A performance evaluation of polypropylene fiber-reinforced mortars containing corn cob ash exposed to high temperature using the Taguchi and Taguchi-based Grey Relational Analysis methods

• Published in: Construction & building materials 2021-08, Vol.297, p.123792, Article 123792
• Main Authors: Arıcı, Erdinç, Çelik, Emrah, Keleştemur, Oğuzhan
• Format: Article
• Language: English
• Subjects: Corn Cob Ash; High temperature; Mortar; Polypropylene fiber; Taguchi-based Grey
• ISSN: 0950-0618; 1879-0526
• DOI: 10.1016/j.conbuildmat.2021.123792

•This paper analyzed the polypropylene fiber-reinforced mortars containing corn cob ash.•Effects of corn cob ash and polypropylene fiber on compressive strength were examined.•Compressive strength of mortars after high-temperature exposure was examined.•Taguchi and Taguchi based grey relational analysis methods were applied in this study.•Water/cement ratio was found the most important parameter on the responses. The sample material for this study was polypropylene fiber-reinforced mortar specimens containing different amounts of corn cob ash. The change in its compressive strength after high-temperature exposure was examined experimentally and statistically. To measure this, specimens with different levels of corn cob ash (0%, 5%, 10% and 20% by volume of cement), polypropylene fiber (0%, 0.03%, 0.06% and 0.1% by volume), water to cement ratio (0.4, 0.45, 0.5 and 0.6) and cement dosage (350 kg/m3, 400 kg/m3, 450 kg/m3 and 500 kg/m3) were prepared. The compressive strengths of the specimens were determined at room temperature (23 ± 2 °C) and at three high-temperature (400 °C, 500 °C, and 600 °C) exposure levels. In the experimental design, an L16(44) Taguchi orthogonal array was used for each temperature level. The statistical analyses of the experimental results were done in two steps. In the first step, the optimum values for each parameter were determined separately for each temperature level using Taguchi method. In the second step, Taguchi-based Grey Relational Analysis (TGA) determined the common optimum values for all temperatures. Additionally, analysis of variance (ANOVA) specified the impacts of the parameters on the experimental results. In the end, experimental and statistical results agreed well with each other, and it was concluded that it will be more appropriate to use Taguchi and TGA methods together in similar studies.