Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (1)
  • Open Access

    ARTICLE

    A Machine-Learning Approach for the Prediction of Fly-Ash Concrete Strength

    Shanqing Shao1, Aimin Gong1, Ran Wang1, Xiaoshuang Chen1, Jing Xu2, Fulai Wang1,*, Feipeng Liu2,3,*

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.12, pp. 3007-3019, 2023, DOI:10.32604/fdmp.2023.029545

    Abstract The composite exciter and the CaO to Na2SO4 dosing ratios are known to have a strong impact on the mechanical strength of fly-ash concrete. In the present study a hybrid approach relying on experiments and a machine-learning technique has been used to tackle this problem. The tests have shown that the optimal admixture of CaO and Na2SO4 alone is 8%. The best 3D mechanical strength of fly-ash concrete is achieved at 8% of the compound activator; If the 28-day mechanical strength is considered, then, the best performances are obtained at 4% of the compound activator. Moreover, the 3D mechanical strength… More >

Displaying 1-10 on page 1 of 1. Per Page