RSM-based modeling and optimization of self-consolidating mortar to predict acceptable ranges of rheological properties

被引:71
作者
Aziminezhad, Mehran [1 ]
Mandikhani, Mandi [1 ]
Memarpour, Mohammad Mandi [1 ]
机构
[1] Imam Khomeini Int Univ, Dept Civil Engn, Qazvin, Iran
关键词
Response surface method; Self-consolidating mortar; Optimization; Silica fume; Slag; Rheological properties; ARTIFICIAL NEURAL-NETWORK; RESPONSE-SURFACE METHODOLOGY; COMPACTING CONCRETE; FLY-ASH; MECHANICAL-PROPERTIES; CEMENT PASTE; SILICA FUME; COMPRESSIVE STRENGTH; GENETIC ALGORITHM; MIX DESIGN;
D O I
10.1016/j.conbuildmat.2018.09.019
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Using a high or low amount of cementitious material, water-cement ratio (W/C), and superplasticizer (SP) cause instability and reduction in compressive strength of concrete according to their impact factor and interaction. However, making a concrete with the optimum amount of variables could improve its properties. So, optimization of concrete ingredient due to absence of proper mix design code is required. The remarkable features of response surface method (RSM) are modeling and optimization. This study was carried out with the aim of investigating rheological and hardened properties of self-consolidating mortar (SCM) using RSM with four factors (silica fume, slag, SP and W/C). Rheological criteria of EFNARC code were used to specify the optimum restriction. According to statistical analysis and validation of equations, it can be concluded that RSM is a confident and efficient method to evaluate the properties of SCM. In addition, according to model, the silica fume increased EFNARC code limitation ranges by improving the rheological properties, however, slag had an almost neutral role. In the best case, the addition of silica fume, reduced the segregation up to 5 times. Although silica fume increased the compressive strength up to 45%, slag totally decreased the compressive strength. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1200 / 1213
页数:14
相关论文
共 43 条
[1]   Predicting the ingredients of self compacting concrete using artificial neural network [J].
Abu Yaman, Mahmoud ;
Abd Elaty, Metwally ;
Taman, Mohamed .
ALEXANDRIA ENGINEERING JOURNAL, 2017, 56 (04) :523-532
[2]   Development of eco-efficient self-compacting concrete with waste marble powder using the response surface method [J].
Alyamac, Kursat Esat ;
Ghafari, Ehsan ;
Ince, Ragip .
JOURNAL OF CLEANER PRODUCTION, 2017, 144 :192-202
[3]   Effect of binder composition on time-dependent stability and robustness characteristics of self-consolidating mortar subjected to prolonged agitation [J].
Amini, Kamran ;
Mehdipour, Iman ;
Hwang, Soo Duck ;
Shekarchi, Mohammad .
CONSTRUCTION AND BUILDING MATERIALS, 2016, 112 :654-665
[4]  
[Anonymous], 2003, 1881116 BS
[5]  
[Anonymous], 2016, C150C150M ASTM INT
[6]   Properties of self-compacting mortar made with various types of sand [J].
Benabed, Benchaa ;
Kadri, El-Hadj ;
Azzouz, Lakhdar ;
Kenai, Said .
CEMENT & CONCRETE COMPOSITES, 2012, 34 (10) :1167-1173
[7]   Fresh and mechanical behavior of a self-compacting concrete with additions of nano-silica, silica fume and ternary mixtures [J].
Bernal, J. ;
Reyes, E. ;
Massana, J. ;
Leon, N. ;
Sanchez, E. .
CONSTRUCTION AND BUILDING MATERIALS, 2018, 160 :196-210
[8]   Response surface methodology (RSM) as a tool for optimization in analytical chemistry [J].
Bezerra, Marcos Almeida ;
Santelli, Ricardo Erthal ;
Oliveira, Eliane Padua ;
Villar, Leonardo Silveira ;
Escaleira, Luciane Amlia .
TALANTA, 2008, 76 (05) :965-977
[9]  
Douglas C., 2012, WILEY DESIGN ANAL EX
[10]  
EFNARC, 2005, European Federation Dedicated to Specialist Construction Chemicals and Concrete Systems: Specifications and Guidelines for Self-compacting Concrete