Predicting the strength of seashell concrete using Adaptive Neuro-Fuzzy Inference System: An experimental study

IF 0.5 Q4 ENGINEERING, MULTIDISCIPLINARY Revista Iteckne Pub Date : 2023-07-11 DOI:10.15332/iteckne.v20i1.2917
P. Sangeetha, M. Shanmugapriya
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Abstract

Seashell is a hard, protective outer layer created by an animal that lives in the sea. Empty seashells are often found washed up on beaches by beachcombers. This marine by-product can be used to partial replacement of coarse aggregate or cement in concrete. This paper describes the use of seashell powder and aggregate in the concrete for the replacement of cement and coarse aggregate. The effect of seashell waste in the concrete was studied in terms of its compressive strength, tensile strength and flexural strength after 28, 56 and 90 days of curing. The replacement of cement by seashell powder were 10%, 20% and 30% and replacement of coarse aggregate by seashell aggregate are 5%, 10% and 15%. The properties of seashell concrete were compared with control mix specimen of M25 grade of concrete. Also, it has been tried to predict the strength of the seashell concrete utilizing adaptive neuro-fuzzy inference system (ANFIS). The prediction of strength with the tool was agreeable with the experimental strength with the minimal error of less than 5%. This study concludes, that partial replacement of cement and coarse aggregate by seashell waste enhances the mechanical properties of the concrete significantly and enable proper utilization of these seashell waste as sustainable material for the concrete.
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基于自适应神经模糊推理系统的贝壳混凝土强度预测实验研究
贝壳是由生活在海洋中的动物创造的坚硬的保护性外层。空贝壳经常被海滩游客冲上海滩。这种海洋副产品可用于部分替代混凝土中的粗骨料或水泥。本文介绍了贝壳粉和骨料在混凝土中代替水泥和粗骨料的应用。从养护28、56和90天后的抗压强度、抗拉强度和抗弯强度三个方面研究了贝壳废弃物对混凝土的影响。贝壳粉对水泥的替代率分别为10%、20%和30%,贝壳骨料对粗骨料的替代率为5%、10%和15%。将贝壳混凝土的性能与M25级混凝土的对照试件进行了比较。此外,还尝试利用自适应神经模糊推理系统(ANFIS)对贝壳混凝土的强度进行预测。该工具对强度的预测与实验强度一致,最小误差小于5%。本研究得出结论,用贝壳废弃物部分替代水泥和粗骨料,显著提高了混凝土的力学性能,并使这些贝壳废弃物能够作为混凝土的可持续材料得到适当利用。
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来源期刊
Revista Iteckne
Revista Iteckne ENGINEERING, MULTIDISCIPLINARY-
自引率
50.00%
发文量
3
审稿时长
24 weeks
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