Stress strain behavior of hybrid steel-PVA fiber reinforced cementitious composites under uniaxial compression

2018 ◽  
Vol 188 ◽  
pp. 349-360 ◽  
Author(s):  
Linzhu Sun ◽  
Qiang Hao ◽  
Junliang Zhao ◽  
Dongyan Wu ◽  
Fang Yang
Keyword(s):  
Uniaxial Compression ◽  
Cementitious Composites ◽  
Fiber Reinforced ◽  
Stress Strain ◽  
Strain Behavior ◽  
Pva Fiber ◽  
Fiber Reinforced Cementitious Composites

Experimental Study on the Uniaxial Compression Curves of Green High-Performance Fiber-Reinforced Cementitious Composites (GHPFRCC)

2014 ◽  
Vol 893 ◽  
pp. 201-204
Author(s):  
Xiu Ling Li ◽  
Juan Wang
Keyword(s):  
Uniaxial Compression ◽  
High Performance ◽  
Strain Curve ◽  
Cementitious Composites ◽  
Peak Strain ◽  
Fiber Reinforced ◽  
Compression Tests ◽  
Stress Strain ◽  
High Performance Fiber ◽  
Fiber Reinforced Cementitious Composites

Green high performance fiber reinforced cementitious composites (GHPFRCC) is the optimized mix proportion of engineered cementitious composites (ECC) with high volume of fly ash and polyvinyl alcohol (PVA) fiber. To study the compressive performance, the prism stress-strain relationship of GHPFRCC is the focus in this study. There are sixteen groups of GHPFRCC specimens with the size 40mm×40mm×160mm. The compressive stress-strain curves were obtained based on the uniaxial compression tests. Experimental results show that the uniaxial compression stress-strain curve belongs to the skewed unimodal curve. The peak strain can steadily reach more than 0.005, and it has put up a great plastic deformation capacity and post-peak ductility. It has still reserved some residual strength even when the strain is up to a bigger value. The research achievements can promote the application of GHPFRCC in the practical engineering.

Experimental Study on Mechanical Properties of PVA Fiber Reinforced Tailings Cementitious Composites

2012 ◽  
Vol 598 ◽  
pp. 618-621 ◽  
Author(s):  
Wen Bo Bao ◽  
Cheng Hong Wang ◽  
Shao Feng Zhang ◽  
Zhi Qiang Huang
Keyword(s):  
Fiber Length ◽  
Iron Ore ◽  
Cementitious Composites ◽  
Fiber Reinforced ◽  
Flexural Test ◽  
Multiple Cracking ◽  
Iron Ore Tailings ◽  
Mix Proportion ◽  
Pva Fiber ◽  
Fiber Reinforced Cementitious Composites

A type of ecological engineered cementitious composites, which use iron ore tailings to replace fine grinding quartz sand in PVA fiber reinforced cementitious composites, was developed. The flexural strength and toughness of this material were studied by four-point flexural test with samples of beam and sheet. The results show that the fiber reinforced tailings cementitious composites exhibit the characteristics of multiple cracking, high ductility and flexural toughness. The studies indicate that the mix proportion and the fiber length have a significant influence on the properties of this material, particularly for tensile toughness.

scholarly journals Compressive Strength Prediction of PVA Fiber-Reinforced Cementitious Composites Containing Nano-SiO2 Using BP Neural Network

Materials ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 521 ◽  
Author(s):  
Ting-Yu Liu ◽  
Peng Zhang ◽  
Juan Wang ◽  
Yi-Feng Ling
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Compressive Strength ◽  
Bp Neural Network ◽  
Cementitious Composites ◽  
Cementitious Composite ◽  
Fiber Reinforced ◽  
Nano Sio2 ◽  
Pva Fiber ◽  
Fiber Reinforced Cementitious Composites

In this study, a method to optimize the mixing proportion of polyvinyl alcohol (PVA) fiber-reinforced cementitious composites and improve its compressive strength based on the Levenberg-Marquardt backpropagation (BP) neural network algorithm and genetic algorithm is proposed by adopting a three-layer neural network (TLNN) as a model and the genetic algorithm as an optimization tool. A TLNN was established to implement the complicated nonlinear relationship between the input (factors affecting the compressive strength of cementitious composite) and output (compressive strength). An orthogonal experiment was conducted to optimize the parameters of the BP neural network. Subsequently, the optimal BP neural network model was obtained. The genetic algorithm was used to obtain the optimum mix proportion of the cementitious composite. The optimization results were predicted by the trained neural network and verified. Mathematical calculations indicated that the BP neural network can precisely and practically demonstrate the nonlinear relationship between the cementitious composite and its mixture proportion and predict the compressive strength. The optimal mixing proportion of the PVA fiber-reinforced cementitious composites containing nano-SiO2 was obtained. The results indicate that the method used in this study can effectively predict and optimize the compressive strength of PVA fiber-reinforced cementitious composites containing nano-SiO2.

scholarly journals Study on Mechanical Properties and Constitutive Equation of Hybrid Fiber Reinforced Cementitious Composites Under Static Loading

2016 ◽  
Vol 10 (1) ◽  
pp. 482-491 ◽  
Author(s):  
Huixian Yang ◽  
Jing Li ◽  
Yansheng Huang
Keyword(s):  
Mechanical Properties ◽  
Tensile Strength ◽  
Elastic Modulus ◽  
Steel Fiber ◽  
Cementitious Composites ◽  
Peak Strain ◽  
Fiber Reinforced ◽  
Hybrid Fiber ◽  
Stress Strain ◽  
Fiber Reinforced Cementitious Composites

The Quasi-static mechanical properties of hybrid fiber (steel fiber and Polyvinyl alcohol (PVA) fiber) reinforced cementitious composites (HFRCC(SP)) were investigated by compressive and tensile experiments. The compressive strength, peak strain, elastic modulus and tensile strength are studied as compared with that of engineered cementitious composite (ECC). Study results indicate that steel fibers can improve the compressive and tensile strength of HFRCC(SP) but the peak strain of HFRCC(SP) decreases. The formulas modified based on codes are proposed to calculate compressive peak strain, elastic modulus and tensile strength. The relationship between tensile strain at peak load and tensile strength of HFRCC with different volume fractions of polyethylene fiber and steel fiber were studied and the tensile stress-strain relation was presented. The parameters k1 and k2 of constitutive formulas for fiber reinforced high strength concrete presented by Mansur are modified to describe the stress-strain curve of HFRCC(SP), the modified formulas show good agreement with the experimental results.

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