• Title/Summary/Keyword: VMA (Viscosity Modifying Admixture)

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Analyzing the Usable Range of Viscosity Modifying Admixture for Prevention Material Segregation of Normal Strength Grade Concrete (일반강도 콘크리트의 재료분리 발생 방지를 위한 증점제 사용 범위 분석)

  • Lee, Yu-Jeong;Han, Dong-Yeop
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2020.11a
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    • pp.83-84
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    • 2020
  • The purpose of this study is to achieve a sufficient fluidity without segregation for normal compressive strength grade concrete mixture. The major obstacle of achieving fluidity of normal compressive strength grade concrete mixture is segregation. Therefore, in this research, the proper use of VMA was suggested to prevent segregation.

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Analyzing the VMA Performance for Segregation Resistance of Normal Compressive Strength Grade Concrete (일반강도 콘크리트의 재료 분리 발생 방지를 위한 증점제의 성능 분석)

  • Lee, Yu Jeong;Lee, Hyang Sun;Han, Dong Yeop
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2020.06a
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    • pp.56-57
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    • 2020
  • The purpose of this study is to achieve a sufficient fluidity without segregation for normal compressive strength grade concrete mixture. The major obstacle of achieving fluidity of normal compressive strength grade concrete mixture is segregation. Hence, in this research, VMA was used to prevent segregation.

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Viscosity analysis of lightweight foamed mortar for foam stability (기포 안정성 확보를 위한 경향 기포 모르타르의 점도 분석)

  • Lee, Hyangsun;Son, Baegeun;Jeon, Jongwoon;Han, Dongyeop
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2018.05a
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    • pp.52-53
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    • 2018
  • In this study, viscosity analysis of the lightweight foamed mortar was conducted to evaluate the foam stability. According to a series of experiment, void volume related with density of the mixture and viscosity of the mixture were infleunced by water-to-binder ratio and addition of viscosity modifying admixture (VMA). Especially, the stability of the foam inside the mortar was confirmed with adding VMA.

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Analysis of Rheological Parameters for Determining Segregation of Mid-Range Workability Concrete (중유동 콘크리트의 재료분리 경계 판단을 위한 레올로지 정수 범위 분석)

  • Lee, Yu Jeong;Kim, Young Ki;Han, Dong Yeop
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2021.05a
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    • pp.142-143
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    • 2021
  • The purpose of this study is to analyze the extent of the rheology parameters at the segregation boundary of mid-range workability concrete. In addition, it was intended to present the extent of the rheology parameters of the normal strength concrete with segregation resistance using the determination of segregation occurrence of concrete and the use of the rheology parameters. However, it was confirmed that segregation occurs even if the measured rheology parameters is in the range of the suggested rheology parameters. Therefore, it is determined that the conditions under which segregation occurs will provide fundamental data that can be rheological defined. Additional studies are also needed on the relationship between rheological parameters and segregation.

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Predicting strength of SCC using artificial neural network and multivariable regression analysis

  • Saha, Prasenjit;Prasad, M.L.V.;Kumar, P. Rathish
    • Computers and Concrete
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    • v.20 no.1
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    • pp.31-38
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    • 2017
  • In the present study an Artificial Neural Network (ANN) was used to predict the compressive strength of self-compacting concrete. The data developed experimentally for self-compacting concrete and the data sets of a total of 99 concrete samples were used in this work. ANN's are considered as nonlinear statistical data modeling tools where complex relationships between inputs and outputs are modeled or patterns are found. In the present ANN model, eight input parameters are used to predict the compressive strength of self-compacting of concrete. These include varying amounts of cement, coarse aggregate, fine aggregate, fly ash, fiber, water, super plasticizer (SP), viscosity modifying admixture (VMA) while the single output parameter is the compressive strength of concrete. The importance of different input parameters for predicting the strengths at various ages using neural network was discussed in the study. There is a perfect correlation between the experimental and prediction of the compressive strength of SCC based on ANN with very low root mean square errors. Also, the efficiency of ANN model is better compared to the multivariable regression analysis (MRA). Hence it can be concluded that the ANN model has more potential compared to MRA model in developing an optimum mix proportion for predicting the compressive strength of concrete without much loss of material and time.

Self-consolidating concrete filled steel tube columns - Design equations for confinement and axial strength

  • Lachemi, M.;Hossain, K.M.A.;Lambros, V.B.
    • Structural Engineering and Mechanics
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    • v.22 no.5
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    • pp.541-562
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    • 2006
  • This paper compares the performance of axially loaded concrete filled steel tube (CFST) columns cast using a conventionally vibrated normal concrete (NC) and a novel self-consolidating concrete (SCC) made with a new viscosity modifying admixture (VMA). A total of sixteen columns with a standard compressive strength of about 50 MPa for both SCC and NC were tested by applying concentric axial load through the concrete core. Columns were fabricated without and with longitudinal and hoop reinforcement (Series I and Series II, respectively) in addition to the tube confinement. The slenderness of the columns expressed as height to diameter ratio (H/D) ranged between 4.8 and 9.5 for Series CI and between 3.1 and 6.5 for Series CII. The strength and ductility of SCC columns were found comparable to those of their NC counterparts as the maximum strength enhancement in NC columns ranged between 1.1% and 7.5% only. No significant difference in strain development was found due to the presence of SCC or NC or due to the presence of longitudinal and hoop reinforcement. Biaxial stress development in the steel tube as per von Mises yield criterion showed similar characteristics for both SCC and NC columns. The confined strength ($f^{\prime}_{cc}$) of SCC was found to be lower than that of NC and $f^{\prime}_{cc}$ also decreased with the increase of slenderness of the columns. Analytical models for the prediction of confined concrete strength and axial strength of CFST columns were developed and their performance was validated through test results. The proposed models were found to predict the axial strength of CFST columns better than existing models and Code based design procedures.