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Prediction of the Tensile Strength of Normal and Steel Fiber Reinforced Concrete Exposed to High Temperatures

Author(s): ORCID

Medium: journal article
Language(s): English
Published in: International Journal of Concrete Structures and Materials, , n. 1, v. 15
DOI: 10.1186/s40069-021-00485-6
Abstract:

The tensile strength of concrete has a great impact on the performance of concrete structures, especially for members exposed to high temperatures. The inclusion of steel fibers in concrete is one of the measures to retrieve the loss of tensile strength. The previous equations for the prediction of the tensile strength, are valid for conventional concrete and can predict the tensile strength after high-temperature exposure. Therefore, they are unsatisfactory for forecasting the tensile strength of plain and steel fiber reinforced concrete under high-temperature exposure. To establish a model that can effectively simulate the tensile strength of plain concrete, specimens with compressive strengths of 20–80 MPa are tested. Then by performing tensile strength tests on the specimens containing various content of steel fiber, an equation for prediction of the tensile strength at the ambient temperature is proposed. Meanwhile, the tensile strength tests are conducted at temperatures of 100–800 °C to develop a model for high-temperature exposure. The results indicate that an increase of compressive strength from 20 to 84 improves the tensile strength by 169.4%, and the incorporation of 0.25 and 0.5% of steel fibers can improve the tensile strength of normal concrete by 58.48 and 80.29% on average at the tested temperatures, respectively. Moreover, the proposed model is able to predict the tensile strength of normal and steel fiber reinforced concrete exposed to high temperatures accurately. This equation would help a wider application of the steel fibers in the construction industry with the risk of a fire accident.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1186/s40069-021-00485-6.
  • About this
    data sheet
  • Reference-ID
    10746233
  • Published on:
    04/12/2023
  • Last updated on:
    04/12/2023
 
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