INTERNATIONAL JOURNAL OF CIVIL AND STRUCTURAL ENGINEERING Volume 1, No 2, 2010

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1 Shape Properties of Natural and Crushed Aggregate using Image Analysis Seracettin Arasan 1, A.Samet Hasiloglu 2, Suat Akbulut 1 1 Department of Civil Engineering, Engineering Faculty, Ataturk University, Erzurum, Turkey 2 Department of Computer Engineering, Engineering Faculty, Ataturk University, Erzurum, Turkey arasan@atauni.edu.tr ABSTRACT The importance of the shape of aggregate particles is well recognized due to their mechanical behavior. Durability, workability, shear resistance, tensile strength, stiffness, and fatigue response of concrete and asphalt concrete is heavily depend on the shape of aggregate particles. In recent years, image analysis is widely used to analyze the particle shape characteristics of aggregate. In this research, shape properties of natural river and crushed basalt aggregate were compared using image analysis by determining the shape characteristics of aggregate such as aspect ratio, elongation, flatness, form factor, roundness, shape factor, and sphericity. Additionally, the area perimeter technique was used to predict the fractal dimensions of aggregates. As a result, the difference between shape properties of natural and crushed aggregate was mentioned by image analysis in this study. Keywords: Natural aggregate, particle shape, fractal dimension, crushed aggregate, image analysis 1. Introduction Aggregates may be natural, processed (crushed) or synthetic origin. The majority of aggregates used in constructions is obtained from naturally occurring deposits and processed quarry rock. Natural aggregates such as sand and gravel are obtained from transported deposits, river deposits, alluvial fans and glacial outwash and processed aggregates are obtained by crushing and screening quarried rock, oversize gravel and boulders [1]. The particle shape characteristics of the aggregate significantly affect the workability, strength, and durability of the concrete [2 5] and asphalt concrete [6 15]. In recent years, image analysis has been used in widespread applications in many disciplines, such as medicine, biology, geography, meteorology, manufacturing, and material science. But, there have been relatively fewer applications of image analysis used in civil engineering. Imaging technology has been used recently to quantify aggregate shape characteristics and several researchers had investigated the role of aggregate shape in concrete and asphalt mixture [4, 7, 8, 16 18]. Some of these studies have focused on characterizing the 3D shape of aggregates [5, 19 22]. Others have 221

2 investigated the determination of shape properties of aggregate [3, 23] and grain size distribution [24 27]. Also, others have been devoted to developing procedures to describe the shape of aggregates with an emphasis on elongation or form [28 32], angularity [33 37], and texture [38 40]. Due to their irregularity, the shape of aggregates is not accurately described by Euclidian geometry. Fractals are relatively a new mathematical concept for describing the geometry of irregularly shaped objects in terms of frictional numbers rather than integers. The concept of fractals introduced by Mandelbrot [41], which has the shape formed in nature, has been usually analyzed using Euclidian geometry. The key parameter for fractal analysis is the fractal dimension, which is a real non integer number, differing from the more familiar Euclidean or topological dimensions. The fractal dimension for a line of any shape varies between one and two, and for a surface between two and three. In this sense, some studies have been devoted to developing procedures to determine the fractal dimension of particles [42 48]. Additionally, Arasan et al [49] indicated that the fractal dimension of aggregates is used for determination of mechanical properties of asphalt concrete. As mentioned above, the importance of the shape of aggregate particles on the performance of concrete and asphalt concrete is well recognized. In literature, only a few studies are focused on the comparison of natural river and crushed aggregate using image analysis. For this reason, this study was undertaken to investigate fractal dimension and aggregate shape indexes such as aspect ratio, elongation, flatness, form factor, roundness, shape factor, and sphericity. 2. Aggregate Shape Properties Particle geometry can be fully expressed in terms of three independent properties: form, angularity (or roundness), and surface texture. Figure 1 shows a schematic diagram that illustrates the differences between these properties. Also, form, roundness and surface texture are essentially independent properties of shape because one of them can vary widely without necessarily affecting the other two properties [50]. Form, the first order property, reflects variations in the proportions of a particle. Angularity, the second order property, reflects variations at the corners, that is, variations superimposed on shape. Surface texture is used to describe the surface irregularity at a scale that is too small to affect the overall shape [50 51]. 222

3 Figure 1: The hierarchical view of form, roundness, and surface texture (Barrett [50]) Different researchers are using different shape indexes to describe the shape of aggregate particles and even different definitions for the same shape index. Barksdale et al [28] defined the flatness as the ratio of thickness to width and the elongation as the ratio of width to length while Kuo et al. [6] defined the flatness as the ratio of width to thickness and the elongation as the ratio of length to width [6, 28]. They also used different definitions for the shape factor and sphericity. Besides, many researchers discussed the image analysis techniques used by most of the available imaging systems that utilize different mathematical procedures for the analysis of aggregate shape characteristics [8, 18, and 38]. These measurements are explained in more detail below. Shape factor, aspect ratio, sphericity, flatness, and elongation which are proposed imaging indexes for the first order of shape (form) are measured for each aggregate particle. To properly characterize the form of an aggregate particle, information about three dimensions of the particle is necessary (longest dimension [L], intermediate dimension [I] and shortest dimension, [S]). Roundness which is proposed imaging index for the second order of shape (roundness) is measured for each aggregate particle. It is also clear that form factor reflects changes in aggregate form, roundness, and surface texture [24]. Furthermore, a new shape factor, area sphericity, was proposed in this study. Shape Factor: Shape factor is defined as Shape Factor = S [6, 7]..... (1) I. L Aspect Ratio: Aspect ratio is defined as L Aspect Ratio = [37] (2) I 223

4 Sphericity: Sphericity is among a number of indices that have been proposed for measuring the form in terms of the three dimensions. I. S Sphericity = 3 [6 8, 49 52] (3) 2 L Flatness: Flatness is defined as S Flatness = [51] (4) I Elongation: Elongation is defined as I Elongation = [51] (5) L Roundness: This is a shape factor that has a minimum value of 1 for a circle and larger values for shapes having a higher ratio of perimeter (P) to area (A), longer or thinner shapes, or objects having rough edges. For the image analysis system used in this study, Roundness is defined as: 2 P Roundness = [6, 8]...(6) 4.. A Form Factor: Several parameters based on object dimensions have been proposed in the literature to measure different aspects of aggregate shape. Form factor compares the perimeter of an equivalent circle to the perimeter of the particle. An equivalent circle has the same area as the particle. Because angularity and texture influence the perimeter of a particle, it follows that form factor not only influenced by particle form but also reflects angularity and texture as well [7]. Form factor has been used to describe surface irregularity and is defined as: 4.. A Form Factor = [7, 37, 40] (7) 2 P Area Sphericity (S A ): This is a new shape factor proposed in this study. It has a maximum value of 1 for equal dimensional particles (such as sphere or cube) and has smaller values for no equal dimensional particles. Area sphericity is defined as: A front S A = (8) A top Where: A front : Front view area of an aggregate, A top : Top view area of an aggregate. 3. Fractal Dimension Fractal theory uses the concept of fractal dimension, D R, as a way to describe the shape of particles. Fractal dimension of particles was calculated with divider, parallel line, and area perimeter methods. Also, the area perimeter method is the easiest method [47]. In 224

5 this study, the fractal dimension of the particles is evaluated using the area perimeter method, introduced by Mandelbrot [53] and later by Hyslip and Vallejo [47], which is based on the ratio of linear extents, proposed by Mandelbrot [53]. The ratio of linear extents of fractal patterns is in themselves fractal, and that:..... (9) Where c is a constant for similar fractal shapes and D R is the roughness fractal dimension of the population. Again, taking the logarithm of Eq.9, c yields a linear relationship between area A and perimeter P with Dr related to the slope coefficient, m, by: D R =2/m (10) Evaluating the roughness fractal dimensions D R using Eq. 10, Dr=2/m is referred to as the area perimeter method which determines D R by evaluating an entire population of related shapes as opposed to individual particles [47]. 4. Materials and Methods Crushed basalt and natural river aggregate was used in this study. Aggregates were selected by hand as flat, elongated, and spherical. In addition, a control sample containing all of particle shapes was prepared. Eight crushed aggregate fractions were analyzed as flat, elongated, spherical, and mixed for 19 to 12.5 mm and for 12.5 to 9.5 mm. Also, four natural aggregate fractions were analyzed as flat, elongated, spherical, and mixed for 16 to 8 mm. Designation codes for the aggregate fractions are given in Table 1. Table 1: Designation codes of the soil fractions Type Crushed Basalt (9,5 to 12,5 mm) Crushed Basalt (12,5 to19 mm) Natural River Aggregate (8 to16 mm) Shape Flat Elongate Spherical Mixed Flat Elongate Spherical Mixed Flat Elongate Spherical Mixed (A1) (A2) (A3) (A4) (A5) (A6) (A7) (A8) (A9) (A10) (A11) (A12) The imaging system used by the authors consists of a Nikon D80 Camera and Micro 60 mm objective manufactured by Nikon. ImageJ was used as the image analysis program. 225

6 In order to compare results of top and front views, the images of both views were separately analyzed and plotted. 100 particles were selected for aggregate fraction. The aggregates were also placed three by three within the sample tray for capturing the top and front images. These images were processed in ImageJ and then output data of ImageJ was transferred to Excel. The output data also contain area, perimeter, L, I, and S values of top and front view of each aggregate in unit of millimeter, and quantity of aggregates. The other properties of used materials test procedures, imaging system and digital image processing steps were also detailed in previously researches of authors [54 55]. 5. Results and Discussion 5.1. Aggregates shape properties Particle shape analysis was carried out using some shape properties of aggregate. The average values for each shape properties are listed in Table 2. The results showed that there exist distinct morphological characteristics for different aggregate shapes (i.e., flat, elongated, spherical, and mixed). Figure 2 shows the average roundness values of aggregates. It is clearly observed that the crushed aggregate gives higher roundness values than the values of natural river aggregate. Crushed basalt aggregate has rough edges, so it gives higher roundness value. Additionally, roundness of flat and spherical aggregates is the highest and the lowest, respectively (Figure 1). The first order shape properties (i.e., form) of aggregate is insignificant when the aggregate shape (i.e., flat, elongated, spherical) put in to consideration (Table 2). Figure 2: Average roundness values of aggregate 226

7 Table 2: The average values of aggregate shape properties Aggregate Type L I S Shape Factor Aspect Ratio Sphericity Flatness Elongation A A A A A A A A A A A A Roundness Form Factor Top Front Top Front Average View View View View Average A A A A A A A A A A A A Aggregate Type 5.2. Fractal Dimension of Aggregates Area Sphericity The area perimeters method was used for determining the aggregate fractal dimensions. The fractal dimensions of crushed basalt aggregate from top and front views are 1,123 and 1,062, respectively [56]. The fractal dimensions of natural river aggregate are also lower than those of crushed aggregate (Figure 3). For natural aggregate, values of 1,074 and 1,029 are obtained from top and front view, respectively. Additionally, Figure 3 indicated that the results of top and front views are different. Hence, it could be said that the direction of image is important for the analysis. 227

8 Figure 3: Comparisons of aggregate type by means of the fractal dimension Different shaped aggregates (i.e., flat, elongated, spherical, and mixed) were also prepared to investigate the effect of aggregate shape on the fractal dimension. The fractal dimensions of crushed and natural aggregates were given in Table 3. Figure 4 also indicate that flat and mixed particles give highest and lowest values of fractal dimension respectively. Table 3: The mean values of particle fractal dimensions from top and front views Crushed Basalt (9,5 12,5mm) Crushed Basalt (12,5 19mm) Natural River (8 16mm) Flat 1,1470 1,2360 1,0605 Elongated 1,0850 1,1760 1,0525 Spherical 1,1020 1,1005 1,0155 Mixed 1,0810 1,0100 1,028 Figure 4: Comparisons of the average values of fractal dimensions from top and front views 228

9 6. Conclusions The present study was undertaken to investigate the comparison of natural and crushed aggregate shape properties. The following conclusions were drawn based on the test results and on the discussion presented in this study: The crushed aggregate gives higher roundness value than the natural river aggregate. The fractal dimensions of natural river aggregate are also lower than crushed aggregate. The results of top and front views are different. Hence, it could be said that the direction of image is important for the analysis. The particle shape affects the fractal dimension of particles. The biggest and smallest values of fractal dimension were obtained from flat and mixed particles, respectively. 7. References 1. Topal T, Sengoz B., Determination of fine aggregate angularity in relation with the resistance to rutting of hot mix asphalt. Construction and Building Materials, 19: Ozol, M.A., Test and Properties of Concrete Aggregates: Chapter 35 Shape, surface texture, surface area, and coatings. STP169B EB p: Kwan, A.K.H., Mora, C.F., Chan, H.C., Particle shape analysis of coarse aggregate using digital image processing. Cement and Concrete Research, 29: Erdogan, S.T., Determination of aggregate shape properties using X ray tomographic methods and the effect of shape on concrete rheology, Ph.D. Dissertation, University of Texas at Austin. 5. Erdogan, S.T, Quiroga, P.N.,. Fowler, D.W, Saleh, H.A., Livingston, R.A., Garboczi, E.J., Ketcham, P.M., Hagedorn, J.G., Satterfield,S.G., Threedimensional shape analysis of coarse aggregates: New techniques for and preliminary results on several different coarse aggregates and reference rocks. Cement and Concrete Research, 36: Kuo CY, Frost JD, Lai JS, Wang LB., Three Dimensional Image Analysis of Aggregate Particles from Orthogonal Projections. Transportation Research Record, 1526:

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