Predicting the strength of seashell concrete using Adaptive Neuro-Fuzzy Inference System: An experimental study
Keywords:
Seashell concrete, Seashell powder, Seashell aggregate, Curing time, ANFIS, Sustainable concrete
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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References
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2. Ghasan Fahim Huseien, Abdul Rahman Mohd Sam, Kwok Wei Shah, A.M.A. Budiea Jahangir Mirza (2019) Utilizing spend garnets as sand replacement in alkali-activated mortars containing fly ash and GBFS. Constr Building Mater 225, pp. 132–145.
3. Zahra Keshavarz, Davood Mostofinejad(2019) Steel chip and porcelain ceramic wastes used as replacements for coarse aggregates in concrete. J Cleaner Produ 230, pp. 339–351.
4. Babita S. Upadhyay S. Gupta K.Abhishek. Yadav M. Sumit, Bindal P. Meena K. Ravi, Kumar Pankaj (2019) Review Paper on Partial Replacement of Cement and Aggregates with Various Industrial Waste Material and Its Effect on Concrete Properties, Lecture Notes in Civil Engineering, pp. 111-117.
5. Ardalan Baradaran-Nasiri, Mahdi Nematzadeh(2017) The effect of elevated temperatures on the mechanical properties of concrete with fine recycled refractory brick aggregate and aluminate cement. Constr Building Mater 147, pp. 865–875.
6. D. Foti, D. Cavallo(2018) Mechanical behavior of concretes made with non-conventional organic origin calcareous aggregates. Constr Building Mater 179, pp. 100–106.
7. A.E. Richardson, T. Fuller(2013) Sea shells used as partial aggregate replacement in concrete Emerald Insight: Newcastle upon Tyne, UK, Stuct. Surv. pp. 347–354.
8. Medina, C, De Rojas, M.S, Frías, M(2012) Reuse of sanitary ceramic wastes as coarse aggregate in eco-efficient concretes. Cement Concr. Compos. 34, pp. 48-54.
9. Medina, C, Frías, M, De Rojas, M.S(2012) Microstructure and properties of recycled concretes using ceramic sanitary ware industry waste as coarse aggregate. Constr. Build. Mater. 31, pp. 112-118.
10. Higashiyama, H, Yagishita, F, Sano, M Takahashi, O(2012) Compressive strength and resistance to chloride penetration of mortars using ceramic waste as fine aggregate. Constr. Build. Mater. 26, pp. 96-101.
11. Torkittikul, P, Chaipanich, A(2010) Utilization of ceramic waste as fine aggregate within Portland cement and fly ash concretes. Cement Concr. Compos. 32, pp. 440 – 449.
12. Ay, N, Unal, M(2000) The use of waste ceramic tile in cement production. Cement Concr. Res. 30, pp. 497 – 499.
13. Pereira-de-Oliveira, L.A, Castro-Gomes, J.P, Santos, P.M(2012) The potential pozzolanic activity of glass and red-clay ceramic waste as cement mortars components. Constr. Build. Mater. 31, pp.197 – 203.
14. Bernal SA, Rodríguez ED, Kirchheim AP, Provis JL(2016) Management and valorisation of wastes through use in producing alkali-activated cement materials. J Chem Technol Biotechnol. 91, pp. 2365–2388.
15. N. Drouiche, P. Cuellar, F. Kerkar, S. Medjahed, N. Boutouchent-Guerfi, M.O. Hamou(2014) Recovery of solar grade silicon from kerf loss slurry waste, Renew. Sust. Energy Rev. 32, pp. 936–943.
16. H.S.G.K. Murthy(2015) Evolution and present status of silicon carbide slurry recovery in silicon wire sawing, Resour. Conserv. Recy. 104, pp. 194–205.
17. S.A. Sergiienko, B.V. Pogorelov, V.B. Daniliuk(2014) Silicon and silicon carbide powders recycling technology from wire-saw cutting waste in slicing process of silicon ingots, Sep. Purif. Technol. 133, pp. 16–21.
18. Engr. Abdul Ghanyoor khan. Bazid khan (2017) Effect of Partial Replacement of Cement by Mixture of Glass Powder and Silica Fume Upon Concrete Strength, Int. J. Engg. Works. 4, pp.124-135.
19. H. Torkian, Z. Keshavarz (2018) Determining the Drift in Reinforced Concrete Building Using ANFIS Soft Computing Modeling, Computational Engineering and Physical Modeling 1-1, pp. 1-11.
20. F. Khademi, S. M. Jamal, N. Deshpande, S. Londhe(2016) Predicting strength of recycled aggregate concrete using Artificial Neural Network, Adaptive Neuro-Fuzzy Inference System and Multiple Linear Regression, International Journal of Sustainable Built Environment. 5, pp. 355–369.
21. H Madani, M. Kooshafar, M. Emadi(2020) Compressive Strength Prediction of Nanosilica-Incorporated Cement Mixtures Using Adaptive Neuro-Fuzzy Inference System and Artificial Neural Network Models, Pract. Period. Struct. Des. Constr., 25(3): 04020021.
22. P.Sangeetha, M. Shanmugapriya(2019) Numerical Study on FRP Wrapped Concrete Columns Under Compression, Indian Journal of Science and Technology. 12(15), pp. 1-7.
23. P.Sangeetha, M. Shanmugapriya (2020) Prediction of Mechanical Strength of Polypropylene Fiber Reinforced Concrete Using Artificial Neural Network, Building Materials and Structures, Lecture notes in Civil Engineering. 63, pp. 79-86.
24. P. Sangeetha, M. Shanmugapriya (2021) Fatigue life prediction of Brass and En-24 using soft computing tool, Material Today: Proceedings. 38, pp. 2912–2918.
25. P. Sangeetha, M. Shanmugapriya (2020) Prediction of Mechanical strength of polypropylene fibre reinforced concrete using Artificial Neural Network, GRAĐEVINSKI MATERIJALI I KONSTRUKCIJE (BUILDING MATERIALS AND STRUCTURES). 63(4), pp. 79-86.
26. P. Sangeetha, M. Shanmugapriya (2020) GFRP wrapped concrete column compressive strength prediction through neural network, SN Applied Sciences. 2, pp. 20-36.
27. J.-S.R. Jang(1993) ANFIS: adaptive-network-based fuzzy inference system, IEEE Transactions on Systems, Man, and Cybernetics. 23(3), pp.665-685.
28. Mosavi, S.M., Nik, A.S (2015) Strengthening of steel–concrete composite girders using carbon fibre reinforced polymer (CFRP) plates. Sadhana. 40 (1), pp. 249–261.
29. J.-S.R. Jang, C.-T. Sun, E. Mizutani (1997) Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence, Prentice Hall, Upper Saddle River, New Jersey.
30. J. S. R. Jang and C. T. Sun (1995) Neuro-fuzzy modeling and control, Proceedings of the IEEE. 8(3), pp. 378–406.
31. Bureau of Indian Standards (BIS) Concrete Mix Proportioning. IS: 10262:2009, New Delhi, India; 2009.
32. Bureau of Indian Standards (BIS) Methods of tests for strength of concrete. IS: 516:1959, New Delhi, India; 1959.
Published
2023-07-11
How to Cite
Palanivelu, S., & Marayanagaraj, S. (2023). Predicting the strength of seashell concrete using Adaptive Neuro-Fuzzy Inference System: An experimental study. ITECKNE, 20(1), 34-44. https://doi.org/https://doi.org/10.15332/iteckne.v20i1.2917
Issue
Section
Research and Innovation Articles
