Abstract

Fiber is effective in restricting cracks and improving the toughness of geopolymer composites, but few studies have focused on the surface crack characteristics of fiber-reinforced geopolymer composites. In this paper, after flexural tests of polypropylene fiber-reinforced geopolymer mortar, the surface cracking image was collected by a digital camera and cracking information was extract by deep learning. Finally, the cracking and fractal characteristics were specifically discussed. The semantic segmentation network can accurately extract surface cracks for calculating various parameters. The results showed that the mean intersection over union (mIoU) and mean pixel accuracy (mPA) of the cracks are 0.8451 and 0.9213, respectively. Generally, the crack length, width, area, and fractal dimension of the specimen are all increased with the increase in the fiber volume fraction. These crack parameters grow rapidly when the fiber content is small, and the growth of the crack parameters gradually slows down as the fiber volume fraction increases to approximately 1.5%. The highest crack parameter values were found in the geopolymer mortar, with a 0.48 water–binder ratio and 12 mm fiber length. The variation of the bottom crack length and the side crack fractal dimension can be used to represent the overall crack variation patterns. Meanwhile, the crack parameters increase with the increased fiber factor in a quadratic function. Based on these crack parameters, the critical fiber factor and dense fiber factor of polypropylene fiber-reinforced geopolymer mortar were 200 and 550, respectively. They are greater than those of fiber-reinforced Portland cementitious composites. The influence of various crack parameters on the flexural strength is in the order of the crack area, width, length, and fractal dimension.

Highlights

  • Geopolymer is an inorganic polymer composed of silicon oxide and alumina, which has good mechanical properties [1]

  • When the fiber volume fraction reaches 1.2%, the cracks are basically fully developed, so the complexity of the cracks does not continue to increase. Both the water–binder ratio and fiber length have an effect on the fractal dimension, but the fiber length has a greater effect on the cracks

  • We show the relationship between the fiber factor and the crack length, width, area, and fractal dimension, respectively

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Summary

Introduction

Geopolymer is an inorganic polymer composed of silicon oxide and alumina, which has good mechanical properties [1]. A further increase in the cotton fiber content will lead to fiber agglomeration, an increase in viscosity and the formation of voids, resulting in a decline in mechanical properties He et al investigated the effect of high-temperature heat treatment on the mechanical properties of carbon fiber-reinforced geopolymer composites [14]. The experimental results showed that the composites shrink less in the temperature range of 600 ◦ C to 1000 ◦ C and contain a higher content of particles and fibers while maintaining good mechanical strength. The quantitative analysis of the cracking and fractal properties can help to explore the factors affecting the mechanical properties of fiber-reinforced geopolymers It is important for the analysis of crack development in large scale members during practical applications

Specimen Preparation
Crack Parameter Extraction Using Deep Learning
Influence of Fiber Volume Fraction on Cracks
Crack Length
Crack Width
Crack Area
Crack Fractal Dimension
Influence of Fiber Factor on Cracks
Relationship between Crack Characteristics and Bending Strength
Findings
Discussion
Conclusions
Full Text
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