ABSTRACT
It is widely known that adding fibers to concrete improves the properties of concrete, which has a brittle behavior. Although concrete has high compressive strength but poor tensile strength, this has led researchers to offer a variety of ways to deal with this weakness. The use of fibers is one of the methods used to enhance concrete behavior. Fire is one of the most important cases in structures; if the temperature is high or its duration is long, it will cause serious damage to the structure. The present study is an experimental study in which different concrete samples with different amounts of polypropylene fibers and different cement content are exposed once at a normal temperature of 25 °C and again at high temperatures, including 250 °C and 500 °C. The effect of temperature on the compressive and tensile strengths of concrete containing 0.5%, 1.5%, and 2% polypropylene fibres and with cement contents of 200 kg/m3, 260 kg/m3, and 320 kg/m3. The compressive and tensile strength was evaluated at curing 28 days of strength. The results showed a severe strength loss for all concretes after exposure to 500 °C. The relative compressive strengths of concretes containing PP fibers were higher than those of concretes without PP fibers. The tensile strength of concrete was more sensitive to high temperatures than the compressive strength. Based on the test results, it can be concluded that adding 2% PP fibers can significantly promote the residual mechanical properties of concrete during heating. The compressive strength at 25 °C with 2% PP fibres decreases by 43% with cement contents of 200 kg/m3 and 64% with cement contents of 260 kg/m3, and 37% with cement contents of 320 kg/m3, respectively. Also, the compressive strength at 500 °C with 2% PP fibres decreases by 61% with 200 kg/m3, 59% with 260 kg/m3, and 42% with cement contents of 320 kg/m3, respectively.
ABSTRACT
The impact of artificial intelligence (AI) in education can be viewed as a multi-attribute group decision-making (MAGDM) problem, in which several stakeholders evaluate the advantages and disadvantages of AI applications in educational settings according to distinct preferences and criteria. A MAGDM framework can assist in providing transparent and logical recommendations for implementing AI in education by methodically analyzing the trade-offs and conflicts among many components, including ethical, social, pedagogical, and technical concerns. A novel development in fuzzy set theory is the 2-tuple linguistic q-rung orthopair fuzzy set (2TLq-ROFS), which is not only a generalized form but also can integrate decision-makers quantitative evaluation ideas and qualitative evaluation information. The 2TLq-ROF Schweizer-Sklar weighted power average operator (2TLq-ROFSSWPA) and the 2TLq-ROF Schweizer-Sklar weighted power geometric (2TLq-ROFSSWPG) operator are two of the aggregation operators we create in this article. We also investigate some of the unique instances and features of the proposed operators. Next, a new Entropy model is built based on 2TLq-ROFS, which may exploit the preferences of the decision-makers to obtain the ideal objective weights for attributes. Next, we extend the VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) technique to the 2TLq-ROF version, which provides decision-makers with a greater space to represent their decisions, while also accounting for the uncertainty inherent in human cognition. Finally, a case study of how artificial intelligence has impacted education is given to show the applicability and value of the established methodology. A comparative study is carried out to examine the benefits and improvements of the developed approach.