Effect of Plant Fiber on Early Properties of Geopolymer.

Geopolymer (GP) is environmentally friendly, has good mechanical properties and long-term workability, and has broad application prospects. However, due to the poor tensile strength and toughness of GPs, they are sensitive to microcracks, which limits their application in engineering. Fiber can be added to GPs to limit the growth of cracks and enhance the toughness of the GP. Plant fiber (PF) is cheap, easy to obtain, and abundant in source, which can be added to GP to improve the properties of composites. This paper reviews recent studies on the early properties of plant fiber-reinforced geopolymers (PFRGs). In this manuscript, the properties of PFs commonly used for GP reinforcements are summarized. The early properties of PFRGs were reviewed, including the rheological properties of fresh GPs, the early strength of PFRGs, and the early shrinkage and deformation properties of PFRGs. At the same time, the action mechanism and influencing factors of PFRGs are also introduced. Based on the comprehensive analysis of the early properties of PFRGs, the adverse effects of PFs on the early properties of GPs and the solutions were summarized.

Research on the prediction of blasting fragmentation in open-pit coal mines based on KPCA-BAS-BP.

The blasting block size of open-pit mines is influenced by many factors, and the influencing factors have a very complex nonlinear relationship. Traditional empirical formulas and a single neural network model cannot meet the requirements of modern blasting safety. To improve the prediction accuracy of blasting block size, the measured data of Beskuduk open-pit coal mine is used as training and testing samples. Seven factors including rock tensile strength, rock compressive strength, and blast hole spacing are selected as input variables of the prediction model. The average size of blasting fragmentation X50 is used as the output variable of the prediction model. The kernel principal component analysis (KPCA) is adopted to reduce the dimensionality of the input variables. The beetle antennae search algorithm (BAS) is selected to optimize the parameters of the initial weights and thresholds of the back propagation (BP) neural network. Finally, prediction model of blasting fragmentation in open-pit coal mine based on KPCA-BAS-BP is established. The results show that the average relative error of the model is 1.77%, and the root mean square error is 1.52%. Compared with the unoptimized BP neural network and the BP neural network optimized by the artificial bee colony algorithm (ABC) model, this model has higher prediction accuracy and is more suitable for predicting the blasting block size of open-pit coal mines, it provides a new method for predicting the fragmentation of blasting under the influence of multiple factors, filling the gap in related theoretical research, and has certain practical application value.

Properties of 3D Printing Fiber-Reinforced Geopolymers Based on Interlayer Bonding and Anisotropy.

The engineering applications and related researches of 3D printing fiber-reinforced geopolymers are becoming more and more extensive. However, compared with traditional mould-casted cement-based materials, the properties of 3D-printed fiber-reinforced geopolymers are significantly different, and their interlayer bonding and anisotropy effects are less studied, so in-depth analysis and summary are needed. Similar to common cement-based materials, the reinforcement fibers for geopolymers include not only traditional fibers, such as steel fibers and carbon fibers, but also synthetic polymer fibers and natural polymer fibers. These fibers have unique properties, most of which have good mechanical properties and bonding properties with geopolymers, as well as excellent crack resistance and enhancement. This paper summarizes and analyzes the effects of traditional fibers, polymer fibers, plant fibers and other reinforcement fibers on the properties of 3D-printed fiber-reinforced geopolymers, especially on the interlayer bonding and anisotropy. The influence of the flow and thixotropic properties of fiber-reinforced fresh geopolymer on the weak bond and anisotropy between layers is summarized and analyzed. At the same time, the influence of fibers on the compressive strength, flexural strength and interlayer binding strength of the hardened geopolymers is investigated. The effect of fibers on the anisotropy of 3D-printed geopolymers and the methods to improve the interlayer binding degree are summarized. The limitations of 3D printing fiber-reinforced geopolymers are pointed out and some suggestions for improvement are put forward. Finally, the research on 3D printing fiber-reinforced geopolymers is summarized. This paper provides a reference for further improving the interlayer bonding strength of 3D-printed fiber-reinforced geopolymers. At the same time, the anisotropy properties of 3D-printed fiber-reinforced geopolymers are used to provide a basis for engineering applications.