Computers and Concrete

  • 제14권3호
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  • Pages.247-262
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  • 2014
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  • 1598-8198(pISSN)
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  • 1598-818X(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Prediction of compressive strength of slag concrete using a blended cement hydration model

  • Wang, Xiao-Yong (Department of Architectural Engineering, Kangwon National University) ;
  • Lee, Han-Seung (School of Architecture & Architectural Engineering, Hanyang University)
  • 투고 : 2014.02.13
  • 심사 : 2014.07.06
  • 발행 : 2014.09.30
⟨ 이전 논문 다음 논문 ⟩

초록

Partial replacement of Portland cement by slag can reduce the energy consumption and $CO_2$ emission therefore is beneficial to circular economy and sustainable development. Compressive strength is the most important engineering property of concrete. This paper presents a numerical procedure to predict the development of compressive strength of slag blended concrete. This numerical procedure starts with a kinetic hydration model for cement-slag blends by considering the production of calcium hydroxide in cement hydration and its consumption in slag reactions. Reaction degrees of cement slag are obtained as accompanied results from the hydration model. Gel-space ratio of hardening slag blended concrete is determined using reaction degrees of cement and slag, mixing proportions of concrete, and volume stoichiometries of cement hydration and slag reaction. Furthermore, the development of compressive strength is evaluated through Powers' gel-space ratio theory considering the contributions of cement hydration and slag reaction. The proposed model is verified through experimental data on concrete with different water-to-binder ratios and slag substitution ratios.

키워드

과제정보

연구 과제번호 : An integrated program for predicting chloride penetration into reinforced concrete structures by using a Cement Hydration Model

연구 과제 주관 기관 : National Research Foundation

참고문헌

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피인용 문헌

  1. Expansion behavior of low-strength steel slag mortar during high-temperature catalysis vol.16, pp.2, 2015, https://doi.org/10.12989/cac.2015.16.2.261