The exploration of micro-polar nanofluid occupied in ‘Hele-Shaw cell’ is examined theoretically in the presence of throughflow and G-jitter. We calculate the ‘linear and non-linear’ results using the ‘normal mode technique’ and the expression of Fourier series, respectively. To check the stability or disability of the system concerning the values of parameters, detected the Rayleigh number. Lewis number and throughflow both cause the system to become unstable. The system is stabilized by the ‘micro-polar parameter’ and the ‘Hele-Shaw number’ and other linear results are discussed in the conclusion part. In non-linear computation, we determined the ‘Nusselt number’ and the ‘Sherwood number’ for both ‘heat and mass transfer’, respectively. We examined the three kinds of gravity modulation and found that the ‘square waveform’ more heat transfer and more mass tansfer than the ‘sine and triangle waveforms’. The impact of several parameters, such as the ‘micro-polar parameter’, the Prandtl number, the amplitude of ‘gravity modulation’, the ‘Hele-Shaw number’, and some other parameters, on ‘heat and mass transfer’ was also investigated. ‘Heat and mass transfer’ in the region are reduced if the ‘Hele-Shaw number’ is increased. More heat transfer and delayed mass transfer in the region when increased the throughflow.
This work presents a numerical investigation of magnetohydrodynamic (MHD) natural convection in an open cavity with a sinusoidal wall, where the heated boundary is subjected to a linearly varying temperature profile. A water-based nanofluid containing different nanoparticles (SWCNT, Cu, and TiO 2 ) is considered, and the lattice Boltzmann method (LBM) is employed to resolve the coupled flow and thermal fields. A second-order boundary treatment is applied to accurately represent the wavy wall condition. The effects of Rayleigh number (Ra), Hartmann number (Ha), nanoparticle volume fraction ( φ ), wall geometry parameters, including the number and amplitude of undulations, and nanoparticle type are systematically explored. The results indicate that increasing the Hartmann number suppresses convection, causing the average Nusselt number to decrease by up to 66.08% at Ra = 10 5 . Increasing the wall amplitude from 0 to 0.12 decreases the average Nusselt number by approximately 19.3% at high Rayleigh numbers. An even greater reduction is observed with increasing wall undulations, where increasing the number of wall undulations from 0 to 4 reduces heat transfer by up to 45.31% at Ra = 10 6 . Under non-magnetic conditions, Cu nanoparticles increase the average Nusselt number by up to 5.24%, whereas under strong magnetic fields, SWCNT nanofluid exhibits the best thermal performance, with a maximum enhancement of 12.66% at low Ra and the smallest reduction of 5.34% at high Ra. These results demonstrate that the combined effects of nonuniform heating and wall geometry significantly influence thermal behavior in applications such as solar receivers and electronic cooling systems.
Nanofluids are rapidly being used in modern thermal duct systems to improve thermal effectiveness in a variety of sectors, such as petrochemical manufacturing and mechanical engineering. Inspired by these advancements, the present work investigates the transport by convection hybrid nanofluid (HNF) through a stiff rectangular duct controlled by buoyancy. The duct’s other walls are heated isothermally, while the upper and lower borders are insulated. Included are the effects of viscous heating. Internal code is used to solve the governing equations. For particular circumstances, benchmarking with prior research is used to verify the accuracy of the FDM code. Additionally, a mesh independence test is carried out. The effects of Grashof number (0.01 ≤ Gr ≤ 50), Brinkman number (0.0 ≤ Br ≤ 2.0), nanoparticle (NP) solid volume fraction (0.001 ≤ φ ≤ 0.02), and aspect ratio (0.5 ≤ A ≤ 2.0) are given on the physical properties for both unitary nanofluid (NF) and HNF. The results show that the velocity increases with increasing Gr and Br, while an increase in φ has the reverse effect. As the Gr and Br, φ , and A increase, the heat transfer rate for both unitary NF and HNF escalates at the left and declines at the right wall.
In the current study, we have analysed the characteristics of entropy generation and thermal transfer of magnetohydrodynamic incompressible Casson fluid flowing across a porous inclined microchannel. The intricate interaction of thermal radiation, Joule heating, heat sink/source and viscous forces are captured in addition to convective boundary constraints. By deploying similarity variables, the governing set of equations are reformed to a nondimensional system and are meticulously evaluated through implementing Taylor wavelet operational matrix method, a numerical technique known for its accuracy and computational efficacy for solving non-linear problems. A meticulous analysis is carried out to elucidate the significance of numerous measurable quantities on temperature, velocity, Bejan number and entropy generation profiles, visualized via detailed graphical representations. The key findings demostrates that a rise in Eckert number, Casson parameter, inclination angle, and Grashof number enhances entropy production and a concurrent decrease in the Bejan number, which offers valuable perspectives on reducing irreversibilities and enhancing thermal efficiency in non-Newtonian flows. The observed congruity with existing literature validates both the efficiency and precision of the adopted numerical approach.
This model is valuable in engineering applications that need accurate forecasting and management of non-Fourier heat transport in sophisticated cooling and thermal management systems. The semi-analytical and Machine Learning-based study of Nimonic 80A-AA7072/HFE-7100 hybrid nanoliquid with Christov-Cattaneo flux effects has applications in high-temperature heat exchangers, aerospace and gas turbine cooling components, electronic and microchannel cooling systems, and energy storage devices. By capturing thermal relaxation effects and maximizing thermal performance, the model aids in the design of efficient, low-energy-loss systems for advanced manufacturing, nuclear and renewable energy technologies, and small thermal devices. Using an intelligent back-propagation neural network with Levenberg Marquardt strategy (IBNN-LMS), the current work aims to assess the significance of Christov-Cattaneo flux model on Nimonic 80A-AA7072/HFE-7100 based hybrid nanoliquid. The simplified equations are evaluated implementing the Homotopy Analysis technique. The impacts of significant variables on microbiological, solutal, thermal, and flow profiles are evaluated using graphs. This study covers the intelligent computing-based neural network of IBNN-LMS, which has been developed using datasets and then trained, tested, and verified to produce approximation results.
