Effect of variable heat source and gravity variance on the convection in porous layer with temperature dependent viscosity

Document Type : Article

Authors

1 Department of Mathematics, RV Institute of Technology and Management, Bangalore-560076, India

2 Department of Mathematics, School of Applied Sciences, REVA University, Bangalore-560064, India

3 Department of Physics, Faculty of Sciences, University of 20 Ao^ut 1955-Skikda, B.P. 26, 21000 Skikda, Algeria

4 Faculty of Mathematics, University of Technology and Applied Sciences, Ibri-516, Sultanate of Oman

Abstract

The joint influence of variable heat source pattern and temperature-reliant viscosity on the onset of convective motion in porous bed in the presence of gravity variance have been investigated. The linear analysis is performed using normal mode analysis and the Galerkin technique is applied to analyze the impact of variable heating and changeable gravity field on the behaviour of system stability. The exponential temperature dependent viscosity is considered. We examined three different types of heat source and gravity variance function combinations: Convection is accelerated by increases in viscosity and the gravity variance parameter, but decelerated by increases in the heat source strength. It has been shown that the configuration is more stable when the gravity variance and heat source functions are combined in instance (ii), but less stable when they are combined in case (iii).

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References

References:
1. Siddesh Kumar, N.G., Suresh, R., and Shiva Shankar, G.S. "High temperature wear behavior of Al2219/n-B4C/MoS2 hybrid metal matrix composites", Composite Communications, 19, pp. 61-73 (2020). https://doi.org/10.1016/j.coco.2020.02.011.
2. Xu, G., Yu, Y., Zhang, Y., et al. "Effect of B4C particle size on the mechanical properties of B4C reinforced aluminum matrix layered composite", Science and Engineering of Composite Materials, 26, pp. 53-61 (2018). https://doi.org/10.1515/secm-2018-0072.
3. Ramadoss, N., Pazhanivel, K., Kumar, S.G., et al. "Effect of B4C and SiC nanoparticle reinforcement on the wear behavior and surface structure of aluminum (Al6063-T6) matrix composite", SN Applied Sciences, 2, 903 (2020). https://doi.org/10.1007/s42452-020- 2712-5.
4. Joshi, A.G., Manjaiah, M., Basavarajappa, S., et al. "Wear performance optimization of SiC-Gr reinforced Al hybrid metal matrix composites using integrated regression-antlion algorithm", Silicon, 13, pp. 3941-3951 (2021). https://doi.org/10.1007/s12633- 020-00704-x.
5. Wahba, M., Kawahito, Y., Kondoh, K., et al. "A fundamental study of laser welding of hot extruded powder metallurgy (P/M) AZ31B magnesium alloy", Materials Science and Engineering: A., 529, pp. 143-150 (2011). https://doi.org/10.1016/j.msea.2011.09.010.
6. Suresh, R. "Comparative study on dry sliding wear behavior of mono (Al2219/B4C) and hybrid (Al2219/B4C/Gr) metal matrix composites using statistical technique", Journal of the Mechanical Behavior of Materials, 29, pp. 57-68 (2020). https://doi.org/10.1515/jmbm-2020-0006.
7. Reihanian, M., Asadullahpour, S.R., Hajarpour, S., et al. "Application of neural network and genetic algorithm to powder metallurgy of pure iron", Materials and Design, 32, pp. 3183-3188 (2011). https://doi.org/10.1016/j.matdes.2011.02.049.
8. Pandey, U., Purohit, R., Agarwal, P., et al. "Effect of TiC particles on the mechanical properties of aluminium alloy metal matrix composites (MMCs)", Materials Today Proceedings, 4, pp. 5452-5460 (2017). https://doi.org/10.1016/j.matpr.2017.05.057.
9. Gotagunaki, S., Mudakappanavar, V.S., and Suresh, R. "Investigation on microstructure and tensile fractography of RE Oxides (CeO2/Y2O3) reinforced AZ91D magnesium matrix composites", Frattura ed Integrita Strutturale, 63, pp. 100-109 (2023). https://doi.org/10.3221/IGF-ESIS.63.10.
10. Suresh, R., Joshi, A.G., and Siddeshkumar, N.G. "Investigation on dry sliding wear behavior of AA5083/nano Al2O3 metal matrix composites", Revista de Metalurgia, 58, pp. 1-8 (2022). https://doi.org/10.3989/revmetalm.213.
11. Riddhisha, C., Siddesh, B., Latha Shankar, B., et al. "Optimization and analysis of dry sliding wear behaviour of N-B4C/MOS2 unreinforced AA2219 nano hybrid composites using response surface methodology", Metallurgical and Materials Engineering, 28, pp. 469-485 (2023). https://doi.org/10.30544/840.
12. Mussatto, A., Ul-Ahad, I., Taherzadeh, R., et al. "Advanced production routes for metal matrix composites", Engineering Reports, 3, pp. 1-25 (2021). https://doi.org/10.1002/eng2.12330.
13. Ravikumar, M., Reddappa, H.N., Suresh, R., et al. "Optimization of wear behaviour of Al7075/SiC/Al2O3 MMCs using statistical method", Advances in Materials and Processing Technologies, 8, pp. 4018-4035 (2022). https://doi.org/10.1080/2374068X.2022.2036583.
14. Tarasasanka, C., Snehita, K., Ravindra, K., et al. "Optimization of dry sliding wear properties of AZ91E/nano-Al2O3 reinforced metal matrix composite with grey relational analysis", International Journal of Engineering, Science and Technology, 11, pp. 41-48 (2019). https://doi.org/10.4314/ijest.v11i4.4.
15. Natrayan, L. and Senthil Kumar, M. "Influence of silicon carbide on tribological behaviour of AA2024/Al2O3/SiC/Gr hybrid metal matrix squeeze cast composite using Taguchi technique", Material Research Express, 6, 1265f9 (2019). http://dx.doi.org/10.1088/2053-1591/ab676d.
16. Arunkumar, S., Ashokkumar, R., Sundaram, M.S., et al. "Optimization of wear behaviour of Al7075 hybrid metal matrix composites using Taguchi approach", Materials Today: Proceedings, 33, pp. 570-577 (2020). https://doi.org/10.1016/j.matpr.2020.05.453.
17. Miloradovic, N., Vujanac, R., Stojanovic, B., et al. "Dry sliding wear behaviour of ZA27/SiC/Gr hybrid composites with Taguchi Optimization", Composite Structures, 264, 113658 (2021). https://doi.org/10.1016/j.compstruct.2021.113658.
18. Velavan, K., Palanikumar, K., and Senthilkumar, N. "Experimental investigation of sliding wear behaviour of boron carbide and mica reinforced aluminium alloy hybrid metal matrix composites using Box-Behnken design", Materials Today: Proceedings, 44, pp. 3803- 3810 (2021). https://doi.org/10.1016/j.matpr.2020.12.333.
19. Gangwar, S. and Pathak, V.K. "Dry sliding wear characteristics evaluation and prediction of vacuum casted Marble Dust (MD) reinforced ZA-27 alloy composites using hybrid improved bat algorithm and ANN", Materials Today: Communications, 25, 101615 (2020). https://doi.org/10.1016/j.mtcomm.2020.101615.
20. Gangwar, S., Sharma, S., and Pathak, V.K. "Preliminary evaluation and wear properties optimization of boron carbide and molybdenum disulphide reinforced copper metal matrix composite using adaptive neurofuzzy inference system", Journal of Bio-Tribology and Corrosion, 7, 4 (2021). https://doi.org/10.1007/s40735-020-00444-w.
21. Stalin, B., Kumar, P.R., Ravichandran, M., et al. "Optimization of wear parameters using Taguchi grey relational analysis and ANN-TLBO algorithm for silicon nitride filled AA6063 matrix composites", Material Research Express, 6, 106590 (2019). http://dx.doi.org/10.1088/2053-1591/ab3d90.
22. Aydin, F. "The investigation of the effect of particle size on wear performance of AA7075/Al2O3 composites using statistical analysis and different machine learning methods", Advanced Powder Technology, 32, pp. 445-463 (2021). https://doi.org/10.1016/j.apt.2020.12.024.
23. Dhiman, G. and Kumar, V. "Spotted hyena optimizer: A novel bio-inspired based metaheuristic technique for engineering applications", Advances in Engineering Software, 114, pp. 48-70 (2017). https://doi.org/10.1016/j.advengsoft.2017.05.014.
24. Panda, N., Majhi, S.K., and Pradhan, R. "A hybrid approach of spotted hyena optimization integrated with quadratic approximation for training wavelet neural network", Arabian Journal of Science and Engineering, 47, pp. 10347-10363 (2022). https://doi.org/10.1007/s13369-022-06564-4.
25. Ilany, A., Booms, A.S., and Holekamp, K.E. "Topological effects of network structure on longterm social network dynamics in a wild mammal", Ecological Letters, 18, pp. 687-95 (2015). https://doi.org/10.1111/ele.12447.
26. Sunar, T. and Ozyurek, D. "Effect of Al2O3 Nanoparticles as reinforcement on the wear properties of A356/Al2O3 nanocomposites produced by powder metallurgy", Journal of Tribology, 144, 081701 (2022). https://doi.org/10.1115/1.4053628.
27. Khan, M.M., Dey, A., and Hajam, M.I. "Experimental investigation and optimization of dry sliding wear test parameters of aluminum based composites", Silicon, 14, pp. 4009-4026 (2022). https://doi.org/10.1007/s12633-021-01158-5.
28. Sharma, S., Nanda, T., and Pandey, O.P. "Effect of particle size on dry sliding wear behaviour of sillimanite reinforced aluminium matrix composites", Ceramics International, 44, pp. 104-114 (2018).
https://doi.org/10.1016/j.ceramint.2017.09.132.
29. Lagisetti, V.K., Reddy, A.P., and Krishna, P.V. "Dry sliding wear study on AA6061/SiCp nano and AA6061/SiCp/Gr hybrid nanocomposites", Silicon, 14, pp. 12235-12250 (2022). https://doi.org/10.1007/s12633-022-01908-z.
Scientia Iranica
Volume 31, Issue 13 - Serial Number 13
Transactions on Mechanical Engineering (B)
July and August 2024
Pages 1056-1062

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