Case Studies in Construction Materials (Jul 2024)

Three-dimensional microscale numerical simulation of fiber-reinforced concrete under sulfate freeze-thaw action

  • Lei Gan,
  • Guohao Liu,
  • Jun Liu,
  • Hongwei Zhang,
  • Xianwei Feng,
  • Lechen Li

Journal volume & issue
Vol. 20
p. e03308

Abstract

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To investigate the sulfate freeze-thaw resistance of hybrid fiber-reinforced concrete, a three-dimensional microscale stochastic fiber-reinforced concrete model was proposed. The hybrid fiber and aggregate were generated randomly in the microscale model. Pore expansion theory was employed to reflect the sulfate freeze-thaw cycles. A plastic damage model and element removal technique were introduced to represent the initiation and propagation of cracks in concrete. The proposed model was taken to simulate the compressive and splitting tensile test of basalt-polypropylene fiber-reinforced concrete. The model was verified through a comparison between the numerical results and experiments, and the concrete damage process and strength were investigated. The stress and deformation evolution of a channel concrete slab repaired by basalt-polypropylene fibers were analyzed under the environment of sulfate freeze-thaw cycles. The maximum deviation of fiber concrete uniaxial compressive and tensile strength between the numerical calculation and test is 2.63%. ASF damage initiates at the concrete surface and progresses toward its interior. Basalt-polypropylene fibers act as bridges in the concrete matrix during the frost heaving process and alleviate stress concentration in crack tips effectively. With the extension of ASF cycles, the peak strain increases, and the peak stress of concrete gradually decreases. After 300 cycles of sulfate freeze-thaw, the maximum horizontal displacement, compressive stress, and tensile stress of the concrete slab repaired by fiber are decreased by 4.98%, 28.20%, and 20.38%, respectively. The research is beneficial for the restoration and fortification of channel engineering, as well as the prediction of long-term functionality.

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