Probabilistic modeling of geopolymer concrete using response surface methodology

被引:11
|
作者
Kathirvel, Parthiban [1 ]
Kaliyaperumal, Saravana Raja Mohan [1 ]
机构
[1] SASTRA Univ, Sch Civil Engn, Thanjavur 613401, India
来源
COMPUTERS AND CONCRETE | 2017年 / 19卷 / 06期
关键词
geopolymer concrete; slag; mechanical properties; response surface methodology; box-behnken design; FLY-ASH; COMPRESSIVE STRENGTH; ALKALINE ACTIVATION; TEMPERATURE; PREDICTION;
D O I
10.12989/cac.2017.19.6.737
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Geopolymer Concrete is typically proportioned with activator solution leading to moderately high material cost. Such cost can be enduring in high value added applications especially when cost savings can be recognized in terms of reduction in size of the members. Proper material selection and mix proportioning can diminish the material cost. In the present investigation, a total of 27 mixes were arrived considering the mix parameters as liquid-binder ratio, slag content and sodium hydroxide concentration to study the mechanical properties of geopolymer concrete (GPC) mixes such as compressive strength, split tensile strength and flexural strength. The derived statistical Response Surface Methodology is beleaguered to develop cost effective GPC mixes. The estimated responses are not likely to contrast in linear mode with selected variables; a plan was selected to enable the model of any response in a quadratic manner The results reveals that a fair correlation between the experimental and the predicted strengths.
引用
收藏
页码:737 / 744
页数:8
相关论文
共 50 条
  • [1] DESIGN AND OPTIMIZATION OF MECHANICAL PROPERTIES OF GEOPOLYMER CONCRETE COMPOSITES USING RESPONSE SURFACE METHODOLOGY
    Mary, I. Regina
    Pushpa, T. Bhagavathi
    REVISTA ROMANA DE MATERIALE-ROMANIAN JOURNAL OF MATERIALS, 2022, 52 (02): : 122 - 133
  • [2] APPLICATION OF RESPONSE SURFACE METHODOLOGY IN THE OPTIMIZATION OF FLY ASH GEOPOLYMER CONCRETE
    Sun, Qingwei
    Zhu, Han
    Li, Haoyu
    Zhu, Haiyang
    Gao, Mingming
    REVISTA ROMANA DE MATERIALE-ROMANIAN JOURNAL OF MATERIALS, 2018, 48 (01): : 45 - 52
  • [3] Probabilistic Modelling of Compressive Strength of Concrete Using Response Surface Methodology and Neural Networks
    Hacene, S. M. A. Boukli
    Ghomari, F.
    Schoefs, F.
    Khelidj, A.
    ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2014, 39 (06) : 4451 - 4460
  • [4] Probabilistic Modelling of Compressive Strength of Concrete Using Response Surface Methodology and Neural Networks
    S. M. A. Boukli Hacene
    F. Ghomari
    F. Schoefs
    A. Khelidj
    Arabian Journal for Science and Engineering, 2014, 39 : 4451 - 4460
  • [5] Strength-based design mix methodology of one-part geopolymer concrete using response surface methodology
    Sharma, Divya
    Singh, Ran Bir
    MULTISCALE AND MULTIDISCIPLINARY MODELING EXPERIMENTS AND DESIGN, 2025, 8 (01)
  • [6] Optimization of concrete walls using the response surface methodology
    Yepes, Victor
    Martinez-Munoz, David
    Marti, Josi, V
    CMMOST 2019: 5TH INTERNATIONAL CONFERENCE ON MECHANICAL MODELS IN STRUCTURAL ENGINEERING (CMMOST 2019), 2019, : 603 - 615
  • [7] Nanocellulose reinforced zeolite based geopolymer concrete: Density analysis through response surface methodology
    Tay, Chai Hua
    Mazlan, Norkhairunnisa
    Wayayok, Aimrun
    Basri, Mohd Salahuddin
    Mustafa, Mohd
    Abdullah, Albakri
    MATERIALS TODAY-PROCEEDINGS, 2022, 66 : 2873 - 2882
  • [8] Statistical modeling and mix design optimization of fly ash based engineered geopolymer composite using response surface methodology
    Zahid, Muhammad
    Shafiq, Nasir
    Isa, M. Hasnain
    Gil, Lluis
    JOURNAL OF CLEANER PRODUCTION, 2018, 194 : 483 - 498
  • [9] Modeling of Concrete Composite Induced by Multi-walled Carbon Nanotubes Using Response Surface Methodology
    Isaac, Rimal R. S.
    Subin, S.
    Prakash, P.
    Praseetha, P. K.
    INTERNATIONAL JOURNAL OF ENGINEERING RESEARCH IN AFRICA, 2015, 17 : 8 - 13
  • [10] Influence of admixtures on properties of concrete and optimization using response surface methodology
    Vasudevan, Shankar
    Poornima, V
    Balachandran, Meera
    MATERIALS TODAY-PROCEEDINGS, 2020, 24 : 650 - 661