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Numerical Analysis of a Novel Shaft Lining Structure in Coal Mines Consisting of Hybrid-Fiber-Reinforced Concrete
 
 
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Editorial

Numerical Study of Concrete

by
Vipulkumar Ishvarbhai Patel
School of Engineering and Mathmatical Sciences, La Trobe University, Bendigo, Victoria 3552, Australia
Crystals 2021, 11(1), 74; https://doi.org/10.3390/cryst11010074
Submission received: 15 January 2021 / Accepted: 15 January 2021 / Published: 18 January 2021
(This article belongs to the Special Issue Numerical Study of Concrete)
This Special Issue, “Numerical Study of Concrete”, consists of 22 research articles.
Wang et al. [1] developed a finite element model for the numerical simulation of a hybrid-fiber-reinforced concrete (HFRC) shaft lining structure. The numerical results indicate that the maximum hoop stress position of the HFRC shaft lining presents a transition trend from the inside surface to the outside surface; the hoop strain of shaft lining concrete is always compressive, and the inside surface is greater than the outside surface. Kolesnikov [2] presents the load–displacement and stress–strain responses of concrete under uniaxial compression as well as three-point bending. The non-destructive test (NDT) method was proposed by Lim et al. [3] for the measurement of concrete’s compressive strength. The water absorption of concrete with different binders was tested by Ding et al. [4]. The pore structure of concrete was investigated by mercury intrusion porosimetry. It was found that the water absorption of concrete with mineral admixtures is lower. This is due to the existence of a reasonable pore structure. Zhao et al. [5] used the finite element method for modeling the fundamental behavior of T-beams with carbon fiber-reinforced plastic under impact loads. The results show that the overall stiffness of the T-beams was significantly improved due to the carbon fiber-reinforced plastic strips.
Zainal et al. [6] conducted an experimental study for predicting the behavior of hybrid fiber-reinforced concrete materials with a high-range water-reducing admixture. It was concluded that the Ferro with a Ferro mix combination improved the performance of concrete in the elastic stage, while the Ferro with the ultra-net combination had the highest compressive strain surplus in the plastic stage. Ahmad et al. [7] utilized artificial neural networks for determining the properties of fiber-reinforced polymers-confined concrete. Lelovic et al. [8] presented a new method for the experimental determination of cohesion at pre-set angles of shear deformation. Alrshoudi et al. [9] developed the concept of a new pre-packed aggregate fiber-reinforced concrete which is reinforced with polypropylene (PP) waste carpet fibres, investigating its mechanical properties and impact resistance under drop weight impact loads. Mohammadyan-Yasouj et al. [10] investigated the thermal performance of alginate concrete reinforced with basalt fiber. The effects of the admixtures, erosion age, concentration of sulfate solution, and sulfate erosion on the mechanical properties of mortar were investigated by Liu et al. [11]. Benbow et al. [12] presented the development of a coupled modeling simulator for assessing the evolution of a geological repository in the near field for radioactive waste disposal where concrete is used as backfill.
Muhtar et al. [13] predicted the stiffness of bamboo-reinforced concrete beams from an experimental results database using artificial neural networks. Karam et al. [14] carried out an analytical investigation on the concrete damage progress of the Perfobond shear connector under the influence of various lateral pressures. Song et al. [15] simulated the adsorption characteristics of five types of common alkanol-amine inhibitors on C-S-H gel in the alkaline liquid environment using the molecular dynamics and grand canonical Monte Carlo methods. Javed et al. [16] developed a model for predicting the ultimate axial strength of concrete-filled steel tubular columns under axial compression. Javed et al. [17] utilized novel Gene Expression Programming and regression techniques for determining the compressive strength of sugarcane bagasse ash concrete. Phutthimethakul et al. [18] used flue gas desulfurization gypsum, construction and demolition waste, and oil palm waste trunks to produce concrete bricks. Chen et al. [19] experimentally and numerically studied the blast-resistant performance of steel fiber-reinforced concrete and polyvinyl alcohol fiber-reinforced concrete panels with a contact detonation test.
The study presented by Alyousef et al. [20] aims to investigate the resistance of concrete composites reinforced with waste metalized plastic fibres to sulphate and acid attacks. Yehia et al. [21] studied the effect of aggregate type on concrete’s compressive strength. The durability of polyvinyl alcohol fiber-reinforced cementitious composite containing nano-SiO2 was evaluated by Liu et al. [22] using the adaptive neuro-fuzzy inference system.

Funding

This research received no external funding.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Acknowledgments

The contribution of all the authors is gratefully acknowledged. The editor would like to express his thanks to the Crystals Editorial Office, and, on top of that, to Debbie Yang (a Technical Coordinator of the issue) for the excellent communication, support, and friendly and professional attitude.

Conflicts of Interest

The author declares no conflict of interest.

References

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  2. Kolesnikov, G. Analysis of concrete failure on the descending branch of the load-displacement curve. Crystals 2020, 10, 921. [Google Scholar] [CrossRef]
  3. Lim, Z.H.; Lee, F.W.; Mo, K.H.; Lim, J.H.; Yew, M.K.; Kwong, K.Z. Compressive strength forecasting of air-entrained rubberized concrete during the hardening process utilizing elastic wave method. Crystals 2020, 10, 912. [Google Scholar] [CrossRef]
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  5. Zhao, H.; Kong, X.; Fu, Y.; Gu, Y.; Wang, X. Numerical investigation on dynamic response of RC T-Beams strengthened with CFRP under impact loading. Crystals 2020, 10, 890. [Google Scholar] [CrossRef]
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  11. Liu, P.; Chen, Y.; Yu, Z. Effects of erosion form and admixture on cement mortar performances exposed to sulfate environment. Crystals 2020, 10, 774. [Google Scholar] [CrossRef]
  12. Benbow, S.J.; Kawama, D.; Takase, H.; Shimizu, H.; Oda, C.; Hirano, F.; Takayama, Y.; Mihara, M.; Honda, A. A coupled modeling simulator for near-field processes in cement engineered barrier systems for radioactive waste disposal. Crystals 2020, 10, 767. [Google Scholar] [CrossRef]
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  14. Karam, M.S.; Yamamoto, Y.; Nakamura, H.; Miura, T. Numerical evaluation of the Perfobond (PBL) shear connector subjected to lateral pressure using coupled Rigid Body Spring Model (RBSM) and Nonlinear Solid Finite Element Method (FEM). Crystals 2020, 10, 743. [Google Scholar] [CrossRef]
  15. Song, Z.; Cai, H.; Liu, Q.; Liu, X.; Pu, Q.; Zang, Y.; Xu, N. Numerical simulation of adsorption of organic inhibitors on C-S-H Gel. Crystals 2020, 10, 742. [Google Scholar] [CrossRef]
  16. Javed, M.F.; Farooq, F.; Memon, S.A.; Akbar, A.; Khan, M.A.; Aslam, F.; Alyousef, R.; Alabduljabbar, H.; Rehman, S.K. New prediction model for the ultimate axial capacity of concrete-filled steel tubes: An evolutionary approach. Crystals 2020, 10, 741. [Google Scholar] [CrossRef]
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  18. Phutthimethakul, L.; Kumpueng, P.; Supakata, N. Use of flue gas desulfurization gypsum, construction and demolition waste, and oil palm waste trunks to produce concrete bricks. Crystals 2020, 10, 709. [Google Scholar] [CrossRef]
  19. Chen, L.; Sun, W.; Chen, B.; Xu, S.; Liang, J.; Ding, C.; Feng, J. A comparative study on blast-resistant performance of steel and PVA fiber-reinforced concrete: Experimental and numerical analyses. Crystals 2020, 10, 707. [Google Scholar] [CrossRef]
  20. Alyousef, R.; Mohammadhosseini, H.; Alrshoudi, F.; Tahir, M.; Alabduljabbar, H.; Mohamed, A.M. Enhanced performance of concrete composites comprising waste metalised polypropylene fibres exposed to aggressive environments. Crystals 2020, 10, 696. [Google Scholar] [CrossRef]
  21. Yehia, S.; Abdelfatah, A.; Mansour, D. Effect of aggregate type and specimen configuration on concrete compressive strength. Crystals 2020, 10, 625. [Google Scholar] [CrossRef]
  22. Liu, T.Y.; Zhang, P.; Li, Q.F.; Hu, S.W.; Ling, Y.F. Durability assessment of PVA fiber-reinforced cementitious composite containing nano-SiO2 using adaptive neuro-fuzzy inference system. Crystals 2020, 10, 347. [Google Scholar] [CrossRef]
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Patel, V.I. Numerical Study of Concrete. Crystals 2021, 11, 74. https://doi.org/10.3390/cryst11010074

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Patel VI. Numerical Study of Concrete. Crystals. 2021; 11(1):74. https://doi.org/10.3390/cryst11010074

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Patel, Vipulkumar Ishvarbhai. 2021. "Numerical Study of Concrete" Crystals 11, no. 1: 74. https://doi.org/10.3390/cryst11010074

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