• Title/Summary/Keyword: ASTM C 1260

Search Result 33, Processing Time 0.016 seconds

ASR Resistance of Ternary Blended Binder Adding Ultra Fine Mineral Admixture (고분말도 광물성 혼화재를 혼입한 삼성분계 결합재의 ASR 저항성 평가)

  • Jeon, Sung Il;Ahn, Sang Hyeok;An, Ji Hwan;Yun, Kyung Ku;Nam, Jeong-Hee
    • International Journal of Highway Engineering
    • /
    • v.15 no.5
    • /
    • pp.81-89
    • /
    • 2013
  • PURPOSES : This study is to evaluate ASR(alkali silica reactivity) resistance of ternary blended binder adding ultra fine mineral admixture. METHODS : This study analyzes ASR expansion using ASTM C 1260 and 1567. RESULTS : This study showed that the fineness of mineral admixture had no effect on ASR expansion. The expansion of ternary blended binder(UFFA 20%+FGGBS 10%) were below 0.1%, and this binder met the ASR standard. Also when adding the CSA expansion agent, ASR expansion slightly decreased. The expansion of latex modified mixture increased by 80% comparing plain mixture. CONCLUSIONS : Ternary blended binder met the ASR standard, and this binder is available in concrete bridge deck overlay.

The Inhibition Effect of Alkali-Silica Reaction in Concrete by Pozzolanic Effect of Metakaolin (메타카오린의 포조란 효과에 의한 콘크리트 내 알칼리-실리카 반응 억제 효과)

  • Lee Hyomin;Jun Ssang-Sun;Hwang Jin-Yeon;Jin Chi-Sub;Yoon Jihae;Ok Soo Seok
    • Journal of the Mineralogical Society of Korea
    • /
    • v.17 no.3
    • /
    • pp.277-288
    • /
    • 2004
  • Alkali-silica reaction (ASR) is a chemical reaction between alkalies in cement and chemically unstable aggregates and causes expansion and cracking of concrete. In the Present study, we studied the effects of metakaolin, which is a newly introduced mineral admixture showing excellent pozzolainc reaction property, on the inhibition of ASR. We prepared mortar-bars of various replacement ratios of metakaolin and conducted alkali-silica reactivity test (ASTM C 1260), compressive strength test and flow test. We also carefully analyzed the mineralogical changes in hydrate cement paste by XRD qualitative analysis. The admixing of metakaolin caused quick pozzolanic reaction and hydration reaction that resulted in a rapid decrease in portlandite content of hydrated cement paste. The expansion by ASR was reduced effectively as metakaolin replaced cement greater than 15%. This resulted in that the amounts of available portlandite decreased to less than 10% in cement paste. It is considered that the inhibition of ASR expansion by admixing of metakaolin was resulted by the combined processes that the formation of deleterious alkali-calcium-silicate gel was inhibited and the penetration of alkali solution into concrete was retarded due to the formation of denser, more homogeneous cement paste caused by pozzolanic effect. Higher early strength (7 days) than normal concrete was developed when the replacement ratios of metakaolin were greater than 15%. And also, late strength (28 days) was far higher than normal concrete for the all the replacement ratios of metakaolin. The development patterns of mechanical strength for metakaolin admixed concretes reflect the rapid pozzolanic reaction and hydration properties of metakaolin.

Estimation of various amounts of kaolinite on concrete alkali-silica reactions using different machine learning methods

  • Aflatoonian, Moein;Mirhosseini, Ramin Tabatabaei
    • Structural Engineering and Mechanics
    • /
    • v.83 no.1
    • /
    • pp.79-92
    • /
    • 2022
  • In this paper, the impact of a vernacular pozzolanic kaolinite mine on concrete alkali-silica reaction and strength has been evaluated. For making the samples, kaolinite powder with various levels has been used in the quality specification test of aggregates based on the ASTM C1260 standard in order to investigate the effect of kaolinite particles on reducing the reaction of the mortar bars. The compressive strength, X-Ray Diffraction (XRD) and Scanning Electron Microscope (SEM) experiments have been performed on concrete specimens. The obtained results show that addition of kaolinite powder to concrete will cause a pozzolanic reaction and decrease the permeability of concrete samples comparing to the reference concrete specimen. Further, various machine learning methods have been used to predict ASR-induced expansion per different amounts of kaolinite. In the process of modeling methods, optimal method is considered to have the lowest mean square error (MSE) simultaneous to having the highest correlation coefficient (R). Therefore, to evaluate the efficiency of the proposed model, the results of the support vector machine (SVM) method were compared with the decision tree method, regression analysis and neural network algorithm. The results of comparison of forecasting tools showed that support vector machines have outperformed the results of other methods. Therefore, the support vector machine method can be mentioned as an effective approach to predict ASR-induced expansion.