Identifying the bond and abrasion behavior of alkali activated concretes by central composite design method

Balcikanli M., Turker H. T., Ozbay E., KARAHAN O., ATİŞ C. D.

CONSTRUCTION AND BUILDING MATERIALS, vol.132, pp.196-209, 2017 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 132
  • Publication Date: 2017
  • Doi Number: 10.1016/j.conbuildmat.2016.10.034
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.196-209
  • Keywords: Bond behavior, Abrasion resistance, Alkali activated concrete, Central composite design, Statistical analysis, FLY-ASH, SLAG CONCRETE, ENGINEERING PROPERTIES, STRENGTH, PERFORMANCE, RESISTANCE, PARAMETERS, CORROSION, ANCHOR, PASTES
  • Kayseri University Affiliated: No


In this paper, bond strength and abrasion resistance of alkali activated concretes (AAC) were examined experimentally by using the central composite design (CCD) method. AAC were designed and produced considering the sodium concentration (SC), silicate modules (SM), curing temperature (CT) and exposed curing time (ECT) as the CCD's independent parameters. Twenty-one AAC mixtures were established depend on the various combinations of independent parameters in CCD at 95% confidence level. Effects of each independent parameter on the dependent parameters were statistically analyzed using experimental measurements and best possible combination of the independent parameters were defined for the maximization of the compressive strength, split tensile strength, UPV and bond behavior of AAC and for the minimization of abrasion value of AAC by solving the multi-objective optimization problems which is generated using the proposed regression models for the dependent parameters. Test results demonstrate that all studied independent parameters have the noteworthy effect on the properties of AAC statistically; however, the most effective independent parameter is SC. The optimum values of the parameters studied were defined as CT of 66 degrees C, ECT of 14.76 h, SC of 5.72% and SM of 1.0 for the defined multi-objective optimization problem. (C) 2016 Elsevier Ltd. All rights reserved.