Evaluation of mathematical models for prediction of slump, compressive strength and durability of concrete with limestone powder

被引:3
|
作者
Bazrafkan, Aryan [1 ]
Habibi, Alireza [2 ]
Sayari, Arash [1 ]
机构
[1] Islamic Azad Univ, Sanandaj Branch, Dept Civil Engn, Sanandaj, Iran
[2] Shahed Univ, Dept Civil Engn, Tehran, Iran
关键词
concrete; limestone powder; slump; compressive strength; water penetration; prediction; SILICA FUME; HARDENED PROPERTIES; HYDRATION HEAT; CEMENT; FILLER; MARBLE; FRESH;
D O I
10.12989/acc.2020.10.6.463
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Multiple mathematical modeling for prediction of slump, compressive strength and depth of water penetration at 28 days were performed using statistical analysis for the concrete containing waste limestone powder as partial replacement of sand obtained from experimental program reported in this research. To extract experimental data, 180 concrete cubic samples with 20 different mix designs were investigated. The twenty non-linear regression models were used to predict each of the concrete properties including slump, compressive strength and water depth penetration of concrete with waste limestone powder. Evaluation of the models using numerical methods showed that the majority of models give acceptable prediction with a high accuracy and trivial error rates. The 15-term regression models for predicting the slump, compressive strength and water depth were found to have the best agreement with the tested concrete specimens.
引用
收藏
页码:463 / 478
页数:16
相关论文
共 50 条
  • [1] Effect of Dolomite Limestone Powder on The Compressive Strength of Concrete
    Mikhailova, Olesia
    Yakovlev, Grigory
    Maeva, Irina
    Senkov, Sergey
    MODERN BUILDING MATERIALS, STRUCTURES AND TECHNIQUES, 2013, 57 : 775 - 780
  • [2] Prediction of Concrete Compressive Strength and Slump by Machine Learning Methods
    Cihan, M. Timur
    ADVANCES IN CIVIL ENGINEERING, 2019, 2019
  • [3] Support vector machine for prediction of the compressive strength of no-slump concrete
    Sobhani, J.
    Khanzadi, M.
    Movahedian, A. H.
    COMPUTERS AND CONCRETE, 2013, 11 (04): : 337 - 350
  • [4] Prediction of the compressive strength of no-slump concrete: A comparative study of regression, neural network and ANFIS models
    Sobhani, Jafar
    Najimi, Meysam
    Pourkhorshidi, Ali Reza
    Parhizkar, Tayebeh
    CONSTRUCTION AND BUILDING MATERIALS, 2010, 24 (05) : 709 - 718
  • [5] Durability of concrete with addition of limestone powder
    Sawicz, Z
    Heng, SS
    MAGAZINE OF CONCRETE RESEARCH, 1996, 48 (175) : 131 - 137
  • [6] Assessment of concrete compressive strength prediction models
    Fayez Moutassem
    Samir E. Chidiac
    KSCE Journal of Civil Engineering, 2016, 20 : 343 - 358
  • [7] Assessment of concrete compressive strength prediction models
    Moutassem, Fayez
    Chidiac, Samir E.
    KSCE JOURNAL OF CIVIL ENGINEERING, 2016, 20 (01) : 343 - 358
  • [8] Effects of Incorporation of Marble Powder Obtained by Recycling Waste Sludge and Limestone Powder on Rheology, Compressive Strength, and Durability of Self-Compacting Concrete
    Alyousef, Rayed
    Benjeddou, Omrane
    Soussi, Chokri
    Khadimallah, Mohamed Amine
    Mohamed, Abdeliazim Mustafa
    ADVANCES IN MATERIALS SCIENCE AND ENGINEERING, 2019, 2019
  • [9] Machine-Learning-Based Predictive Models for Compressive Strength, Flexural Strength, and Slump of Concrete
    Vargas, John F.
    Oviedo, Ana I.
    Ortega, Nathalia A.
    Orozco, Estebana
    Gomez, Ana
    Londono, Jorge M.
    APPLIED SCIENCES-BASEL, 2024, 14 (11):
  • [10] Effect of limestone powder on compressive strength and drying shrinkage of mixed sand concrete
    He, Zhi-Hai
    Du, Shi-Gui
    He, Ling-Ling
    Xia, Meng-Lu
    Bai, Ke
    Journal of Advanced Microscopy Research, 2015, 10 (03) : 233 - 236