Advances in Civil Engineering

Advances in Civil Engineering / 2019 / Article

Research Article | Open Access

Volume 2019 |Article ID 2386590 | https://doi.org/10.1155/2019/2386590

Yu Qin, Hua Wu, Yong Zheng, Weina Wang, Zhijian Yi, "Microscopic Texture of Polypropylene Fiber-Reinforced Concrete with X-Ray Computed Tomography", Advances in Civil Engineering, vol. 2019, Article ID 2386590, 9 pages, 2019. https://doi.org/10.1155/2019/2386590

Microscopic Texture of Polypropylene Fiber-Reinforced Concrete with X-Ray Computed Tomography

Academic Editor: Amir Si Larbi
Received02 Sep 2019
Revised26 Nov 2019
Accepted05 Dec 2019
Published23 Dec 2019

Abstract

Polypropylene fiber-reinforced concrete (PFRC) is a cement-based composite material with short-cut fibers which has been utilized to provide multidimensional reinforcement and enhance toughness of concrete. However, this improvement is closely related to the microstructural morphology of the concrete. A nondestructive technique using X-ray computed tomography (CT) was therefore used to grasp the microscopic texture of PFRC samples. The results showed that the orientation of microcracks, which appear in the interfacial transition zone, are along the surface of the coarse aggregate. The range of distribution of fibers is proportional to fiber volume fraction. The coarse aggregate influence distribution and orientation of polypropylene fibers whose shape are mainly fold line and curve. The dispersion of pores with small volume is uniform, and the distance between the pores with larger volume is short. The proportion of pores with the diameter in the range 0∼199 μm exceeds 70%, of which the sum of volume exceeds a half of total volume with the amount being about 1% of total amount.

1. Introduction

The inferior fracture resistance of concrete is a drawback that seriously affects the long-term durability of bridge engineering. Polypropylene fiber-reinforced concrete (PFRC), which is a cementitious composite material with short-cut fibers, has better resistance to cracking. This improvement in mechanical performance is closely related to the microscopic structure of concrete, crucial for the tensile strength and the long-term evolution of the material [1, 2]. X-ray computed tomography (CT) is a nondestructive evaluation method that can be used to generate a 3D image representation of the microscale texture of concrete [3, 4]. Therefore, it is necessary to reveal the microcomposition characteristics of polypropylene fiber-reinforced concrete based on CT in order to better solve the problem of cracking.

The fiber-reinforced concrete with computed tomography has been highlighted in a number of investigations. Bordelon and Roesler [5] quantified dispersion of synthetic fibers within concrete using X-ray computed tomography combined with a postprocessing image analysis. Mishurova et al. [6] focused on the CT experimental evaluation of the key microstructural parameters of a short fiber-reinforced concrete. Balázs et al. [7] studied the distribution and orientation of steel fiber with computed tomography. Zhou and Uchida [8] evaluated steel fiber orientation/distribution throughout the ultra-high performance fiber-reinforced concrete using image analysis and 3D visualization of fiber orientation based on X-ray computed tomography data. Snoeck et al. [9] analyzed the self-healing efficiency of cementitious materials promoted by superabsorbent polymers using X-ray CT. Ren et al. [10] developed two-dimensional mesoscale finite element models with realistic aggregates, cement paste, and voids of concrete using microscale X-ray computed tomography images.

The previous research mostly focused on dispersion of synthetic fibers [5, 11, 12], distribution and orientation of metal fibers [68], oriented fiber [13, 14], defect and damage of fiber-reinforced concrete [9, 15, 16], fabrication of cementitious materials [17, 18], or modeling based on CT image [10, 19]. However, these studies do not provide much attention to microscopic texture of polypropylene fiber-reinforced concrete.

The aim of this paper is to gain insight into the microstructure of fiber-reinforced concrete at the scale of dozens of micrometers by using the X-ray computed tomography. The unveiling of holistic characterization of specimens, spatial distribution of fibers, and morphological character and size of pores provides new insights into the microscopic texture of polypropylene fiber-reinforced concrete.

2. Materials and Methods

2.1. Materials and Specimens
2.1.1. Materials and Mixing Procedure

The fiber-reinforced concrete is composed of water, cement, coarse aggregate, fine aggregate, superplasticizer, and polypropylene fiber. The mixture proportion of concrete, which is used for high-speed railway bridges in China, is given in Table 1.


Specimenw/cComponent kg/m3Fiber volume fraction (%)
CementFly ashWaterFACASuperplasticizer

S10.3641573.215064911557.320.1
S20.3641573.215064911557.320.2
S30.3641573.215064911557.320.3

Notes: w/c, water-cement ratio; FA, fine aggregate; CA, coarse aggregate.

The monofilament polypropylene fibers manufactured from 100% virgin polypropylene resin have a nominal length of 19 mm and an equivalent diameter of about 35 μm. This fiber meets the requirements of ASTM C-1116, (Section 4.1.3) Type III fiber. Polypropylene fiber has the characteristics of high strength, low density, no water absorption, and extremely stable chemical properties.

The Ordinary Portland Cement (OPC), equivalent to ASTM Type I, was used in this study. Crushed limestone with a maximum size of 20 mm was chosen as the coarse aggregate. River sand having a fineness modulus of 3.0 was used as the fine aggregate. Polycarboxylic acid water-reducing agent that is a composite admixture of polycarboxylate copolymers and other auxiliaries was also used in mixes.

The main production process of PFRC specimens is as follows. First, the gravels, river sands, and polypropylene fibers were evenly mixed in the container. Subsequently, the cement and fly ash were added and mixed. According to the mixture proportions, water and water-reducing agent were added, and the mixture was then stirred until it is homodispersed at room temperature. Specimens were produced by placing the reaction mixture into mold with the sizes of 100 × 100 × 100 mm. All specimens were consolidated using a high-frequency vibrating table. The specimens were demolded after 24 hours and then cured at more than 95% relative humidity (RH) and a temperature of 20 ± 2°C until 28 days.

2.1.2. Specimens

The casted specimens have a size of 100 × 100 × 100 mm. For the X-ray CT scanning, the dimension of the small cuboid sample is 20 mm (height) × 10 mm (side length). First, the marking was drawn on the surface of the original cast specimen. And then, the small cuboid samples were taken along the marking line by using a cutting machine. One of the three samples of each group was randomly selected for testing.

Figure 1 displays the appearance of the small cuboid specimen, where the surface features can be appreciated. There are scattered white polypropylene fibers on the cutting surface, as well as a small amount of pores. The dense domains with significantly darker color are coarse aggregates.

2.2. X-Ray Computed Tomography

The high-resolution microfocus industrial CT system Diondo d2 made in Germany, which uses the highest resolution digital radiography DR panel available for superior nondestructive testing, was used for detailed analysis of specimens. The X-ray CT system has a pixel resolution of 0.5 μm and capability to provide adequate contrast resolution for a 10 mm-thick concrete sample with use of a 300 kV X-ray tube. The working principle (see Figure 2) of this industrial X-ray CT system is that the inspection object is rotated 360 degrees within the detection range and irradiated, and a 2D image is acquired at each angle, which is reconstructed to obtain a digitized 3D image of the test sample without any image correction by using the software VGStudio MAX. Regular system analyses ensure the proper functioning of the X-ray CT system with its components and the evaluation environment.

2.3. 3D Image Reconstruction

Figure 3 illustrates the process of X-ray CT and the 3D image reconstruction. When multiple 2D projection images are acquired of an PFRC sample from many angles, mathematical tools are used to reconstruct a 3D representation of that object. To make the image easy to analyze and identify, important information such as coarse aggregate, polypropylene fiber, and pores are highlighted, and secondary information such as mortar are weakened. The 2D projection image needs to be segmented in order that the selected pixels are extracted and given the corresponding mark of material, before the 3D image reconstruction.

The image thresholding techniques are used to extract the components of sample microstructure, that is, the different components correspond to different gray values. The grayscale threshold is segmented using Otsu’s method, which is to select the appropriate threshold value and extract the required components from the background image based on maximizing “between class variance” of the segmented classes. The automatic threshold method may cause errors, such as coarse aggregates confused with cement mortar. In contrast, the result of manual segmentation with larger workload is more accurate. In order to accurately extract the components of the sample, this experiment uses an effectual combination of a manual threshold method and automatic segmentation.

In a grayscale picture of the sample, the value of the pixel may broadly be classified into two categories: the target component and the background. According to the probability theory, the larger the variance of different gray values, the smaller the error.

The aggregate has the highest gray value with the bright white color in the projection image. The color of cement mortar and polypropylene fiber is gray black and light black, respectively. Figure 4 shows the structures of the reconstructed 3D image of specimens and their features which are basically consistent with the original digital image.

3. Results and Discussion

3.1. Holistic Characterization of Specimens

Figure 5 illustrates the sliced X-ray images of the samples containing polypropylene fibers, showing the reconstructed 3D images with bright colors to highlight the morphology and spatial distribution of fibers and pores. The red color is given to the fibers, giving the blue color to the pores. The fibers, pores and aggregates are randomly distributed in the specimen. The polypropylene fibers, which are dispersed without obvious agglomeration, constitute a spatial network. The vast majority of the coarse aggregates are polygon in shape. The white spot with high brightness are the gravel with high density.

The vertical orthogonal slices were made by segmenting the 3D image based on grayscale. The profiles show that the majority of the pores, which are produced by the vaporisation of the water caused by the drying shrinkage or temperature variation, are distributed at the interfacial transition zone between the cement paste and aggregate or fiber, with a small amount of pores being located in the mortar matrix. The pores whose size was distributed between nanometer and micron are irregular in shape and are connected.

The microcracks that were formed during hydration appear in the interfacial transition zone without fiber crossing. The orientation of microcracks are along the surface of aggregate, with a maximum length of 3.2 mm and a maximum width of 0.3 mm. The microcracks are the initial imperfections of the internal structure with bad influence, because the paths of propagation of crack are seldom straight for the heterogeneity of material from the nanoscale to the macroscale.

3.2. Spatial Distribution of Fibers

Figure 6 shows the polypropylene fibers within samples and their distribution. The X-ray CT images provide novel insight into experimental data. The larger the volume fraction of fiber, the wider the range of distribution. The dispersion of fibers is substantially uniform, but the clumping of fibers, which can be visualized near the coarse aggregate of Figure 6(c), is also more obvious as the volume fraction increases. The presence of fibrous reinforcement in the interfacial transition zone, which the weakest area of the tensile capacity, plays an important role in improving the crack resistance of the concrete.

The clump of fibers may have led to some of nonuniform distribution in the specimen volume. The distribution of fibers appears to be randomly oriented. The directionality of fiber distribution is not strongly correlated with fiber volume fraction. The shape of most polypropylene fibers is fold line and curve with different degrees, and the shape of a small amount of fibers is approximately straight.

The total quantity of fibers within the inspection object was estimated with the stereology approach. The amount of polypropylene fibers seen through visual inspection of the image of specimen S3 is relatively small with distributing along the length direction of the sample. This scenario is formed by the coarse aggregate inside the sample shown by the blue dotted line superimposed on the image to aid in visualization, which affects the distribution and orientation of fibers. As illustrated in Figures 6(a) and 6(b), the fiber dispersion is uniform without coarse aggregate.

3.3. Spatial Distribution of Pores
3.3.1. Morphological Distribution

Figure 7 shows 3D image of distribution of pores within samples. In the process of three-dimensional reconstruction of micropores, different colors are used to distinguish the volume of pores, from blue to green to red, indicating that the volume gradually becomes larger. A large amount of blue pores being isolated uniformly disperse within samples.

The pore structures that develop during hydration form a complex network. The spatial shape of pores is mainly divided into spheres and irregular spaces. The spherical pores which contain capillary water or air are mainly distributed inside the cement mortar and far from the coarse aggregate. Some of these pores are isolated and have great implications in terms of transport properties of confined fluids (electrolytes) for cement paste durability [20]. The formation of spherical pores is not significantly affected by the polypropylene fibers. The pores with irregular space are connected in the interfacial transition zone. The irregular shape of these pores is mainly caused by the distribution of fibers and the outline of the coarse aggregate. The pores with irregular space in the interfacial transition zone are prone to form initial defects and crack first under load.

3.3.2. Distribution of Pore Diameter

The dispersion of diameter of overall pores is presented in Figure 8(a). For the three samples S1, S2, and S3, the distribution of pore diameter is generally the same. The larger the diameter of pores, the smaller the number of pores. The proportion of pores with the diameter in the range 0∼199 μm exceeds 70%. The percentage of pores with the diameter in the range 200∼399 μm is close to 20%.

Figure 8(b) shows the distribution of diameter in the range 0∼199 μm. As the diameter increases, the number of pores increases and then decreases. The number of pores with diameter in the range 60∼99 μm is the largest and close to 40%. The average diameter of pores is about 110 μm.

3.3.3. Distribution of Pore Volume

Figure 9(a) plots the distribution of volume and number of pores. The outer ring means the ratio of volume of individual pore to total volume. The central ring shows the total volume of overall pores. The inner ring displays the total number of pores with volume greater than 1 μm3. The total volume and number of pores are roughly proportional to the fiber volume fraction. These total volumes are 9.3 mm3, 20.4 mm3, and 18.5 mm3 for the three samples S1, S2, and S3. Also, the number of pores are 575, 1516, and 1496. The total volume and number of pores of sample S3 are slightly less than those of sample S2 because of the coarse aggregate occupying part of the space of sample S3. The number of pores with the ratio of volume to total volume more than 1% are 9, 16, and 14 for the three samples. The sum of volumes of these pores, whose number are about 1% of total number, exceed a half of total volume for each sample.

Figure 9(b) is the single-peaked distribution of volume of one hundred pores which were chosen by sorting from large to small. As the fiber volume fraction increases, the width of bottom of the triangle gradually increases, with the area of enclosed region enlarging, meaning that the number of pores with large volume rise. The porosity which is the ratio of total volume of pores to the volume of sample is 0.50%, 1.10%, and 0.85% for the three samples S1, S2, and S3. The porosity increases with fiber volume fraction.

4. Conclusions

(1)The microcracks that were formed during hydration appear in the interfacial transition zone, of which the orientation are along the surface of the coarse aggregate. The microcrack is the initial disadvantage because the paths of propagation of crack are seldom straight for the heterogeneity of the concrete.(2)The larger the volume fraction of fiber, the wider the range of distribution, and the more obvious the clumping of fibers. The shape of polypropylene fibers is mainly fold line and curve line with different curvature. The distribution and orientation of fibers are affected by the coarse aggregate.(3)The majority of pores are distributed at the interfacial transition zone between cement paste and aggregate or fiber. The proportion of pores with the diameter in the range 0∼199 μm exceeds 70%, whose mean diameter is about 110 μm. The amount of pores having large volume increases with the volume fraction of fiber enhancing. The porosity of fiber-reinforced concrete is about 1%.

Data Availability

All data included in this study are available upon request by contact with the corresponding author.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Acknowledgments

This paper was sponsored by National Science Foundation of China (51408083 and 51978114), Chongqing Science & Technology Commission (cstc2019jcyj-msxmX0796), and CREEC (KYY2019061(19-23)).

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Copyright © 2019 Yu Qin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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