Research ArticleThe Effect of Morphological Characteristic of CoarseAggregates Measured with Fractal Dimension on AsphaltMixture’s High-Temperature Performance
1School of Highway, Chang’an University, Xi’an, Shaanxi 710064, China2Department of Civil and Environmental Engineering, Michigan Technological University, 1400 Townsend Drive,Houghton, MI 49931-1295, USA
Correspondence should be addressed to Hainian Wang; [email protected]
Received 17 November 2015; Accepted 3 February 2016
The morphological properties of coarse aggregates, such as shape, angularity, and surface texture, have a great influence onthe mechanical performance of asphalt mixtures. This study aims to investigate the effect of coarse aggregate morphologicalproperties on the high-temperature performance of asphalt mixtures. A modified Los Angeles (LA) abrasion test was employedto produce aggregates with various morphological properties by applying abrasion cycles of 0, 200, 400, 600, 800, 1000, and 1200on crushed angular aggregates. Based on a laboratory-developed Morphology Analysis System for Coarse Aggregates (MASCA),the morphological properties of the coarse aggregate particles were quantified using the index of fractal dimension. The high-temperature performances of the dense-graded asphalt mixture (AC-16), gap-graded stone asphalt mixture (SAC-16), and stonemastic asphalt (SMA-16) mixtures containing aggregates with different fractal dimensions were evaluated through the dynamicstability (DS) test and the penetration shear test in laboratory. Good linear correlations between the fractal dimension and high-temperature indexes were obtained for all three types of mixtures. Moreover, the results also indicated that higher coarse aggregateangularity leads to stronger high-temperature shear resistance of asphalt mixtures.
1. Introduction
Asphalt mixture is a multiphase composite material whichconsists of aggregates with gradation as the rigid solid andasphalt as the binder [1].Themechanical properties of asphaltmixtures are influenced by the fractions and properties ofeach phase. Since aggregate occupies the majority of boththe volume (over 80%) and the mass (about 95%) of theasphalt mixture, the physical and mechanical performancesof asphalt mixture are greatly influenced by the geometricmorphology of aggregate particles and themutual interactionamong them.
The morphological characteristics of coarse aggregatesinclude shape, angularity, and surface texture. In compactedasphaltmixtures, the spatial distribution and effective contactbetween stone particles depend on the shape, angularity, andsurface texture of aggregate particles, especially for coarseaggregates (Figure 1). Due to the lower modulus of asphalt
binder at high temperatures, the high-temperature shearstrength of the asphalt mixture is notably contributed toby aggregate interlock, which is mostly influenced by themorphological characteristic of mineral aggregate. Tokyayand Akcaoglu reported that the irregular shape of coarseaggregates may lead to stress concentration in compositematerial, consequently causing the initiation and prop-agation of microcracking, which will finally change themacrostructure and microstructure of materials and lead tothe degradation of the mixture’s overall strength [2]. Thus,the successful quantification of shape, angularity, and surfacetexture is essential in understanding their effects on pavementperformance and selecting aggregates to produce asphaltpavementswith adequate quality tomeet the increasing trafficvolume and loading.
The National Association of Aggregate (NAA) proposedan “uncompacted void content” testing method for aggre-gates, which is included in the specification by the American
Hindawi Publishing CorporationAdvances in Materials Science and EngineeringVolume 2016, Article ID 6264317, 9 pageshttp://dx.doi.org/10.1155/2016/6264317
2 Advances in Materials Science and Engineering
(a) (b)
Angularity
TextureShape
(c)
Figure 1: Illustration of morphological characteristic of aggregates: (a) angular aggregates; (b) subround aggregates; (c) shape characteriza-tion.
Society for Testing and Materials (ASTM) and the AmericanAssociation of State Highway and Transportation Officials(AASHTO) [3]. In addition, ASTM put forward the standard“number of fractured faces” testing method (ASTM D58212006), the “percentage of flat-elongated particles” testingmethod (ASTMD4791), and the standard “shape and textureindicators of aggregate particles” testing method (ASTMD3398), and so forth. Some of these methods were adoptedby AASHTO [4]. However, the current testing methods areempirical and time-consuming in assessing the angularity ofcoarse aggregate. The development of computer science hasmotivated the application of cutting-edge methods such asdigital image processing in the engineering field [5]. Variousdevices and measuring methods were successfully developedfor the morphological characteristic of aggregates based onthe digital image processing technology, such as the computerprograms of Particles Analysis (CPA) [6], Aggregate ImageAnalyzer (UIAIA) [7], Aggregate Imaging System (AIMS)[8], and Fourier Transform Interferometry (FTI) system [9].More objective, simple, and credible testing methods werecontributed by these research results to quantify the aggregateshape features.
Fractal geometry has been known as a modern math-ematical tool to describe the irregular geometric shapesby the French mathematician, Mandelbrot. The degree of
irregularity can be measured by fractal dimension by pro-viding a quantitative index to describe the statistical self-similarity of complex phenomena [10].The fractal dimensionis a quantitative parameter which can describe the complexgraphics of geometric forms and connect the microstructureand the macroperformance of a compound material [11].Therefore, the fractal dimension was employed in this studyto characterize the morphological characteristics of coarseaggregate particles including shape and angularity. Due to thelimitations of the developed system, the surface texture wasnot evaluated in this research.
A uniquemethod was presented in this paper for evaluat-ing the morphological characteristic of the coarse aggregatesand demonstrating their effects on the mechanical perfor-mance. Rutting, which normally occurs at high tempera-tures and under heavy loads, is common distress of asphaltpavement [12].The high-temperature performance of asphaltpavement is primarily influenced by aggregate gradation,asphalt properties, climate conditions, traffic conditions, andaggregate characteristics [13]. While most previous studiesfocused on the first four factors, it is also worthy to investigatethe effect of the coarse aggregate morphological charac-teristics on the high-temperature performance of asphaltmixtures.This paper aims to provide someuseful informationfor highway engineers to improve and optimize the mixture
Advances in Materials Science and Engineering 3
508
711 30–33 r/min
Figure 2: LA abrasion tester.
design by relating the macrostructure of aggregate to theactual performance of the pavement.
2. Materials and Methods
2.1. Aggregate Preparation. Andesite crushed aggregates wereused in this study. The morphological characteristic of theaggregates was modified by the Los Angeles (LA) abrasiontester (Figure 2). The inner diameter and length of theLA abrasion tester’s cylinder are 710 ± 5mm and 510 ±5mm, respectively (ASTM C 131-01). Four different particlesizes of aggregates (16/19mm, 13.2/16mm, 9.5/13.2mm, and4.75/9.5mm) obtained by sieving were washed and thendried in an oven at 105 ± 5∘C to a constant weight. Then,the dried aggregates were abraded for 200, 400, 600, 800,1000, and 1200 cycles, respectively, at 30–33 r/min by theLA abrasion tester without steel balls, as they may easilybreak the aggregates in the abrasion. The edges and cornersof aggregates can be polished by the interaction betweenthe aggregates, also between aggregates and the steel wall.Each sample was sieved again to remove the crumb ofaggregates. Finally, along with aggregates without abrasion,there were 28 types of coarse aggregate samples (4 sizes × 7abrasion cycles) to prepare the asphalt mixtures, which wereclassified by different abrasion cycles and different aggregatesizes.
2.2. Measurement of Fractal Dimension. Several approacheshave been developed to measure the fractal dimension ofaggregate particles, like the slit islandmethod, vertical sectionmethod, secondary electron curve method, and so forth[14]. In this study, the aggregate particles’ fractal dimensionwas measured by the slit island method, which calculatesthe fractal dimension, 𝐷, by utilizing the perimeter, 𝑃, andthe surrounding region’s area, 𝐴, of the enclosed fractalcurve, 𝐶. The aforementioned parameters are illustrated inFigure 3.
2.3. Determination of Fractal Dimension. According todimensional analysis, for the Euclidean length of the fractalcurve, 𝐶, the perimeter of the aggregate particle, 𝑃
𝐸, can be
expressed as
𝑃𝐸
1/𝐷
= 𝑎0𝛿(1−𝐷)/𝐷
𝐴1/2
, (1)
where 𝛿 is the measured size, 𝑎0is a dimensionless constant
called the shape factor, and 𝐴 is the area of the aggregateparticle [15].
Perimeter (P)
Area (A)
Enclosed curve (C)
Perimet
e (C)
Figure 3: Illustration of the parameters for the slit island method.
The fractal dimension,𝐷, can be expressed as
𝐷 =log (𝑃
𝐸/𝛿)
[log 𝑎0+ log (𝐴1/2/𝛿)]
. (2)
The morphological image information of the coarseaggregate particles was obtained by a laboratory-developedMorphology Analysis System for Coarse Aggregates(MASCA), as shown in Figure 4.The symmetric illuminationsystem was used in order to eliminate the occurrence ofparticle shadows in MASCA. A digital camera was installedabove aggregates to obtain the information from the image.The calculated fractal dimension values are not dependenton the resolution of the imaging system if the digitalcamera can get a clear image of the shape and angularityof aggregates. In the MASCA system, the camera’s highestresolution is 4272 ∗ 2848, and it has 12.2 million effectivepixels; in addition, the EF 100mm f/2.8 prime lens wasused. The geometric irregularity of coarse aggregates can bequantized by fractal dimension as the MASCA system canprecisely obtain the shape and angularity. This system can beapplied to easily measure the fractal dimension of 2.36mmaggregate particles. The image was then transferred into thecomputer through a data cable. Based on the digital imagesobtained, 𝑛 perimeter values, 𝑃
𝐸𝑖, and 𝑛 area values, 𝐴
𝑖, to
various measuring sizes, and 𝛿𝑖(𝑖 = 1, 2, . . . , 𝑛) for each
aggregate particle, the samples were then measured using theImage-Pro Plus software. Finally, the fractal dimension, 𝐷,was determined using linear regression between log(𝑃
𝐸𝑖/𝛿𝑖)
and log(𝐴𝑖
1/2
/𝛿𝑖) as 𝐷 and 𝑎
0are constants for a certain
image with values ranging between 1 and 2. The bigger thefractal dimension is, 𝐷, the more angular the aggregate is.The 140 aggregate particles of a certain size for differentabrasion cycles were tested and were randomly taken fromthe corresponding stock pile. Three replicate tests wereconducted to determine their variability. Table 1 presents thefractal dimensions of all the coarse aggregates used in theasphalt mixtures.
2.4. Mixture Materials. To evaluate the effects of the coarseaggregate morphological characteristics on the performance
4 Advances in Materials Science and Engineering
(a) (b)
Figure 4: Illustration of fractal dimensionmeasurement: (a)MorphologyAnalysis System forCoarseAggregates (MASCA) and (b) boundaryidentification of aggregates.
Table 1: Average fractal dimension and coefficient of variation ofaggregates with different abrasion cycles and different sizes.
Abrasion cycles Fractal dimension𝐷/coefficient of variation16/19mm 13.2/16mm 9.5/13.2mm 4.75/9.5mm
of various mixtures, three different aggregate gradations ofasphalt mixture specimens, namely, dense-graded asphaltconcrete (AC-16), gap-graded stone asphalt concrete (SAC-16), and stone mastic asphalt (SMA-16), were fabricated toconduct the dynamic stability (DS) test and penetrationshear test. SAC-16 is the skeleton dense-graded stone asphaltmixture which has a high percentage of coarse aggregateand a low void ratio. The gradation of each mixture type isshown in Figure 5. For all specimens, the effect of the coarseaggregate morphological characteristics on the performanceof the asphalt mixture was investigated by altering abrasioncycles (0, 200, 400, 600, 800, 1000, and 1200) on the coarseaggregate. Unprocessed fine aggregates were taken fromthe construction site from Shiyan City to Tianshui Cityto avoid interference of the fine aggregate morphologicalcharacteristics. A 90 penetration grade SK� pure asphalt wasused to prepare all of the mixtures. A lignin fiber with adensity of 1.48 g/cm3 was added to the SMA-16 mixture. Thebasic properties of the asphalt and aggregates used in thethree mixtures are shown in Tables 2 and 3, respectively.
The optimum asphalt content, determined by the Mar-shall mixture design method, was 4.3%, 4.1%, and 5.8% forAC-16, SAC-16, and SMA-16mixtures, respectively.The sameoptimum asphalt content was used for the same gradingmixture composed of the coarse aggregates with differentnumbers of abrasion cycles. The reason for using the sameoptimum asphalt content in the same grading mixture is toobtain the same asphalt film thickness [15] and to remove theinfluence of asphalt content on the rutting and penetrationshear test results.
Table 2: Technical properties of the asphalt.
Properties Testing method Tested valueSpecific gravity at 25∘C (g/cm3) ASTM D 70 1.032Penetration at 25∘C, 100 g (0.1mm) ASTM D 5 83.5Penetration index (PI) ASTM D 5 −1.29Softening point (∘C) ASTM D 36 47.6Ductility at 25∘C (cm) ASTM D 113 ≥100Flash point (∘C) ASTM D 92 310Mass loss (RTFO, 85min, at 163∘C)(%) ASTM D 6 0.4
0.01 0.1 1 10Sieve size (mm)
AC-16SAC-16SMA-16
0.075 0.15 0.3 0.6 1.18 2.36 4.75 9.5 13.216
190102030405060708090
100
Pass
ing
(%)
Figure 5: Gradation curves of three types of mixtures.
2.5. The Dynamic Stability Test and Penetration Shear Test.Both the dynamic stability (DS) test and the penetrationshear test have been previously used to evaluate the high-temperature performance of asphalt mixtures. In order tounderstand the effects of the morphological characteristicsof coarse aggregates on the high-temperature performanceof asphalt mixtures, both tests were employed in this study.Based on the high-temperature performance test results, arelationship can be established between the coarse aggregatemorphological characteristic and the high-temperature per-formance index of asphalt pavement. The dynamic stability(DS) test and penetration shear test were conducted on
Advances in Materials Science and Engineering 5
Table 3: Technical properties of coarse aggregates.
Properties Technical requirements Tested value Specification usedApparent specific gravity (g/cm3) >2.6 2.746 T0304-2005Crushing value % <15 12.54 T0316-2005Abrasion value % <26 23.3 T0317-2005Water absorption % <2.0 0.52 T0304-2005Soundness % ≤12 10.92 T0314-2000
Figure 6: Internal part illustration for wheel rutting tester.
21 different mixtures comprised of different gradations andcoarse aggregates subjected to different abrasion cycles. Testswere repeatedly conducted on three of the same specimensfor each mixture. The DS test was conducted in accordancewith Standard Test Methods (T0719-2011) of Bitumen andBituminous Mixtures for Highway Engineering. Asphaltmixture slabs (300mm × 300mm × 50mm) were preparedfor the rutting test. The wheel of rutting tester is 200mm(diameter) × 50mm (wide). For the rutting tests, the tem-perature, applied load, and loading rate were set at 60∘C,0.7MPa, and 42 cycles/min, respectively. The internal part ofthe wheel rutting tester is shown in Figure 6. The permanentdeformation value, 𝑑
1, was recorded at 45 minutes of rolling,
and then the second permanent deformation value, 𝑑2, was
recorded at 60 minutes of rolling. The dynamic stability wasrepresented by the number of rolls while adding 1mm ofdeformation [16]. The expression is shown as follows:
DS = 630𝑑2− 𝑑1
, (3)
where DS is the dynamic stability.The penetration shear test was conducted by the universal
material testing device (MTS-810), as shown in Figure 7.The test’s principle is that the circular steel head pressurewas carried out on the specimen with a certain loading rateto simulate actual stress states of pavement structure. Themaximum shear stress obtained by the penetration shearmethod can reflect the high-temperature shear performanceof asphalt mixture. Before running the test, the specimens(101mm (diameter) × 63.5mm (height)) were conditioned
Table 4: Basic parameters of shear strength of the 100mm ×63.5mm specimen.
Poisson’s ratio 𝜎1
𝜎2
𝜏max
Parameter value 0.35 0.757 0.0686 0.344
Figure 7: Penetration shear test device.
for 6 hours at a temperature of 60∘C. A load was appliedwith a rate of 1mm/min. The penetration pressure head’ssize is set to 28.5mm in order to simulate the actual stresscondition in pavement. As basic parameters of shear strength,the main stress values at 1MPa head pressure were acquiredby the three-dimensional finite element method [17]. Thetesting parameter values are summarized in Table 4. Basedon the parameters, the maximum shear stress was calculatedconsidering the test penetration pressure. The relationshipbetween the maximum shear stress and penetration pressurecan be obtained as follows:
𝑆 = 𝜏max𝑃, (4)
where 𝑆 is the maximum shear stress and 𝑃 is the penetrationpressure.
3. Results and Discussions
3.1. Results of Dynamic Stability Test and Penetration ShearTest. As shown in Figure 8, the dynamic stability, which is thehigh-temperature performance indicator, decreased with theincrease in abrasion cycles, indicating that themorphologicalcharacteristic of coarse aggregates is an important factor
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AC SAC SMAGradation
0 cycles200 cycles400 cycles600 cycles
800 cycles1000 cycles1200 cycles
0
500
1000
1500
2000
2500
3000
Dyn
amic
stab
ility
(tim
e/m
m)
Figure 8: Rutting test results for AC-16, SMA-16, and SAC-16.
AC SAC SMAGradation
0.40.50.60.70.80.91.01.11.21.31.41.5
Max
imum
shea
r stre
ss (M
Pa)
0 cycles200 cycles400 cycles600 cycles
800 cycles1000 cycles1200 cycles
Figure 9: Maximum penetration shear test results for AC-16, SMA-16, and SAC-16.
that affects the high-temperature performance. Similarly,Figure 9 shows that the maximum shear stress decreasedwith the increase in abrasion cycles. Shape and angularitycreate greater interlock between particles; in addition, tex-ture develops a strong friction surface among the coarseaggregates, resulting in better stability and shear resistanceof the mixture [18]. The dynamic stability and maximumshear stress of the AC-16 mixture significantly decreasedwhen the abrasion cycles changed from 0 to 600, but thisseems not to be significant when the abrasion time changedfrom 600 to 1200. Unlike the AC-16 mixture, the dynamicstability andmaximum shear stress for the SAC-16 and SMA-16 mixtures decreased continuously when the abrasion timechanged from 0 to 1200.
This is because the morphological characteristic of coarseaggregate became weaker as abrasion times increase. Inaddition, it can be concluded that the influence of themorphological characteristic of coarse aggregates on therutting resistance of the AC-16 asphalt mixture was very
Table 5: Correlation analysis results between fractal dimensionof coarse aggregates and high-temperature stability of asphaltmixtures.
Mixture type Correlation coefficient (𝑟)16/19mm 13.2/16mm 9.5/13.2mm 4.75/9.5mm
limited when abrasion cycle is above a certain extent, asthe AC-16 asphalt mixture has a small percentage of coarseaggregates, and its antideformation performance at hightemperature is contributed by both the coarse aggregate andthe asphalt mastic (asphalt and fine aggregates). However,the gap-graded mixture (SAC-16, SMA-16) mainly relies oninterlocked skeleton structure formed by coarse aggregate tobear vehicle loading, so that the rutting resistance of SAC-16and SMA-16 mixtures kept reducing with the increase of theabrasion cycle.
3.2. Correlation between Fractal Dimension of Coarse Aggre-gate Particles and High-Temperature Performance Index.Considering the effect of different particle sizes of coarseaggregates on mixture performance, partial correlation anal-ysis was applied by the Statistical Product and Service Solu-tions (SPSS) software, which provides the functions of datamanagement, statistical analysis, chart analysis, and outputmanagement. Partial correlation analysis can eliminate theeffect of different particle sizes so that it can analyze thelinear correlation between different abrasion cycles and thehigh-temperature performance index of asphalt mixturesindependently. Tables 4 and 5 show the correlation betweenthe fractal dimension of coarse aggregate particles withdifferent particle sizes and abrasion cycles and the high-temperature performance index of the asphalt mixtures withdifferent gradations.
As presented in Tables 5 and 6, the fractal dimension ofcoarse aggregate particles correlates well with the dynamicstability and maximum shear stress indexes for AC, SAC,and SMA mixtures. Partial correlation analysis results showthat the fractal dimension is a good index to quantita-tively characterize coarse aggregates geometric morphology,including shape and angularity. The fractal dimension canhelp to improve the high-temperature performance of asphaltpavement in terms of coarse aggregate shape. The fractaldimensions of different sizes of aggregates may have variouseffects on the high-temperature performance (in regard tohigh-temperature stability and maximum shear stress). Forthe AC-16, the fractal dimension of the coarse aggregates
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1.014 1.016 1.018 1.020 1.022 1.024
Linear fit of dynamic stabilityLinear fit of maximum shear stress
0.86
0.88
0.90
0.92
0.94
0.96
0.98
1.00
1.02
1.04
AC m
axim
um sh
ear s
tress
(MPa
)
1000
1200
1400
1600
1800
2000
2200
2400
2600
2800AC
dyn
amic
stab
ility
(tim
e/m
m)
13.2mm fractal dimension
y = −178690.38 + 177145.06x
R2 = 0.99
y = −10.88 + 11.64x
R2 = 0.977
(a)
1.030 1.032 1.034 1.036 1.038 1.0400.90
0.95
1.00
1.05
1.10
1.15
1.20
1.25
1.30
1.35
SAC
max
imum
shea
r stre
ss (M
Pa)
600
800
1000
1200
1400
1600
1800
2000
2200
2400
SAC
dyna
mic
stab
ility
(tim
e/m
m)
Linear fit of dynamic stabilityLinear fit of maximum shear stress
with the size of 13.2/16mm has the strongest correlation withthe high-temperature performance compared to aggregates ofother sizes. For the SAC-16 and SMA-16, the most influentialaggregate size is 4.75/9.5mm.
3.3. Analysis of Regression between Fractal Dimension ofCoarse Aggregate Particles and High-Temperature Perfor-mance Index of Asphalt Mixtures. To further analyze therelationship between the fractal dimension of coarse aggre-gate particles and high-temperature performance of asphaltmixtures, SPSS software was used to make linear regressionto fit the relation between the fractal dimension of coarseaggregate particles with the best correlation and the high-temperature performance index for the three types of asphaltmixtures. The regression results are shown in Figure 10.
Figure 10 shows that the fractal dimension of coarseaggregate particles with the best correlation has a strongcorrelation with the dynamic stability index for the AC,SAC, and SMA asphalt mixtures. The dynamic stability ofthe asphalt mixture decreased with the decrease in fractal
dimension of coarse aggregate particles. In addition, thecorrelation between the fractal dimension of coarse aggregateparticles with the best correlation and maximum shear stressindex is also good for the AC, SAC, and SMA asphaltmixtures. The maximum shear stress of asphalt mixturedecreases with the decrease in the fractal dimension ofcoarse aggregate particles. Because of the decrease in coarseaggregate angularity, the interlocking of asphalt mixture wasweakened, causing a drop in the shear resistance of the asphaltmixture. As trend line in the penetration shear test results isconsistent with that of the rutting test results for all mixtures,the penetration shear test is also a valid method to evaluatethe high-temperature performance of asphalt mixtures. Thefractal dimension of coarse aggregate particles is a usefulindex to quantify the aggregate morphology characteristics(shape, angularity). To regulate the quality of aggregateseffectively and reliably, the fractal dimension values of coarseaggregates are recommended to provide a basis for theproperties of asphalt mixtures in terms of the morphologicalcharacteristics of the aggregate.
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4. Conclusions
The fractal dimension was proposed to characterize themorphological characteristics of coarse aggregate throughthe application of the fractal geometry method. The mainobjective of this study was to study the influence of themorphological characteristics of the coarse aggregates onthe high-temperature performance of the asphalt mixture.To achieve this objective, the dynamic stability test andpenetration shear tests were employed for the purpose ofhigh-temperature performance evaluation.
The dynamic stability and penetration shear test resultsindicate that higher angularity of coarse aggregates leads tostronger permanent deformation resistance for all three typesof asphalt mixtures. However, the effect of the morphologicalcharacteristic of coarse aggregates on the performance ofthe dense-graded asphalt mixture is inconspicuous whenit changes to a certain extent. Compared with the dense-graded asphalt mixture, the morphological characteristicof coarse aggregates affects the performance of gap-gradedmixturesmore strongly due to the higher percentage of coarseaggregates (>70%).
The fractal dimension of coarse aggregate particlesretained on the 13.2mm control sieve correlates best withhigh-temperature performances for the AC-16 mixture, fol-lowed by those retained on 16mm, 9.5mm, and 4.75mmsieve, respectively. For the SAC-16 and SMA-16 mixtures,the fractal dimension of coarse aggregate particles retainedon the 4.75mm control sieve correlates best with high-temperature performances, followed by those retained on9.5mm, 16mm, and 13.2mm sieve, respectively.
Good linear correlations were observed between thefractal dimension and the high-temperature performanceindexes (the dynamic stability and maximum shear stressfrom the DS test and the penetration shear test, resp.).
It is recommended that the impact of the morphologicalcharacteristic of coarse aggregates on the other propertiesof asphalt mixture be investigated. Furthermore, a similarapproach may be applied to analyze the morphological char-acteristic of fine aggregates. Coarse aggregate characteristicswith fractal dimension as a quantified index should becombined with aggregate gradation, asphalt binder prop-erty, and air voids to estimate the performance of asphaltpavement. In addition, it is recommended that the three-dimensional morphological characteristic of aggregates beinvestigated using nondestructive testing equipment, such asX-ray computer tomography.
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper.
Acknowledgments
This research is supported by the research project of theMin-istry of Science and Technology of China (2014BAG05B04),the National Natural Science Foundation of China (NSFC)(no. 51378074), the Fundamental and Applied Research
Project of the Chinese National Transportation Department(2014 319 812 180), and the Special Fund for Basic Sci-entific Research of Central Colleges, Chang’an University(CHD310821153503).
References
[1] Y. Liu, Z. You, Q. Dai, and J. Mills-Beale, “Review of advancesin understanding impacts of mix composition characteristicson asphalt concrete (AC) mechanics,” International Journal ofPavement Engineering, vol. 12, no. 4, pp. 385–405, 2011.
[2] M. Tokyay and T. Akcaoglu, “Determining aggregate size &shape effect on concrete microcracking under compression bymeans of a degree of reversibility method,” in Proceedings of the11th International Conference on Fracture (ICF11 ’05), vol. 2, pp.1357–1362, Turin, Italy, March 2005.
[3] AASHTO, Standard Specifications for Transportation Materialsand Methods of Sampling and Testing, T304, AASHTO Book-store, 2015.
[4] I. Ishai and H. Gellber, “Effect of geometric irregularity ofaggregates on the properties and behavior of asphalt concrete,”Journal of Association of Asphalt Paving Technologists, vol. 51, pp.494–521, 1982.
[5] C. Chandan, K. Sivakumar, T. Fletcher, and E. Masad, “Appli-cation of imaging techniques to geometry analysis of aggregateparticles,” Journal of Computing in Civil Engineering, vol. 18, no.1, pp. 75–82, 2004.
[6] C. Browne, F. A. Rauch, T. C. Haas, and H. Kim, “Com-parison tests of automated equipment for analyzing aggregategradation,” in Proceedings of the 9th Annual Symposium of theInternational Center for Aggregates Research (ICAR ’11), Austin,Tex, USA, 2011.
[7] C. Rao, E. Tutumluer, and I. T. Kim, “Quantification of coarseaggregate angularity based on image analysis,” TransportationResearch Record, no. 1787, pp. 117–124, 2002.
[8] E. Masad, “The development of a computer controlled imageanalysis system for measuring aggregate shape properties,”National Cooperative Highway Research Program NCHRP-IDEA Project 77 Final Report, Transportation Research Board,National Research Council, 2003.
[9] L. Wang, W. Sun, E. M. Lally, and A. Wang, “Application ofLADAR in the analysis of aggregate characteristics,” NationalCooperative Highway Research Program Report 724, Trans-portation Research Board, National Research Council, 2012.
[10] W. D. Fei, W. G. Chu, and D. Z. Yang, “Fractal characteristicof the microstructure in Alnico8,” Journal of Materials ScienceLetters, vol. 19, no. 14, pp. 1221–1223, 2000.
[11] A. G. Kokkalis, G. H. Tsohos, and O. K. Panagouli, “Con-sideration of fractals potential in pavement skid resistanceevaluation,” Journal of Transportation Engineering, vol. 128, no.6, pp. 591–595, 2002.
[12] H. Wang, Y. Bu, D. Wang, and M. Oeser, “3D characterisationof the grain sphericity and angularity with the aid of computedtomography,” Bauingenieur, vol. 90, pp. 436–443, 2015.
[13] J. Zhang, Z. Fan, K. Fang, J. Pei, and L. Xu, “Development andvalidation of nonlinear viscoelastic damage (NLVED) modelfor three-stage permanent deformation of asphalt concrete,”Construction and BuildingMaterials, vol. 102, no. 1, pp. 384–392,2016.
[14] K. Sasajima and T. Tsukada, “Measurement of fractal dimensionfrom surface asperity profile,” International Journal of MachineTools and Manufacture, vol. 32, no. 1-2, pp. 125–127, 1992.
Advances in Materials Science and Engineering 9
[15] A. Topal and B. Sengoz, “Determination of fine aggregateangularity in relation with the resistance to rutting of hot-mixasphalt,” Construction and Building Materials, vol. 19, no. 2, pp.155–163, 2005.
[16] X. Ji, N. Zheng, Y. Hou, and S. Niu, “Application of asphaltmixture shear strength to evaluate pavement rutting withaccelerated loading facility (ALF),” Construction and BuildingMaterials, vol. 41, pp. 1–8, 2013.
[17] Y.-F. Bi and L.-J. Sun, “Research on test method of asphaltmixture’s shearing properties,” Journal of Tongji University, vol.33, no. 8, pp. 1036–1040, 2005 (Chinese).
[18] J. E. Stephens and K. C. Sinha, “Effect of aggregate shape onbituminous mix characteristic,” Association of Asphalt PavingTechnologists, vol. 47, pp. 434–456, 1978.
