Magnetic Field Parameters Research Articles

Designing machine learning based intelligent network for assessment of heat transfer performance of ternary hybrid nanofluid flow between a cone and a disk: Case of MLP feed forward neural network

In the current study, authors have studied the heat transfer through ternary hybrid nanofluid (THNF) between the gap of a disk and cone, where both are co-rotating with regard to the other. The authors have developed a mathematical model of THNF flow inside a gap between a cone and a disk with the effects of magnetic field, Hall effects, and radiation parameters. The unique aspect of this study is the implementation of a powerful artificial neural network (ANN) that exhibits improved robustness and accurate predictive performance for the Nusselt number at the surface of both the cone and disk. Through the use of proper similarity transformations, the model equations are transformed into a collection of nonlinear ODEs. Using MATLAB and an inbuilt bvp4c function, these equations are numerically solved. The main objective of this research is to examine the impacts of cone and disk rotation within the co-rotation system. The heat transfer rate is seen to be higher at the surface of the disk. It is followed from the analysis of the ANN model that the regression value for each case varies between 0.99574 and 1, and in many cases, it is exactly equal to 1. In addition, the mean square error (MSE) for every dataset is notably very close to zero. The effect of the angle of the conical gap is also one of the noteworthy subjects due to the significance of its effects in several engineering sector applications.

Exploiting and Enhancing the Heat Transport Rate of MoS2-Ag/EO Hybrid Nanofluid Flow via a Stretching Cylinder using Extended Yamada-Ota and Xue Models.

The current model offers valuable insights for materials science, heat exchangers, renewable energy production, nanotechnology, manufacturing, medicinal treatments, and environmental engineering. The findings of this study have the potential to improve material design, increase heat transfer efficiency across various systems, enhance energy conversion processes, and drive advancements in nanotechnology, medicinal treatments, and engineering design. The goal of the current research is to analyze the effects of thermal radiation and the volume fraction of nanoparticles in MoS2-Ag/engine oil-based hybrid nanofluid flow passing through a cylinder. After performing a substantial similarity transformation, the nonlinear dimensionless framework is recast as ODEs. The Yamada-Ota and Xue models are then applied to the dimensionless equation setup, which is numerically solved using the BVP4C approach. The resulting velocity and temperature fields, corresponding to various parameters, are examined and compared across both models. This investigation demonstrates a significant variation in heat transfer rates between the Yamada-Ota and Xue models, with the former having a larger impact. The velocity and temperature fields decrease as the magnetic field parameter increases in both nanofluids. However, as the magnetic field parameter values grow, the velocity fields in the two nanofluids behave differently. The Yamada-Ota and Xue models are used to determine the behavior of the hybrid nanofluid flow over a nonlinear extended cylinder. In all situations, the velocity and temperature fields exhibit superior decay characteristics.

Analysis of MHD third-grade hybrid nanofluid model in Darcy-Forchheimer porous medium: Evaluation of the thermal performance of [formula omitted]-[formula omitted] cylindrical nanoparticles dispersed in ethylene glycol fluid

Researchers and scientists became interested in the newly developed idea of hybrid nanofluids because of their exceptional thermal conductivities, which resulted in enhanced thermal performance. These fluids have a wide range of uses in the industrial and technical fields. This novel class of fluids is playing a vital role in solar energy, automotive industry, cooling of the machine and manufacturing, heating and ventilation systems, electronic cooling, nuclear systems cooling, biomedical fields, space, ships, and defense systems. In light of the physical significance of the above-mentioned class of fluids, the current investigations are carried to examine the thermal performance of the mixture of cylindrical shaped aluminum oxide Al2O3 and copper Cu nanoparticles suspended in ethylene glycol using third-grade non-Newtonian fluid flow model. The fluid flow is induced by the stretching of the permeable sheet in exponential manner that is embedded in a Dacry-Forchheimer porous medium. The effects of Lorentz force applied normal to the flow and suction impacts have been incorporated in the current proposed model. The solutions of the flow model transformed to ordinary differential equations are computed using MATLAB built-in solver bvp4c. The solutions are presented in graphical representations. Graphical solutions reflect that fluid velocity slows down by growing the volume fractions of the nanoparticles. Increasing values of viscoelastic parameters reflect that there is a reduction in velocity and intensification in profiles of temperature and concentration have been noted. Rising values of cross-diffusion parameter is leading to the reduction in magnitude of velocity, and augmenting behavior of temperature and concentration has been seen. Observations indicate rising third-grade fluid parameter and porosity parameter lead to reduction in velocity. Increasing Schmidt number gives reduced Sherwood number, and magnetic field parameter improves the rate of hear transfer (Nusselt number) and skin friction coefficient for both Al2O3/ethylene glycol nanofluid and Al3O3-Cu/ethylene glycol-based hybrid nanofluid. The suggested model's validity is confirmed through comparison with previously released findings. Additionally, a grid independence test (sensitivity analysis) has been performed to verify the accuracy and verification of the numerical model.

Thermal Transportation in Heat Generating and Chemically Reacting MHD Maxwell Hybrid Nanofluid Flow Past Inclined Stretching Porous Sheet in Porous Medium with Solar Radiation Effects

The emerging concept of hybrid nanofluids has grabbed the attention of researchers and scientists due to improved thermal performance because of their remarkable thermal conductivities. These fluids have enormous applications in engineering and industrial sectors. Therefore, the present research study examines thermal and mass transportation in hybrid nanofluid past an inclined linearly stretching sheet using the Maxwell fluid model. In the current problem, the hybrid nanofluid is engineered by suspending a mixture of aluminum oxide Al2O3 and copper Cu nanoparticles in ethylene glycol. The fluid flow is generated due to the linear stretching of the sheet and the sheet is kept inclined at the angle ζ=π/6 embedded in porous medium. The current proposed model also includes the Lorentz force, solar radiation, heat generation, linear chemical reactions, and permeability of the plate effects. Here, in the current simulation, the cylindrical shape of the nanoparticles is considered, as this shape has proven to be excellent for the thermal performance of the nanomaterials. The governing equations transformed into ordinary differential equations are solved using MATLAB bvp4c solver. The velocity field declines with increasing magnetic field parameter, Maxwell fluid parameter, volume fractions of nanoparticles, and porosity parameter but increases with growing suction parameter. The temperature drops with increasing magnetic field force and suction parameter values but increases with increasing radiation parameter and volume fraction values. The concentration profile increases with increasing magnetic field parameters, porosity parameters, and volume fractions but reduces with increasing chemical reaction parameters and suction parameters. It has been noted that the purpose of the inclusion of thermal radiation is to augment the temperature that is serving the purpose in the current work. The addition of Lorentz force slows down the speed of the fluid and raises the boundary layer thickness, which is visible in the current study. It has been concluded that, when heat generation parameters increase, the temperature field increases correspondingly for both nanofluids and hybrid nanofluids. The increase in the volume fraction of the nanoparticles is used to enhance the thermal performance of the hybrid nanofluid, which is evident in the current results. The current results are validated by comparing them with published ones.

Numerical study of Carreau fuzzy nanofluid across a stretching cylinder using a modified version of Buongiorno's nanofluid model

The principal intention of the currently analysis is to investigate the impacts of the naturally convective nanofluid using a model of Carreau fluid with engine oil (CnH2n+2)as the base fluid and Manganese Zinc Ferrite (MnZnFe2O4)as the nanoparticle, the fluid flowing through a stretched cylinder in a fuzzy ambient. It examines the impact of assorted parameters, Weissenberg number(We), Prandtl numeral(Pr), Schmidt numeral (Sc), and curvature (k)with magnetic field(B) and nanoparticle parameter, in order to manipulate an analogous conversion, the regulating equations of velocity, energy, and concentration profiles permute from a set of partial differential equations stand to ordinary differential equations. The present analysis focuses on the no slip assumption, which gives rise to a nonlinear Dirichlet boundary condition in axial velocity. The bvp5c approach was utilized to solve the resulting series of equations by the MATLAB. This is a highly effective approach with minimal computing expenditure. The volume quantity of nanoparticles in MnZnFe2O4 is considered an uncertain parameter respect to TFNs (triangular fuzzy numbers) ranging [0, 0.5, 0.1]. Triangular membership function (TMF) is used to study the uncertainty variability while α − cut controls the TFNs. Fuzzy linear regression analysis makes use of TFNs to determine the middle (crisp), left, and right values of the fuzzy velocity profile. In comparison to the crisp velocity profile (mid value), the study's result and the fuzzy velocity profile have the maximum rate of flow. Tables and graphs are used to illustrate the outputs.

Do Magnetic murmurs guide birds? A directional statistical investigation for influence of Earth's Magnetic field on bird navigation.

This paper delves into the intricate relationship between changes in Magnetic inclination and declination at specific geographical locations and the navigational decisions of migratory birds. Leveraging a dataset sourced from a prominent bird path tracking web resource, encompassing six distinct bird species' migratory trajectories, latitudes, longitudes, and observation timestamps, we meticulously analyzed the interplay between these avian movements and corresponding alterations in Magnetic inclination and declination. Employing a circular von Mises distribution assumption for the latitude and longitude distributions within each subdivision, we introduced a pioneering circular-circular regression model, accounting for von Mises error, to scrutinize our hypothesis. Our findings, predominantly supported by hypothesis tests conducted through circular-circular regression analysis, underscore the profound influence of Magnetic inclination and declination shifts on the dynamic adjustments observed in bird migration paths. Moreover, our meticulous examination revealed a consistent adherence to von Mises distribution across all bird directions. Notably, we unearthed compelling correlations between specific bird species, such as the Black Crowned Night Heron and Brown Pelican, exhibiting a noteworthy negative correlation with Magnetic inclination and a contrasting positive correlation with Magnetic declination. Similarly, the Pacific loon demonstrated a distinct negative correlation with Magnetic inclination and a positive association with Magnetic declination. Conversely, other avian counterparts showcased positive correlations with both Magnetic declination and inclination, further elucidating the nuanced dynamics between avian navigation and the Earth's magnetic field parameters.

Magneto Axisymmetric Vibration of FG-GPLs Reinforced Annular Sandwich Plates with an FG Porous Core Using DQM and a New Shear Deformation Theory

Based on the differential quadrature procedure (DQP), the vibrational response of functionally graded (FG) sandwich annular plates enhanced with graphene platelets (GPLs) and with an FG porous core is illustrated in this paper. The current annular plate is assumed to deform axisymmetrically and expose to a radial magnetic field. The Lorentz magnetic body force is deduced via Maxwell’s relations. The effective physical properties of the upper and lower layers of the sandwich plate are obtained by employing the Halpin–Tsai model. Our technique depends on a new four-unknown shear deformation theory to depict the displacements. In addition, the motion equations are established via Hamilton’s principle. The motion equations are solved by employing the DQP. In order to study the convergence of the DQ method, the minimum number of grid points needed for a converged solution is ascertained. In addition, the current theory’s outcomes are compared with those of previous higher-order theories. The effects of the porosity distribution type, porosity factor, GPLs distribution pattern, GPLs weight fraction, inner-to-outer radius ratio, outer radius-to-thickness ratio, magnetic field parameters, core thickness, and elastic substrate parameters on the nondimensional vibration frequencies are discussed.

Honeycomb-configured dissipative nanofluid flow within a squeezed channel with entropy generation: regression and numerical evaluations

PurposeNanosized honeycomb-configured materials are used in modern technology, thermal science and chemical engineering due to their high ultra thermic relevance. This study aims to scrutinize the heat transmission features of magnetohydrodynamic (MHD) honeycomb-structured graphene nanofluid flow within two squeezed parallel plates under Joule dissipation and solar thermal radiation impacts.Design/methodology/approachMass, energy and momentum preservation laws are assumed to find the mathematical model. A set of unified ordinary differential equations with nonlinear behavior is used to express the correlated partial differential equations of the established models, adopting a reasonable similarity adjustment. An approximate convergent numerical solution to these equations is evaluated by the shooting scheme with the Runge–Kutta–Fehlberg (RKF45) technique.FindingsThe impression of pertinent evolving parameters on the temperature, fluid velocity, entropy generation, skin friction coefficients and the heat transference rate is explored. Further, the significance of the irreversibility nature of heat transfer due to evolving flow parameters are evaluated. It is noted that the heat transference rate performance is improved due to the imposition of the allied magnetic field, Joule dissipation, heat absorption, squeezing and thermal buoyancy parameters. The entropy generation upsurges due to rising magnetic field strength while its intensification is declined by enhancing the porosity parameter.Originality/valueThe uniqueness of this research work is the numerical evaluation of MHD honeycomb-structured graphene nanofluid flow within two squeezed parallel plates under Joule dissipation and solar thermal radiation impacts. Furthermore, regression models are devised to forecast the correlation between the rate of thermal heat transmission and persistent flow parameters.

Effect of bias magnetic field on transducer efficiency in electromagnetic ultrasonic non-destructive testing of Rock bolt

Non-destructive testing (NDT) of rock bolt anchoring quality is an important part of engineering quality and safety control, electromagnetic ultrasonic NDT is one of the promising detection methods, and improving the efficiency of ultrasonic transducer by optimizing the bias magnetic field is an important factor to obtain effective information. In this paper, several factors affecting the bias magnetic field are studied, and the work is divided into simulation and demonstration: COMSOL was used to simulate the electromagnetic ultrasonic transducer(EMAT) in order to analyze the influence of the number of magnetic circuit, the thickness of magnet and the thickness of yoke iron on the bias magnetic field. Then, an experimental platform was built, the magnetic circuit structure of the transducer was set with reference to the simulation results, and several important parameters of the bias magnetic field were determined by analyzing the collected signals. The results show that with the increase of the bias magnetic field magnetic circuit structure from independent to ring form, the magnetic field strength of the rock bolt increases, the magnetic field uniformity becomes better, and the efficiency of the transducer is also improved accordingly. In addition, under the same magnetic circuit condition, increasing the thickness of permanent magnet and yoke iron does not increase the magnetic flux density of the rock bolt axis proportionally, and has a limited effect on the efficiency of the transducer. In practical application, the corresponding structure is selected according to the needs, and the better bias magnetic field structure is selected while meeting the efficiency of the transducer.

Sensitivity Analysis of MHD Hybrid Nanofluid Flow over a Radially Shrinking Disk with Heat Generation

This work features the numerical computation and statistical analysis (response surface and sensitivity) for the flow and thermal progress of an axisymmetric copper-alumina/water hybrid nanofluid subjected to a permeable shrinking disk. The simultaneous factors of magnetic field (MHD), heat generation and suction parameter in the heat transfer development and flow characteristic are observed. The flow and energy equations are mathematically developed based on the boundary layer assumptions. These equations are then simplified with the aids of the similarity variables. The numerical results are then generated by the bvp4c solver in the Matlab software. The dual solutions are possible and exist up to a separation value upon the inclusion of suction effect. The increment of heat generation parameter from 0% to 1% reduces the heat transfer rate for all values of the stretching/shrinking parameter. For the response surface analysis, the responses (skin friction coefficient and heat transfer rate) are analyzed for three factors (magnetic, suction, heat generation) and three magnitudes (low, medium, high). Based on this analysis, the magnetic and suction parameters provide a significant effect on the skin friction with p-values < 0.05. Meanwhile, for the heat transfer coefficient, all factors give significant impact with zero p-values. Meanwhile, the sensitivity analysis reveals that the suction parameter has higher sensitivity to the heat transfer as compared to the magnetic and heat generation parameter. Even though these parameters being less sensitive, their influence on heat transfer remains statistically significant.

Spectropolarimetric Radio Imaging of Faint Gyrosynchrotron Emission from a CME: A Possible Indication of the Insufficiency of Homogeneous Models

The geo-effectiveness of coronal mass ejections (CMEs) is determined primarily by their magnetic fields. Modeling of gyrosynchrotron (GS) emission is a promising remote sensing technique to measure the CME magnetic field at coronal heights. However, faint GS emission from CME flux ropes is hard to detect in the presence of bright solar emission from the solar corona. With high dynamic-range spectropolarimetric meter wavelength solar images provided by the Murchison Widefield Array, we have detected faint GS emission from a CME out to ∼8.3 R ⊙, the largest heliocentric distance reported to date. High-fidelity polarimetric calibration also allowed us to robustly detect circularly polarized emission from GS emission. For the first time in the literature, Stokes V detection has jointly been used with Stokes I spectra to constrain GS models. One expects that the inclusion of polarimetric measurement will provide tighter constraints on the GS model parameters. Instead, we found that homogeneous GS models, which have been used in all prior works, are unable to model both the total intensity and circular polarized emission simultaneously. This strongly suggests the need for using inhomogeneous GS models to robustly estimate the CME magnetic field and plasma parameters.

Dual-phase superconductivity in high-pressure high-temperature synthesized TaNbZrHfTi

We report on a novel TaNbZrHfTi-based high entropy alloy (HEA) which demonstrates distinctive dual-phase superconductivity. The HEA was synthesized under high pressures and high temperatures starting from a ball milled mixture of elemental metals in a large-volume Paris–Edinburgh cell with P ≈ 6 GPa and T = 2300 K. The synthesized HEA is a phase mixture of BCC (NbTa)0.45(ZrHfTi)0.55 with Tc1 = 6 K and FCC (NbTa)0.04(ZrHfTi)0.96 with Tc2 = 3.75 K. The measured magnetic field parameters for the HEA are lower critical field, Hc1(0) = 31 mT, and a relatively high upper critical field, Hc2(0) = 4.92 T. This dual-phase system is further characterized by the presence of a second magnetization peak, or the fishtail effect, observed in the virgin magnetization curves. This phenomenon, which does not distort the field-dependent magnetization hysteresis loops, suggests intricate pinning mechanisms that could be potentially tuned for optimized performance. The manifestation of these unique features in HEA superconductivity reinforces phase-dependent superconductivity and opens new avenues in the exploration of novel superconducting materials.

The Klein-Gordon equation in the cosmic string and rainbow gravity spacetime under the influence of an external magnetic field and Coulomb potential for PDM particles

Abstract The Klein-Gordon equation in the cosmic string and rainbow gravity spacetime under the influence of an external magnetic field and Coulomb potential for PDM particles is investigated using the NU method. From solution of the Klein-Gordon system with PDM particles, the energy levels are obtained. The energy levels are numerically calculated as a function of rainbow gravity parameters, as a function of magnetic field parameters, as a function of position-dependent mass parameters. We apply some rainbow functions and the results show that the negative and positive energy levels for rainbow function 1 are symmetrical compared to rainbow function 2.

Artificial Neural Network and Numerical Simulation for Magneto Hydrodynamics Hybrid Nanofluid Flow Towards a Stretching Cylinder

The present study focuses on influence of boundary layer flow of heat transfer analysis on hybrid nanofluid through a stretching cylinder. Moreover, the impressions of porous medium, heat generation/absorption are discussed. Further, the stimulus of non-linear thermal radiation and MHD are part of this investigation. For motivation, the Artificial Neural Networks also deliberated. Arrogate similarity variables are employed to transform the governing modelled PDEs into a couple of highly nonlinear ODEs. A numerical approach based on the shooting approach with MATLAB bvp5c built in function is employed for solution of the set of resulting ODEs and acquired outcomes are compared with existing literature, obtained results an exceptional agreement. Artificial nerve cells or node locations form a network of nerves, a contemporary name for a chain composed of human brain cells. The impact of physical parameters like Magnetic Field, Eckert number, Porosity, Prandtl number, Heat generation, thermal radiation, parameters on dimensionless velocity and energy fields are discussed through graphs and tables. The velocity profile decreased by about 42% when the magnetic field parameter values increases from 0.5 to 1.5. On the other hand increased by 78% on energy profile. The energy profile improved by about 97% when the Eckert number values increases from 1.0 < Ec < 3.0. The current model may be applicable in real life practical implications of employing Water–Cu/Ag/Al2O3 nanofluids on cylinders encompass enhanced heat transfer efficiency, and extended component lifespan, energy savings, and environmental benefits. This kind of theoretical analysis may be used in daily life applications, such as industrial and biomedical industries.

Utilization of OHAM on mixed convective flow of Williamson fluid model with viscous dissipation over a stretched cylinder

This research focuses on the fluid dynamics and heat transfer characteristics of the Williamson fluid over a permeable stretched cylinder, accounting for heat generation effects. Incorporating elements such as viscous dissipation, mixed convection, Joule heating, entropy generation, and magnetic field presence, the investigation utilizes the Optimal Homotopy Analysis Method for solution development. Through the process of similarity transformations, the partial differential equations undergo a conversion that results in dimensionless ordinary differential equations. Numerical results from this study align well with existing literature, emphasizing the examination of key dimensionless parameters like Reynolds number, suction parameter, magnetic field parameter, mixed convection parameter, heat source parameter and Williamson fluid parameter. The analysis extends to local Nusselt number and skin friction coefficient computations, offering insights into heat transfer and shear stress rates, correspondingly. Additionally, the research delves into the effects of several physical parameters on temperature and velocity profiles, presenting a comprehensive overview in academic discourse. The study's methodology and findings contribute to the understanding of phenomenon related to heat transfer and fluid flow, making it a valuable addition to the scholarly domain.

Evolution of heat transfer in MHD nanofluid flow over a porous plate: Insights into the influences of slip and variable viscosity

Temperature-dependent viscosity finds application in various industries such as oil and gas, polymer processing, and food manufacturing. Understanding how viscosity changes with temperature is critical for optimizing processes like drilling operations, polymer molding, and food product consistency. Additionally, it plays a vital role in controlling flow behavior, ensuring efficient heat transfer, and maintaining product quality across different temperature conditions. The exploration of temperature-dependent viscosity in Powell-Eyring nanofluid models represents a novel and unexplored avenue in the field. The study’s novelty is underscored by its comprehensive investigation into a range of factors, such as surface suction, thermal radiation, slip velocity effects, and nanoparticle concentration slip, all integrated within the Powell-Eyring nanofluid model. Moreover, the adoption of bvp4c as a numerical tool further emphasizes the research’s unique contributions. The curves of temperature, concentration, and velocity as a consequence of changes in physical parameters are discussed. Increasing the value of the suction parameter promotes heat transfer but slows the velocity of the nanofluid. The injection of a magnetic field is responsible for compensating for the suction rate. An improvement in the concentration of nanoparticles and temperature is observed as a result of an increase in the slip rate. It is evident that both nanoparticle concentration and temperature rise significantly when Bi, the Biot number, is increased. In the boundary layer, a decrease in velocity is observed as a consequence of an increase in velocity slip, porosity, and magnetic field parameters.

Employing the Akbari Ganji Method (AGM) to conduct a semi-analytical analysis of transient Eyring-Powell compressible flow in a tensile Surface under the influence of a magnetic field

This study explores the transfer of mass and heat within unstable two-dimensional flows of non-Newtonian material under conditions involving radiation generation, absorption, and thermal radiation. Additionally, it investigates the impact of magnetic hydromagnetic joule (MHD) heating on these processes. The researchers converted the partial differential equations into ordinary ones through appropriate transformations. Subsequently, a new idea was considered, involving coupling fractional differential equations using the AGM method, with an order of 0.5 < a <0.8 and the initial condition x (0) = x0. A new technique is introduced to find the exact solution of fractional differential equations by solving the correct order differential equations. The primary aim of this paper is to explore the impact of parameter variations on velocity, temperature, local skin friction coefficient, and local Nusselt and Sherwood numbers. This article investigates the effect of multi-parameter changes on local skin friction coefficient and Schmidt number. In most fluid heat transfer problems, especially in non-Newtonian fluids, fractional differential equations are widely used in liquids. The obtained results indicate that the Lorentz force, influenced by the magnetic field parameter (Ha), diminishes the velocity distribution. Additionally, it is observed that the temperature profile decreases as the radiation parameter (R) increases.

Classification of Major Solar Flares from Extremely Imbalanced Multivariate Time Series Data Using Minimally Random Convolutional Kernel Transform

Solar flares are characterized by sudden bursts of electromagnetic radiation from the Sun’s surface, and are caused by the changes in magnetic field states in active solar regions. Earth and its surrounding space environment can suffer from various negative impacts caused by solar flares, ranging from electronic communication disruption to radiation exposure-based health risks to astronauts. In this paper, we address the solar flare prediction problem from magnetic field parameter-based multivariate time series (MVTS) data using multiple state-of-the-art machine learning classifiers that include MINImally RandOm Convolutional KErnel Transform (MiniRocket), Support Vector Machine (SVM), Canonical Interval Forest (CIF), Multiple Representations Sequence Learner (Mr-SEQL), and a Long Short-Term Memory (LSTM)-based deep learning model. Our experiment is conducted on the Space Weather Analytics for Solar Flares (SWAN-SF) benchmark data set, which is a partitioned collection of MVTS data of active region magnetic field parameters spanning over nine years of operation of the Solar Dynamics Observatory (SDO). The MVTS instances of the SWAN-SF dataset are labeled by GOES X-ray flux-based flare class labels, and attributed to extreme class imbalance because of the rarity of the major flaring events (e.g., X and M). As a performance validation metric in this class-imbalanced dataset, we used the True Skill Statistic (TSS) score. Finally, we demonstrate the advantages of the MVTS learning algorithm MiniRocket, which outperformed the aforementioned classifiers without the need for essential data preprocessing steps such as normalization, statistical summarization, and class imbalance handling heuristics.

Magnetohydrodynamic Marangoni fluid flow, heat, and mass transfer over a radially stretching disk in the presence of heat generation and chemical reaction

The analysis of magnetohydrodynamic (MHD) Marangoni fluid flow, heat, and mass transport over a disk is considered in this article. The fluid is assumed to pass radially over a stretching disk. Suction/blowing at the boundary, internal heat generation/absorption, and a first-order chemical reaction are also considered. By using appropriate similarity transformations, the governing nonlinear partial differential equations (PDEs) are transformed into ordinary differential equations (ODEs). These ODEs along with the appropriate boundary conditions for the model are solved numerically by a shooting technique using MATHEMATICA software. The obtained results are compared with the available results in the literature for some special cases. The effects of the magnetic parameter, the Marangoni number, Marangoni ratio parameter along with the other pertinent parameters on fluid flow, heat and mass transport are analyzed and discussed in detail. It is noted that higher magnetic field depresses the fluid velocity whereas the fluid temperature and fluid concentration are uplifted with an increase in the magnetic field parameter. A quite opposite behavior is observed for Marangoni number. Marangoni ratio parameter boosted the fluid velocity as well as the fluid concentration and the temperature. Also externally applied suction significantly affects the fluid behavior. Increasing chemical reaction parameter reduces the fluid concentration. It is observed that a maximum increase in the Nusselt number occurs for Marangoni parameter Ma, which is 34.75595% when the suction/injection parameter s = 0.5. Also, for Marangoni ratio parameter Ra, a maximum increase in Nusselt number occurs, which is 6.7884% when suction/injection parameter s = 0.5.

Mass-Based Hybrid Nanofluid Model for Thermal Radiation Analysis of MHD Flow over a Wedge Embedded in Porous Medium

This study addresses the intricate interplay of magnetohydrodynamics (MHD), thermal radiation, and porous media effects, which are crucial in numerous engineering applications, including aerospace, energy systems, and environmental processes. The development of a mass-based hybrid nanofluid model signifies a novel approach, potentially yielding more accurate predictions and insights into the thermal behavior of fluids in diverse scenarios. Thus, the current research explores the heat transfer characteristics of a unique nanofluid known as TiO2 (titania)-CuO (copper oxide)/H2O (water) hybrid nanofluid. This nanofluid flows past a static or moving wedge considering the impact of thermal radiation and magnetic field in the appearance of porous medium. To calculate the effective thermophysical attributions of the hybrid (TiO2-CuO) nanofluid, a mass-based strategy is employed. This approach involves analyzing the masses of both the first and second nanoparticles, along with the mass of the base fluid, as essential input parameters. The proposed mathematical model is modified to a dimensionless form by applying similarity transformations. The numerical solution is obtained by utilizing the bvp4c built-in function within the MATLAB environment. Graphs illustrate the influence of various parameters on temperature and velocity trends, including the magnetic field parameter and heat absorption/generation parameter as well as the thermal radiation parameter. It is noted that along with the enhancement in the values of parameters related to porous medium or magnetic field, the velocity of the hybrid nanofluid improves. This occurs when the moving wedge parameter’s value is below 1. Conversely, when the moving wedge parameter’s value exceeds 1, the velocity of the hybrid nanofluid decreases. The shape factor is more effective in the temperature profile for developed inputs of heat absorption/generation parameter. A juxtaposition of enhancement in heat transfer rate due to nanofluid (TiO2/H2O) and hybrid nanofluid (TiO2-CuO/H2O) is likewise presented. The main outcome indicates that the hybrid nanofluid exhibits superior thermal conductivity relative to the conventional nanofluid.