Fluid Flow Problems Research Articles

Optimization and sensitivity analysis of heat transfer for Powell–Eyring fluid between rotating rolls with temperature-dependent viscosity: A mathematical modeling approach

This study explores the flow of a non-Newtonian fluid between two rolls that are counter-rotating at the same speed and of equal size. The fluid's viscosity depends on temperature, and we investigate its theoretical impact on the thickness of the sheet and other engineering parameters relevant to the process. We derive non-dimensional mass and momentum balance equations using suitable transformation and the lubrication approximation theory. The expressions for velocity distribution, pressure gradient, flow rate, temperature profile, and pressure fields have been obtained by utilizing the perturbation method. After obtaining these expressions, we compute engineering quantities such as the roll separation force, streamline, Nusselt number, and the power input required to drive both cylinders based on the system's kinematical and geometrical parameters. We also obtain numerical solutions using the finite difference method and built-in (BVP method) in Maple. Further, we use response surface methodology and analysis of variance to determine what the mathematical models mean and whether they are good enough for sensitivity and optimization analysis of the heat transmission and roll separation force. Using statistical tools such as the R2, we determine that our Nusselt number and roll separation force provide the best solution for the considered model. Additionally, it has been observed that as the Weissenberg number increases, velocity tends to rise; conversely, velocity decreases with a higher velocity ratio. Also, the temperature profile is notably influenced by the Brickman number and increases with the increase in the Brickman number. It has also been noted that as the values of velocities ratio increase, the separation points shift toward the nip region, while concurrently, the coating thickness decreases. Furthermore, we also demonstrate that compression between analytical and numerical solutions for the considered problem of fluid flow, which suggests that the results presented here are reasonable. Finally, we compare our work with published studies to validate our findings. Hence, these factors help in an efficient fluid coating process and improve the substrate life.

Dissipative Non-Slip MHD Nanofluid Flow with Variable Viscousity and Thermal Conductivity in the Presence of Arrhenius Chemical Reaction

This research investigates the intricate dynamics of dissipative non-slip magnetohydrodynamic (MHD) nanofluid flow, characterized by variable viscosity and thermal conductivity, under the influence of an Arrhenius chemical reaction. The inclusion of the Arrhenius chemical reaction adds complexity through heat generation or absorption, impacting temperature and concentration gradients. The study is motivated by the extensive applications of nanofluids in engineering and industrial processes, where precise control of heat and mass transfer is critical. We develop a comprehensive mathematical model that incorporates the variable properties of the nanofluid, the effects of the Lorentz force due to the applied magnetic field, and the temperature-dependent reaction rates dictated by the Arrhenius equation. The formulated governing equations were non-dimensionalised to identify the flow governing parameters. Finite Element Method (FEM), grid generation, solution algorithms, and post-processing to analyse velocity, temperature, and concentration distributions were used to obtain the numerical methods to solve fluid flow problems based on the Navier-Stokes equations, involving concepts of discretization. pdsolve subpackage in Maple 2023 was used to numerically solve PDEs with specific initial and boundary conditions, incorporating the plot and display commands for graphical analysis, and the results are presented and discussed. The findings reveal that the interplay between parameters like Hartmann number, Darcy parameter, and heat generation or absorption profoundly influences flow behaviour and thermal characteristics. The reactivity parameter is crucial, dictating the rate of chemical reactions and affecting system dynamics. This research enhances understanding of the interdependencies among fluid properties, chemical reactions, and external parameters in nanofluid flows.

A variational data assimilation approach for sparse velocity reference data in coarse RANS simulations through a corrective forcing term

The Reynolds-averaged Navier–Stokes (RANS) equations provide a computationally efficient method for solving fluid flow problems in engineering applications. However, the use of closure models to represent turbulence effects can reduce their accuracy. To address this issue, recent research has explored data-driven techniques such as data assimilation and machine learning.An efficient variational data assimilation (DA) approach is presented to enhance steady-state eddy viscosity based RANS simulations. To account for model deficiencies, a corrective force term is introduced in the momentum equation. In the case of only velocity reference data, this term can be represented by a potential field and is divergence-free. The DA implementation relies on the discrete adjoint method and approximations for efficient gradient evaluation.The implementation is based on a two-dimensional coupled RANS solver in OpenFOAM, which is extended to allow the computation of the adjoint velocity and pressure as well as the adjoint gradient. A gradient-based optimizer is used to minimize the difference between the simulation results and the reference data. To evaluate this approach, it is compared with alternative data assimilation methods for canonical stationary two-dimensional turbulent flow problems. For the data assimilation, sparsely distributed reference data from averaged high-fidelity simulation results are used.The results suggest that the proposed method achieves the optimization goal more efficiently compared to applying data assimilation for obtaining the eddy viscosity, or a field modifying the eddy viscosity, directly. The method works well for different reference data configurations and runs efficiently by leveraging coarse meshes.

Chelyshkov wavelet-based numerical technique for the solution of Darcy–Forchheimer flow of Erying–Powell radiated dusty fluid over a stretching sheet with Cattaneo–Christov heat flux

This article presents the Chelyshkov wavelet-based numerical technique (CWBNT) for the solution of the system of non-linear differential equations arising in the study of Darcy–Forchheimer flow of Erying–Powell radiated dusty fluid over a stretching sheet with Cattaneo–Christov heat flux. Initially, the proposed technique is implemented on the test problem having exact solution. The obtained results are highly accurate in comparison with the solutions obtained by shooting technique based Runge–Kutta Fehlberg 4th–5th order method. The proposed technique is applied to the governing equations of the considered dusty fluid problem. The results obtained for some fixed values of parameters resemble the previously published results. The comparisons validate the method. The flow behavior of dusty fluid is analyzed and the effect of various factors on the velocity and thermal attribute of the dust and fluid phase are studied. It is inferred that the Erying–Powell fluid parameters ε and α have entirely different effects on temperature, velocity profiles, and skin-friction coefficient. The local inertia parameter decreases the velocity and thermal relaxation parameter decreases the temperature. Enhancement in temperature ratio and radiation parameters escalates the temperature and Nusselt number. The proposed technique is simple, reliable, efficient tool to solve the differential equations arising in dusty fluid flow problems.

An inverse analysis of fluid flow through granular media using differentiable lattice Boltzmann method

This study presents a method for the inverse analysis of fluid flow problems. The focus is put on accurately determining boundary conditions and characterizing the physical properties of granular media, such as permeability, and fluid components, like viscosity. The primary aim is to deduce either constant pressure head or pressure profiles, given the known velocity field at a steady-state flow through a conduit containing obstacles, including walls, spheres, and grains. The lattice Boltzmann method (LBM) combined with automatic differentiation (AD) (AD-LBM) is employed, with the help of the GPU-capable Taichi programming language. A lightweight tape is used to generate gradients for the entire LBM simulation, enabling end-to-end backpropagation. Our AD-LBM approach accurately estimates the boundary conditions for complex flow paths in porous media, leading to observed steady-state velocity fields and deriving macro-scale permeability and fluid viscosity. The method demonstrates significant advantages in terms of prediction accuracy and computational efficiency, making it a powerful tool for solving inverse fluid flow problems in various applications.

Entropy production in the flow of Bingham-Papanastasiou fluid having temperature and shear rate-dependent viscosity

This article comprehensively examines entropy production in a peristaltic flow of Bingham-Papanastasiou fluid in an asymmetric wavy wall channel. The viscosity of the fluid is selected to depend on the temperature in addition to the shear rate. Furthermore, viscous dissipation is considered. The equations governing momentum and energy are adjusted to incorporate the existence of a nonlinear correlation between stress and strain rate. The energy dissipation caused by viscosity in the energy equation exhibits variation between Newtonian and non-Newtonian fluids due to their distinct rheological behaviors and response to shear forces. Newton’s law of viscosity states that the viscous dissipation term for Newtonian fluids follows a simple linear relationship between shear stress and shear rate. In contrast, non-Newtonian fluids exhibit more complex rheological behaviors, with the correlation between shear stress and shear rate described by various constitutive equations, depending on the specific type of non-Newtonian behavior. Consequently, the energy equation for non-Newtonian fluid flow problems becomes more intricate and nonlinear compared to the energy equation for Newtonian fluids, resulting in a more challenging analysis. Modeling of the equations is traditionally obtained using all steps involved in analyzing peristaltic flow. Using MATLAB's bvp5c solver, the obtained coupled set of differential equations is numerically solved. The research explores how the Bingham number and stress growth exponent parameters affect different dimensionless variables, including velocity, streamlines, temperature, axial pressure gradient, entropy production, and the Bejan number.

Stagnation point flow in a Maxwell fluid with a slip condition and the role of viscous dissipation and radiation

This research aims to examine the impact of viscous dissipation, slip conditions, and radiation on the stagnation point flow when a stretching/shrinking sheet is immersed in a Maxwell fluid. The significance of viscous dissipation has great importance in an extensive range of engineering applications, including heat exchangers, lubrication systems, polymer processing, and biofluid mechanics. In heat and mass transfer fluid flow problems, viscous dissipation can have significant effects, particularly in situations involving high fluid velocities or high viscosity fluids. In this computational study, the governing equations, namely the momentum, and energy equations, are formulated and non-dimensionalized using appropriate similarity parameters and the Runge-Kutta-Fehlberg method is then employed to resolve the problem. The obtained results provide detailed insights into the velocity, temperature, skin friction and wall temperature distributions in the flow domain. Additionally, the role of viscous dissipation in altering the heat transfer characteristics of the Maxwell fluid is examined. The results indicate that the existence of viscous dissipation significantly impacts the flow behaviour of the Maxwell fluid. It alters the boundary layer thickness, temperature distribution, and the overall heat transfer rate. Additionally, it is observed that the values of the Prandtl number strongly affect the influence of viscous dissipation on the velocity and temperature distribution. The outcomes of this study correlate with those that have been previously reported.

Influence of thermal radiation and shape factor on a hybrid nanofluid flow over a permeable flat plate with cross-diffusion effects: An irreversibility analysis

Understanding and controlling the shape factors of nanoparticles in fluid flow problems is crucial for optimizing heat transfer, fluid dynamics, and various applications such as nanofluids, drug delivery systems, catalysis, and nanocomposites. By tailoring the shape of nanoparticles, researchers can manipulate their behavior, dispersion, and interaction with the fluid, thereby optimizing the desired outcomes in various fluid flow problems. The meticulous investigation uncovers the integration of entropy analysis in the investigation of the flow of convective magnetohydrodynamic hybrid nanofluid via a permeable flat surface, by considering the effects of Dufour, viscous dissipation, Soret, and thermal radiation. The governing equations are converted into a set of nonlinear ordinary differential equations using appropriate similarity transformations and then solved using the bvp4c solver, a MATLAB in-built function. We display the outcomes for three different shape factors: platelet, cylinder, and brick. The skin friction coefficient increases at a rate of 1.5089 for the brick shape, 1.5163 for the cylindrical shape, and 1.5212 for the platelet shape when the mixed convection parameter lies between 1 and 5. In this regard, it is important to point out that there is a direct connection between the increase in temperature transmission rate and a decline in the Dufour number ( Du ). It has been found that when 1 ≤ Du ≤ 2.4 , the Nusselt number decreases by 0.4786, 0.4618, and 0.4512 for brick, cylinder, and platelet shapes, respectively. A decline in the Sherwood number is noticed with an upsurge in the Soret number ( Sr ). There is a noticeable increase of 0.0442 in the Sherwood number for brick shape, 0.0438 for cylinder form, and 0.0435 for platelet form when 1 ≤ Du ≤ 2.4 . Furthermore, we have detected that an increase in the radiation parameter amplifies both the Bejan number and the profiles of entropy formation.

Overview of the Application of Physically Informed Neural Networks to the Problems of Nonlinear Fluid Flow in Porous Media

To describe unsteady multiphase flows in porous media, it is important to consider the non-Newtonian properties of fluids by including rheological laws in the hydrodynamic model. This leads to the formation of a nonlinear system of partial differential equations. To solve this direct problem, it is necessary to linearize the equation system. Algorithm construction for inverse problem solution is problematic since the numerical solution is unstable. The application of implicit methods is reduced to matrix equations with a high rank of the coefficient matrix, which requires significant computational resources. The authors of this paper investigated the possibility of parameterized function (physics-informed neural networks) application to solve direct and inverse problems of non-Newtonian fluid flows in porous media. The results of laboratory experiments to process core samples and field data from a real oil field were selected as examples of application of this method. Due to the lack of analytical solutions, the results obtained via the finite difference method and via real experiments were proposed for validation.

Impact of porous material and slip condition on the MHD flow of immiscible Couple stress-Newtonian fluids through an inclined channel: Head loss and pressure difference

Nowadays, non-Newtonian and Newtonian non-miscible fluid flow problems are much more effective in real-life physical problems. The understanding of flow behavior of magneto-hydrodynamic non-miscible fluids through a porous region playing an important role in the areas of biochemical sciences, crude oil extraction, transport issues and biomedicine. The aim of the present study is to know the impact of inclination angle of the channel, porous material used in the channel, slip boundary condition and applied magnetic field on the flow variables such as velocity profile, wall shear stress, pressure differences, head loss and volumetric flow rate of the two electrically conducting non-miscible couple stress and Newtonian fluids flowing through an inclined channel occupied with porous material of different porosity and permeability. An inclined channel is divided into two sub-regions of equal width through which the Newtonian and Couple stress fluids flow, respectively. Here, Brinkman’s model has been used to study the flow of immiscible fluid in their respective porous region. The equations that govern the flow of non-miscible fluids are solved using a well-defined analytical method and Mathematica 10.3 software. The present study concludes that the porous materials can be used to control the velocity of immiscible fluids in an inclined channel. It is also concluded from the present study that the use of slip condition promotes the values of velocity, volumetric flow rate, pressure differences and head loss. This work is validated with the previously published research work. Such models can be helpful in industries for filtering or refining immiscible oils.

The influence of micro-channel shape filled by nanofluid on heat transfer characteristics: Numerical and experimental study

The integration of nanofluid effects and channel shape effects in a heat sink, which exhibits both variable and constant cross-section, has gained significant traction as an efficient cooling method for thermal devices, particularly microelectronic devices. This research presents an experimental and numerical analysis to compare the performance of microchannel heat sink designs (straight, zigzag, wavy, and circular cavities). In addition, the study dealt with the use of pure water and nanofluid (CuO-H2O) with volumetric concentrations of (0.01, 0.02, and 0.03) as coolants. COMSOL Multiphysics was used for numerical analysis to simulate and solve the problem of fluid and heat flow in 3D. The bottom wall of the four microchannels is subjected to a steady heat flux of 170 kW/m2. The simulations were only performed within the laminar domain, encompassing a spectrum of Reynolds numbers ranging from 50 to 150. The influence on the microchannel's wall temperature, thermal resistance, pressure drop, and friction factor is exhibited. According to the findings, the wavy and zigzag microchannel heat sink cooled by nanofluid displays higher performance in terms of heat transmission and dissipation in comparison to the heat sink that was cooled by distilled water. as evidenced by a 12% increase in mussel number at volume concentrations of 0.03%.

Effects of viscous dissipation, gravity modulation and Joule heating on MHD Casson fluid flow over a vertically moving plate with second-order slip velocity

The study of magnetohydrodynamic flow problems for non-Newtonian fluids is significant in many engineering problems. The current inquiry is concerned with a time-dependent, incompressible magnetohydrodynamic Casson fluid flow in a vertically moving plate. The aim of this study is to analyse the effect of viscous dissipation, gravity modulation, heat source and Joule heating with second-order slip velocity. Governing equations are converted to non-dimensional ones using appropriate similarity transformations. To solve the altered equations, the perturbation method is applied, together with MATLAB software. The important physical outcome of this research is that the gravity modulation parameter increases the temperature and velocity of fluid inside the boundary layer. The Eckert number enhances the fluid velocity, concentration boundary layer, skin friction and Nusselt number, whereas the temperature boundary layer reduces for heat sink parameter. The permeability of the porous parameter raises the fluid’s concentration. The work of Kodi et al. [2021. “Investigation of MHD Casson Fluid Flow Past a Vertical Porous Plate Under the Influence of Thermal Diffusion and Chemical Reaction.” Heat Transfer 51 (1): 377–394] has been expanded in this study by adding the novel effects of gravity modulation, Joule heating and viscous dissipation. In addition, the boundary condition includes second-order slip velocity. The obtained results are compared with Kodi et al. [2021. “Investigation of MHD Casson Fluid Flow Past a Vertical Porous Plate Under the Influence of Thermal Diffusion and Chemical Reaction.” Heat Transfer 51 (1): 377–394] and it shows an excellent agreement when added effects are neglected.

Body‐fitted topology optimization via integer linear programming using surface capturing techniques

AbstractRecent advancements in computational tools and additive manufacturing have expanded design possibilities on fluid devices and structures to also include aesthetics. However, traditional discrete density‐based topology optimization methods usually use square and cubic regular meshes, resulting in jagged contour patterns that require mesh refinement and post‐processing to numerical solution steps of complex physics problems. In this article, we propose a new isosurface boundary capture strategy for topology optimization in structural and fluid flow problems. The capture of smoothed boundaries is done via a simple strategy through element splitting and analysis domain remeshing. The smoothing procedure novelty lies on the optimizer regular mesh decomposition into smaller triangular or tetrahedral elements with a pseudo‐density nodal function that produces implicit geometry boundaries. We employ the TOBS‐GT (topology optimization of binary structures with geometry trimming) method to solve optimization problems for mean compliance and fluid flow energy dissipation, subject to a volume fraction constraint. Since, we perform discrete body‐fitted optimization, the material interpolation models are expressed in linear form without penalty factors. Our method produces a lower computational cost topology evolution with high resolution and mitigated sharp details, achieved via smooth edges and surfaces, as demonstrated through benchmark numerical examples in two‐ and three‐dimensional space. In addition, the proposed strategy facilitates the optimization of benchmark fluid flow examples for moderate Reynolds numbers.

Impact of new similarity transformations on heat transfer analysis of Casson tri-hybrid nanofluid in blood with thermal radiation through a stretching sheet: a homotopy perturbation Sumudu transformation approach

ABSTRACT The investigation of nonlinearly stretching surface has been conducted using the Casson model, focusing on a unique mixture known as a ternary nanofluid. This specific nanofluid comprises a combination of blood with suspended aluminum alloys, namely AA 7072 and AA 7075 , as well as A l 2 O 3 oxide. The nanoparticles dispersed in the underlying fluid are envisioned to possess a sphere-like structure, thereby ensuring optimal contact between the nanoparticle’s extensive surface area and the base fluid. Consequently, this design enables enhanced heat absorption from the surface. Additionally, the unique combination of the nanoparticles facilitates swift mobility within the nanofluid, expediting their movement. We derived a novel set of similarity transformations, in which the similarity variable is dimensionless and appears in the formulation as a function of all independent variables. The Runge-Kutta Fehlberg 4- 5 th methodology was used to solve the modified equations numerically. In previous research papers, the Homotopy perturbation Sumudu transform method (HPSTM) was employed to derive the analytical solution solely for the momentum equation. However, in this current study, the Homotopy perturbation Sumudu transform method (HPSTM), is applied to solve the coupled momentum and heat equations of trihybrid nanofluid, resulting in an innovative analytical solution that has not been previously explored. The comparison with the numerical results demonstrates the precision of the present work. The repercussions of unique components on thermal and velocity plots are explained in graphical records for each case of nanofluid, hybrid nanofluid and trihybrid nanofluid separately. This study encourages the application of Homotopy perturbation Sumudu transform technique in more fluid flow problems.

Improve Solutions of Differential Transform Method for Jeffrey Hamel Magneto-hydrodynamic Non-Newtonian Casson Fluid Flow Problem

In this article, Magneto-hydrodynamic flow of a non-Newtonian Casson fluid in converging and diverging channels subject to stretching -shrinking cases is an important problem in the field of fluid flow that has been highlighted by the combination of the differential transformation method and the optimal method so-called optimal differential transformation method (ODTM). In this synthesis that is used achieves improved analytical results for this problem. This study examines the impact of several developing characteristics, including channel angle, stretching-shrinking parameter, Casson fluid parameter, Hartmann number, and Reynolds number with the velocity profiles. Results obtained from the DTM and the numerical method BVP4c are compared to those resulting from ODTM which consist of the collocation differential transform method (CDTM), the sub-domain differential transform method (SDTM), the least squares differential transform method (LSDTM), and the Galerkin differential transform method (GDTM). The comparison shows that the percentage errors of the optimal methods (ODTM) are more accurate than those of the DTM for a similar number of parts of the repeated series over a wide range of physical parameters. Finally, it can be said that the results of the proposed method for third-order nonlinear Jeffrey Hamel flow in the non-Newtonian Casson fluid problem are high accuracy.

Potential of physics-informed neural networks for solving fluid flow problems with parametric boundary conditions

Fluid flows are present in various fields of science and engineering, so their mathematical description and modeling is of high practical importance. However, utilizing classical numerical methods to model fluid flows is often time consuming and a new simulation is needed for each modification of the domain, boundary conditions, or fluid properties. As a result, these methods have limited utility when it comes to conducting extensive parameter studies or optimizing fluid systems. By utilizing recently proposed physics-informed neural networks (PINNs), these limitations can be addressed. PINNs approximate the solution of a single or system of partial differential equations (PDEs) by artificial neural networks (ANNs). The residuals of the PDEs are used as the loss function of the ANN, while the boundary condition is imposed in a supervised manner. Hence, PDEs are solved by performing a nonconvex optimization during the training of the ANN instead of solving a system of equations. Although this relatively new method cannot yet compete with classical numerical methods in terms of accuracy for complex problems, this approach shows promising potential as it is mesh-free and suitable for parametric solution of PDE problems. This is achieved without relying on simulation data or measurement information. This study focuses on the impact of parametric boundary conditions, specifically a variable inlet velocity profile, on the flow calculations. For the first time, a physics-based penalty term to avoid the suboptimal solution along with an efficient way of imposing parametric boundary conditions within PINNs is presented.

Nodal integral method to solve the two-dimensional, time-dependent, incompressible Navier-Stokes equations in curvilinear coordinates

The numerical solution of the two–dimensional, time–dependent, incompressible Navier–Stokes equations (NSE) in curvilinear coordinates using the nodal integral method (NIM) is presented in this paper. The developed numerical scheme is applied to solve fluid flow problems in domains discretized using quadrilateral cells. Three test problems are numerically solved to assess the accuracy and efficiency of the method. The scheme is second-order accurate in space for all considered deformation levels and Re numbers. The results of the current scheme are compared with the other numerical results in the literature, and good agreement is obtained for all considered cases. The NIM demonstrates superior accuracy per cell compared to other second–order finite–volume schemes considered in this work. New benchmark results obtained from the solution on fine meshes are presented.

Latest advancements in fluid flow and heat transfer: A review studyLatest advancements in fluid flow and heat transfer: A review study

The present paper aims to provide a varied and wide range of recent advancement in fluid flow and heat transfer in different flow geometries considering the effects of different flow parameters. Several parameters like “magnetic field (applied as well as induced), porosity of the surface as well as medium, heat source/sink, radiation, absorption, free/forced convection, chemical reactions etc.” have their impact on the flow. These fluid flow problems have their applications in many engineering as well as astrophysical and geophysical problems of interests. Present study may provide the readers a brief idea about the fluid flow and heat transfer problems.

Current advancements in fluid-flow Problems: A brief review

This specific article is a compilation of a few current studies on fluid flow issues. This article provides an overview of current research on the experimental and theoretical analysis of various nanofluids' thermal conductivity. The current study examines a number of variables that have a significant impact on a nanofluid's ability to transfer heat, including temperature, solid volume fraction, type, size, shape, magnetic field, pH, ultrasonic time, and surfactant. In addition, some plausible and appealing theories that enhance the thermal conductivity of nanofluids are mentioned. The final important heat transmission mechanisms that play a significant part in improving thermal conductivity are Brownian motion, thermophoresis, nanoclustering, interfacial nano-layer, and osmophoresis. Thus, consideration is given to the heat transmission properties of nanofluids. And also discussed some Numerical method to solve fluid flow problems.

Heat and mass transfer phenomena for fractal interfacial layer model on metallic-nanomaterials nanofluids flow with chemical reaction effect

This study presents a comprehensive investigation into the intricacies of single-phase simulation concerning the behavior of fractal interfacial magnetized metallic chemical-reactive nanoparticles within fluid systems. The research focuses on unraveling the multifaceted phenomena associated with heat and mass transfer in complex nanoscale environments. To achieve this, we employ numerical techniques to address the intricate fluid flow problems that arise due to the presence of these nanoparticles. Fractal complexities are linked to critical phenomena, such as mixing and mass transport, at the turbulent/non-turbulent interface of shear layers and boundary layers. This study primarily concentrates on the phenomena of heat and mass transfer, with a focus on estimating thermal conductivity models that have significant impacts on the flow of metallic nanofluids under convective conditions. The combination of a high thermal conductivity model with a novel interfacial fractal theory reveals a substantial effect on heat and mass transfer enhancement. Furthermore, this research explores hybrid types of porous channel geometries under the combined influence of magnetohydrodynamics and chemical reaction mechanisms in the presence of metallic nanoparticles. A comprehensive numerical analysis of higher-order nonlinear differential equations is conducted, which exposes the flow field’s behavior concerning momentum, energy, and mass transfer. These insights are envisioned through single-phase simulations of nanofluids. The influence of the nanoparticles’ radius and diameter is found to play a significant role in thermal performance, with nanoparticles ranging from 1% to 8% exhibiting a notable impact on thermal conductivity. Highlights A new mathematical relation of mass, as well as heat transfer for metallic-nanomaterial being affected by thermal conductivity (T.C.), has been established. The important role of the physical number is observed under the effect of T.C. and heat and mass transfer through orthogonal porous surfaces. An injection/suction, as well as an expansion/contraction phenomenon related to the porous surface is observed.