.5 5 mm.and 6. Each image was divided into 12 segments for the evaluation of distribution illustrateduniformity. in Figures After 5 Image and 6. 1 was segmented, anti-icing ﬁller points were marked, as illustrated in Figures5 and6.

Appl. Sci. 2017, 7, 583 8 of 22 Appl. Sci. 2017, 7, 583 8 of 22 Appl. Sci. 2017, 7, 583 8 of 22

((aa)) BeforeBefore imageimage processingprocessing ((bb)) AfterAfter imageimage processingprocessing Figure 5. Image partition. FigureFigure 5. 5. ImageImage partition. partition.

22 55 99 11 10 77 88 10 11 33 44 11 6 6 1212

FigureFigure 66 6... ExtractExtract scatter.scatter.

In Figure 6, the numbers of anti-icing filler points in Segments 1–12 are 22, 29, 19, 14, 28, 21, 15, InIn Figure Figure 66,, the numbers of anti-icing filler ﬁller poin pointsts in Segments 1–12 1–12 are are 22, 22, 29, 29, 19, 19, 14, 14, 28, 28, 21, 21, 15, 15, 20, 26, 25, 20, and 13, respectively. The variance S is 25.83. The U value is equal to −1.41 (more than 20,20, 26, 26, 25, 25, 20, 20, and and 13, 13, respectively. The variance S is 25.83. The U value is equal to −1.411.41 (more (more than than −2), indicating a great uniformity in the transverse direction. The results of the other five images are −−2),2), indicating indicating a agreat great uniformity uniformity in in the the transverse transverse direction. direction. The The results results of of the the other other five ﬁve images images are are shown in Table 9. shownshown in in Table Table 99..

TableTableTable 9.9. CalculationCalculation resultsresults ofof horizontalhorizontal uniformity. uniformity.

RegionRegion NumberNumber Region Number 11 2 2 33 44 55 6 6 7 7 8 8 9 9 10 10 11 11 12 12 Variance Variance UniformityUniformity − 22 1 23 232 2525 3 1818 4 2424 5 2020 6 1919 7 1313 81919 92525 101616 111919 122222 Variance 12.52 12.52 Uniformity−1.101.10 − 233 23 2225 22 22 1822 27 2427 2424 20 1919 19 2525 13 2727 19 2929 25 2828 161616 191717 222121 12.52 17.08 17.08 −1.10−1.231.23 − 344 22 2422 24 28 2728 20 2420 1616 19 2525 25 2222 27 2727 29 1818 28 2424 162424 171919 212323 17.08 12.08 12.08 −1.23−1.081.08 − 455 24 1928 19 15 2015 22 1622 2525 25 2020 22 2121 27 2020 18 2424 24 2323 242222 192020 232525 12.08 7.39 7.39 −1.08−0.870.87 − 566 19 1815 18 25 2225 20 2520 2626 20 1919 21 2020 20 2525 24 2424 23 2121 222626 202121 252121 7.39 7.47 7.47 −0.87−0.870.87 6 18 25 20 26 19 20 25 24 21 26 21 21 7.47 −0.87 TheThe averageaverage longitudinallongitudinal andand transversetransverse uniformityuniformity valuesvalues areare −−0.9990.999 andand −−1.094,1.094, respectively.respectively. BothBoth Theareare more averagemore thanthan longitudinal −−2,2, indicatingindicating and thatthat transverse thethe anti-icinganti-icing uniformity fillerfiller values waswas uniformlyuniformly are −0.999 distributeddistributed and −1.094, inin respectively.thethe asphaltasphalt mixture.mixture.Both are more than −2, indicating that the anti-icing ﬁller was uniformly distributed in the asphaltWhenWhen mixture. thethe anti-icinganti-icing fillerfiller isis uniformlyuniformly distributeddistributed insideinside ofof thethe asphaltasphalt mixture,mixture, thethe salting-outsalting-out isis uniform,uniform,When so theso thethe anti-icing snowsnow meltmelt ﬁller effecteffect is uniformly ofof everyevery part distributedpart ofof thethe pavementpavement inside of theisis consistentconsistent asphalt mixture, andand thethe the asphaltasphalt salting-out mixturemixture is performancesperformancesuniform, so the areare snow lessless affected. meltaffected. effect BecauseBecause of every ofof partthethe uniforunifor of themm pavement salting-out,salting-out, is consistent thethe voidvoid volumevolume and the willwill asphalt notnot increaseincrease mixture sharplyperformancessharply inin certaincertain are parts. lessparts. affected. AsAs aa result,result, Because uniformuniform of the changeschanges uniform ofof salting-out, pavementpavement performancesperformances the void volume cancanwill bebe guaranteed.guaranteed. not increase sharply in certain parts. As a result, uniform changes of pavement performances can be guaranteed.

Appl. Sci. 2017, 7, 583 9 of 22

Appl. Sci. 2017, 7, 583 9 of 22 2.3. Experimental 2.3. Experimental 2.3.1. Evaluation of Self-Snow-Melting Performance 2.3.1. Evaluation of Self-Snow-Melting Performance In this study, using a self-developed experimental device (as shown in Figure7), the effect of theIn load this of study, vehicles using was a simulatedself-developed under experimental different snowfall device intensities(as shown andin Figure different 7), the temperature effect of the for loadquantitatively of vehicles evaluating was simulated the snow-melting under different performance snowfall ofintensities the anti-icing and different asphalt pavement. temperature for quantitatively evaluating the snow-melting performance of the anti-icing asphalt pavement.

FigureFigure 7. 7.MeltingMelting ice-snow ice-snow quality quality measuring measuring device device of self-ice-melting of self-ice-melting pavement: pavement: (1) specimen; (1) specimen; (2) (2) snow; (3) wheel; (4) waterproof material; (5) temperature sensing device; (6) density meter; (7) ﬂoater; snow; (3) wheel; (4) waterproof material; (5) temperature sensing device; (6) density meter; (7) floater; (8) volume measuring device; (9) diversion meter; (10) loading device; (11) external refrigeration system; (8) volume measuring device; (9) diversion meter; (10) loading device; (11) external refrigeration and (12) control system. system; and (12) control system.

2.3.2.2.3.2. Determination Determination of of Snow Snow Amount Amount Generally,Generally, snowfall snowfall intensity intensity can can be be classified classiﬁed into into four four levels: levels: light light snow, snow, moderate moderate snow, snow, heavy heavy snowsnow and and blizzard. blizzard. Taking Taking the the condition condition in in China China as as an an example, example, light light snow snow has has snowfall snowfall of of less less than than 1.01.0 mm mm in in 12 12 h h or or less less than than 2.5 2.5 mm mm in in 24 24 h; moderate snow hashas snowfallsnowfall ofof betweenbetween 1.01.0 and and 3.0 3.0 mm mm in in12 12 h h or or between between 2.5 2.5 and and 5.0 5.0 mm mm in in 24 24 h; h; heavy heavy snow snow has has snowfall snowfall of of between between 3.0 3.0 and and 6.0 6.0 mm mm in 12in h12 or h betweenor between 5.0 and5.0 and 10.0 10.0 mm mm in 24 in h; 24 and h; blizzardand blizzard has snowfallhas snowfall of greater of greater than 6.0than mm 6.0 in mm 12 hin or 12 greater h or 3 2 greaterthan 10.0 than mm 10.0 in mm 24 h.in One24 h. millimeterOne millimeter of snowfall of snowfall means means 0.001 0.001 m of m water3 of water added added over over 1 m 1 ofm2 area. of area.When When using using visibility visibility or the or otherthe other indexes indexes for measuring for measuring snowfall snowfall intensity, intensity, the accumulative the accumulative snow snowthickness thickness within within 12 or 2412 hor can 24 beh acquiredcan be acquired and the correspondingand the corresponding relationships relationships are then established. are then established.The dimensions of the specimen are 100 mm (length) × 100 mm (width) × 50 mm (height). 2 TheThe surface dimensions area S is of 0.01 the m specimen: are 100 mm (length) × 100 mm (width) × 50 mm (height). The 2 surface area S is 0.01 m2: (S = a × b = 0.1 × 0.1 m ). (3) −5 3 Hence, 1 mm of snowfall on the(S specimen = a × b = 0.1 surface × 0.1 correspondsm2). to 10 m : (3)

Hence, 1 mm of snowfall(V = on0.001 the specimen m × S = 0.001surface× 0.1corresponds m3 = 1 × to10 −105 −m5 m3)3: (4) ( = 0.001 m = 0.001 0.1 m =110 m) (4) or 10 g of water; water density is 1.0 g/cm3 and: or 10 g of water; water density is 1.0 g/cm3 and: 1000 kg M = V × ρ = 1 × 10−5 m3 ×1000 kg = 0.01 kg = 10 g (5) = 1 =110 m m3 =0.01kg=10g (5) m 3 InIn other other words, words, the the icing icing layer layer thickness thickness h hisis 1.1 1.1 mm; mm; ice ice density density is is 0.9 0.9 g/cm g/cm3 and:and: / 10/0.9 M/ρ 2 10/0.9 =h = == cmcm == 0.110.11 cm cm == 1.11.1 mm mm (6) (6) S 1101 × 102 The corresponding snow layer thickness H is 15 mm; snow density is 1/15 of water density. The thickness values of icing layer and snow layer in different snowing weathers are depicted in Table 10.

Appl. Sci. 2017, 7, 583 10 of 22

The corresponding snow layer thickness H is 15 mm; snow density is 1/15 of water density. The thickness values of icing layer and snow layer in different snowing weathers are depicted in Table 10.

Table 10. Snowfall scale.

Index Snowfall Intensity Snowfall (mm) Water Quality (g) Ice Thickness (mm) Snow Thickness (mm) Light snow 0.1–2.5 1–25 0.1–2.8 1.5–37.5 Moderate snow 2.5–5.0 25–50 2.8–5.6 37.5–75.0 Heavy snow 5–10 50–100 5.6–11.1 75.0–150.0 Blizzard 10–20 100–200 11.1–22.2 150.0–300.0

2.3.3. Determination of the Freezing Point of Anti-Icing Filler Solutions Calcium chloride and sodium chloride are two main components used in the anti-icing products in China and abroad. Thus, calcium chloride is the main ingredient in both V-260 and IGD. To better compare the freezing points between V-260 and IGD, another anti-icing product—Mafilon (Beijing Mafilon Anti-Icing Technology Limited Company, Beijing, China) (MFL)—is introduced, and it’s main components are silicon dioxide, sodium chloride, calcium chloride and calcium carbonate; among these components, the sodium chloride content is about 55% of the total mass. V-260, IGD, and MFL were separately dissolved in water to prepare 600 mL of solutions (5.0 wt %), and the quality of the anti-icing fillers was 30 g. These solutions were denoted by numbers 2, 3, and 4, while 600 mL water solution, denoted by 1, was adopted as the control group. These solutions were placed into an environmental chamber at a certain temperature. The freezing condition of each solution was observed, and the results are listed in Table 11.

Table 11. Different time and different temperature Salt storage solution freezing conditions.

Temperature Time (h) 1# (water) 2# (V-260) 3# (IGD) 4# (MFL) (◦C) Thin layer of 1 Ice free Ice free Ice free 0 ice Most of the ice, Completely 5 Ice free Ice free with a small −5 frozen amount of water Completely The surface began Appearance 6 Thin layer of ice −7 frozen to have thin ice completely frozen Most of the ice, Completely Appearance Appearance 8 with a small −18 frozen completely frozen completely frozen amount of water Completely Appearance Appearance Appearance 10 −19 frozen completely frozen completely frozen completely frozen

As shown in Table 11, MFL, IGD, and V-260 were completely frozen at −7, −18 and −19 ◦C, respectively, indicating that IGD and V-260 have lower action temperatures and can more effectively prohibit freezing. The reason is that the main component of IGD and V-260 is CaCl2, the MFL is NaCl, and the freezing point of CaCl2 solution is lower than that of NaCl solution at the same concentration. The salt content in V-260 is higher than that in IGD.

2.3.4. Experimental Procedure The mixtures were compacted to a block of the size 300 mm (length) × 300 mm (width) × 50 mm (height). Three groups were independently added with 4%, 5%, and 6% of V-260. The fourth group was the conventional asphalt mixture as reference group. Appl. Sci. 2017, 7, 583 11 of 22

Each specimen was cut into a standard size (100 mm × 100 mm × 50 mm) in a dry state. After the side wall was encapsulated with the waterproof materials, the specimen was placed on a porous plate in the environmental chamber. The specimens were frozen at −15, −10, −5, 0 and 5 ◦C according to the results in Table 11. In order to prevent the effects of environment temperature on experimental results and simulate the pavement’s actual conditions, the specimens were pre-frozen under the corresponding temperatures until the specimens’ surface temperature equaled the temperature of the environmental cabinet. Generally, the pre-freezing time was set within 2–4 h. Based on the snowfall intensity level in Table 10, corresponding quality of water was taken and injected to the specimen container; the water was separately frozen in the environmental cabinet and the ice was made into snowﬂakes by an ice crusher, then the snowﬂakes were evenly spread on the specimen surface. The testing device was started and the specimen was subjected to a load of 0.7 MPa. The values of density meter and volume measurement device are read every 1 h. According to:

M = ρ × V (7)

The quality of melted snow is calculated, and average value is obtained. The mass of melted ice and snow was the dependent variable and time was the independent variable. The test variables are asphalt mixture type, snowfall intensity, temperatures, and (anti-icing ﬁller) content. There are 328 specimens in total. The parameters measured are the time and melting quality of snow.

2.3.5. Evaluation of Deicing Performance Freezing rains and the melted snows refreeze at low temperatures, which will also increase the occurrence of trafﬁc accidents. Anti-icing ﬁller can effectively suppress the freezing of rain and snow water. In this study, the Marshall specimen was not demolded and the edge was sealed with hot asphalt. The specimen was placed in a −20 ◦C environmental chamber. A certain amount of water corresponding to the snowfall intensity was poured on the Marshall specimen. The conventional asphalt mixture was frozen for 10 h as well as asphalt mixture containing 5% of V-260. The frozen specimens were placed on a Marshall Compaction Apparatus, (Chang Sha Ya Xing Digit-Control Limited Company, Changsha, China) and the impact load produced in the hammer’s free fall was calibrated with an impact sensor. The height was adjusted so that the impact load equaled to 100 KN (standard axial load). According to the frequency of the vehicles passing through a section, the impact frequency was 30 times per minute. The number of impact was recorded until the ices over the specimen were completely cleared. The test variable is asphalt mixture type. There are eight specimens. The parameter measured is the frequency of load application.

3. Results and discussion

3.1. Self-Snow-Melting Test

3.1.1. Effect of Snowfall Intensity With the asphalt mixture containing 5% of V-260, the effect of different snowfall intensity on the melting quality of snow at −15, −10, −5, 0, and 5 ◦C is illustrated in Figure8. Appl. Sci. 2017, 7, 583 12 of 22 Appl. Sci. 2017, 7, 583 12 of 22

-15℃ -10℃ 9 35 Blizzard Blizzard 8 Heavy snow 30 Heavy snow Moderate snow Moderate snow 7 Light snow Light snow Conventional asphalt mixture 25 6 Ordinary asphalt mixture

5 20

4 15 3 10 Melting quality of snow/g of quality Melting 2 snow/g of quality Melting 5 1

0 0 1 3 5 7 9 11 13 15 17 19 21 1 3 5 7 9 111315171921 Times/h Times/h (a) effect of snowfall intensity at −15 °C (b) effect of snowfall intensity at −10 °C 0℃ -5℃ 100 Blizzard 90 70 Blizzard Heavy snow Heavy snow 80 Moderate snow 60 Moderate snow Light snow Light snow 70 Conventional asphalt mixture 50 Conventional asphalt mixture 60

40 50

30 40

Melting quality of snow/g of quality Melting 30

Melting quality of snow/g of quality Melting 20 20 10 10

0 0 1 3 5 7 9 11 13 15 17 19 21 135791113 Times/h Times/h (c) effect of snowfall intensity at −5 °C (d) effect of snowfall intensity at 0 °C 5℃ 100 Blizzard 90 Heavy snow 80 Moderate snow Light snow 70 Conventional asphalt mixture 60

30 Meltingquality snow/g of 20

0 123456789 Times/h (e) effect of snowfall intensity at 5 °C

Figure 8. The effect of different snowfall intensity on the melting quality of snow at different Figure 8. The effect of different snowfall intensity on the melting quality of snow at different temperatures. temperatures.

TheThe followingfollowing conclusionsconclusions are are drawn: drawn: 1.1. AtAt thethe five five different different temperatures, temperatures, the the anti-icing anti-icing asphalt asphalt mixture mixture exhibited exhibited a higher a higher snow snow melting efficiencymelting efficiency compared compared with the with conventional the conventional asphalt asphalt mixture. mixture. The reason The reason is that is the that snow the increasedsnow theincreased air humidity, the air whichhumidity, promoted which promoted the precipitation the precipitation of anti-icing of anti-icing filler and filler formed and a formed salt solution. a Thesalt saltsolution. could The be transferredsalt could be from transferred inside thefrom high-concentration inside the high-concentration zone to the zone low-concentration to the low- surface, further promoting the precipitation of anti-icing filler and thereby accelerating the snow melting.

Appl. Sci. 2017, 7, 583 13 of 22 Appl. Sci. 2017, 7, 583 13 of 22

2. Underconcentration the condition surface, of moderatefurther promoting or lightsnow, the pr theecipitation appropriate of anti-icing application filler temperature and thereby of the anti-icingaccelerating asphalt the snow mixture melting. is not less than −10 ◦C. Under the condition of heavy snow or blizzard, 2. Under the condition of moderate or light snow, the appropriate application temperature of the the appropriate application temperature is not less than 0 ◦C, because snow was evidently melted anti-icing asphalt mixture is not less than −10 °C. Under the condition of heavy snow or blizzard, at these temperature ranges. At below 0 and −10 ◦C, respectively, in both cases, snow was rarely the appropriate application temperature is not less than 0 °C, because snow was evidently melted melted. However, the brine solution can lower the adhesion between pavement and ice-snow at these temperature ranges. At below 0 and −10 °C, respectively, in both cases, snow was rarely layer, and the snow-removing efﬁciency can be improved when other snow-removing methods melted. However, the brine solution can lower the adhesion between pavement and ice-snow are applied. layer, and the snow-removing efficiency can be improved when other snow-removing methods are applied. 3.1.2. Effect of the Dosage of Anti-Icing Filler

3.1.2.At Effect−5 ◦ Cof inthe the Dosage environmental of Anti-Icing chamber, Filler when the snowfall intensity was blizzard, heavy snow, moderateAt − snow,5 °C in and the lightenvironmental snow, the chamber, quality of when melted the snow snowfall with intensity the V-260 was addition blizzard, of 4%,heavy 5%, snow, and 6% weremoderate determined, snow, and respectively. light snow, the quality of melted snow with the V-260 addition of 4%, 5%, and 6% Figurewere determined,9 shows the respectively. following results: Figure 9 shows the following results: 1. Compared with the conventional asphalt mixture, the asphalt mixtures with different amounts of 1. V-260Compared addition with all the exhibit conventional an obviously asphalt improved mixture, icethe andasphalt snow mixtures melting with performances. different amounts 2. Atof −V-2605 ◦C, addition the effect all exhibit of the an amount obviously of anti-icing improved fillerice and had snow a minor melting influence performances. on the melting 2. qualityAt −5 °C, of the snow. effect At of− the15, amount−10, 0, of and anti-icing 5 ◦C, the filler results had a of minor these influence effects were on the similar, melting as quality shown in Figuresof snow. 10 At–13 −.15, This −10, can 0, beand attributed 5 °C, the toresults low additionof these e amountsffects were and similar, short as test shown times. in Figures 10–13. This can be attributed to low addition amounts and short test times.

Blizzard Heavy snow 70 25 4% 5% 6% 4% 5% 6% Conventional asphalt mixture 60 Conventional asphalt mixture 21 50 17 40 13 30 9 20 Melting quality snow/g quality Melting Melting quality of snow/g of quality Melting 5 10

1 0 1 3 5 7 9 11 13 15 17 19 21 1 3 5 7 9 111315171921 Times/h Times/h (a) blizzard (b) heavy snow Moderate snow light snow 25 4% 5% 6% 16 4% 5% 6% Conventional asphalt mixture Conventional asphalt mixture 14 20

15 10

8 10 6

4 Melting snow/g quality of Melting quality of snow/g 5 2

0 0 135791113 123456 Times/h Times/h (c) moderate snow (d) light snow

Figure 9. The effect of different dosage of anti-icing filler on the melting quality of snow at different Figure 9. The effect of different dosage of anti-icing ﬁller on the melting quality of snow at different snowfall intensity and −5 °C. snowfall intensity and −5 ◦C.

Appl.Appl. Sci. Sci. 20172017, ,77, ,583 583 1414 of of 22 22 Appl. Sci. 2017, 7, 583 14 of 22

Blizzard Heavy snow 9 Blizzard 6 Heavy snow 9 4%Palatino 5%Linotype 6% 6 4% 5% 6% 8 conventional 4%Palatino asphalt 5%Linotype mixture 6% Conventional 4% asphalt5% mixture 6% 8 conventional asphalt mixture 5 7 5 Conventional asphalt mixture 7 6 4 6 4 5 5 3 4 3 4 3 2 3 2 Melting quality of snow/g 2 snow/g of quality Melting Melting quality of snow/g 2 1 snow/g of quality Melting 1 1 1 0 0 10 3 5 7 9 111315171921 10 3 5 7 9 111315171921 1 3 5 7 9Times/h 111315171921 1 3 5 7 9Times/h 111315171921 (a) blizzardTimes/h (b) heavy snowTimes/h (a) blizzard (b) heavy snow Moderate snow Light snow 5 Moderate snow 5 Light snow 5 4% 5% 6% 5 4% 5% 6% Conventional 4% asphalt5% mixture 6% Conventional 4% asphalt5% mixture 6% 4 Conventional asphalt mixture 4 Conventional asphalt mixture 4 4

3 3 3 3

2 2 2 2 Melting of snow/g quality 1 Melting quality of snow/g 1 Melting of snow/g quality 1 Melting quality of snow/g 1

0 0 1 3 5 7 9 11 13 15 17 19 21 0 10 3 5 7 9 111315171921 1 3 5 7 9 11 13 15 17 19 21 Times/h 1 3 5 7 9Times/ 111315171921h Times/h (c) moderate snow (d) light snowTimes/ h (c) moderate snow (d) light snow Figure 10. The effect of different dosage of anti-icing filler on the melting quality of snow at different FigureFigure 10. 10.The The effect effect of of different different dosage dosage of of anti-icing anti-icing ﬁller filler on on the the melting melting quality quality of of snow snow at at different different snowfall intensity and −15 °C.◦ snowfallsnowfall intensity intensity and and− −1515 °C.C.

Blizzard Heavy snow Blizzard 32 4% 5% 6% Heavy snow 32 32 Conventional 4% asphalt 5% mixture 6% 4% 5% 6% 32 28 Conventional asphalt mixture Conventional 4% asphalt 5% mixture 6% 28 28 Conventional asphalt mixture 28 24 24 24 24 20 20 20 20 16 16 16 16 12 12 12 12 8

Melting qualityof snow/g 8 Melting quality of snow/g 8

Melting qualityof snow/g 8 Melting quality of snow/g 4 4 4 4 0 0 10 3 5 7 9 111315171921 10 3 5 7 9 111315171921 1 3 5 7 9Times/h 111315171921 1 3 5 7 9Times/h 111315171921 Times/h (a) blizzardTimes/h (b) heavy snow (a) blizzard (b) heavy snow

Figure 11. Cont.

Appl. Sci. 2017, 7, 583 15 of 22 Appl. Sci. 2017, 7, 583 15 of 22 Appl. Sci. 2017, 7, 583 15 of 22

Moderate snow Light snow 22 11 Light snow Moderate snow 11 22 4% 5% 6% 20 10 4% 5% 6% 4% 5% 6% 20 Conventional asphalt mixture 10 4% Conventional 5% asphalt 6% mixture 18 Conventional asphalt mixture 9 Conventional asphalt mixture 18 9 16 8 16 8 14 7 14 7 12 6 12 6 10 5 10 5 8 4 8 4 6 3 Melting quality ofsnow/g 6 Melting quality of snow/g 3 4 2 Melting quality ofsnow/g Melting quality of snow/g 4 2 2 1 2 1 0 0 0 1 3 5 7 9 1113151719 0 2 4 6 8 1012141618 1 3 5 7 9 1113151719 Times/h 2 4 6 8Times/h 1012141618 Times/h Times/h (c) moderate snow (d) light snow (c) moderate snow (d) light snow Figure 11. The effect of different dosage of anti-icing filler on the melting quality of snow at different FigureFigure 11. 11. TheThe effect effect of of different different dosage dosage of of anti-icing anti-icing fi ﬁllerller on on the the melting melting quality quality of of snow snow at at different different snowfall intensity and −10 °C.◦ snowfallsnowfall intensity intensity and and −10−10 °C.C. Blizzard Heavy snow 100 Blizzard 70 Heavy snow 100 70 4% 5% 6% 4% 5% 6% 4% Conventional 5% asphalt 6% mixture 60 4% Conventional 5% asphalt 6% mixture 80 Conventional asphalt mixture 60 Conventional asphalt mixture 80 50 50 60 40 60 40

30 40 30 40 20 20 Melting qualitysnow/g of 20 snow/g of quality Melting Melting qualitysnow/g of 20 snow/g of quality Melting 10 10

0 0 0 135791113 0 012345678910 135791113 012345678910 Times/g Times/h Times/g Times/h (a) blizzard (b) heavy snow (a) blizzard (b) heavy snow Moderate snow Light snow 40 Moderate snow 20 40 4% 5% 6% Light snow 4% 5% 6% 20 4% 5% 6% 35 Conventional asphalt mixture Conventional asphalt mixture 4% Conventional 5% asphalt 6% mixture 35 Conventional asphalt mixture 30 15 30 15 25 25 20 10 20 10 15 15 10 5 Melting quality of snow/g 10 snow/g of quality Melting 5 Melting quality of snow/g Melting quality of snow/g of quality Melting 5 5 0 0 0 012345670 0123 012345670123 Times/h Times/h Times/h Times/h (c) moderate snow (d) light snow (c) moderate snow (d) light snow Figure 12. The effect of different dosage of anti-icing filler on the melting quality of snow at different Figure 12. The effect of different dosage of anti-icing filler on the melting quality of snow at different Figuresnowfall 12. intensityThe effect and of 0 different °C. dosage of anti-icing ﬁller on the melting quality of snow at different snowfall intensity and 0 °C. snowfall intensity and 0 ◦C.

Appl. Sci. 2017, 7, 583 16 of 22 Appl.Appl. Sci.Sci. 20172017,, 77,, 583583 1616 ofof 2222

BlizzardBlizzard HeavyHeavy snowsnow 100100 6060 4%4% 5%5% 6%6% 4%4% 5%5% 6%6% 9090 ConventionalConventional asphaltasphalt mixturemixture ConventionalConventional asphaltasphalt mixturemixture 5050 8080

7070 4040 6060

30 5050 30

4040 2020 3030 Melting quality of snow/g Melting quality of snow/g Melting quality of snow/g of quality Melting Melting quality of snow/g of quality Melting 2020 1010 1010 0 00 0 135791234512345 13579 Times/h Times/hTimes/h Times/h ((aa)) blizzardblizzard ((bb)) heavyheavy snowsnow Light snow ModerateModerate snowsnow 20 Light snow 3535 20 4% 5% 6% 4% 5% 6% 1818 Conventional asphalt mixture 3030 Conventional asphalt mixture 1616

2525 1414

1212 2020 1010 4% 5% 6% 1515 8 4% 5% 6% 8 ConventionalConventional asphaltasphalt mixturemixture 66 1010 Melting quality of snow/g Melting quality of snow/g of quality Melting Melting quality of snow/g Melting quality of snow/g of quality Melting 44 55 22

0 00 0 123 123123123 Times/hTimes/h Times/hTimes/h ((cc)) moderatemoderate snowsnow ((dd)) lightlight snowsnow Figure 13. The effect of different dosage of anti-icing filler on the melting quality of snow at different FigureFigure 13. 13. TheThe effect effect of of different different dosage dosage of of anti-icing anti-icing fi ﬁllerller on on the the melting melting quality quality of of snow snow at at different different snowfall intensity and 5 °C. snowfallsnowfall intensity intensity and and 5 5 °C.◦C.

3.1.3. Effect of Temperature 3.1.3.3.1.3. Effect Effect of of Temperature Temperature With the asphalt mixture containing 4% of V-260, the quality of melted snow at different WithWith the the asphalt asphalt mixture mixture containing containing 4% 4% of of V-26 V-260,0, the the quality quality of of melted melted snow snow at at different different temperatures and snowfall intensities was studied, as shown in Figure 14. temperaturestemperatures and and snowfall snowfall intensities intensities was was studied, studied, as as shown shown in in Figure Figure 14.14.

Blizzard Blizzard HeavyHeavy snowsnow -15℃ -10℃ -5℃ 0℃ -15℃ -10℃ -5℃ 0℃ 70 -15-15℃℃ -10℃-10℃ -5℃-5℃ 0℃0℃ 100100 5℃ 70 5℃ ConventionalConventional asphaltasphalt mixturemixture 5℃5℃ ConventionalConventional asphaltasphalt mixturemixture 6060 8080 5050

60 60 4040

3030 4040

2020 Melting quality of snow/g of quality Melting Melting quality of snow/g of Melting quality Melting quality of snow/g of quality Melting 2020 snow/g of Melting quality 1010

00 00 11 3 3 5 5 7 7 9 9 111315171921 111315171921 11 3 3 5 5 7 7 9 9 111315171921 111315171921 Times/hTimes/h Times/hTimes/h ((aa)) blizzardblizzard ((bb)) heavyheavy snowsnow

Figure 14. Cont.

Appl. Sci. 2017, 7, 583 17 of 22 Appl. Sci. 2017, 7, 583 17 of 22

Moderate snow Light snow 40 25 -15℃ -10℃ -5℃ 0℃ -15℃ -10℃ -5℃ 0℃ 35 5℃ Conventional asphalt mixture 5℃ Conventional asphalt mixture 20 30

25 15 20

15 10

10 Melting quality of snow/g Melting qualityof snow/g 5 5

0 0 1 3 5 7 9 11 13 15 17 19 21 1 3 5 7 9 11 13 15 17 19 21 Times/h Times/h (c) moderate snow (d) light snow

Figure 14. The effect of different temperatures on the melting quality of snow at different snowfall intensity. Figure 14. The effect of different temperatures on the melting quality of snow at different snowfall intensity.

It can be observed that moderate snow was melted within 18, 13, 6 and 3 h at −10, −5, 0, and 5 °C, It can be observed that moderate snow was melted within 18, 13, 6 and 3 h at −10, −5, 0, and 5 ◦C, respectively; light snow was melted within 17, 5, 3 and 2 h at −10, −5, 0, and 5 °C, respectively; snow respectively; light snow was melted within 17, 5, 3 and 2 h at −10, −5, 0, and 5 ◦C, respectively; snow from a blizzard was melted within 13 and 5 h at 0 and 5 °C, respectively; and heavy snow was melted from a blizzard was melted within 13 and 5 h at 0 and 5 ◦C, respectively; and heavy snow was melted within 9 and 8 h at 0 and 5 °C, respectively. The melting rate rose with the increase of temperature. within 9 and 8 h at 0 and 5 ◦C, respectively. The melting rate rose with the increase of temperature. Under same snowfall intensity, anti-icing filler spent less time on melting the snows with same Under same snowfall intensity, anti-icing filler spent less time on melting the snows with same masses masses at a higher temperature. It is indicated that the snow-melting effect of anti-icing admixture is at a higher temperature. It is indicated that the snow-melting effect of anti-icing admixture is strongly strongly dependent on temperature. The melting effect is weak at low temperatures. dependent on temperature. The melting effect is weak at low temperatures. 3.1.4. Regression Analysis of Snow Melting Effect 3.1.4. Regression Analysis of Snow Melting Effect The profile in Figure 8 was regressed following the model (y = ax + b, where x is the time; y is the The profile in Figure8 was regressed following the model ( y = ax + b, where x is the time; y is the melting quality of snow with the use of V-260; a and b are coefficients) and the regression formula melting quality of snow with the use of V-260; a and b are coefficients) and the regression formula and and the determination coefficient (R2) are listed in Table 12. The determination coefficients reflect that the determination coefficient (R2) are listed in Table 12. The determination coefficients reflect that the the regression is reliable. regression is reliable.

Table 12. Regression formula between melting quality and times of anti- icing asphalt mixture. Table 12. Regression formula between melting quality and times of anti- icing asphalt mixture. Temp. Blizzard Heavy Snow Moderate Snow Light Snow (°C)Temp. (◦C) Blizzard Heavy Snow Moderate Snow Light Snow Y = 0.3945Y =× 0.3945X − 0.4067× X − 0.4067Y = 0.2481Y = 0.2481 × X − 0.1905× X − 0.1905 Y =Y 0.2016= 0.2016 × X× − X0.1743− 0.1743 Y = 0.1812 0.1812 × XX ++ 0.0119 0.0119 –15− 15 R² = 0.9794R2 = 0.9794 R² = 0.9767R2 = 0.9767 R² =R 20.9896= 0.9896 R²2 == 0.9931 0.9931 Y = 0.9108Y =× 0.9108X +10.981× X +10.981Y = 0.7427Y = 0.7427 × X + 10.24× X + 10.24 Y =Y 0.4408= 0.4408 × X× + X10.496+ 10.496 Y = 0.5728 0.5728 × XX −− 0.29040.2904 –10− 10 R² = 0.9685R2 = 0.9685 R² = 0.8598R2 = 0.8598 R² =R 20.978= 0.978 R²2 == 0.9976 0.9976 Y =3.1771 × X − 0.9438 Y = 0.5817 × X + 12.759 Y = 0.9016 × X + 8.9885 Y = 1.06 × X + 7.66 –5 Y =3.1771 × X − 0.9438 Y = 0.5817 × X + 12.759 Y = 0.9016 × X + 8.9885 Y = 1.06 × X + 7.66 −5 R² = 0.9779R2 = 0.9779 R² = 0.9988R2 = 0.9988 R² =R 20.9248= 0.9248 R²2 == 0.7721 0.7721 Y = 6.5769 × X + 5.4 Y = 4.3533 × X + 17.433 Y = 3.2971 × X + 18.327 Y = 1.06 × X + 7.66 0 Y = 6.5769 × X + 5.4 Y = 4.3533 × X + 17.433 Y = 3.2971 × X + 18.327 Y = 1.06 × X + 7.66 0 R² = 0.9832 R² = 0.9381 R² = 0.8165 R² = 0.7721 R2 = 0.9832 R2 = 0.9381 R2 = 0.8165 R2 = 0.7721 Y = 10.112 × X + 8.8964 Y = 9 × X + 7.66 5 Y = 10.112 × X + 8.8964 Y = 9 × X + 7.66 - - 5 R² = 0.9857 R² = 0.9808 -- R2 = 0.9857 R2 = 0.9808 All the regression results in Table 12 show a significant linear relationship between time and the mass Allof melted the regression snow. On results the other in Table hand, 12 with show the a increase signiﬁcant of temperature, linear relationship the melting between rate time was and2–3 timesthe mass increased of melted under snow. the Onsame the snowfall other hand, intensity. with At the the increase same temperature, of temperature, the the melting melting rate rate varied was slightly2–3 times under increased different under snow the intensities, same snowfall consistent intensity. with the At theresults same in temperature,Section 3.1.1. the melting rate variedMoreover, slightly IGD under was different also selected snow as intensities, the anti-icing consistent filler for with validati theng results the above-described in Section 3.1.1. regression results.Moreover, The experiments IGD was were also cond selecteducted following as the anti-icing the gradation ﬁller in forSection validating 2.2.1 (4.8% the asphalt-aggregate above-described ratio,regression 5.0% mass results. ratio The of IGD experiments to asphalt weremixture, conducted and 5.0% following mineral powder). the gradation The experimental in Section 2.2.1results (4.8% are shownasphalt-aggregate in Figure 15, ratio,and the 5.0% regression mass ratioresults of are IGD shown to asphalt in Equations mixture, (8) and and (9). 5.0% The mineral melting powder).rate also correspondsThe experimental with the results linear are relationsh shown inip, Figure and the 15 melting, and the rate regression of the above results two are temperatures shown in Equations has a nearly (8)

Appl. Sci. 2017, 7, 583 18 of 22 andAppl. (9).Sci. 2017 The, 7 melting, 583 rate also corresponds with the linear relationship, and the melting rate of18 of the 22 above two temperatures has a nearly twofold relationship. Besides, the snow melting performance of twofoldAppl. Sci. relationship. 2017, 7, 583 Besides, the snow melting performance of anti-icing asphalt mixture with18 IGDof 22 is anti-icing asphalt mixture with IGD is approximate to that of anti-icing asphalt mixture with V-260 in approximate to that of anti-icing asphalt mixture with V-260 in a short term. a shorttwofold term. relationship. Besides, the snow melting performance of anti-icing asphalt mixture with IGD is 2 ◦ approximate to that of anti-icingy= =0.9125 0.9125 asphaltx + mixture1.0581 1.0581 (withR = V-260=0.9375 0.9375 in a)( shortat (at− term.−1010 C°C) ) (8)(8) y = =0.5086 0.9125x + 0.5058 1.0581(R 2 = =0.9547 0.9375)( at(at− −1510 ◦°C)C) (8) (9) = 0.5086 0.5058 = 0.9547 (at −15 °C) (9)

= 0.5086 0.5058 = 0.9547 (at −15 °C) (9)

25 -15℃ -10℃ 25 -15 -15℃℃ Fit curve 20 -10-10℃ Fit curve -15℃ Fit curve 20 -10℃ Fit curve 15

10 Melt quality/g Melt 10 Melt quality/g Melt 5 5

0 0 4 8 12 16 20 24 0 4 8 12 16 20 24 times/h times/h Figure 15.15. The effect of asphalt mixture withwith IGDIGD onon thethe meltingmelting qualityquality ofof snowsnow atat blizzard.blizzard. Figure 15. The effect of asphalt mixture with IGD on the melting quality of snow at blizzard. 3.2.3.2. Deicing TestTest 3.2. Deicing Test Deicing test processes of the conventional (left specimen) and anti-icing (right specimen) asphalt DeicingDeicing test test processes processes of of the the conventional conventional (left(left specimen) and and anti-icing anti-icing (right (right specimen) specimen) asphalt asphalt mixturesmixturesmixtures withwith with V-260V-260 V-260 areare are shownshown shown inin in FigureFigure Figure 16 16.16.. DuringDuringDuring thethe the freezingfreezing freezing process,process, process, thethe the anti-icinganti-icing anti-icing ﬁller fillerfiller precipitatedprecipitated from from the thethe inside, inside,inside, and andand thus thusthus the thethe surface surface ofof theofthe the anti-icinganti-icing anti-icing asphaltasphalt asphalt mixturesmixtures mixtures waswas was white. white.white. ByByBy contrast,contrast, the the ice iceice on onon the thethe top toptop of ofof conventional conventionalconventional asphalt asphaltasphalt mixturemixturemixture waswas was nearlynearly nearly transparent.transparent. transparent. AfterAfter After 4646 46 impactimpact impact loads,loads, thethe iceice over overover the thethe anti-icing anti-icinganti-icing asphalt asphaltasphalt surface surfacesurface was waswas completelycompletelycompletely removed, removed, while while the the the ice iceice over over the the the normalnormal normal asphalt asphalt mixturemixture mixture was was was completely completely completely removed removed removed after after after61 61 61impact impact loads. loads. loads. Affected Affected Affected by by bythe the the loads loads loads and and and humidity,humidity, humidity, the the anti-icinganti-icing anti-icing filler filler ﬁller continuously continuously continuously precipitated precipitated precipitated to to toform form a salta a salt salt solution. solution. solution. The The Thefreezing freezing freezing point point point was was hencehence was hence decreased decreased andand a a small andsmall aamou amou smallntnt of amount of ice ice was was of melted, icemelted, was melted,reducingreducing reducing the the adhesion adhesion the adhesion between between between the the specimen specimen the specimen andand ice. Therefore, and ice. Therefore, the the ice ice is is more themore ice easily easily is more to to be be easilyremoved removed to be removedon onthe the anti-icing anti-icing on the anti-icingasphalt asphalt surface, surface, asphalt especially especially surface, especiallywhenwhen subjected when toto subjected impact impact loads. loads. to impact According According loads. to to Accordingdeicing deicing test test to deicingresults,results, testself-ice-melting self-ice-melting results, self-ice-melting pavements pavements pavementsare are recommendabrecommendab are recommendablele whenwhen iceice and and when snow snow ice freeze freeze and snowon on the the freeze pavement pavement on the pavementunderunder a greata undergreat snowfall snowfall a great intensity snowfall intensity intensityat at a a low low temperature attemperature a low temperature since itit cancan since accelerate accelerate it can accelerate the the removal removal the of removal ofice ice and and of icesnow.snow. and snow.

(a) no load applied (b) apply 5 loads (a) no load applied (b) apply 5 loads Figure 16. Cont.

Appl. Sci. 2017, 7, 583 19 of 22 Appl. Sci. 2017, 7, 583 19 of 22

(e) apply 40 loads (f) apply 46 loads

Figure 16. Dropping experiment with different loading times. Figure 16. Dropping experiment with different loading times. 3.3. Climate Zone of the Anti-Icing Asphalt Mixture 3.3. Climate Zone of the Anti-Icing Asphalt Mixture Because the climatic conditions in different regions of the world are very different, the climate zoneBecause of the theanti-icing climatic asphalt conditions pavement in different is presented regions for ensuring of the world that arethe veryanti-ice different, asphalt theroad climate can zoneadapt of theto the anti-icing climate. asphaltFirstly, the pavement extremely is minimu presentedm temperature, for ensuring snowfall that the intensity anti-ice and asphalt the coldest road can adaptmonth’s to the average climate. temperature Firstly, the of extremely a region minimumin the last temperature,30 years should snowfall be considered intensity to and ensure the coldest the month’scontinuous average self-snow temperature effect of of anti-icing a region filler. in the Secondly, last 30 yearsthe high should temperature be considered indicators to ensureand the the continuousrainfall are self-snow considered effect to make of anti-icing anti-ice asphalt filler. Secondly,pavement theperfor highmance temperature to meet the indicators requirements. and the rainfallTaking are China considered as an example to make to introduce anti-ice asphaltthe method pavement of climate performance zone, the climate to meet zone the index requirements. is shown Takingin Table China 13, asthe an climate example zone to boundaries introduce theare methodshown in of Figure climate 17. zone, the climate zone index is shown in TableRegion 13, the 1: climate The area zone with boundaries the extremely are minimu shownm in temperature Figure 17. in the last 30 years between −9 and −21.5Region °C is 1:chilling The area region. with In the this extremely region, the minimum average temperaturetemperature inin thethe lastcoldest 30 yearsmonth between is above− −910 and −21.5°C; in◦C terms is chilling of snowfall region. intensity, In this moderate region, the and average light snows temperature frequently in thefall. coldestBecause month snow can is above be −10melted◦C; in in terms a short of time, snowfall the anti-icing intensity, asphalt moderate mixture and lightis most snows applicable. frequently fall. Because snow can be Region 2: The area with the extremely minimum temperature in the last 30 years between −21 melted in a short time, the anti-icing asphalt mixture is most applicable. and −37 °C is cold region. In this region, the average temperature in the coldest month is above −15 Region 2: The area with the extremely minimum temperature in the last 30 years between −21 and °C. Moderate snowfalls frequently occur while heavy snowfalls occasionally occur. Because of the −37 ◦C is cold region. In this region, the average temperature in the coldest month is above −15 ◦C. variance of temperature, the anti-icing asphalt mixture is also applicable. Moderate snowfalls frequently occur while heavy snowfalls occasionally occur. Because of the variance Region 3: The area with the extremely minimum temperature in the last 30 years above −9 °C is ofwarm temperature, region. theIn this anti-icing region, asphalt the average mixture temper is alsoature applicable. in the coldest month is above 0 °C. Light ◦ snowfallsRegion most 3: The frequently area with occur. the extremelyThe frozen minimumrain or melted temperature snow in some in the regions last30 could years be aboveiced again,−9 C ◦ is warmand hence region. the anti-icing In this region, asphalt the mi averagexture can temperature be paved in some in the special coldest sections month such is above as bridges 0 C. and Light snowfallstunnel entrances. most frequently occur. The frozen rain or melted snow in some regions could be iced again, and henceRegion the 4: anti-icing The area asphaltwith the mixture extremely can mini bemum paved temperature in some special in the sections last 30 years such below as bridges −37 °C and tunnelis severely entrances. cold region. Moderate and heavy snowfalls dominate the snowfalls in this region, and blizzardRegion occasionally 4: The area occur. with The the extremelyanti-icing filler minimum is ineffective temperature for a long in time the last in this 30 yearsregion. below Hence,− the37 ◦ C is severelyanti-icing coldfiller region.is not suitable Moderate in this and region. heavy However, snowfalls the dominate afore-mentioned the snowfalls experiments in this in region, Section and blizzard3.2 proved occasionally that the application occur. The of anti-icing the anti-icing filler filler is ineffective can reduce for the a long adhesion time inbetween this region. pavement Hence, and the anti-icingice-snow. filler Hence, is not anti-icing suitable asphalt in this region.mixtures However, are applicable the afore-mentioned to some special experimentssections such inasSection bridges 3.2 provedand tunnel that theentrances application for accelerating of the anti-icing the removal filler of can ice reduceand snow. the adhesion between pavement and ice-snow. Hence, anti-icing asphalt mixtures are applicable to some special sections such as bridges and tunnel entrances for accelerating the removal of ice and snow.

Appl.Appl. Sci.Sci.2017 2017,,7 7,, 583 583 2020 of of 22 22

FigureFigure 17.17.Climatic Climatic DivisionDivision ofof anti-icinganti-icing asphaltasphaltmixture. mixture.

Table 13. Climatic Division of anti-icing asphalt mixture. Table 13. Climatic Division of anti-icing asphalt mixture. Extreme Minimum Average Climatic Applicable Situation Temperature of 30 Temperature of the Snow Intensity Division Extreme Minimum Average Climatic Years Coldest Month Applicable Situation Temperature of Temperature of Snow Intensity Division 30 Years the Coldest Month Light snow (Mostly) Region 1 Most suitable −9 to −21.5 °C ≥−10 °C Moderate snow Light snow (Mostly) (Occasionally) Region 1 Most suitable −9 to −21.5 ◦C ≥−10 ◦C Moderate snow Light snow and Moderate (Occasionally) Region 2 suitable −21 to −37 °C ≥−15 °C snow (Mostly), Heavy snow Light(Occasionally) snow and Moderate snow (Mostly), Region 2 suitable −21 to −37 ◦C ≥−15 ◦C Light snow, Frozen rain or Heavy snow Region 3 Special section > ≥0 °C snow after melting ice −9 °C (Occasionally) (Occasionally) Special sections ModerateLight snow, snow Frozen and Heavy rain Region 3 Special section >−9 ◦C ≥0 ◦C or snow after melting ice Region 4 combined with other <−37 °C ≤−20 °C snow (Mostly), Blizzard (Occasionally) snow removal methods (Occasionally) Special sections Moderate snow and Region 4 combined with other <−37 ◦C ≤−20 ◦C Heavy snow (Mostly), 4. Conclusions snow removal methods Blizzard (Occasionally) 1. The application temperatures of the anti-icing asphalt mixture should exceed −10 °C for the 4. Conclusionsmoderate or light snow conditions and exceed 0 °C for heavy or blizzard conditions. 1.2. TheA linear application dependence temperatures between ofthe the anti-icing anti-icing asphalt asphalt mixture mixture snowmelt should exceed quality− and10 ◦ Ctime for was the moderateobserved orfor lightall tested snow values conditions of snowfall and exceed intensity 0 ◦C forand heavy temperature. or blizzard On conditions.the other hand, under 2. Athe linear same dependence snowfall intensity between conditions, the anti-icing a two- asphalt to threefold mixture increase snowmelt of qualitythe melting and timerate waswith observedtemperature for was all tested observed. values At of the snowfall same temperature, intensity and only temperature. a slight variation On the otherof the hand, melting under rate thefor different same snowfall snowfall intensity intensities conditions, was observed. a two- to threefold increase of the melting rate with

3. temperatureThe anti-icing was asphalt observed. mixture At the has same the temperature,function of deicing only a slightperformance variation so of that the the melting adhesion rate forbetween different ice snowfalland pavement intensities can be was reduced. observed. 3. TheFour anti-icing regions of asphalt the anti-icing mixture asphalt has the mixture function application of deicing climate performance zone have so thatbeen the identified adhesion as follows:between Region ice 1, and which pavement is denoted can beas reduced.the chilling region, and the extremely minimum temperature range is between −9 and −21.5 °C; Region 2, which is denoted as the cold region, and the extremely minimumFour regions temperature of the range anti-icing is between asphalt − mixture21 and − application37 °C; Region climate 3, which zone haveis denoted been identiﬁedas the warm as follows:region, and Region the 1,extremely which is minimum denoted as temperature the chilling is region, above and −9 °C; the and extremely Region minimum 4, which is temperature denoted as ◦ rangethe severely is between cold− region,9 and −and21.5 theC; extremely Region 2, minimum which is denotedtemperature as the is coldbelow region, −37 °C. and the extremely minimum temperature range is between −21 and −37 ◦C; Region 3, which is denoted as the warm ◦ region,Acknowledgments: and the extremely This research minimum was temperature supported by is abovethe Fundamental−9 C; and Research Region 4,Funds which for is denotedthe Central as ◦ theUniversities severely in cold China region, (No. and310821163502), the extremely the Customize minimum Traffic temperature Science and is below Technology−37 C.Project of Rizhao city in Shandong Province, the Science and Technology Innovation Plan of Shandong Province (Grant No. LU

Appl. Sci. 2017, 7, 583 21 of 22

Acknowledgments: This research was supported by the Fundamental Research Funds for the Central Universities in China (No. 310821163502), the Customize Traffic Science and Technology Project of Rizhao city in Shandong Province, the Science and Technology Innovation Plan of Shandong Province (Grant No. LU Transport Technology [2011] 22), the Science and Technology Project of Tianjin city and the Transportation Science and Technology project of Henan Province (Grant No. 2010P229). Author Contributions: Mulian Zheng was in charge of the whole research plan and paper submission matters. The first author extends gratitude to Shujuan Wu, Chongtao Wang and Lei Peng for performing the experiment and analyzing test data; and Yifeng Li and Zonghui Ma for offering help in doing the experiment. Conflicts of Interest: The authors declare no conflict of interest.

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