Aggregate Surface Texture Research Articles

INVESTIGATION OF AGGREGATE PARTICLES SHAPE ON CHARACTERISTICS OF HOT MIX ASPHALT

This research represents a laboratory study of the effect of the aggregate shape in HMA. The shape ofaggregates particles is not the only factor of aggregate characteristics which effect on HMA. OtherParameters such as aggregate gradation and aggregate surface texture are also effect. The aggregateshapes considered for the study were cubical, disk and blade shapes. Two aggregate surface textures usedin the mix which were smooth and rough particles. The aggregate gradations used in the mixtures weremaximum, medium and minimum gradation .Shape of aggregate was determined through two methods.The first method was an image measurement of coarse aggregate while the second method was particleshape index. Marshal tests and indirect tensile test were performed to investigate the different inbehaviors of different samples with different parameters considered in this study taking into account thatthe control mix contains crushed gravel, rough aggregate particles with disk shape, medium gradation ofaggregate and 4% of limestone powder as mineral filler.The results showed that using of cubical aggregate shape increased each of Marshall Stability, bulkdensity, Marshall Stiffness, Marshall Quotient, Stiffness Modulus and the Indirect Tensile Strengthof the mix than disk and blade shapes while decreased each of flow and air voids. The results also,showed that medium gradation of aggregate had good results than other gradations. By using roughparticles the values of ITS and stiffness modulus were higher than using smooth particles

Aggregate Shape Properties and Their Influence on the Behavior of Hot-Mix Asphalt

Aggregate shape properties, such as form, angularity, and surface texture, highly influence the performance of hot-mix asphalt (HMA). Rutting is related to aggregate angularity and form, which affects the interlock among particles. Fatigue cracking can be decreased by an aggregate rough surface texture, which improves the aggregate-binder interaction. Several researchers have been studying new automated and more precise techniques, such as the aggregate image measurement system (AIMS), to improve the determination of aggregate shape parameters. This paper presents an analysis of aggregates from three different mineralogical sources, investigating the influence of shape properties on HMA design and mechanical properties. The results indicated that the aggregates had similar shape properties, despite differences in the mineralogical composition. This might be a direct effect of similar quarrying procedures. Surface texture resulted in different values, which can be explained by results from the petrographic analyses. In general, the aggregates’ shape properties resulted in HMA samples with similar mechanical behavior. The HMA specimens were also analyzed in terms of their internal structure, which included the investigation of a number of contact points, and aggregate particles’ segregation and orientation characteristics.

Experimental procedure for evaluation of coarse aggregate polishing resistance

This paper presents the development of experimental methods for measuring aggregate textural retention, which is a very important property that influences pavement skid resistance. The 2nd version Aggregate Image Measurement System (AIMS-II) is used to measure coarse aggregate surface texture before and after different polishing time intervals in a modified Micro-Deval (MD) test procedure. The use of AIMS-II to compare aggregate surface texture and the evolution of aggregate polishing curves was verified and determined to be successful because AIMS-II texture measurement closely reflected historical data on aggregate frictional properties obtained by Illinois Department of Transportation (IDOT). Analytical functions, considering aggregate surface texture at different polishing times, were then used to describe the initial texture, rate of polishing, and terminal texture. Statistical analysis was used to determine that the required polishing time to achieve terminal texture in the modified MD is 210min.

Fine Aggregate Angularity Effects on Rutting Resistance of Asphalt Mixture

Fine Aggregate Angularity (FAA) has been identified as one of the important aggregate properties contributing to the stability of Hot Mix Asphalt (HMA) and its resistance against permanent deformation. The performance of dense graded asphalt mixture is significantly influenced by the shape, angularity and surface texture of fine aggregates. This study determines the FAA for different types of aggregates namely granite and natural sand and evaluates the rutting resistance of AC 10 mixture added with the aforementioned aggregates. Marshall test and wheel tracking test were carried out in order to assess stability and rutting resistance. It was found from FAA test, crushed granite has higher percentage of FAA (46%) compared to natural sand (37%). With higher FAA value, crushed granite mix was found to have better stability, stiffness, and flow compared to specimen with natural sand. From wheel tracking test, it was observed that the rut depth for specimen with crushed granite is lower compared to specimen with natural sand. Therefore it can be concluded that fine aggregates with more angular shape, provides better stability and increase the rutting resistance.

Laboratory evaluation of warm mix asphalt mixtures containing electric arc furnace (EAF) steel slag

This paper presents the results of a laboratory study which was aimed to verify possibility of using electric arc furnace (EAF) steel slag (SS) in substitution of natural limestone (LS) aggregates in warm mix asphalt (WMA) mixture. The SS was used as fine and coarse portion of aggregate gradation in HMA mixtures, and as coarse portion of aggregate gradation in WMA mixture. The surface texture of both LS and SS aggregates was observed through scanning electron microscope (SEM). The results illustrated that the porosity and the roughness of the SS aggregate are higher than that of the LS aggregate. Moreover, laboratory tests results indicated that use of coarse SS aggregate in WMA mixture enhances Marshall stability, resilient modulus, tensile strength, resistance to moisture damage and resistance to permanent deformation of the mixture. Hence use of coarse electric arc furnace steel slag aggregate in production of WMA mixture is recommended.

Evaluation of Aggregate Imaging Techniques for Quantification of Morphological Characteristics

Aggregate morphological characteristics, including shape, angularity, and surface texture, have a significant impact on the engineering properties of construction materials such as hot-mix asphalt and hydraulic cement concrete. Consequently, the quantification of morphological characteristics of aggregates is essential for quality control of both aggregate production and pavement construction. Imaging techniques provide a cost-effective means for measuring the aggregate morphological characteristics conveniently without tedious work. However, these imaging techniques adopt various mathematical methods with different instrument setups and result in different definitions of morphological descriptors that are usually incomparable with each other. This paper evaluates prevalent imaging techniques used for aggregate morphological characteristics analysis, including equipment cost, repeatability, reliability, accuracy, and measured morphological parameters. Three imaging techniques (second-generation Aggregate Imaging Measurement System, first-generation University of Illinois aggregate image analyzer, and Fourier transform interferometer system), are further evaluated by comparing the analysis results of seven types of aggregates passing a ¾-in. sieve and retained on a ½-in. sieve with manual measurements and visual rankings. Analysis of variance between measurements using different methods is also conducted to evaluate the accuracy of each aggregate imaging system. From the data analysis, recommendations that depend on morphological characteristics of most interest to engineers are made for the selection of appropriate imaging-analysis techniques.

Investigation of the shape, size, angularity and surface texture properties of coarse aggregates

The shape, size, angularity and surface texture properties of coarse aggregates were studied in this paper. Aggregates with different shapes were separated manually and the percentage by number of each shape was computed. The three sizes (length, width and thickness) of aggregates were extracted using an image analysis approach and their statistical distributions were studied. An indicator called angularity and surface texture (AT) index was developed to characterize the combined effect of the coarse aggregate angularity and surface texture based on two-dimensional aggregate images. The statistical distributions of the AT indices of different sized limestone and basalt aggregates and their composite AT indices were studied. The void contents of different sized limestone and basalt aggregates in loose condition were tested to validate the AT index.

Effect of size and type of fine aggregates on flowability of mortar

The present study investigated how the aggregate characteristics namely individual size, grade and type affects flowability of mortar mixes. Two types, river sand and crusher dust four single sizes namely 1.18 mm, 0.600 mm, 0.300 mm, 0.150 mm and for single gradation of each fine aggregate were considered in the present research work. In total, 103 mortar batches was made with three different sand to cement ratios [s/c] and two different water to cement ratios [w/c] to find out the flowability of mortar and tested using standard flow table. Out of 103 mortar batches, 52 were with river sand and 51 were with crusher dust. Tests were performed as per ASTM 109 standards. S/c ratio varied from 1 to 3 with an increment of one and w/c ratio was chosen in such a way that all the mixes to give measurable flow. The influence of particle shape and surface texture of aggregate were characterized with an angularity test based on ASTM C1252 in terms of percent of air voids in a loosely compacted fine aggregate. The results indicate that the size of aggregate and uncompacted void content have greater impact flowability of mortar. Mortar made with river sand has got better flowability than that of mortar made with crusher dust due to its higher degree of irregularities. Mortar with higher aggregate content has low percentage of spread compared to mortar with low aggregate content. Similarly, graded aggregate has lesser percentage of spread due to its proper packing compared to single sized aggregates.

Effect of crushed sand on mortar and concrete rheology

This article describes an experimental study conducted on fresh mortars and concretes made with crushed sand. The aim of this research was to assess the effect of aggregate particle shape and surface texture as well as dust content on mortar and concrete rheology. The experimental programme also addressed the impact of angular grains on chemical admixture performance and concrete bleeding. The findings showed that the use of crushed sand induces rheological behaviour that differs from the behaviour observed in natural sand and that superplasticisers can improve this behaviour considerably.

Comparison of 2D and 3D image-based aggregate morphological indices

Significant progress has been made over the last two decades in the characterisation of aggregate shape using automated image analysis and processing methods. Aggregate shape characteristics have been quantified using three distinct shape parameters, namely the aggregate form, angularity and surface texture. Several mathematical procedures have been developed to quantify these parameters. For practical reasons, most of these procedures were limited to two-dimensional (2D) and utilised 2D aggregate images. This paper investigates the ability of some of the most widely used 2D aggregate form and angularity indices to describe the shape of five different types of aggregates (natural gravel, basalt, granite, diabase and slate). In addition, it provides a comparison between 2D and three-dimensional (3D) aggregate shape indices developed based on fitting the 3D aggregate shape using spherical harmonic functions.

Evolution of aggregate surface texture due to tyre-polishing

Three kinds of aggregates were polished by genuine pneumatic rubber tyres. The initial states of surface texture and dynamic friction coefficient were measured and their developments in polishing process were monitored. The characterizations of height distribution and power spectral density of aggregate surface texture were estimated. The changes of micro-texture were also investigated based on a fractal filtering method with sound theoretical backgrounds of rubber friction on rough surfaces. Global height reduction and differential removal of mineral component are observed in polishing process. It is concluded that the tyre-polishing action plays the critical roles in the micro-scale texture, and the evolution of friction of aggregate is governed by the micro-texture changes due to the differential removal of mineral component.

A novel aggregate classification technique using moment invariants and cascaded multilayered perceptron network

Occupying more than 70% of the concrete's volume, aggregates play a vital role as the raw feed for construction materials; particularly in the production of concrete and concrete products. Often, the characteristics such as shape, size and surface texture of aggregates significantly affect the quality of the construction materials produced. This article discusses a novel method for automatic classification of aggregate shapes using moment invariants and artificial neural networks. In the processing stage, Hu, Zernike and Affine moments are used to extract features from binary boundary and area images. In the feature selection stage, discriminant analysis is employed to select the optimum features for the aggregate shape classification. In the classification stage, a cascaded multilayered perceptron (c-MLP) network is proposed to categorize the aggregate into six shapes. The c-MLP network consists of three MLPs which are arranged in a serial combination and trained with the same learning algorithm. The proposed method has been tested and compared with twelve machine learning algorithms namely Levenberg–Marquardt (LM), Broyden–Fletcher–Goldfarb–Shanno quasi-newton (BFG), Resilient back propagation (RP), Scaled conjugate gradient (SCG), Conjugate gradient with Powell–Beale restarts (CGB), Conjugate gradient with Fletcher–Reeves updates (CGF), Conjugate gradient with Polak–Ribiere updates (CGP), One step secant (OSS), Bayesian regularization (BR), Gradient descent (GD), Gradient descent with momentum and adaptive learning rate (GDX) and Gradient descent with momentum (GDM) algorithms. Also, the classification performance of the c-MLP network is compared with those of the hybrid multilayered perceptron (HMLP), the radial basis function (RBF) as well as discriminant analysis classifiers. Concerning the cascaded MLP, 3 stage c-MLP gives the best accuracy compared to the 2 stage c-MLP and the standard MLP. Compared to other learning algorithms, LM algorithm achieved the best result. As far as the overall conclusion is concerned, c-MLP gives better classification performance than that of the HMLP, RBF and discriminant analysis.

Experimental Methods for the Evaluation of Aggregate Resistance to Polishing, Abrasion, and Breakage

This paper presents the development of new methods for measuring aggregate resistance to polishing, and degradation. These are important properties that influence pavement skid resistance and resistance to distresses under traffic loading. The aggregate imaging system is used to measure aggregate surface texture after different polishing time intervals in the micro-Deval test. Mathematical functions are then used to describe the initial texture, rate of polishing, and final texture. Aggregate abrasion is quantified by the percent difference in surface angularity before and after the micro-Deval test, while aggregate breakage is described by the weight loss in this test. The efficacy of the new methods is demonstrated through the analysis of aggregates from different sources that exhibit a wide range of properties. In addition, the new methods are verified by comparing the measured aggregate properties to the degradation of these aggregates in hot mix asphalt mixtures due to compaction forces.

Quantification of Coarse Aggregate Surface Texture Using Image Analysis

Abstract Aggregate surface texture affects the performance of pavement and railroad track structural layers, such as the unbound aggregate base/ballast, asphalt concrete, and Portland cement concrete. A quantitative surface texture (ST) index is defined in this paper based on image analysis to measure the irregularities on the surface of coarse aggregate particles in the extent that is not characterized by the commonly used large-scale morphological descriptors, such as flatness, elongation, and angularity. Using an image analysis approach referred to as erosion and dilation, the new ST index quantifies the coarse aggregate surface irregularities at the pixel level. Samples of natural gravel and crushed aggregate were used in establishing a realistic range for the ST index independent of particle size. The effectiveness and practical applicability of the defined ST index in characterizing aggregate surface texture were evaluated by measuring surface irregularities or texture of commonly used coarse aggregate materials.

Suitable features selection for the HMLP and MLP networks to identify the shape of aggregate

Aggregates are one of the main ingredients for producing concrete. In order to produce ‘high performance’ concrete, the properties of aggregates matter most. In particular, shape and surface texture of aggregates immensely influence the strength and structure of the resulting concrete. Often, low quality shape aggregates reduce the durability and strength of the concrete with much more requirement of sand, cement and water. Because the strength of concrete depends on the ratio of well-shaped aggregates to poor shape ones contained in the concrete mixture, the classification process for aggregates into well shaped and poor shaped is an essential step toward high quality concrete. Traditional technique requires aggregate to pass a stringent series of mechanical, chemical and physical test in order to demonstrate that they will perform satisfactorily, and meet or exceed specifications. Such stringent tests, often perform manually, tends to be slow, highly subjective and laborious. Therefore, an intelligent system that can separate the aggregates automatically could help to overcome these problems. This paper discusses an implementation of an intelligent classification system for the aggregate particles using neural network. The features obtained with image analysis, which are area, perimeter, Hu’s moments, Zernike’s moments of the aggregate’s area and perimeter were used as input data for the neural network. The hybrid multilayered perceptron network trained using modified recursive prediction error algorithm is employed to perform the classification. Performance analysis of the hybrid multilayered perceptron network is compared with the standard multilayered perceptron network trained using four different training algorithms, i.e. recursive prediction error, Bayesian Regulazation, Levenberg–Marquardt and scale conjugate gradient. The experimental results show that the performance for hybrid multilayered perceptron and multilayered perceptron networks are significantly better using the moments extracted based on object’s perimeter compared to object’s area. Model comparison confirms that the selected features combined with hybrid multilayered perceptron network attains the best performance in aggregates recognition.

Aggregate Morphology Affecting Resilient Behavior of Unbound Granular Materials

The resilient modulus (MR) defines the nonlinear elastic response of pavement geomaterials, such as the unbound aggregate base-subbase materials, under repeated traffic loading. The resilient behavior of unbound aggregate layers is affected by the stress states experienced because of wheel loading and physical properties of aggregate materials. Among the physical properties, the influence of aggregate morphology on the resilient behavior of base-subbase materials is not yet well understood because of a lack of quantitative measurements of shape, angularity, and surface texture characteristics of aggregate particles. This paper focuses on investigating the influence of aggregate angularity and surface texture properties on the resilient behavior of unbound granular materials expressed by a nonlinear, stress-dependent resilient response model. With an image analysis approach, two important aggregate morphological indices [the angularity index (AI) and the surface texture index (ST)] were defined to quantify...

Aggregate Morphology Affecting Resilient Behavior of Unbound Granular Materials

The resilient modulus (MR) defines the nonlinear elastic response of pavement geomaterials, such as the unbound aggregate base–subbase materials, under repeated traffic loading. The resilient behavior of unbound aggregate layers is affected by the stress states experienced because of wheel loading and physical properties of aggregate materials. Among the physical properties, the influence of aggregate morphology on the resilient behavior of base–subbase materials is not yet well understood because of a lack of quantitative measurements of shape, angularity, and surface texture characteristics of aggregate particles. This paper focuses on investigating the influence of aggregate angularity and surface texture properties on the resilient behavior of unbound granular materials expressed by a nonlinear, stress-dependent resilient response model. With an image analysis approach, two important aggregate morphological indices [the angularity index (AI) and the surface texture index (ST)] were defined to quantify accurately the angularity and surface texture properties of six types of commonly used aggregate materials with varying surface irregularities. Twenty-one unbound specimens were prepared with the blending of six aggregate materials and tested for resilient moduli in a laboratory triaxial setup as per the AASHTO T 307-99 protocol. Both AI and ST were found to be closely linked to MR values of the aggregate specimens blended in different percentages. As the aggregate angularity and surface roughness increased, the resilient moduli were considerably improved, which was primarily because of the increased shear strength with better aggregate interlock and frictional properties and the increased confinement levels expressed by higher bulk stresses.

Unified Method to Quantify Aggregate Shape Angularity and Texture Using Fourier Analysis

Aggregates are an important constituent of asphalt concrete, hydraulic cement concrete, and granular base. The shape, angularity, and surface texture of aggregates are basically variations of asperities at different dimensional scales and affect mixture properties in different ways. This paper presents a unified Fourier morphological analysis method to quantify the shape, angularity, and surface texture of aggregates. Evaluation of these characteristics of 10 aggregates of known quality indicates that Fourier morphological analysis quantitatively ranks these aggregates in consistence with qualitative evaluations.

Measuring the fractal dimension of diesel soot agglomerates by fractional Brownian motion processor

This work explores the application of fractional Brownian motion (FBM) analysis to SEM micrographs of soot aggregates exhausted by a model dynamometer. By directly quantifying the surface texture of fractal-like aggregates to extract their Hurst coefficients (H), the FBM analysis was successful in parameterizing fractal dimension (Df) values, from which the relative aggregate structure variables could easily be determined. For two microscopic magnification scales (×50,000 and ×105), the soot aggregate Df fell in the range of 1.6–1.7. The experimental results closely agreed with the main conclusions derived from previous studies. An alternative approach is to clarify the impact of image properties on Df measurements due to digital image processing and data recording. A twofold change in SEM magnification size gave rise to a 7% deviation, and scaling up from the original image increased the discrepancy compared to miniaturization. In conclusion, texture characterization is useful for estimating the fractal properties of most chain-like or cluster soot aggregates.

Index of Aggregate Particle Shape and Texture of coarse aggregate as a parameter for concrete mix proportioning

Aggregates occupy bulk of the volume of concrete. Their size, grading, shape and surface texture have significant influence on the properties of concrete, both in fresh and hardened state. Specifications in various codes, on concrete mix proportioning, regarding size and grading of the aggregate are much clear than their counterparts regarding shape and surface texture, which is broadly classified into angular/crushed and rounded/uncrushed. The lack of quantitative definition of aggregate particle shape and surface texture often leads to inconsistent results, and requirement of number of trials for achieving desirable properties of concrete. Index of Aggregate Particle Shape and Texture (IAPST) as per ASTM D-3398-97, provides a quantitative measure of shape and surface texture of aggregate. The present investigation covers coarse aggregate with different IAPST. The data of 45 concrete mixes has been presented and the potential of IAPST of coarse aggregate as a parameter for concrete mix proportioning is discussed in the paper.