TY - JOUR
T1 - A new intelligence fuzzy-based hybrid metaheuristic algorithm for analyzing the application of tea waste in concrete as natural fiber
AU - Cao, Yan
AU - Zandi, Yousef
AU - Rahimi, Abouzar
AU - Wu, Yujia
AU - Fu, Leijie
AU - Wang, Qiangfeng
AU - Denić, Nebojša
AU - Amine Khadimallah, Mohamed
AU - Milič, Momir
AU - Paunović, Marija
N1 - Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2021/11
Y1 - 2021/11
N2 - Concrete is an ecologically friendly substance in which green concrete is a revolutionary subject in concrete industry records. The emphasis of this study was on the impact of Tea Waste (CA) as natural fiber on hardened concrete characteristics as a substitution for cement. Taking account of CO2 generation in cement manufacture, green concrete decreases emissions of CO2 into environmental production to an environmentally-friendly technique of pollution prevention. C1, C2, C3, C4 were then made of concrete of a class of 1, 2, 3, 4 kg reinforced in 1 m3 mix, then prepared and molded 4 distinct concrete types. After 28 days, the flexural and compressive strength tests have been carried out in a proper curing environment on the concrete. The findings were evaluated using the adaptive inference system neuro-fuzzy (ANFIS) to accurately predict the concrete flexural and compressive strength with low error rates. Finally, the reinforced concrete with tea wastes raised the water requirement, but reduced the compressive and flexural strength compared to control mix, however, it was raised while using up to 5.4 kg waste in 1 m3 concrete. The result showed that up to 5 kg of tea wastes in 1 m3 of concrete could also be utilized as natural fibers. Also, ANFIS could show its outperformance in analyzing test results in predicting the compressive and flexural strength.
AB - Concrete is an ecologically friendly substance in which green concrete is a revolutionary subject in concrete industry records. The emphasis of this study was on the impact of Tea Waste (CA) as natural fiber on hardened concrete characteristics as a substitution for cement. Taking account of CO2 generation in cement manufacture, green concrete decreases emissions of CO2 into environmental production to an environmentally-friendly technique of pollution prevention. C1, C2, C3, C4 were then made of concrete of a class of 1, 2, 3, 4 kg reinforced in 1 m3 mix, then prepared and molded 4 distinct concrete types. After 28 days, the flexural and compressive strength tests have been carried out in a proper curing environment on the concrete. The findings were evaluated using the adaptive inference system neuro-fuzzy (ANFIS) to accurately predict the concrete flexural and compressive strength with low error rates. Finally, the reinforced concrete with tea wastes raised the water requirement, but reduced the compressive and flexural strength compared to control mix, however, it was raised while using up to 5.4 kg waste in 1 m3 concrete. The result showed that up to 5 kg of tea wastes in 1 m3 of concrete could also be utilized as natural fibers. Also, ANFIS could show its outperformance in analyzing test results in predicting the compressive and flexural strength.
KW - Concrete
KW - Fuzzy-based hybrid
KW - Natural Fiber
KW - Tea Waste
UR - https://www.scopus.com/pages/publications/85114499688
U2 - 10.1016/j.compag.2021.106420
DO - 10.1016/j.compag.2021.106420
M3 - Article
AN - SCOPUS:85114499688
SN - 0168-1699
VL - 190
JO - Computers and Electronics in Agriculture
JF - Computers and Electronics in Agriculture
M1 - 106420
ER -
