Numerical and Artificial Neural Network Analysis of Magnetohydrodynamic Natural Convection in a Nano-encapsulated Phase Change Suspension Filled Quadrantal Circular Enclosure

Ghalambaz, Mehdi; Pop, Ioan; Sheremet, Mikhail; Ali, Mohammed Hasan; Ghalambaz, Mohammad

doi:10.22055/jacm.2024.47986.4891

Numerical and Artificial Neural Network Analysis of Magnetohydrodynamic Natural Convection in a Nano-encapsulated Phase Change Suspension Filled Quadrantal Circular Enclosure

Document Type : Research Paper

Authors

Mehdi Ghalambaz ¹

Ioan Pop ²

Mikhail Sheremet ³

Mohammed Hasan Ali ⁴

Mohammad Ghalambaz ³

¹ Department of Mathematics, Saveetha School of Engineering, SIMATS, Chennai, India

² Department of Mathematics, Babes-Bolyai University, 400084 Cluj-Napoca, Romania

³ Laboratory on Convective Heat and Mass Transfer, Tomsk State University, 634050 Tomsk, Russia

⁴ College of Technical Engineering, Imam Ja’afar Al-Sadiq University, Al-Muthanna 66002, Iraq

10.22055/jacm.2024.47986.4891

Abstract

This article deals with the heat transfer dynamics of a quadrantal circular enclosure filled with nano-encapsulated phase change material (NEPCM) suspension. Central to the investigation is the examination of nanoparticles that exhibit phase transitions and their consequential effects on the thermophysical attributes of the NEPCM suspension. The transformative states of these nanoparticles - solid, liquid, or phase change - are pivotal in modifying localized heat capacity, influenced by various parameters. Among these, the concentration of NEPCM particles, the Rayleigh number, the Hartmann number, and the fusion temperature stand out as critical to heat transfer dynamics. The governing equations for fluid flow and heat transfer of NEPCM suspension are introduced in the form of partial differential equations and were solved using the finite element method. The results showed that while an increase in the Rayleigh number augments heat transfer rates, a rise in the Hartmann number reduces it due to the Lorenz force's influence on fluid velocity. Optimal fusion temperature values, crucial to heat transfer, have been pinpointed at θ_f = 0.35 and θ_f = 0.675. The study further unveils the augmentation in heat transfer rates with an increased concentration of nanoparticles, particularly at the wall’s commencement. A significant contribution is developing a neural network model, demonstrating high predictive accuracy for heat transfer rates. This model, through contour diagrams, offers insights into heat transfer dynamics, sidestepping the need for extensive numerical simulations.

Keywords

Heat transfer enhancement

Magnetohydrodynamic

Nano encapsulated phase change suspensions

Free convection

Composite nanoparticles

Subjects

Heat and Mass Transfer

Publisher’s Note Shahid Chamran University of Ahvaz remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

[1] Favakeh, A., Khademi, A., Shafii, M. B., Experimental investigation of the melting process of immiscible binary phase change materials, Heat Transfer Engineering, 44(2), 2023, 154-174.

[2] Khademi, A., Abtahi Mehrjardi, S. A., Said, Z., Chamkha, A. J., Heat Transfer Improvement in a Thermal Energy Storage System‎ using Auxiliary Fluid Instead of Nano-PCM in an Inclined‎ Enclosure: A Comparative Study, Journal of Applied and Computational Mechanics, 9(2), 2023, 475-486.

[3] Shank, K., Tiari, S., A review on active heat transfer enhancement techniques within latent heat thermal energy storage systems, Energies, 16(10), 2023, 4165.

[4] Yesilyurt, M. K., Çomakli, Ö., Encapsulated phase change material slurries as working fluid in novel photovoltaic thermal liquid systems: a comprehensive review, Iranian Journal of Science and Technology, Transactions of Mechanical Engineering, 47(4), 2023, 1275-1305.

[5] Ghalambaz, S., A Scientometric Study of Nano Encapsulated Phase Change Material (NEPCM): Trends and Categories, Journal of Nanofluids, 13(4), 2024, 985-998.

[6] Sharma, H. K., Kumar, S., Kumar, S., Verma, S. K., Performance investigation of flat plate solar collector with nanoparticle enhanced integrated thermal energy storage system, Journal of Energy Storage, 55, 2022, 105681.

[7] Alhashash, A., Saleh, H., Enhancement of conjugate heat transfer in an enclosure by utilizing water and nano encapsulated phase change materials with active cylinder, Journal of Energy Storage, 66, 2023, 107422.

[8] Almutairi, K., Cooling three integrated circuits by embedding them inside an inclined cavity using nano-encapsulated phase change material, Journal of Energy Storage, 52, 2022, 104837.

[9] Ghalambaz, M., Jin, H., Bagheri, A., Younis, O., Wen, D., Convective Flow and Heat Transfer of Nano-Encapsulated Phase Change Material (NEPCM) Dispersions along a Vertical Surface, Facta Universitatis, Series: Mechanical Engineering, 20(3), 2022, 519-538.

[10] Zhang, K., Wang, J., Xu, L., Xie, H., Guo, Z., Preparation and thermal characterization of n-octadecane/pentafluorostyrene nanocapsules for phase-change energy storage, Journal of Energy Storage, 35, 2021, 102327.

[11] Shajahan, M. I., Narayana, D. R., Radha Krishnan, N. S., Michael, J. J., Evaluation of efficiency of double slope solar still and drinking water yield using silver nanoparticle mixed with phase change material, Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 44(4), 2022, 8679-8693.

[12] Jain, A., Parhizi, M., Theoretical analysis of phase change heat transfer and energy storage in a spherical phase change material with encapsulation, International Journal of Heat and Mass Transfer, 185, 2022, 122348.

[13] Qaderi, A., Veysi, F., Modelling and optimisation of a battery thermal management system with nano encapsulated phase change material slurry for 18650 Li-ion batteries, Thermal Science and Engineering Progress, 37, 2023, 101552.

[14] Cao, Y., Farouk, N., Ayed, H., Aly, A. A., Jarad, F., Dahari, M., Wae-hayee, M., Saleh, B., Heat transfer improvement between a pair of heater and cooler inside an energy storage by using nano-encapsulated phase change material/water: A numerical modeling, Case Studies in Thermal Engineering, 30, 2022, 101770.

[15] Golab, E., Goudarzi, S., Kazemi-Varnamkhasti, H., Amigh, H., Ghaemi, F., Baleanu, D., Karimipour, A., Investigation of the effect of adding nano-encapsulated phase change material to water in natural convection inside a rectangular cavity, Journal of Energy Storage, 40, 2021, 102699.

[16] Aly, A. M., Lewis, R. W., Alsedias, N., Effects of magnetic field and thermal radiation on double diffusion of solid phase in the two connected circular cylinders suspended by NEPCM and porous media, Journal of Porous Media, 26(5), 2023, 121-138.

[17] Abderrahmane, A., Younis, O., Al-Khaleel, M., Laidoudi, H., Akkurt, N., Guedri, K., Marzouki, R., 2D MHD mixed convection in a zigzag trapezoidal thermal energy storage system using NEPCM, Nanomaterials, 12(19), 2022, 3270.

[18] Jiang, Z., Shu, J., Ge, Z., Jiang, Z., Wang, M., Ge, X., Preparation and performance of magnetic phase change microcapsules with organic-inorganic double shell, Solar Energy Materials and Solar Cells, 240, 2022, 111716.

[19] Shin, D. H., Kim, S., Karng, S. W., Shin, Y., Development of a new type of PCM thermal capsule transport system, International Journal of Heat and Mass Transfer, 183, 2022, 122034.

[20] Wang, X., Zhang, C., Wang, K., Huang, Y., Chen, Z., Highly efficient photothermal conversion capric acid phase change microcapsule: Silicon carbide modified melamine urea formaldehyde, Journal of Colloid and Interface Science, 582, 2021, 30-40.

[21] Aly, A. M., Raizah, Z., Ghalambaz, M., The magnetic field on thermosolutal convection in an annulus between two super ellipses, Waves in Random and Complex Media, 2022, 1-20.

[22] Raizah, Z., Aly, A. M., Effect of dual-rotation on MHD natural convection of NEPCM in a hexagonal-shaped cavity based on time-fractional ISPH method, Scientific Reports, 11(1), 2021, 22687.

[23] Alazzam, A., Qasem, N. A., Aissa, A., Abid, M. S., Guedri, K., Younis, O., Natural convection characteristics of nano-encapsulated phase change materials in a rectangular wavy enclosure with heating element and under an external magnetic field, Journal of Energy Storage, 57, 2023, 106213.

[24] Aly, A. M., Alsedais, N., Natural convection of NEPCM in a partial porous H-shaped cavity: ISPH simulation, International Journal of Numerical Methods for Heat & Fluid Flow, 33(6), 2023, 2232-2249.

[25] Shehzad, S., Alshuraiaan, B., Kamel, M. S., Izadi, M., Ambreen, T., Influence of fin orientation on the natural convection of aqueous-based nano-encapsulated PCMs in a heat exchanger equipped with wing-like fins, Chemical Engineering and Processing-Process Intensification, 160, 2021, 108287.

[26] Ahmed, S. E., Khamis, A. K., Exploration of the entropy due to the nano–encapsulated phase change materials (NEPCMs) within oblique prismatic containers, Physica Scripta, 96(11), 2021, 115204.

[27] Aly, A. M., Mohamed, E. M., El-Amin, M. F., Alsedais, N., Double-diffusive convection between two different phases in a porous infinite-shaped enclosure suspended by nano encapsulated phase change materials, Case Studies in Thermal Engineering, 26, 2021, 101016.

[28] Aly, A. M., Hyder, A.-A., Alsedias, N., Time-Conformable fractal systems of natural convection of tall fin inside two circular cylinders suspended by NEPCM, Alexandria Engineering Journal, 61(12), 2022, 12311-12328.

[29] Raizah, Z., Aly, A. M., Dual convection of NEPCM inside an annulus between two circular cylinders mounted on rectangles, Alexandria Engineering Journal, 72, 2023, 415-429.

[30] Athanasopoulos, N., Baltopoulos, A., Matzakou, M., Vavouliotis, A., Kostopoulos, V., Electrical conductivity of polyurethane/MWCNT nanocomposite foams, Polymer Composites, 33(8), 2012, 1302-1312.

[31] Dutta, S., Pati, S., Baranyi, L., Numerical analysis of magnetohydrodynamic natural convection in a nanofluid filled quadrantal enclosure, Case Studies in Thermal Engineering, 28, 2021, 101507.

[32] Barlak, S., Sara, O. N., Karaipekli, A., Yapıcı, S., Thermal conductivity and viscosity of nanofluids having nanoencapsulated phase change material, Nanoscale and Microscale Thermophysical Engineering, 20(2), 2016, 85-96.

[33] Ghalambaz, M., Chamkha, A. J., Wen, D., Natural convective flow and heat transfer of nano-encapsulated phase change materials (NEPCMs) in a cavity, International Journal of Heat and Mass Transfer, 138, 2019, 738-749.

[34] Ghalambaz, M., Zadeh, S. M. H., Mehryan, S., Pop, I., Wen, D., Analysis of melting behavior of PCMs in a cavity subject to a non-uniform magnetic field using a moving grid technique, Applied Mathematical Modelling, 77, 2020, 1936-1953.

[35] Sheikholeslami, M., Vajravelu, K., Nanofluid flow and heat transfer in a cavity with variable magnetic field, Applied Mathematics and Computation, 298, 2017, 272-282.

[36] Selimefendigil, F., Öztop, H. F., Chamkha, A. J., MHD mixed convection and entropy generation of nanofluid filled lid driven cavity under the influence of inclined magnetic fields imposed to its upper and lower diagonal triangular domains, Journal of Magnetism and Magnetic Materials, 406, 2016, 266-281.

[37] Chen, B., Wang, X., Zeng, R., Zhang, Y., Wang, X., Niu, J., Li, Y., Di, H., An experimental study of convective heat transfer with microencapsulated phase change material suspension: laminar flow in a circular tube under constant heat flux, Experimental Thermal and Fluid Science, 32(8), 2008, 1638-1646.

[38] Khanafer, K., Vafai, K., A critical synthesis of thermophysical characteristics of nanofluids, International Journal of Heat and Mass Transfer, 54(19-20), 2011, 4410-4428.

[39] Chai, L., Shaukat, R., Wang, L., Wang, H. S., A review on heat transfer and hydrodynamic characteristics of nano/microencapsulated phase change slurry (N/MPCS) in mini/microchannel heat sinks, Applied Thermal Engineering, 135, 2018, 334-349.

[40] Seyf, H. R., Zhou, Z., Ma, H., Zhang, Y., Three dimensional numerical study of heat-transfer enhancement by nano-encapsulated phase change material slurry in microtube heat sinks with tangential impingement, International Journal of Heat and Mass Transfer, 56(1-2), 2013, 561-573.

[41] Zaraki, A., Ghalambaz, M., Chamkha, A. J., Ghalambaz, M., De Rossi, D., Theoretical analysis of natural convection boundary layer heat and mass transfer of nanofluids: effects of size, shape and type of nanoparticles, type of base fluid and working temperature, Advanced Powder Technology, 26(3), 2015, 935-946.

[42] Chamkha, A., Doostanidezfuli, A., Izadpanahi, E., Ghalambaz, M., Phase-change heat transfer of single/hybrid nanoparticles-enhanced phase-change materials over a heated horizontal cylinder confined in a square cavity, Advanced Powder Technology, 28(2), 2017, 385-397.

[43] Mehryan, S., Ghalambaz, M., Gargari, L. S., Hajjar, A., Sheremet, M., Natural convection flow of a suspension containing nano-encapsulated phase change particles in an eccentric annulus, Journal of Energy Storage, 28, 2020, 101236.

[44] Kelley, C. T., Solving nonlinear equations with Newton's method, SIAM, 2003.

[45] Deuflhard, P., Newton methods for nonlinear problems: affine invariance and adaptive algorithms, Springer Science & Business Media, 2005.

[46] Bollhöfer, M., Schenk, O., Janalik, R., Hamm, S., Gullapalli, K., State-of-the-art sparse direct solvers, Parallel Algorithms in Computational Science and Engineering, 2020, 3-33.

[47] Bollhöfer, M., Eftekhari, A., Scheidegger, S., Schenk, O., Large-scale sparse inverse covariance matrix estimation, SIAM Journal on Scientific Computing, 41(1), 2019, A380-A401.

[48] Kuehn, T., Goldstein, R., An experimental and theoretical study of natural convection in the annulus between horizontal concentric cylinders, Journal of Fluid Mechanics, 74(4), 1976, 695-719.

[49] Sathiyamoorthy, M., Chamkha, A. J., Natural convection flow under magnetic field in a square cavity for uniformly (or) linearly heated adjacent walls, International Journal of Numerical Methods for Heat & Fluid Flow, 22(5), 2012, 677-698.

[50] Mehrjardi, S. A. A., Khademi, A., Fazli, M., Optimization of a thermal energy storage system enhanced with fins using generative adversarial networks method, Thermal Science and Engineering Progress, 49, 2024, 102471.

[51] Edalatifar, M., Tavakoli, M. B., Ghalambaz, M., Setoudeh, F., Using deep learning to learn physics of conduction heat transfer, Journal of Thermal Analysis and Calorimetry, 146, 2021, 1435-1452.

[52] Loyola-Fuentes, J., Nazemzadeh, N., Diaz-Bejarano, E., Mancin, S., Coletti, F., A framework for data regression of heat transfer data using machine learning, Applied Thermal Engineering, 248, 2024, 123043.

[53] Jais, I. K. M., Ismail, A. R., Nisa, S. Q., Adam optimization algorithm for wide and deep neural network, Knowledge Engineering and Data Science, 2(1), 2019, 41-46.

[54] Standardscaler. Scikit. (n.d.), https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.StandardScaler.html, 2024.