Radiative heat transfer analysis of a concave porous fin under the local thermal non-equilibrium condition: application of the clique polynomial method and physics-informed neural networks

doi:10.1007/s10483-024-3143-6

Applied Mathematics and Mechanics (English Edition) ›› 2024, Vol. 45 ›› Issue (9): 1613-1632.doi: https://doi.org/10.1007/s10483-024-3143-6

收稿日期:2024-04-14 出版日期:2024-09-01 发布日期:2024-08-27

Radiative heat transfer analysis of a concave porous fin under the local thermal non-equilibrium condition: application of the clique polynomial method and physics-informed neural networks

K. CHANDAN¹, K. KARTHIK², K. V. NAGARAJA³, B. C. PRASANNAKUMARA²^,*(), R. S. VARUN KUMAR⁴, T. MUHAMMAD⁵

¹ Amrita School of Artificial Intelligence, Amrita Vishwa Vidyapeetham, Bengaluru 560035, Karnataka, India
² Department of Studies in Mathematics, Davangere University, Davangere 577002, Karnataka, India
³ Computational Science Lab, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Bengaluru 560035, Karnataka, India
⁴ Department of Pure and Applied Mathematics, School of Mathematical Sciences, Sunway University, Petaling Jaya 47500, Malaysia
⁵ Department of Mathematics, College of Science, King Khalid University, Abha 61413, Saudi Arabia

Received:2024-04-14 Online:2024-09-01 Published:2024-08-27
Contact: B. C. PRASANNAKUMARA E-mail:prasannakumarabc@davangereuniversity.ac.in

摘要/Abstract

Abstract:

The heat transfer through a concave permeable fin is analyzed by the local thermal non-equilibrium (LTNE) model. The governing dimensional temperature equations for the solid and fluid phases of the porous extended surface are modeled, and then are nondimensionalized by suitable dimensionless terms. Further, the obtained non-dimensional equations are solved by the clique polynomial method (CPM). The effects of several dimensionless parameters on the fin's thermal profiles are shown by graphical illustrations. Additionally, the current study implements deep neural structures to solve physics-governed coupled equations, and the best-suited hyperparameters are attained by comparison with various network combinations. The results of the CPM and physics-informed neural network (PINN) exhibit good agreement, signifying that both methods effectively solve the thermal modeling problem.

Key words: heat transfer, fin, porous fin, local thermal non-equilibrium (LTNE) model, physics-informed neural network (PINN)

中图分类号:

. [J]. Applied Mathematics and Mechanics (English Edition), 2024, 45(9): 1613-1632.

K. CHANDAN, K. KARTHIK, K. V. NAGARAJA, B. C. PRASANNAKUMARA, R. S. VARUN KUMAR, T. MUHAMMAD. Radiative heat transfer analysis of a concave porous fin under the local thermal non-equilibrium condition: application of the clique polynomial method and physics-informed neural networks[J]. Applied Mathematics and Mechanics (English Edition), 2024, 45(9): 1613-1632.

图/表 16

参考文献 28

1	ZHAO, Q., TAO, L., and XU, H. Analysis of periodic pulsating nanofluid flow and heat transfer through a parallel-plate channel in the presence of magnetic field. Applied Mathematics and Mechanics (English Edition), 44 (11), 1957- 1972 (2023) doi: 10.1007/s10483-023-3048-7
2	XU, H. Mixed convective flow of a hybrid nanofluid between two parallel inclined plates under wall-slip condition. Applied Mathematics and Mechanics (English Edition), 43 (1), 113- 126 (2022) doi: 10.1007/s10483-021-2801-6
3	HUMNEKAR, N., and SRINIVASACHARYA, D. Influence of variable viscosity and double diffusion on the convective stability of a nanofluid flow in an inclined porous channel. Applied Mathematics and Mechanics (English Edition), 45 (3), 563- 580 (2024) doi: 10.1007/s10483-024-3096-6
4	RIASAT, S., RAMZAN, M., SALEEL, C. A., EL-SHORBAGY, M. A., KADRY, S., SAEED, A. M., and ELDIN, S. M. A comparative analysis of dovetail and rectangular fins with insulated tips wetted with ZnO-SAE 50 nanolubricant for energy transfer process. Case Studies in Thermal Engineering, 51, 103576 (2023)
5	RAMZAN, M., RIASAT, S., GHAZWANI, H. A. S., PASHA, A. A., ISLAM, N., and ALJURBUA, S. F. Performance comparison appraisal of a fully wetted longitudinal fin of different profiles with variable thermal conductivities. International Communications in Heat and Mass Transfer, 138, 106354 (2022)
6	PAVITHRA, C. G., GIREESHA, B. J., and KEERTHI, M. L. Semi-analytical investigation of heat transfer in a porous convective radiative moving longitudinal fin exposed to magnetic field in the presence of a shape-dependent trihybrid nanofluid. Applied Mathematics and Mechanics (English Edition), 45 (1), 197- 216 (2024) doi: 10.1007/s10483-024-3069-6
7	GIREESHA, B. J., KEERTHI, M. L., and SOWMYA, G. Effects of stretching/shrinking on the thermal performance of a fully wetted convective-radiative longitudinal fin of exponential profile. Applied Mathematics and Mechanics (English Edition), 43 (3), 389- 402 (2022) doi: 10.1007/s10483-022-2836-6
8	WASEEM, W., SULAIMAN, M., ISLAM, S., KUMAM, P., NAWAZ, R., RAJA, M. A. Z., FAROOQ, M., and SHOAIB, M. A study of changes in temperature profile of porous fin model using cuckoo search algorithm. Alexandria Engineering Journal, 59 (1), 11- 24 (2020)
9	DAS, R., and KUNDU, B. Simultaneous estimation of heat generation and magnetic field in a radial porous fin from surface temperature information. International Communications in Heat and Mass Transfer, 127, 105497 (2021)
10	NABATI, M., JALALVAND, M., and TAHERIFAR, S. Sinc collocation approach through thermal analysis of porous fin with magnetic field. Journal of Thermal Analysis and Calorimetry, 144, 2145- 2158 (2021)
11	ULLAH, I., ULLAH, S., ALI, A., SHAH, S. I., WEERA, W., and ALAM, M. M. Heat transfer analysis from moving convection-radiative triangular porous fin exposed to heat generation. Case Studies in Thermal Engineering, 38, 102177 (2022)
12	PATI, S., BORAH, A., BORUAH, M. P., and RANDIVE, P. R. Critical review on local thermal equilibrium and local thermal non-equilibrium approaches for the analysis of forced convective flow through porous media. International Communications in Heat and Mass Transfer, 132, 105889 (2022)
13	LIU, X., TONG, Z. X., and HE, Y. L. Enthalpy-based immersed boundary-lattice Boltzmann model for solid-liquid phase change in porous media under local thermal non-equilibrium condition. International Journal of Thermal Sciences, 182, 107786 (2022)
14	KADHIM, H. T., AL-MANEA, A., AL-SHAMANI, A. N., and YUSAF, T. Numerical analysis of hybrid nanofluid natural convection in a wavy walled porous enclosure: local thermal non-equilibrium model. International Journal of Thermofluids, 15, 100190 (2022)
15	YERRAMALLE, V., PREMACHANDRAN, B., and TALUKDAR, P. Mixed convection from a heat source in a channel with a porous insert: a numerical analysis based on local thermal non-equilibrium model. Thermal Science and Engineering Progress, 25, 101010 (2021)
16	LAGARIS, I. E., LIKAS, A., and FOTIADIS, D. I. Artificial neural networks for solving ordinary and partial differential equations. IEEE Transactions on Neural Networks, 9 (5), 987- 1000 (1998)
17	RAISSI, M., PERDIKARIS, P., and KARNIADAKIS, G. E. Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations. Journal of Computational Physics, 378, 686- 707 (2019)
18	KRISHNAPRIYAN, A., GHOLAMI, A., ZHE, S., KIRBY, R., and MAHONEY, M. W. Characterizing possible failure modes in physics-informed neural networks. Advances in Neural Information Processing Systems, 34, 26548- 26560 (2021)
19	CAI, S., MAO, Z., WANG, Z., YIN, M., and KARNIADAKIS, G. E. Physics-informed neural networks (PINNs) for fluid mechanics: a review. Acta Mechanica Sinica, 37 (12), 1727- 1738 (2021)
20	WANG, X., WEN, H., HU, T., and WANG, B. Flow-field reconstruction in rotating detonation combustor based on physics-informed neural network. Physics of Fluids, 35 (7), 076109 (2023)
21	CAI, S., WANG, Z., WANG, S., PERDIKARIS, P., and KARNIADAKIS, G. E. Physics-informed neural networks for heat transfer problems. Journal of Heat Transfer, 143 (6), 125089 (2021)
22	NGUYEN, T. N. K., DAIRAY, T., MEUNIER, R., and MOUGEOT, M. Physics-informed neural networks for non-Newtonian fluid thermo-mechanical problems: an application to rubber calendering process. Engineering Applications of Artificial Intelligence, 114, 105176 (2022)
23	BUONOMO, B., CASCETTA, F., MANCA, O., and SHEREMET, M. Heat transfer analysis of rectangular porous fins in local thermal non-equilibrium model. Applied Thermal Engineering, 195, 117237 (2021)
24	JALILI, P., ALAMDARI, S. G., JALILI, B., SHATERI, A., and GANJI, D. D. Analytical and numerical investigation of heat transfer of porous fin in a local thermal non-equilibrium state. Heliyon, 10 (4), e2024 (2024)
25	KIWAN, S. Effect of radiative losses on the heat transfer from porous fins. International Journal of Thermal Sciences, 46 (10), 1046- 1055 (2007)
26	DAS, R., and KUNDU, B. Prediction of heat generation in a porous fin from surface temperature. Journal of Thermophysics and Heat Transfer, 31 (4), 781- 790 (2017)
27	WAZWAZ, A. M. A new method for solving singular initial value problems in the second-order ordinary differential equations. Applied Mathematics and Computation, 128 (1), 45- 57 (2002)
28	KARIMI VANANI, S., and AMINATAEI, A. On the numerical solution of differential equations of Lane-Emden type. Computers & Mathematics with Applications, 59 (8), 2815- 2820 (2010)

Radiative heat transfer analysis of a concave porous fin under the local thermal non-equilibrium condition: application of the clique polynomial method and physics-informed neural networks

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

图/表 16

参考文献 28

相关文章 0

编辑推荐

Metrics

本文评价