Effects of Strain Rate and Temperature on the Flexural Behavior of Basalt and Glass Textile–Reinforced Concrete

Published on Aug 1, 2018in Journal of Materials in Civil Engineering2.169
· DOI :10.1061/(ASCE)MT.1943-5533.0002387
Sai Liu6
Estimated H-index: 6
(Hunan University),
Deju Zhu27
Estimated H-index: 27
(Hunan University)
+ 1 AuthorsCaijun Shi71
Estimated H-index: 71
(Hunan University)
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Abstract
AbstractFlexural behavior of textile-reinforced concrete (TRC) samples were investigated by using three-point bending test systems under quasi-static and low-velocity (1.0–4.5  m/s) impact loadings...
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#1M. E. Gunes (Karabük University)
#2B. Y. Pekmezci (ITU: Istanbul Technical University)
Last. Zehra Canan Girgin (YTU: Yıldız Technical University)H-Index: 3
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The textile reinforced mortar (TRM) composites are widely utilized for the seismic strengthening of masonry walls subjected to in-plane and out-of-plane actions. The probability of out-of-plane failure via snap-through mechanism is dominated by the flexural characteristics of relatively slender masonry wall. In this study, a rapid and early decisive procedure is proposed to direct the design of TRM composite through the bending tests combining accelerated ageing. The durability of natural hydrau...
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#1Sai Liu (Hunan University)H-Index: 6
#2Prashant Rawat (Hunan University)H-Index: 7
Last. Deju Zhu (Hunan University)H-Index: 27
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Abstract Textile reinforced concretes (TRCs) have many extraordinary features that make them a future-ready material exposed to complex environmental situations. However, current knowledge related to TRCs under mechanical loading and environmental conditions is not fully explored as compared to conventional fiber reinforced concretes. The present work investigates the quasi-static pullout performance of single-yarn and textile type (AR-glass and basalt fiber) reinforced cement mortars under diff...
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#1Wei Wang (Hunan University)H-Index: 4
#2Peng Shi (Hunan University)H-Index: 1
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Residual strength of corroded textile-reinforced concrete (TRC) is evaluated using the deep learning-based method, whose feasibility is demonstrated by experiment. Compared to the traditional method, the proposed method does not need to know the climatic conditions in which the TRC exists. Firstly, the information about the faster region-based convolutional neural networks (Faster R-CNN) is described briefly, and then procedures to prepare datasets are introduced. Twenty TRC specimens were fabri...
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#1Yawei Fang (Hunan University)H-Index: 2
#2Zhi Fang (Hunan University)H-Index: 11
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Abstract This paper experimentally investigated the effect of temperature on the transverse impact response of preloaded carbon fiber reinforced polymer (CFRP) wire. The CFRP wires with a glass transition temperature of 99 °C were tested in the temperature range of -40 to 80 °C using a drop-weight impact test system. The results show that the maximum impact force, maximum wire tension and transverse deflection at fracture of the wire increased as the temperature increased from -40 to 80 °C, due ...
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