Authors:
T. Pradhan,G. K. Mahato,S. Jena,DOI NO:
https://doi.org/10.26782/jmcms.2026.09.00004Keywords:
Nanofluid,Hybrid Nanofluid,Response Surface Methodology,Artificial Neural Networks,Machine Learning,AI,Abstract
Response Surface Methodology (RSM) is a powerful statistical and mathematical tool in designing experiments, modeling, and optimizing the heat transfer efficiency in nanofluids. This paper provides a detailed review of the use of Response Surface Methodology in nanofluids-based heat transfer systems, particularly in experimental design, modeling, interaction between factors, and optimization. Some of the common design techniques used for establishing a relationship between second-order polynomials with operating parameters and thermal response include Box-Behnken Design (BBD) and Central Composite Design (CCD). Applications of RSM in thermal conductivity, heat transfer augmentation, flow analysis, entropy generation, and hybrid nanofluids are covered in this paper. Comparison with artificial neural networks (ANN) suggests that ANN gives more accurate prediction results in the case of a highly non-linear system, while RSM gives explicit correlation between the operating parameters and the thermal responses along with sensitivity analysis. Some of the important areas requiring more research include experimental validation, multi-objective optimization, transient analysis, and uncertainty analysis, among others.Refference:
I. Alhadri, Muapper, et al. “Response Surface Methodology (RSM) and Artificial Neural Network (ANN) Simulations for Thermal Flow Hybrid Nanofluid Flow with Darcy-Forchheimer Effects.” Journal of the Indian Chemical Society, vol. 99, no. 8, 2022, article 100607. 10.1016/j.jics.2022.100607.
II. Alsaedi, Ahmed, K. Muhammad, and Tasawar Hayat. “Numerical Study of MHD Hybrid Nanofluid Flow between Two Coaxial Cylinders.” Alexandria Engineering Journal, vol. 61, 2022, pp. 8355–8362.
III. Ahmad, N., S. Khan, and T. Mahmood. “Response Surface Methodology for Adsorption Optimization Using Nanofluid-Assisted Systems.” Journal of Environmental Chemical Engineering, vol. 13, 2025, article 112045.
IV. Buongiorno, Jacopo. “Convective Transport in Nanofluids.” Journal of Heat Transfer, vol. 128, no. 3, 2006, pp. 240–250. 10.1115/1.2150834.
V. Choi, Stephen U. S., and Jeffrey A. Eastman. “Enhancing Thermal Conductivity of Fluids with Nanoparticles.” ASME International Mechanical Engineering Congress & Exposition, San Francisco, 1995, pp. 99–106. 10.1115/IMECE1995-0926.
VI. Das, S. K., N. Putra, P. Theisen, and W. Roetzel. “Temperature Dependence of Thermal Conductivity Enhancement for Nanofluid.” Journal of Heat Transfer, vol. 125, 2003, pp. 567–574.
VII. Eastman, Jeffrey A., and Stephen U. S. Choi. “Enhanced Thermal Conductivity through Development of Nanofluids.” MRS Proceedings, vol. 457, 1997, pp. 3–11.
VIII. Hosseini, S. M., M. Bahiraei, and M. Hangi. “Comparison of Response Surface Methodology and Artificial Neural Network for Predicting Nanofluid Thermal Performance.” Applied Thermal Engineering, vol. 190, 2021, article 116801.
IX. Islam, T., S. Gama, and M. M. Afonso. “Artificial Neural Network and Response Surface Methodology-Driven Optimization of Cu–Al?O?/Water Hybrid Nanofluid Flow in a Wavy Enclosure with Inclined Periodic Magnetohydrodynamic Effects.” Mathematics, vol. 13, 2025, article 78.
X. Kakaç, Sad?k, and Anchasa Pramuanjaroenkij. “Review of Convective Heat Transfer Enhancement with Nanofluids.” International Journal of Heat and Mass Transfer, vol. 52, nos. 13–14, 2009, pp. 3187–3196. 10.1016/j.ijheatmasstransfer.2009.02.006.
XI. Khan, M. I., A. M. Alqahtani, and S. Elattar. “Optimization of Heat Transfer Characteristics in Nanofluid Flow Using Statistical Techniques.” Alexandria Engineering Journal, vol. 89, 2024, pp. 215–228.
XII. Khan, Shan Ali. “Application of Central Composite Design (CCD)-Response Surface Methodology (RSM) for Optimization of Heat Transfer in Dusty Nanofluid Flow with Velocity Slip.” Numerical Heat Transfer, Part A: Applications, vol. 87, no. 1, 2026. 10.1080/10407782.2024.2372044.
XIII. Khashi'ie, Najiyah Safwa, et al. “Response Surface Methodology (RSM) on the Hybrid Nanofluid Flow Subject to a Vertical and Permeable Wedge.” Nanomaterials, vol. 12, no. 22, 2022, article 4016. 10.3390/nano12224016.
XIV. Kshirsagar, D. P., and M. A. Venkatesh. “A Review on Hybrid Nanofluids for Engineering Applications.” Materials Today: Proceedings, vol. 44, 2021, pp. 744–755.
XV. Kumar, P., et al. “Response Surface Technique for Time-Dependent Carreau Nanofluid Flow with Entropy Generation: A Statistical Modelling.” International Journal of Thermofluids, vol. 28, 2025, article 101291. 10.1016/j.ijft.2025.101291.
XVI. Manjunatha, S., et al. “Thermal Radiation and Thermo-Diffusion in Casson-Ferrofluid over a Magnetized Porous Surface: RSM Analysis.” International Journal of Thermofluids, vol. 26, 2025, article 101130. 10.1016/j.ijft.2025.101130.
XVII. Mishra, S. R., et al. “Predictive Analysis of Flow Profiles of Ag-Au/Blood Hybrid Nanofluid Using ANN with BVP4C for the Combined Impact of Dissipative Heat and Convective Condition.” South African Journal of Chemical Engineering, vol. 56, 2026, article 100864.
XVIII. Peng, Y., et al. “Potential Application of Response Surface Methodology (RSM) for the Prediction and Optimization of Thermal Conductivity of Aqueous CuO (II) Nanofluid: A Statistical Approach and Experimental Validation.” Physica A: Statistical Mechanics and Its Applications, vol. 554, 2020, article 124353. 10.1016/j.physa.2020.124353.
XIX. Pradhan, T., S. Jena, and S. R. Mishra. “Time-Dependent Free Convection of MHD Newtonian Fluid over a Vertical Oscillating Plate for the Interaction of the Heat Source and the Chemical Reaction: The Laplace Transformation Technique.” Heat Transfer, vol. 55, 2026, pp. 5–17.
XX. Raja, M. A. Z., et al. “Intelligent Computing and Response Surface Methodology for Entropy Generation in MHD Nanofluids.” Waves in Random and Complex Media, vol. 35, 2025, pp. 250–268.
XXI. Raja, M. A. Z., et al. “Intelligent Computing through Neural Networks for Entropy Generation in MHD Third-Grade Nanofluid under Chemical Reaction and Viscous Dissipation.” Waves in Random and Complex Media, vol. 35, 2025, pp. 250–270. 10.1080/17455030.2022.2044095.
XXII. Rana, P., and R. Bhargava. “Flow and Heat Transfer of a Nanofluid over a Nonlinearly Stretching Sheet: A Numerical Study.” Communications in Nonlinear Science and Numerical Simulation, vol. 17, 2012, pp. 212–226.
XXIII. Ramirez-Tijerina, R., et al. “Numerical Study of Heat Transfer Enhancement for Laminar Nanofluids Flow.” Applied Sciences, vol. 8, 2018, article 2661.
XXIV. Salehi, S., D. Nori, et al. “Numerical Investigation of MHD Nanofluid Flow and Heat Transfer over Stretching Surfaces under Thermal Radiation Effects.” International Journal of Heat and Mass Transfer, vol. 145, 2020, article 118755.
XXV. Uysal, C., O. Ayd?n, and M. K?l?ç. “Artificial Neural Network Modeling of Thermal Conductivity in Nanofluids.” Applied Thermal Engineering, vol. 150, 2019, pp. 1138–1147.
XXVI. Vajjha, R. S., D. K. Das, and P. K. Namburu. “Numerical Study of Fluid Dynamic and Heat Transfer Performance of Al?O? and CuO Nanofluids in the Flat Tubes of a Radiator.” International Journal of Heat and Fluid Flow, vol. 31, 2010, pp. 613–621. https://doi.org/10.1016/j.ijheatfluidflow.2010.02.016.
XXVII. Wang, Xiang-Qi, and Arun S. Mujumdar. “Heat Transfer Characteristics of Nanofluids: A Review.” International Journal of Thermal Sciences, vol. 46, no. 1, 2007, pp. 1–19. 10.1016/j.ijthermalsci.2006.06.010.
XXVIII. Xuan, Yimin, and Qiang Li. “Heat Transfer Enhancement of Nanofluids.” International Journal of Heat and Fluid Flow, vol. 21, no. 1, 2000, pp. 58–64. 10.1016/S0142-727X(99)00067-3.
XXIX. Yaw, M. K., K. O. Boateng, and R. A. Mensah. “Multi-Objective Optimization of Nanofluid Heat Transfer Systems Using Response Surface Methodology.” Case Studies in Thermal Engineering, vol. 45, 2023, article 102945.
XXX. Yaw, C. T., et al. “An Approach for the Optimization of Thermal Conductivity and Viscosity of Hybrid (Graphene Nanoplatelets, GNPs: Cellulose Nanocrystal, CNC) Nanofluids Using Response Surface Methodology (RSM).” Nanomaterials, vol. 13, no. 10, 2023, article 1596. 10.3390/nano13101596.
XXXI. Zhang, Y., H. Liu, and Q. Wang. “Entropy Generation Analysis and Modeling in Nanofluid Heat Transfer Systems.” Energy Conversion and Management, vol. 320, 2025, article 118945.