scholarly journals Effect of aggregate particle shape and granulometry on the workability and mechanical properties of glass reinforced concrete

2019 ◽  
Author(s):  
Rimvydas Moceiki ◽  
Asta Kičaitė ◽  
Gintautas Skripkiūnas
Keyword(s):  
Reinforced Concrete ◽  
Particle Shape ◽  
Glass Fibers ◽  
Round Shape ◽  
Crushed Granite ◽  
Glass Fibre Reinforced ◽  
Numeric Representation ◽  
Shape Characteristics ◽  
Good Workability ◽  
Fibre Matrix

Modern alkali resistant glass fibers (ARG) modified with 17% ZrO2 are getting more popular as reinforcement of cementitious matrixes. Typical matrix compositions with quartz, Portland cement, 13 mm length ARG glass fibres and PCE superplasticizer can offer good workability, product quality and highly increased mechanical characteristics. In production of self compacting fibre reinforced premix highly siliceous fine sands with nearly round shape particles are usually preferred. This article investigates influence of particle shape for workability of glass fibre reinforced concrete when alternative fillers- crushed granite and regular sand are used. 12 compositions were made whith different quantities of fillers, changing quartz from 0% to 50% with alternative aggregates. Slump tests according to EN 1170-1 were made and showed major impact of particle shape characteristics on mix workability. When quantity of altrernative aggrates was increased, slump of fresh mix decreased and fibre- matrix segregation occurred. New workability factor W is offered and values calculated, to have numeric representation of workability. Alternative aggregates had no clear influence for flexural strenght, when beams 40×40×160 were tested. Compressive strength dropped by 25% when regular sand was used. Typical quartz matrix resulted in lower water absorbtion.

scholarly journals Analytical Study on Reinforced Concrete Beam With Carbon, Steel and Glass Fibers

2021 ◽  
pp. 708-712
Author(s):  
Muthamil Priyatharshini G ◽  
Rama Devi K
Keyword(s):  
Reinforced Concrete ◽  
Carbon Steel ◽  
Concrete Beam ◽  
Glass Fibers ◽  
Construction Materials ◽  
Reinforced Concrete Beam ◽  
Fibre Reinforced Concrete ◽  
Steel Fibre Reinforced Concrete ◽  
Glass Fibre Reinforced ◽  
Preliminary Study

Reinforced concrete mostly used in construction materials in the world. Fibre reinforced concrete in which small and discontinuous fibres are dispersed commonly. Fibre reinforced concrete used in fibres may be in different materials like carbon, steel and glass fibres etc. In addition of these fibres increases the compressive strength, tensile strength, flexural strength, and impact strength of concrete. carbon fibre reinforced concrete (CFRC) containing fibres of 1.5% and 0.2 of poisons ratio and steel fibre reinforced concrete (SFRC) containing fibres of 1.5% and 0.21 of poisons ratio and Glass fibre reinforced concrete (GFRC) containing fibres of 1.5% and 0.2 of poisons ratio. The results that comparing normal beam with fibre beam results. Its type and dimensions are selected based on preliminary study using ANSYS Software.

scholarly journals Preparation and characterization of glass fibers – polymers (epoxy) bars (GFRP) reinforced concrete for structural applications

2016 ◽  
Vol 11 (1) ◽  
pp. 15-22
Author(s):  
Saeed Alkjk ◽  
Rafee Jabra ◽  
Salem Alkhater
Keyword(s):  
Tensile Strength ◽  
Reinforced Concrete ◽  
Concrete Beams ◽  
Glass Fibers ◽  
Reinforce Concrete ◽  
Experimental Program ◽  
Gfrp Bars ◽  
Structural Applications ◽  
Steel Bars ◽  
Deflection Test

Abstract The paper presents some of the results from a large experimental program undertaken at the Department of Civil Engineering of Damascus University. The project aims to study the ability to reinforce and strengthen the concrete by bars from Epoxy polymer reinforced with glass fibers (GFRP) and compared with reinforce concrete by steel bars in terms of mechanical properties. Five diameters of GFRP bars, and steel bars (4mm, 6mm, 8mm, 10mm, 12mm) tested on tensile strength tests. The test shown that GFRP bars need tensile strength more than steel bars. The concrete beams measuring (15cm wide × 15cm deep × and 70cm long) reinforced by GFRP with 0.5 vol.% ratio, then the concrete beams reinforced by steel with 0.89 vol.% ratio. The concrete beams tested on deflection test. The test shown that beams which reinforced by GFRP has higher deflection resistance, than beams which reinforced by steel. Which give more advantage to reinforced concrete by GFRP.

scholarly journals Prediction Model of Minimum Void Ratio for Various Sizes/Shapes of Sandy Binary Mixture

2020 ◽  
Vol 2020 ◽  
pp. 1-19
Author(s):  
Chaojie Shen ◽  
Zhaoyang Xu ◽  
Jie Yin ◽  
Jinfeng Wu
Keyword(s):  
Particle Size ◽  
Binary Mixture ◽  
Particle Shape ◽  
Void Ratio ◽  
Soil Mechanics ◽  
Influence Factors ◽  
Natural Sand ◽  
Undetermined Coefficient ◽  
Shape Characteristics ◽  
Different Origins

The minimum void ratio is a fundamental physical index for evaluating particle properties in soil mechanics, ceramic processing, and concrete mixes. Previous research found that both particle size distribution and particle shape characteristics would affect minimum void ratio, while the current research generally uses a linear model to estimate the minimum void ratio of a binary mixture, ignoring quantitative effect of particle shape on the minimum void ratio. Based on a study of binary mixtures of natural sand from three different origins and iron particles of two different shapes, this paper analyzes the influence factors of the minimum void ratio, and a quadratic nonlinear model is proposed for estimating the minimum void ratio of binary mixture. The model contains only one undetermined coefficient, a, the value of which is correlated to the particle sphericity, particle size, and particle size ratio. A theoretical calculation formula for the coefficient a is proposed to quantitatively analyze the effects of these three factors on the size of the parameters. In the end, the model is used to estimate the minimum void ratios of sand and substitute particles from different producing areas; the average difference between the estimated values and the fitted values is about 2.03%, suggesting that the estimated values of the model fit well with the measured data.

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