Magnetic Parameters Research Articles

An investigation of heat transfer and optimization of entropy in bio-convective flow of Eyring-Powell nanomaterial with gyrotactic microorganisms

Entropy generation in nanofluid flows is a critical parameter that influences the performance, efficiency, and sustainability of thermal systems. Understanding and optimizing entropy creation can lead to noteworthy advancements in numerous engineering applications, from renewable energy systems to industrial processes and biomedical equipments. The purpose of this article is to examine the entropy produced in the bioconvection flow of Eyring-Powell nanomaterial with gyrotactic microorganisms. The mathematical equations representing the flow are modeled considering the flow towards a porous surface of a cylinder. Together with the effects of the governing parameters, the mass and heat transfer components of the problem are discussed. The thermal effects of different natures are used in a new way. Overall, entropy creation is designed with regard to the second law of thermodynamics. Activation energy, chemical reaction, thermal radiation, and internal friction force effects are accounted for the development of the mathematical model. Coupled non-linear dimensional equations have been altered into ordinary differential equations (ODEs) and then treated using the MATLAB Finite Difference Method (FDM). Consequence of diverse sundry parameters on entropy production, thermal field, mass concentration profile, Bejan quantity, and motile density of microorganisms is deliberated via plots. Through tables, engineering quantities are analyzed. According to the findings, the velocity profile rises as the curvature and Eyring-Powell fluid parameters rise, while it falls when the magnetic parameter is enhanced. Additionally, it is noted that as the curvature variable enhances, the rate of heat transfer and skin friction coefficient decays.

Analytical investigation of convective phenomena with nonlinearity characteristics in nanostratified liquid film above an inclined extended sheet

Abstract This work focuses on the time-variant convective thin-film nanoliquid fluid flow and heat transfer over a stretching, inclined surface under the effect of magnetism for different energy technologies for sustainability. It is crucial to understand how solid materials can be treated with thin films while focusing on the actual ability to improve the body surface features for infiltration, shock resistance, rigidness, brightness, dispersal, absorption, or electrical efficiency. All of these improvements are invaluable, especially in the field of nanotechnology. As with any mass and thermal transport phenomena, the study breaks down important factors such as thermophoresis and Brownian movement, in an attempt to improve the energetic balance and lessen fuel consumption. Utilizing the mathematical model of the temporal evolution on the liquid film flow characteristics over an inclined surface, we obtain a system of nonlinear partial differential equations and convert it to a system of coupled ordinary differential equations appropriately. Finally, the results of the model problem computational analysis are produced using the Laplace Adomian decomposition method (LADM) and are shown both quantitatively and visually. During the flow analysis, the impact of specific flow parameters such as the magnetic, Brownian, and thermophoresis parameters are examined and found to be highly significant. Furthermore, it is found that the effects of ( M M ) and (Nt) factors on ( F F ), ( Φ \Phi ), and ( ϕ \phi ) lead to decreased conduction. Conversely, the thermal gradient within the liquid films rises in proportion to the (Nb) factor. This research is distinguished from similar attempts made in the past in terms of thin-film nanoliquid flow from inclined planes and application of LADM approach toward modeling. The findings have provided tangible use in coming up with new methods of cooling electronics gadgets, energy harvesting for solar energy, and eco-friendly industrial processes.

Optimization Design of Cogging Torque for Electric Power Steering Motors

Excessive cogging torque can cause torque fluctuations, noise, and vibration in electric power steering (EPS) motors, which is a key factor in the high-precision and high-performance optimization design of EPS motors for electric vehicles. This article takes a 12-slot 10-pole electric power steering motor for a certain car as an example. By establishing the corresponding electromagnetic field model and theoretical analysis of the motor, the influence of the pole arc coefficient and eccentricity parameters of the permanent magnet on the cogging torque of the electric power steering motor is explored. A comprehensive optimization scheme for reducing the cogging torque of the motor structure is proposed. The effectiveness of the designed scheme was verified through finite-element simulation and experimental testing of motor electromagnetism. Compared with the original design, the optimized structure of the EPS motor resulted in an 86.62% reduction in cogging torque during experimental testing.

Design of Nonlinear Autoregressive Neuro-Computing Structure for Bioconvective Micropolar Nanofluidic Model

In the present arena, the tools of artificial intelligence (AI) play a significant role in research across various fields by enabling advanced data analysis, pattern recognition and decision-making. This research work presents the numerical investigation of bioconvective micropolar nanofluidic model (BCMNFM) by employing the knacks of AI-based nonlinear autoregressive (NAR) approach with a combination of backpropagated Levenberg–Marquardt neural networks (BLMNNs) represented as NAR-BLMNNs. This research work investigates the flow design to highlight the attributes of mass and heat exchange. A dataset for BCMNFM is created by applying the Adam numerical procedure by variation of unsteadiness parameter ([Formula: see text], magnetic field parameter ([Formula: see text] thermophoresis parameter (Nt), Brownian motion parameter (Nb), bioconvection Peclet number (Pe) and spin gradient viscosity parameter ([Formula: see text] The skills of AI-based NAR-BLMNNs technique is then utilized on the dataset created for BCMNFM to investigate the approximate solutions. The achieved and impactful values of performance consistently range between [Formula: see text] and [Formula: see text] across all scenarios of BCMNFM. The precision and the validation of predicted approach NAR-BLMNNs is exceptionally established by the graphical demonstration for all scenarios of MSE, regression metrics, error histograms and time series graphs. The numerical calculations attained through AI-based NAR-BLMNNs technique further rationalize the precision of the proposed methodology for solving the BCMNFM effectively and efficiently.

Can dynamic contrast-enhanced MR imaging based on radiomics improve the diagnostic efficiency of clinically significant prostate cancer?

Aims/Background Prostate cancer stands out as one of the most prevalent malignant tumours among males. The non-invasive identification of clinically significant prostate cancer via magnetic resonance imaging plays a critical role in circumventing unnecessary biopsies and determining suitable treatment strategies for patients. Our study aimed to evaluate the potential improvement in predictive accuracy for clinically significant prostate cancer by incorporating perfusion data obtained from dynamic contrast-enhanced magnetic resonance imaging acquisition protocols into multiparametric magnetic resonance imaging parameters. Methods Radiomics extracted from perfusion parameters (Ktrans, Kep, Ve) of dynamic contrast-enhanced magnetic resonance imaging were analysed in patients suspected of prostate cancer who underwent 3T multiparametric magnetic resonance imaging between January 2017 and June 2023 in this retrospective study. The pathological findings obtained from biopsy or therapy were categorised into groups based on the Gleason sum score as either clinically significant prostate cancer (Gleason sum score > 7) or non-clinically significant prostate cancer (Gleason sum score ≤ 6). Diagnostic models were constructed using logistic regression analysis, incorporating prostate imaging reporting and data system V2.1 scores and clinical data, with or without radiomics extracted from dynamic contrast-enhanced. The area under curve (AUC) values were compared using the DeLong test. Results Overall, 214 men (clinically significant prostate cancer [n=78] and non-clinically significant prostate cancer [n=136]) were included. The clinical-prostate imaging reporting and data system model demonstrated an AUC of 0.89 (95% confidence interval: 0.84-0.95) in the training cohort and 0.91 (95% confidence interval: 0.84-0.98) in the test cohort. For the clinical-prostate imaging reporting and data system-radscore model, the AUC values were 0.97 (95% confidence interval: 0.95-0.99) for Ktrans, 0.98 (95% confidence interval: 0.96-1.00) for Ve, and 0.96 (95% confidence interval: 0.93-0.98) for Kep in the training cohort, and 0.97 (95% confidence interval: 0.94-1.00) for Ktrans, 0.95 (95% confidence interval: 0.91-1.00) for Ve, and 0.97 (95% confidence interval: 0.94-1.00) for Kep in the test cohort. Radiomics based on perfusion parameters exhibited good diagnostic performance in predicting clinically significant prostate cancer. The clinical-prostate imaging reporting and data system-radscore model demonstrated superior diagnostic capability compared to perfusion-based radiomics or clinical-prostate imaging reporting and data system models alone. Conclusion The application of radiomics, which involves extracting perfusion parameters from dynamic contrast-enhanced imaging, has the potential to enhance diagnostic accuracy for clinically significant prostate cancer.

Influence of calcination temperature and particle size distribution on the physical properties of SrFe12O19 and BaFe12O19 hexaferrite powders

The paper deals with the economic optimisation of ferrite powder preparation during producing hard ferrite magnets. The magnetic properties of ferrites are investigated by replacing feedstock and reducing calcination temperature and particles in the order of tens of microns. The granulates about 8–10 mm in size were calcined for 2 h in the temperature range from 1100 °C to 1300 °C and additionally crushed and milled to an average particle size of about 80–90 µm. The scanning electron microscopy images confirmed the agglomerates of particles with different shapes and sizes in tens of µm. The X-ray diffraction measurements revealed that, besides the SrFe12O19 and BaFe12O19 phases, there was also the presence of 2–39% hematite. The highest values of maximum energy product (BH)max = 930 J/m3 and remanent magnetic induction Br = 72.8 mT were obtained at a calcination temperature of 1300 °C. The Henkel plots confirmed the presence of exchange-coupling and dipolar magnetic interactions at lower and higher magnetic fields, respectively. The strength of interactions was also dependent on the calcination temperature. Replacing strontium with barium led to a deterioration of the magnetic parameters, which were optimal at a lower calcination temperature (1100 °C). This phenomenon was partly overcome by reducing the mean particle size of Ba-based hexaferrites to 45–50 µm.

Sensitivity analysis and optimization of heat transfer in the time-reliant magnetohydrodynamic bioconvective flow of radiative couple-stress hybrid nanofluid through a squeezing channel with viscous dissipation: Entropy analysis

This research presents a statistical investigation of heat transmission in the time-reliant flow of blood-based hybrid nanofluid-containing microorganisms via a squeezing permeable channel utilizing a couple-stress non-Newtonian fluid model. Nanoparticles of SWCNT (single-wall carbon nanotubes) and MWCNT (multi-wall carbon nanotubes) are incorporated in the base liquid due to their low toxicity, special physio-chemical characteristics, and suitable surface modifications. In addition, chemical reactions, heat sources and sinks, radiation, viscous dissipation, and an external magnetic field impact the flow. The current numerical study stands out because it optimizes heat transmission rate using a face-centered central composite design framework with RSM (Response Surface Methodology) and analyses its sensitivity toward effective parameters. Examining the system's efficiency by evaluating the entropy produced in the flow process is another noteworthy part of this research. The complex system of interrelated non-linear partial differential equations is converted into a set of ordinary differential equations using suitable transformations. Later, solved via a semi-analytical technique, HAM (homotopy analysis method). According to the outcomes of the comparison, the hybrid nanofluid (blood/SWCNT-MWCNT) outperforms the nanofluid (blood/SWCNT) in terms of thermal performance. The rates of thermal energy transmission are very sensitive to the Eckert number and somewhat least affected by thermal radiation. Nanofluids and hybrid nanofluids have their heat transmission rates improved by including nanoparticles, heightened radiation, and magnetic effects. The system produces more entropy when the magnetic parameter and Eckert number are higher; however, it can be minimized by controlling the radiation effect. The results have important consequences for engineering industries, especially in the development and improvement of biomedical equipment and drug delivery systems, where accurate management heat transfer is crucial.

Changes in the magnetic properties of a tropical red soil following the conversion of forest into agricultural land

Land uses have a large impact on the magnetic properties of soil. Understanding the changes in such properties caused by different land uses will help to correctly explain and apply magnetic parameters. In this study, the magnetic susceptibility, magnetic mineral types, and magnetic domain state of iron oxide particles in soil after the transformation of a forest into a tea garden and cornfield in a tropical area were compared. 1)The vertical distribution characteristics of soil magnetism under the three land uses in tropical red soil area were similar. The magnetic properties of soil in the 0–20 cm surface layer was significantly different, but there were no significant differences below 20 cm. The low-frequency mass magnetic susceptibility and anhysteretic susceptibility of topsoil were largest in the cornfield, followed by the forest and tea garden, and the magnetic susceptibility of the topsoil in the cornfield was significantly higher than in the tea garden and forest. 2)The magnetic minerals in tropical red soil area were mainly ferrimagnetic minerals (maghemite and magnetite). The content of ferrimagnetic minerals decreased with depth, while the content of antiferromagnetic minerals (hematite) increased. 3)The magnetic particles were mainly composed of superparamagnetic (SP), single domain (SD), and pseudo single domain (PSD) particles. The magnetic differences in the topsoil were mainly caused by changes in the ferrimagnetic mineral concentration of SD particles. Tea garden and cornfield are the two main agricultural land in the study area. Through the correct application of magnetic parameters, it is helpful to monitor the influence of land use change on soil properties, so as to provide the necessary reference for the rational use of soil.

Thermally radiative flow of MHD Powell-Eyring nanofluid over an exponential stretching sheet with swimming microorganisms and viscous dissipation: A numerical computation

This work deals with the study of mass and heat transmission in nanofluid flow in the Powell-Eyring model over a sheet that is exponentially stretched with motile microorganisms. Additionally, viscous dissipation and radiation sources are considered. The governing flow expressions are remodeled into nonlinear ordinary differential equations by implementing the appropriate transformations. The remodeled equations are numerically computed by using the bvp4c technique via MATLAB. The various flow parameters are used to investigate and explain in depth the nanofluid velocity, thermal, nanoparticle volume fraction, and motile microbe density profiles. It is noted that the nanofluid velocity decreases with enlarging the values of the magnetic field parameter. The fluid thermal profile develops for greater quantities of radiation thermophoresis and Brownian motion parameters. The nanoparticle concentration decays when the Prandtl number and Lewis number are increased. The motile microbe density profiles suppress when heightening the values of the Peclet number, bioconvection Lewis number, and bioconvection parameter. The magnetic field parameter leads to a decrease in local skin friction, heat, and mass transfer rates.

Linear stability analysis of micropolar nanofluid flow across the accelerated surface with inclined magnetic field

PurposeThe purpose of this paper is to study the two-dimensional micropolar fluid flow with conjugate heat transfer and mass transpiration. The considered nanofluid has graphene nanoparticles.Design/methodology/approachGoverning nonlinear partial differential equations are converted to nonlinear ordinary differential equations by similarity transformation. Then, to analyze the flow, the authors derive the dual solutions to the flow problem. Biot number and radiation effect are included in the energy equation. The momentum equation was solved by using boundary conditions, and the temperature equation solved by using hypergeometric series solutions. Nusselt numbers and skin friction coefficients are calculated as functions of the Reynolds number. Further, the problem is governed by other parameters, namely, the magnetic parameter, radiation parameter, Prandtl number and mass transpiration. Graphene nanofluids have shown promising thermal conductivity enhancements due to the high thermal conductivity of graphene and have a wide range of applications affecting the thermal boundary layer and serve as coolants and thermal management systems in electronics or as heat transfer fluids in various industrial processes.FindingsResults show that increasing the magnetic field decreases the momentum and increases thermal radiation. The heat source/sink parameter increases the thermal boundary layer. Increasing the volume fraction decreases the velocity profile and increases the temperature. Increasing the Eringen parameter increases the momentum of the fluid flow. Applications are found in the extrusion of polymer sheets, films and sheets, the manufacturing of plastic wires, the fabrication of fibers and the growth of crystals, among others. Heat sources/sinks are commonly used in electronic devices to transfer the heat generated by high-power semiconductor devices such as power transistors and optoelectronics such as lasers and light-emitting diodes to a fluid medium, thermal radiation on the fluid flow used in spectroscopy to study the properties of materials and also used in thermal imaging to capture and display the infrared radiation emitted by objects.Originality/valueMicropolar fluid flow across stretching/shrinking surfaces is examined. Biot number and radiation effects are included in the energy equation. An increase in the volume fraction decreases the momentum boundary layer thickness. Nusselt numbers and skin friction coefficients are presented versus Reynolds numbers. A dual solution is obtained for a shrinking surface.

Microwave-absorbing behavior of rare-earth-ion-doped copper manganese nanoferrites in X-band frequency

In this study, the technology important Cu0.5Mn0.5Fe2O4 and Cu0.5Mn0.5Fe1.80RE0.2O4 (RE = La, Gd, Nd, and Dy) nanoferrites were synthesized via sonochemical method and characterized to overcome the electromagnetic pollution problems. Crystalline, morphological, electrical, magnetic, and microwave-absorbing parameter were identified by doping of RE (La, Gd, Nd, and Dy) in Cu0.5Mn0.5Fe2O4 nanoferrites. The XRD analysis revealed a cubic spinel structure with a single-phase composition for Cu0.5Mn0.5Fe2O4 nanoferrites whereas Cu0.5Mn0.5Fe1.80RE0.2O4 (RE = La, Gd, Nd, and Dy) nanoferrites had a cubic structure with the presence of a secondary phase. SEM images confirmed the spherical shape of the particle and the grain size within the range of 19.25–28.19 nm, with elemental stoichiometry confirmed by EDS spectra. The dielectric constant and conductivity of Cu0.5Mn0.5Fe1.80RE0.2O4 nanoferrites were low at higher frequencies, which lead good candidates for microwave-absorbing technologies. The substitution of RE decreases saturation magnetization (43.38–23.96 emu/g) and squareness ratio values of prepared nanoferrites were less than 0.5. The SET values of the prepared nanoferrites were in the range of 32.31–41.81 dB. The minimal reflection loss (RL) values of Cu0.5Mn0.5Fe2O4 and Cu0.5Mn0.5Fe1.80RE0.2O4 nanoferrites were less than 10 dB and which indicated that the prepared nanoferrites possessed great potential for applications as microwave-absorbing materials.

The Culprit of Bias for Paleointensity Estimation in the Shaw‐Type Protocol and an Innovative Calculation Method

AbstractPaleointensity records are vital for understanding the Earth's evolution, but obtaining accurate paleointensity is a challenging task. The Shaw‐type method, a widely‐used paleointensity protocol, produces biased results occasionally despite strict selection criteria. By examining the relationships between paleointensities and rock magnetic parameters from a pseudo‐Tsunakawa‐Shaw experiment, we ascertain that changes in the ratio of thermal to anhysteretic remanent magnetization (R) are proportional to bias in paleointensity, especially prominent in samples with hundred‐nanometer‐scale magnetic grains, and thus proved to be the culprit for the bias. Furthermore, we develop a method exploiting the Linear regression of R with Diverse cut‐off coercivity intervals for estimating Shaw‐type paleointensities (LoRD‐Shaw). Combined with a curve fit technique for samples with “folding" phenomenon, the LoRD‐Shaw method yields high‐accuracy results in all tested samples, demonstrating its efficiency in mitigating paleointensity bias from thermal alteration. The new method will enhance acquisition of high‐precision paleointensities for constraining the geodynamo evolution.

Numerical investigation of unsteady MHD immiscible Casson micropolar and Jeffery fluid in a horizontal channel with heat transfer using MCB-DQM approach

The dynamics of immiscible Casson micropolar and Jeffery fluid flow offer new possibilities for enhancing momentum and heat transfer efficiencies. Motivated by numerous applications of immiscible fluid flows in natural and industrial systems, the current work presents a numerical investigation of unsteady, incompressible, magnetohydrodynamic (MHD) flow involving two immiscible fluids, namely, Casson micropolar and Jeffery fluid, in a horizontal channel. The flow, driven by a uniform pressure gradient, assumes no-slip conditions at the channel walls and a continuous, nondeformable interface between the immiscible fluids. The well-established rapid converging modified cubic B-spline differential quadrature method (MCB-DQM) is applied to solve the partial differential equations governing the flow. The impact of crucial fluid parameters comprising the Casson micropolar fluid parameter, Jeffery fluid parameter, thermal, magnetic, and various other fluid parameters on temperature, microrotation, and velocity profile is illustrated graphically. Notably, the parameters of each fluid influence the profiles in both fluid zones. The flow dynamics are significantly affected by viscous dissipation, Lorentz force, fluid–wall interactions, and interfacial conditions. Key parameters such as time, Jeffery fluid, Casson micropolar, ion slip and Hall parameters, Reynolds number, Eckert number, the ratio of viscosities, the ratio of densities, and pressure gradient show significant impacts on the velocity, microrotation, and temperature profiles. However, reverse or mixed behavior is observed for other parameters. The novelty of current work lies in modeling the unsteady, immiscible, MHD flow of Casson micropolar and Jeffery fluid and proposing a numerical solution by deploying the MCB-DQM method. The findings have potential applications in various industrial and engineering processes, such as the design of oil extraction, optimizing processes in the food processing and cosmetics industry, and developing effective strategies for environment conservation.

Magnetic field, radiation, and Joule heating effects on natural convection Williamson fluid flow through a vertical channel using Levenberg–Marquardt algorithm

The study examined the natural convection flow of Williamson fluid through a vertical channel under the influence of the magnetic field, radiation, and joule heating effects. The governing partial differential equations are turned into ordinary differential equations using suitable transformations and solved by using the spectral quasi-linearization method (SQLM). The study explained a neural network algorithm called feed-forward back-propagation using the Levenberg–Marquardt technique (BPFF-LMT). Furthermore, a reference dataset is created for several parameters, including the magnetic parameter, Hall parameter, radiation parameter, Weissenberg number, Biot number, and Joule heating parameter. This dataset encompasses velocity and temperature profiles for different scenarios, employing the SQLM. The BPFF-LMT method’s accuracy was evaluated through a comprehensive analysis involving training, validation, and testing phases, along with mean squared error, error histograms, and performance and regression graphs. The artificial neural network’s result shows good accuracy when compared to the SQLM solution numerically. The results are presented visually through graphical representation and further analyzed quantitatively concerning the active parameters featured in the mathematical formulations. The result indicates that increasing values of the magnetic parameter result in decreased velocity and temperature profiles. Additionally, the heat transfer rate increases in the left channel. Both the radiation parameter and Weissenberg number contribute to higher velocity and temperature profiles, leading to increased skin friction in the left channel. The accuracy of the BPFF-LMT method is illustrated through graphs displaying the absolute error falling within the range of [Formula: see text] to [Formula: see text].

Analysis of Darcy–Forchheimer flow of magnetized hybrid nanofluid (MoS 2+ZnO/E) with non-linear heat source and quartic autocatalytic chemical reaction

In this article, an effort is made to analyze the 3 − D flow of hybrid nanofluid over a rotating stretching sheet. The hybrid nanofluid contains engine oil as a base fluid amalgamated with nano-particles Mo S 2 and ZnO . The flow is assumed to pass through a Darcy–Forchheimer medium subjected to the influence of an inclined magnetic field. In addition, heat radiation, Joule heating, viscous dissipation, nonlinear heat source, and quartic autocatalytic chemical reaction are applied to discourse heat and mass transfer features. The PDEs representing the physical problem are converted to ODEs with the introduction of similarity transformations. The solution of the problem is determined numerically by using MATLAB built-in bvp4c method. The proposed mathematical model’s validation is ascertained by comparing it with an earlier study in limiting case. In this regard, an excellent consensus is accomplished. The current investigation reveals that the flow along axial direction gets retarded by enhancing the values of rotational parameter, inertial parameter, and magnetic parameter, whereas the flow along radial direction gets accelerated. The increasing value of angle of inclination admirably resists the motion of nanofluid and hybrid nanofluid. The concentration profile gets decreased under the increasing influence of inclination angle and Schmidt number while it enhances for homogeneous reaction parameter. The enhancing values of rotational parameter, solid volume fraction and temperature, and exponential dependent heat generation parameters enhance the value of Nusselt number.

Insight into the thermal transport by considering the modified Buongiorno model during the silicon oil-based hybrid nanofluid flow: probed by artificial intelligence

This work aims to analyze the impacts of the magnetic field, activation of energy, thermal radiation, thermophoresis, and Brownian effects on the hybrid nanofluid (HNF) (Ag++silicon oil) flow past a porous spinning disk. The pressure loss due to porosity is constituted by the Darcy–Forchheimer relation. The modified Buongiorno model is considered for simulating the flow field into a mathematical form. The modeled problem is further simplified with the new group of dimensionless variables and further transformed into a first-order system of equations. The reduced system is further analyzed with the Levenberg–Marquardt algorithm using a trained artificial neural network (ANN) with a tolerance, step size of 0.001, and 1,000 epochs. The state variables under the impacts of the pertinent parameters are assessed with graphs and tables. It has been observed that when the magnetic parameter increases, the velocity gradient of mono and hybrid nanofluids (NFs) decreases. As the input of the Darcy–Forchheimer parameter increases, the velocity profiles decrease. The result shows that as the thermophoresis parameter increases, temperature and concentration increase as well. When the activation energy parameter increases, the concentration profile becomes higher. For a deep insight into the analysis of the problem, a statistical approach for data fitting in the form of regression lines and error histograms for NF and HNF is presented. The regression lines show that 100% of the data is used in curve fitting, while the error histograms depict the minimal zero error −7.1e6 for the increasing values of Nt. Furthermore, the mean square error and performance validation for each varying parameter are presented. For validation, the present results are compared with the available literature in the form of a table, where the current results show great agreement with the existing one.

Examining Hybrid Nanofluid Flow Dynamics in the Conical Gap between a Rotating Disk and Cone Surface: An Artificial Neural Network Approach

To comprehend the thermal regulation within the conical gap between a disk and a cone (TRHNF-DC) for hybrid nanofluid flow, this research introduces a novel application of computationally intelligent heuristics utilizing backpropagated Levenberg–Marquardt neural networks (LM-NNs). A unique hybrid nanoliquid comprising aluminum oxide, Al2O3, nanoparticles and copper, Cu, nanoparticles is specifically addressed. Through the application of similarity transformations, the mathematical model formulated in terms of partial differential equations (PDEs) is converted into ordinary differential equations (ODEs). The BVP4C method is employed to generate a dataset encompassing various TRHNF-DC scenarios by varying magnetic parameters and nanoparticles. Subsequently, the intelligent LM-NN solver is trained, tested, and validated to ascertain the TRHNF-DC solution under diverse conditions. The accuracy of the LM-NN approach in solving the TRHNF-DC model is verified through different analyses, demonstrating a high level of accuracy, with discrepancies ranging from 10−10 to 10−8 when compared with standard solutions. The efficacy of the framework is further underscored by the close agreement of recommended outcomes with reference solutions, thereby validating its integrity.

Heat and Mass Transfer Effects on MHD Mixed Convective Flow of a Vertical Porous Surface in the Presence of Ohmic Heating and Viscous Dissipation

The present paper addresses the combined effects of thermal radiation and chemical reaction on steady MHD mixed convective flow of heat and mass transfer past a vertical surface under the influence of Joule and viscous dissipation. The governing system of the partial differential equations is transformed into the dimensionless equations using dimensionless variables. The dimensionless equations are solved numerically using two term perturbation technique and numerical solution as in graphically. The effects of the various parameters entering the problem on the dimensionless velocity, temperature and concentration fields within the boundary layer are discussed qualitatively. The velocity increases with an increase in Grashof number Gr, permeability parameter and solutal Grashof number Gm but decreases in magnetic parameter.

Effects of Activation Energy and Diffusion Thermo an Unsteady MHD Maxwell Fluid Flow over a Porous Vertical Stretched Sheet in the Presence of Thermophoresis and Brownian Motion

This article discusses the effects of Activation energy and Diffusion thermo on an unsteady MHD flow of an electrically conducting Maxwell Nanofluid over a stretching sheet in a porous medium in the presence of thermophoresis and Brownian motion. Using the similarity transformations, the partial differential equations corresponding to the momentum, energy, and concentration equations are transformed into a system of nonlinear ordinary differential equations, which are solved numerically using a RungeKutta fourth-order method along with the shooting technique, and the results obtained for different governing flow parameters are drawn graphically, and their effects on velocity, temperature, and concentration profiles are discussed. The values of the skin friction coefficient, Nusselt number coefficient, and Sherwood number coefficient are presented in the table. A comparison with previously reported data is made, and an excellent agreement is noted. The objective of the present study is to use the Activation energy and Diffusion thermo parameters to increase the concentration of chemical species on the boundary layer and temperature, respectively. The temperature of the fluid increases as the radiation parameter, Brownian motion, thermophoresis, and magnetic parameters increase.

A numerical analysis on magnetized dissipative non-Darcian Maxwell fluid with heat radiation through stretching horizontal surface

This work examines the numerical representation of boundary layer flow across a horizontal plate using the non-Darcian Maxwell model. The inspiration of mass transfer, heat generation, the Soret effect, the non-Darcy effect, Arrhenius activation energy and thermal radiation are all covered in this study. The relevant similarity transformations are applied in primary equations and a built-in bvp4c program is employed for solutions. The effectiveness of the numerical approach is demonstrated by a thorough agreement with results that have been published in the past. The results are shown in tables and graphical representations that highlight multiple parameters including the non-Darcy parameter, Deborah number, magnetic parameter, Soret parameter, chemical reactions, activation energy, etc. Figures show that fluid velocity is enhanced by Deborah number whereas it slips due to non-Darcy parameter and magnetic parameter. Eckert number, Radiation enhances the temperature profile and slips due to the Prandtl number. Activation energy enhances the Concentration field but it declines due to chemical reaction.