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Relationship between the aggregate structure and mechanical properties of GB5® road base mix
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Pouget Simon1, Olard François1, Hammoum Ferhat2
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EIFFAGE Infrastructures, 8 rue du dauphiné 74005 69964 Corbas, France,
[email protected] &
[email protected] 2 IFSTTAR, Laboratoire MIT, Route de Bouaye, 44341 Bouguenais Cedex, France,
[email protected] Abstract
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Since 2008, EIFFAGE has developed an aggregate optimisation method (maximum contact and minimum space between aggregate particles) combined with the use of special binders (pure, multigrade or polymer-modified bitumen depending on the traffic concerned), to design the highperformance bituminous mix known as GB5®. Actually, numerous roads designed for heavy traffic have been built using this innovative technique, representing more than 600,000 tonnes at the end of 2014, mainly in France and, more recently, in South Africa.
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This article presents the result of collaboration between IFSTTAR and EIFFAGE aimed at scientifically relating the specific characteristics of the aggregate structure of GB5® to its outstanding mechanical properties, via 2D-image analysis and mechanical characterisation.
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Keywords: Aggregate packing optimisation, polymer modified bitumen, image analysis
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1. Introduction
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This study is the result of a long-standing partnership between IFSTTAR and EIFFAGE, initially formalised by a research framework agreement in 2005.
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The work presented here was carried out after the signature of additional agreement n°6, in 2012.
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The aim, for EIFFAGE, is to benefit from the competence of IFSTTAR's transport infrastructure materials laboratory (MIT) in relation to the image analysis technique correlated with the internal structure of civil engineering materials in order to develop aggregate optimisation methods associated with GB5® road base bitumen [1][2][3][4][5] for long-life sub-base and road base layers.
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The stakes are high, both for the company and for IFSTTAR: the specific properties of the aggregate structure of GB5® must be related to its outstanding mechanical properties. In addition to the study of GB5®, determining accurately the relationship between the composition, structure and properties of bituminous mix is a major line of research for EIFFAGE and IFSTTAR's researchers.
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For this purpose, 2D image analyses and mechanical characterisation were performed at IFSTTAR's MIT laboratory and EIFFAGE’s central laboratory located in Ciry-Salsogne respectively, on three types of mixes: EME2, GB4 and GB5®. 1
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2. Description of materials
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To carry out a comparative study, several 0/14 bituminous mixes were used. This material is made of crushed aggregate from the Roche Blain quarry:
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standard EME2, continuously-graded aggregate skeleton and 5.5% of 20/30 hard penetration grade binder standard GB4, continuously-graded aggregate skeleton and 4.2% of 35/50 grade binder GB5®, 6/10 gap-graded aggregate skeleton and 4.2% or 4.6% of binder: o Multigrade o Biprene® 41 IPE (polymer-modified multigrade)
The gradation curves are given in Figure 1.
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Figure 1. Gradation curves of used mixes
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3. Methods and tools
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3.1 Image analysis - Identification of internal structure
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Bituminous mix consists of a relatively dense assembly of aggregate and binder which gives the mix cohesion and impermeability. The aggregate structure of bituminous mix, which depends on both the components used and the manufacturing and laying conditions, has a direct, decisive influence on the mechanical properties of the mix. Optical imaging is being increasingly used to obtain digital images with high resolution at micrometric scale. Applications have been developed in numerous fields (biology, biometry, metallurgy and materials science). Although this technique can only be used to observe the surface of a sample but it provides rapid and reliable data [6]. Based on previous studies [7][8][9][10], IFSTTAR's MIT laboratory used image processing and analysis methods combining robust mathematical methods able to determine several quantifiers of the microstructure of bituminous materials and, more precisely : i) identification of the bituminous material phases (aggregate, mastic and porosity). The contrast of the different phases represent an advantage of the success of this step.
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Figure 2. Identification of the different phases of a material by image analysis of a crosssection ii) description of the arrangement of the aggregates with respect to each other and the distribution of mastic around the aggregate, via a Dirichlet (Voronoi) tessellation. When applied to bituminous materials for the first time in 2004 [10], this type of discretisation easily enabled the different phases of the aggregate structure to be identified. Based on a network of straight segments connecting up the centroids of the aggregate particles (Delaunay triangulation), the mediator of each segment can be determined. All mediators form Voronoi tessellations: the image is decomposed of a mosaic of cells. Each cell thus consists of a mastic ring of variable thickness surrounding the aggregate. The mastic surrounding the aggregate is defined as the Voronoi region. A methodology has been developed to study the optimised aggregate structure of GB5® (dense gap-graded aggregate) and try to relate the aggregate arrangement to the final mechanical properties. This methodology is based on geometric quantifiers that characterise the distribution of the aggregate structure within the mix, in order to compare the mechanical properties of different mixes. To relate the aggregate structure to the mechanical properties of GB5®, a comparative study was carried out with two standard mixes having relatively similar aggregate characteristics but different mechanical properties (EME2, GB4). For the three mixes (EME2, GB4 and GB5®), 180 x 500 x 100 mm prismatic specimens were made by EIFFAGE for the purpose of observation by optical imagery. Cuts were then performed by IFSTTAR's MIT laboratory along the three main planes. A high-performance digital camera was used to take images with good resolution (between 20 µm/pixel and 50 µm/pixel) and cover a minimum surface area of 100 cm². With a standard device type of equipment, easily available on the market, a single image pickup is sufficient to cover a representative surface area of the specimen. A study of the representativeness of an image was presented during the Eurasphalt & Eurobitume conference in 2004 [10]. Using a 150 x 500 mm specimen plate of one of the mixes, a plane section has been removed vertically with a diamond saw. An image is taken of each side of the specimen, under uniform lighting (Figure 3).
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Figure 3. Photo acquisition system for image analysis In the following section, we study the distribution of the particles having a surface area of more than 50 mm² which form the main skeleton of the mix (Figure 4). This 50 mm² minimum limit corresponds to the average surface area of the particles in the area studied.
Figure 4. Counting the number of aggregate particles intercepted in the image according to size in mm²
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3.2 Mechanical properties
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Four mixes design tests were carried out to evaluate the behaviour of the mixes:
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Compactability by using the gyratory shear compactor test, with measurement of the shear strength to evaluate the mechanical stability of the mix. Resistance to rutting Stiffness modulus Resistance to mechanical fatigue (2-point bending)
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4. Results of analyses
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4.1 Image analysis - Identification of internal structure
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An example is presented below of images of the specimens tested (EME2, GB4 and GB5®) with the results after thresholding and extraction of particles greater than 50 mm² in order to better visualise the aggregate skeleton (Figure 5). The distribution of nearest-neighbour particles is shown in Figure 6.
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Figure 5. Different stages of image analysis of the surface area of a cross-section of the bituminous mix specimen plate Extraction of the largest aggregate particles whose area is greater than 50 mm² shows a random, non-uniform distribution of particles, more especially for the GB4 and EME2 mixes. It can be seen that the aggregate particles are grouped together in certain areas of the image to form clusters of varying density while single aggregate particles can also be observed. In order to quantify the spatial distribution of the largest particles, the distance separating each particle from its nearest neighbour is calculated. The particle distribution is analysed using the Voronoi method. The minimum distance of a particle from its neighbours is identified by NNDist parameter.
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Figure 5. Spatial distribution of the largest particles (distance from nearest neighbour) The calculation results for the nearest neighbour distance are given in Figure 6. The average values for each mix show considerable differences in the distribution of the largest aggregate particles. The gradient of the curve shows the distribution of distances between nearest neighbours. The distance of the largest particles from each other can thus be evaluated. The distribution of nearest-neighbour distances is very spread out for mixes EME2 and GB4 with a very different distribution of nearest-neighbour distances for the two GB5 mixes, which indicates a higher density of large particles for this type of mix. The next step consists in examining the distribution of the skeleton particles with greater precision in order to deduce morphological differences between the different mixes with the help of the following indications: a) LAF-average: the local area fraction (LAF) is the ratio of the area of the aggregate particle intercepted to the area of the cell around it. A detailed examination of the space around large particles indicates the positioning of the particles considered in the study area. For a number of comparable particles, the higher value of LAF-average means a more uniform distribution of aggregates. b) Kurtosis-NNDist: The histogram of all the NN Dist (Nearest-Neighbour Distance) values is calculated. The Kurtosis histogram shows the spatial distribution of the largest particles. A low Kurtosis-NNDist value indicates an irregular arrangement with the formation of clusters which can locally present high interaction on a mechanical level but result in a lack of homegeneity due to the presence of a different aggregate class in an overall mix (problem of segregation). On the contrary, a higher value means better occupation of the surface area covered. c) ∑ (Area/NN Dist): The previous indicators do not take the different particle sizes into account. This last parameter combines both the area of the particle considered and the distance from its nearest neighbour. In other words, the interaction zone of a skeleton particle must be considered in relation to its size and the distance from its nearest neighbours. The results of analysis of the images acquired for the different mixes are given in Table 1. Table 1. Results of image analyses Specimen
Number of
LAFaverage (%) 6
NN Dist Kurtosis
∑ (Area/NN Dist) (x1000)
EME2 GB4 GB5®
particles 34 34 48
(Average) 25 22 33
4 11 18
4.5 9.5 17.0
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The averages of the local area fractions clearly show better particle distribution for GB5®, with an average LAF of 33% which is notably higher than the standard mixes. In relation to the distance from the nearest neighbour, NN DIST, this coefficient indicates a distribution mainly located around an average value. The least localised distribution is obtained with the EME2 mix with a coefficient of 4 which indicates non-uniform distribution. The arrangement of particles of more than 50 mm² in the GB5 mix is more uniform, resulting in a more localised distribution with a higher Kurtosis coefficient than the standard mixes. Finally, if both the size of the particles (>50 mm²) and the nearest-neighbour distance are considered, it can be seen once again that the GB5® mix stands out clearly, with a coefficient ∑ (Area/NN Dist) of 17, the highest in the study. These analyses show significant differences between the distribution of large particles of more than 50 mm² in the so-called standard mixes - EME2 and GB4 - and the GB5® mix. These differences correspond to a better occupation of the spaces between the particles in the case of GB5® and a less dispersed distribution of nearest-neighbour distances. Both these indicators emphasise the specific character of the optimised aggregate arrangement of GB5®.
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First, the results of the gyratory shear compact tests are plotted (up to 500 gyrations). The graphs showing the change in the percentage of voids are based on an average of 3 specimens.
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Figure 6. Change in the percentage of voids with the number of gyrations
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At 100 gyrations, the percentage of voids is 8.1% for the GB4 mix and 2.9% for the EME2 mix. For the GB5® mixes, intermediate values are obtained with 5.9% and 4.1% depending on the binder content.
4.2 Mechanical properties
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The shape of the shear strength curve reflects the behaviour of the material during compaction, with inter-particle friction in the presence of the binder which provides lubrication. During compaction, the final packing of the aggregate skeleton takes place once the shear force required to overcome inter-aggregate friction has been reached. This is demonstrated in figure 8 by still decrease of the shear force curve after 40 gyrations for the EME and GB5® mixes. The drop in shear force for a given number of gyrations also indicates the compaction energy transferred to the material to overcome inter-particle friction.
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Figure 7. Change in the pseudo-shear strength according to the number of gyrations
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4.3 Correlation between the internal structure and the mechanical properties
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Observation of the aggregate structure of a mix shows that the aggregate forms a network of inter-particle contacts that is quite specific to each mix studied (GB4, EME2, GB5®). Since the mechanical stress supported by the skeleton and transmitted through a network of inter-particle contacts, a correlation must be found between the mechanical properties of the materials tested and the morphological characteristics of the aggregate structure. In this study, the binder differs from one material to another. As a result, it is not easy to correlate all the mechanical properties because the binder can play a decisive role. Table 2. Results of mechanical characterisation Gyratory shear compact test
Rutting NF EN 12697-22 + A1
NF EN 12697-31
Modulus (15° C, 10 Hz)
Fatigue (10° C, 25 Hz)
NF EN 12697-26 – annex D/E
NF EN 12697-24 – annex A
Voids at 100 gyrations
% of voids
Depth of rutting (%)
% of voids
Modulus (MPa)
% of voids
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EME2 0/14
2.9
3.7
3.8
4.5
13 300
2.9
146
GB4 0/14
8.1
7.8
2.7
7.6
14 200
7.2
100
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GB5® 0/14 Multigrade GB5® 0/14 Biprene® 41 IPE 1 2 3 4 5 6 7 8 9 10 11 12
4.9
7.3
2.0
2.9
15 500
2.5
121
5.9
7.2
2.1
2.1
16 200
2.8
142
Table 3 gives the results of analysis of the distribution of particles greater than 50 mm². The parameter selected is ∑▒〖Area/NNDist〗 because it combines both the area of the particle considered and the nearest-neighbour distance. In other words, this parameter considers the interaction zone of a skeleton particle according to its size and distance from its nearest neighbours. In addition to the characteristics of the binders used in this study, we propose to study the correlation between the distribution of skeleton particles using, as an indicator, the relative distance from particles greater than 50 mm² and the mechanical properties of the materials studied. Table 3. Relationship between the aggregate skeleton and the mechanical properties Mix EME2 GB4 GB5® Multigrade GB5® Biprene IPE
Stiffness Modulus (15° C, 10 Hz) 13 300 14 200 15 500 16 200
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Rutting depth (%)
∑ 𝑨𝒓𝒆𝒂/𝑵𝑵𝑫𝒊𝒔𝒕 (x1000)
4.5 7.6 2.9 2.1
4.5 9.5 14.0 18.0
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Figure 9. Correlation between the nearest-neighbour distance of 10/14 aggregate particles and the mechanical properties. Above: stiffness modulus at 15° C/10 Hz; Below: rutting depth
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It can be seen that the distribution and the nearest-neighbour distance of the aggregate particles of the skeleton (greater than 50 mm²) can be correlated with the stiffness modulus. It seems that the stiffness of the material is proportional to the nearest-neighbour distance of the skeleton particles. To a lesser extent, there is also a correlation between the rutting resistance and the nearest-neighbour distance of the skeleton particles.
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5. Conclusions
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This study, conducted within the framework of a long-standing partnership between IFSTTAR and EIFFAGE, has established correlations between the distribution of the skeleton aggregate particles of bituminous materials and their final mechanical properties. The specific nature of the
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internal structure of GB5® (maximum contact and packing between aggregate particles) is highlighted by 2D imaging analyses and complete mechanical characterisation. The mechanical properties of GB5® 0/14 mix (with a binder content of 4.6%) are of the same order (or higher in terms of rutting resistance and stiffness modulus) as those of the standard 0/14 EME2 mix (with a binder content of 5.4%), thus requiring 15% less fossil bitumen in the base course. As a result, the GB5® mix clearly presents both a technical and economic advantage. Independently of its carbon content, the re-allocation of bitumen of fossil origin as a subsequent source of energy is beneficial to both the environment and society.
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6. References [1]
Olard, F., 2012. GB5 mix design: high-performance&cost-effective asphalt concretes by use of gap-graded curves & SBS modified bitumens. Road Mater. Pavement Des. 1, 234–259, Special Issue: Papers from the 87th Association of Asphalt Paving Technologists’ Annual Meeting, April 1–4, 2012. Olard, F., Perraton, D., 2010a. On the optimization of the aggregate packing characteristics [2] for the design of high-performance asphalt concretes. Int. J. Road Mater. Pavement Des. 11 (Special Issue EATA Parma), Best Scientific Paper Award. Olard, F., Perraton, D., 2010b. On the optimization of the aggregate packing for the design [3] of self-blocking high-performance asphalts. In: Congress of the International Society for Asphalt Pavements, Nagoya. [4]OlarOlard, F., and Pouget., S. A New Approach for Aggregate Grading Optimization for Mixtures. In Advances in Asphalt Materials, 427–57. Elsevier, 2015. http://linkinghub.elsevier.com/retrieve/pii/B9780081002698000143. F. Hammoum, F. Olard, S. Pouget (2015), Relations entre structure interne et performances [5] mécaniques de la grave-bitume GB5®, Revue Générale des Routes et de l’Aménagement (RGRA), n°925, pp. 18-23, February 2015 [In French]. Hammoum F. (2004), Quantitative study of bituminous materials microstructure by digital [6] image analysis , 3rd Eurasphalt & Eurobitume Congress, Vienna, Austria, 12-14 May 2004 [7] Russ J.C. et Dehoff R.T. (2001): Practical Stereology, Plenum Press, New-York, 2nd edition, pp. 307 [8] M. Coster, J-L. Chermant (2001), Image Analysis and Mathematical Morphology for Civil Engineering Materials, Cement and Concrete Composites, 23, p.133-151 [9] Boselli J, Pitcher P, Gregson P, Sinclair I (1999), Secondary phase distribution analysis via finite body tessellation, Journal of Microscopy, Journal of Microscopy,195, 104-112 [10] S. Ghosh, Z. Nowak and K. Lee (1997), Tessellation-based computational methods for the characterization and analysis of heterogeneous microstructures, Composite Science and Technology, 57, pp.1187-1210. 10
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