Magnetized Hybrid Research Articles

Entropy generation minimization and activation energy in magneto-thermo-solutal stratified Ellis hybrid nanofluid flow through a stretching stenotic artery: Insights into cardiovascular disease

This article explores the impact of binary chemical reactions with activation energy on the flow of magnetized mono and hybrid nanofluids within a porous artery under the effects of viscous dissipation, nonlinear thermal radiation, and Joule heating. The main novelty of this study lies in considering a non-Newtonian Ellis fluid model of blood through a stretching stenotic artery consisting of gold (Au) and silver (Ag) nanoparticles. Additionally, velocity slip, convective temperature, and concentration boundary conditions are applied at the arterial surface. The proposed model compares the performance of Ag/Blood nanofluid and Au-Ag/Blood hybrid nanofluid models. The governing equations are solved using the bvp4c built-in solver in MATLAB, which employs advanced numerical techniques and algorithms tailored for BVPs, ensuring quicker convergence with minor errors and accurate solutions. Graphs are plotted for concentration, temperature, velocity, entropy minimization, skin friction coefficient, Nusselt number, and Sherwood number for various physical parameters. The results show that with increased nonlinear thermal radiation (0.1≤Nr≤2.0), thermal Biot number (0.1≤Bi1≤0.3), and Eckert number (0.01≤Ec≤0.2), the thermal distribution profile exhibits a rising trend. In contrast, with increasing fluctuations in the chemical reaction rate parameter (0.1≤Rc≤0.3) and Schmidt number (1.0≤Sc≤3.0), the concentration distribution profile exhibits a decreasing trend. In terms of mass and heat transfer efficiency, the Au-Ag/Blood hybrid nanofluid flow outperforms the Ag/Blood nanofluid model. More entropy is observed for Au-Ag/Blood compared to Ag/Blood in the stenotic artery. Heat energy may be created by targeting the injured area and avoiding harm to nearby tissues. Localized heating can widen arteries and increase blood flow to the affected locations, potentially aiding cardiovascular health management and personalized therapy. This study has various implications for the design of drug delivery systems, biophysical models, innovative materials, and our knowledge of fluid dynamics and heat transfer. However, nanofluid/hybrid nanofluid stability is challenging for current researchers since this modeled flow can be considered over a shrinking artery or in the trihybrid model in future studies.

Formation of a magnetized hybrid star with a purely toroidal field from phase-transition-induced collapse

ABSTRACT Strongly magnetized neutron stars are popular candidates for producing detectable electromagnetic and gravitational-wave signals. Gravitational collapses of neutron stars triggered by a phase transition from hadrons to deconfined quarks in the cores could also release a considerable amount of energy in the form of gravitational waves and neutrinos. Hence, the formation of a magnetized hybrid star from such a phase-transition-induced collapse is an interesting scenario for detecting all these signals. These detections may provide essential probes for the magnetic field and composition of such stars. Thus far, a dynamical study of the formation of a magnetized hybrid star from a phase-transition-induced collapse has yet to be realized. Here, we investigate the formation of a magnetized hybrid star with a purely toroidal field and its properties through dynamical simulations. We find that the maximum values of rest-mass density and magnetic field strength increase slightly and these two quantities are coupled in phase during the formation. We then demonstrate that all microscopic and macroscopic quantities of the resulting hybrid star vary drastically when the maximum magnetic field strength goes beyond a threshold of $\sim 5 \times 10^{17}$ G, but they are insensitive to the magnetic field below this threshold. Specifically, the magnetic deformation makes the rest-mass density drop significantly, suppressing the matter fraction in the mixed phase. These behaviours agree with those in the equilibrium models of previous studies. Therefore, this work provides a solid support for the magnetic effects on a hybrid star.

Entropy Analysis in Magnetized Blood-Based Hybrid Nanofluid Flow via Parallel Disks

Magnetized hybrid nanofluid combined with ferrite and silver in a blood-based liquid presents their vital role in several aspects such as artificial heart pumping system, drug delivery process, the flow of blood in the artery, etc. This is because the high heat transportation rate of the nanofluid is caused by the inclusion of nanoparticles. The current investigation is based on the characteristic of particle concentration comprised of Fe3O4 and Ag in the base liquid blood that passed in between two infinite parallel disks filled with porous matrix. The electrically conducting fluid associated to maximum of 1.5% of volume concentration from each of the solid particles affects the flow phenomena. However, the impact of thermal radiation vis-à-vis the heat dissipation provides efficient heat transport properties with the inclusion of the effective thermal conductivity assumed from the Hamilton-Crosser model. The proposed conductivity model describes the role of particle shapes on the enhanced thermal properties. Further, numerical treatment is obtained for the transformed designed problem following similarity rules that are used for the conversion of the governing equations into their non-dimensional form. The computation of various flow profiles leads to get the entropy generation due to the irreversibility processes. Along with the fluid velocity and temperature distributions, the study is carried out for the entropy as well as the computation of Bejan number and afterwards the simulation of the shear and heat transportation rate are also depicted graphically. The main finding of the proposed study is that solid particle concentrations have a substantial impact to increasing fluid velocity in magnitude, resulting in a narrower wall thickness at both channel walls. Thermal radiation was shown to be more effective at increasing entropy generation and Bejan value.

Entropic thermodynamic analysis and radiative performance of unsteady magnetized squeezing hybrid nanofluid flowing via two disks with time-dependent heat generating

Entropic thermodynamic analysis and radiative performance of unsteady magnetized squeezing hybrid nanofluid flowing via two disks with time-dependent heat generating

Exploration of melting heat transfer and entropy generation in a magnetized hybrid nanoliquid over an extending sheet of varying thickness

The analysis of melting heat transfer over an expansive sheet of variable thickness is of the utmost importance in various industrial and engineering sectors, such as injection molding of polymers and composites, cooling of nuclear reactors, hot rolling, etc. Thus, the current work examines the flow dynamics, melting heat transport, and entropy generation of a magneto-hybrid nanofluid over a stretching device with variable thickness in porous media. A water-based hybridized nanofluid is formed using copper (Cu) and aluminium oxide (Al2O3) nanoparticles in the presence of thermal radiation, viscous dissipation, and Joulean heating. The transport partial derivatives were transmuted to ordinary derivatives using appropriate similarity quantities. These equations were numerically solved through shooting techniques combined with the Runge–Kutta–Fehlberg (RKF) method. Diverse figures and tables are sketched to illustrate the outcomes of the various parameters involved in the study. The investigation reveals an enlargement in the heat-bounding surface with an escalation in the magnitude of volume fraction, melting heat transfer, and magnetic field terms. In contrast, the momentum-bounding surface depletes with these parameters. Furthermore, as thermal radiation and Eckert numbers rise, the thermal gradient increases. The entropy generation increases with higher Brikman number and porosity term, but the melting heat parameter causes a decline in the entropy profiles.

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.

A numerical investigation of the magnetized water-based hybrid nanofluid flow over an extending sheet with a convective condition: Active and passive controls of nanoparticles

Abstract This study presents a numerical investigation of a viscous and incompressible three-dimensional flow of hybrid nanofluid composed of Ag and Al2O3 nanoparticles over a convectively heated bi-directional extending sheet with a porous medium. The main equations are converted into dimensionless form by using appropriate variables. The effects of magnetic field, porosity, Brownian motion, thermophoresis, and chemical reaction are investigated. Furthermore, the mass flux and zero-mass flux constraints are used to study heat and mass transfer rates. The obtained data show that the growing magnetic factor has reduced the velocity profiles while increasing the thermal profile. The increased porosity factor has decreased the velocity profiles. The increased thermal Biot number has increased the concentration and thermal profiles. When compared to passive control of nanoparticles, the hybrid nanofluid flow profiles are strongly influenced by the embedded factor in the active control of nanoparticles.

Intelligent neural computing to investigate the heat and mass transmission in nanofluidic system between two rotating permeable disks: Supervised learning mechanism

The prime objective of the present study is to investigate the effectiveness and accuracy of a single-trained artificial neural network. The Levenberg-Marquardt Backpropagated networks are tested for heat and mass transmission in magnetized hybrid nanofluid flow between the rotating permeable system. The reference data to generate different cases for distinct scenarios has been obtained using the Adams method in Mathematica using the ND-Solver function. Additionally, the system of highly nonlinear PDE's is achieved and transformed into ODE's. The effect of body forces such as thermophoresis particle diffusion and Brownian motion are incorporated in the hybrid nanofluid system. Configuration under observation is permeable and under constant impact of the magnetic field. Rosseland thermal radiation approximation relation is utilized to investigate the linear impact of radiation on velocity and temperature profile. The accuracy and effectiveness of the proposed ANNLMB are depicted with performance demonstrations. Mean square error, histogram error, and regression plots are generated for all the scenarios to discuss the varying impact of different key study parameters on the performance of the proposed ANNLMB. Furthermore, the generated reference data is distributed in the following manner 82 %, 9 %, and 9 % for training, testing, and validation, respectively.

Inclusion of Hall and Ion slip consequences on inclined magnetized cross hybrid nanofluid over a heated porous cone: Spectral relaxation scheme

The cone geometry has a great significant for heat transmission in many industrial processes due to its ability to induce turbulence, enable directional flow, promote uniform temperature distribution, and offer versatility in applications. The current study aims to investigate the heat transport process of an inclined magnetized cross hybrid nanofluid over a heated porous cone under the influence of Hall and Ion slip consequences. Additionally, porous medium the flow is past under the effect of inclined uniform magnetic field and porosity of the medium is used to enhance heat transfer. The framed set of governing equations took the form of dimension free structure through appropriate transformations and then finally solved by an effective spectral relaxation method. Thermal impacts and heat transport mechanism associated with the hybrid flow is seen through different values of emerging parameters. Heat transport is seen higher with higher radiation parameters, as radiation and rising temperature are similar. Augmented values of Fr causes pressure drop in fluids which reduces the fluid motion and brings depreciation in velocity field. Eckert number also boosts the temperature of the fluid stirring via a porous rotating cone.

Recent developments in the Darcy-Forchheimer model of magnetized tetra hybrid nanofluid activation energy/joule heating in a stenotic artery

The impact of heat generation and activation energy on the Darcy-Forchheimer flow of magnetized fluid with nanoparticles in the condition of blood flowing arteries is being investigated by researchers from all over the world in an effort to understand the heat transmission component for the treatment of numerous diseases. The assessment of heat transmission has been made with the enclosure of influence like the viscous dissipation, heat source, Joules heating, and thermal radiation. Utilized is a tetra hybrid nanofluid made up of silver (Ag), gold (Au), titanium oxide (TiO2), coper (Cu), and Blood as the base fluid. The main justification for the use of gold, copper, and silver nanoparticles as drug delivery nanomaterials is their potential for drug transport and imaging. The purpose of the presented model is to assess the performance of the well-known tetra hybrid nanofluid models developed by Yamada-Ota and Xue. The main PDE are transformed into ODE via similarity renovations, and these ODE are then numerically solved using the MATLAB built-in bvp4c scheme. The arteries' internal temperature rises as a result of thermal radiation and viscous dissipation. The velocity and thermal distributions show an increasing behavior with greater variations in the flow parameter. The Yamada-Ota model outperforms the Xue tetra hybrid nanofluid model in terms of heat transmission effectiveness.

Magnetized hybrid nanofluid flow across a wedge: A computational three-dimensional study

The boundary layer fluid flow past a wedge surface occurs in various industrial processes, including wire drawing, metal foaming, polymer extraction, fiber processing, and in determining the dynamic properties (shear stress, drag) of working fluids. Theoretically, the boundary layer three-dimensional flow of a magnetized hybrid nanoliquid over a wedge surface is studied with viscous dissipation and radiation effects. The flow is due to moving wedge surface and power-law free-stream velocities. The current study unifies three different classical flow problems, namely, the Blasius flow, the Hiemenz flow, and the Falkner-Skan flow. Single-phase description of hybrid nanofluid is considered, and the problem is kept realistic by considering the experimental thermophysical properties of the nanomaterial. The governing system consists of conservation of mass, momentum, and the energy equations for hybrid nanofluids. Prandtl’s boundary layer approximations are applied to study the viscous dominant fluid regimes. The entropy equation and the Bejan number are also derived. Numerical computations of self-similar equations are obtained to explore the rheological and the heat transport features against the physical parameters. The Nusselt number and the drag on the wedge surface are computed and analyzed. Of the three classical flow problems, the maximum thickness of the momentum layer occurs for the Blasius flow problem. A minimum drag force on the wedge surface occurs for lower Hartmann number values. Furthermore, an increase in the volume fraction of the hybrid nanoparticles leads to an enhanced heat transport. The use of carbon nanotubes which has exceptional characteristics are taken into consideration in this study. This study also demonstrates the comparison on three-different classical flow problems (Blasius flow, Hiemenz flow, and Falkner-Skan flow).

Non-similar bioconvective analysis of magnetized hybrid nanofluid (Ag + TiO2) flow over exponential stretching surface

Scientists have studied fluid flow over a stretching sheet to explore its potential applications in industries. This study investigates the exponential stretching flow of a bioconvective magnetohydrodynamic (MHD) hybrid nanofluid in porous medium taking into consideration thermal radiations, heat generation, chemical reaction, porosity, and dissipation. Moreover, microorganisms are present in the fluid, so the fluid is more stable, which is crucial in biotechnology, biomicrosystems, and bio-nano coolant systems. Silver and titanium dioxide in a water-based medium are the prototypical nanoparticles. The present study involves a transformation of the governing system into a set of dimensionless, coupled and nonlinear partial differential equations (PDEs) using nonsimilar techniques. The local non-similarity (LNS) technique is used to truncate these equations to ordinary differential equations (ODEs). This technique is also used to estimate transformed equations numerically until the second level of truncation takes place via the bvp4c algorithm, which is a built-in MATLAB solver. Furthermore, tables are provided that presents the drag coefficients, Nusselt numbers, Sherwood numbers, and densities of motile microorganisms. Results show a negative correlation between the velocity and the magnetic field parameter as well as the porosity parameter, as evidenced by a decrease in velocity corresponds to rises in these parameters. The temperature distribution exhibits a positive correlation with the rising values of both radiation parameter and Eckert number. The concentration profiles also exhibit a negative correlation with the increasing values of Lewis and bioconvection Lewis number, chemical reaction parameter, Peclet number and the differences in microbial concentration. This study will improve the future research on hybrid nanofluid regarding industrial applications. There haven't been any previous publications that have investigated the use of this model with the local non-similarity method. The main objective of this article is to enhance the heat transfer performance in a hybrid nanofluid.

Neural network architecture to optimize the nanoscale thermal transport of ternary magnetized Carreau nanofluid over 3D wedge

SignificanceIncorporation of nanoparticles in base fluid water is significant for analysis of thermal behavior of nanofluid mixtures, which has various applications in materials science and thermal engineering, and supervised neural scheme predicts the thermal behavior by solving Carreau nanofluid model. MotiveThis article brings the investigation related to prediction of thermal transport of a ternary magnetized hybrid nanofluid [(Al2O3, CuO, TiO2)/H2O] with a three-dimensional Carreau nanofluid model over a wedge. Three nanoparticles dispersed in water (H2O). Inclined magnetic field is considered for judgement of velocity profile and thermal radiation is utilized to scrutinize the temperature distribution of nanofluid. The Carreau mathematical model is chosen to depict the rheological characteristics of non-Newtonian fluids at very high and very low shear rate. MethodologyPhysical assumptions creates the system of Partial differential equations (PDEs) and these are converted into ordinary differential equations (ODEs) by similarity tool. Further ODEs are dealt with bvp4c scheme and further prediction of solution is made by Levenberg-Marquardt neural network (LM-NN) supervised neural scheme. FindingsIncreased volume friction coefficients of nanoparticles increases the transport of heat. High inclined magnetic effect, thermal radiation, pressure gradient and shear strain parameter predict higher thermal transport.

Artificial neural network approach to simulate the impact of concentration in optimizing heat transfer rate on water-based hybrid nanofluid under slip conditions: A regression analysis

The recent era of science depends upon the efficient performance of the heat transfer rate in several engineering applications for which the role of nanofluids have a greater impact. Therefore, the impact of particle concentration in optimizing heat transfer analysis of water-based hybrid nanofluid is conducted via an artificial neural network. The combined effect of oxide nanoparticles such as MgO and TiO2 in water performs their effective role with various factors involved in the flow phenomena. The magnetized hybrid nanofluid flow over an expanding surface filled with porous material shows its noble behavior on the flow properties. Further, it is not usual to omit the effectiveness of the dissipative heat impact. Therefore, the role of viscous, Joule, and Darcy dissipation is incorporated in the energy profile for which the profiles became coupled. The designed nonlinear model invokes suitable similarity rules that give rise to a system of nonlinear ordinary equations in non-dimensional form. Afterwards, the traditional numerical approach is beneficial to conduct the simulation of the flow profiles. The optimization of the heat transfer rate analysis is obtained by the implementation of an artificial neural network (ANN) for the response of Nusselt number using various factors. The regression analysis for the embedding data shows the effectiveness of the proposed approach in this discussion. The proposed study describes the important outcomes as; an increasing slip produces a thinning in the bounding surface thickness for the case of pure fluid comparing to the nanofluid and hybrid nanofluid. Further, the data set used for the hybrid nanofluid shows an efficient fitting than the case of nanofluid.

Neural network and thermodynamic optimization of magnetized hybrid nanofluid dissipative radiative convective flow with energy activation

This article, motivated by hybrid magnetic coating manufacturing developments, utilizes a neural network-based computational program to study the dynamics of hybrid magnetic nanofluids with entropy generation. A new physico-chemo-mathematical model has been presented to simulate the hybrid magnetic nano-coating flow along a stretching surface to a porous medium with viscous heating. A Rosseland flux model is used for radiation heat transfer and Darcy’s model for the isotropic porous medium. The stretching sheet is porous, and wall suction or injection are possible. A robust neural network has been deployed to optimize the physical parameters controlling the transport characteristics of hybrid nanofluids. Specifically, two hybrid nanoparticle combinations are addressed, namely graphite oxide (GO)-molybdenum disulfide ( Mo S 2 ) and copper (Cu)-silicon dioxide ( Si O 2 ), both with engine oil as the base fluid. The dimensional boundary layer model is transformed via suitable scaling variables from a partial differential system into a dimensionless non-linear coupled ordinary differential system. The transformed boundary value problem is solved numerically with the BVP4C subroutine in the symbolic software MATLAB, which achieves exceptional accuracy. Validation with previous simpler studies is conducted and a good correlation is obtained. The neural network optimization analysis incorporates Bayesian regularization as the training algorithm. The Bejan entropy generation minimization (EGM) analysis shows that with increasing radiation parameter R d , both entropy generation rate and Bejan number are increased. Furthermore, an elevation in Brinkman number Br leads to an upsurge in entropy generation rate and a downtrend in the Bejan number. The numerical solution of the boundary value problem reveals that with an increment in nanoparticle solid volume fraction φ 2 , magnetic parameter M , inverse permeability parameter ϵ , surface injection parameter ( s < 0 ) , Eckert number Ec and radiation parameter R d and with a decrement in suction parameter ( s > 0 ) and Prandtl number Pr , there is a strong enhancement in temperature magnitude and thermal boundary layer thickness. With greater nanoparticle solid volume fraction φ 2 , magnetic parameter M , inverse permeability parameter ϵ , suction parameter s and a reduction in thermal buoyancy parameter λ , strong flow deceleration is induced, and momentum boundary layer thickness is increased. The skin friction coefficient is substantially boosted with lower values of magnetic parameter M , inverse permeability parameter ϵ , suction parameter s and higher values of thermal buoyancy parameter λ . There is a significant decrement also computed in Nusselt number with a greater radiation parameter R d . The simulations provide a good benchmark for future extensions that may consider non-Newtonian behavior.

Heat transfer enhancement of forced convection magnetized cross model ternary hybrid nanofluid flow over a stretching cylinder: Non-similar analysis

Nanofluids have exhibited substantial promise in amplifying thermal efficiency across a spectrum of industrial domains. Concurrently, the study of flow dynamics through a stretching cylinder assumes paramount importance within contemporary construction paradigms, spanning the realms of polymer processing, metal sheet manipulation, biomechanics, and advanced medical applications. Bolstering these pragmatic contexts, the ongoing inquiry is focused on scrutinizing the reverberations of thermal radiation upon the laminar Cross model flow, ensconced within a magnetized ternary hybrid nanofluid. This, in turn, reverberates through the intricate tapestry of heat transfer phenomena. The fluidic flux is orchestrated by a stratified stretching cylinder, ensconced within the labyrinthine confines of a porous medium. The research intricately highlights pivotal attributes of the fluid, encompassing its intricately temperature-tethered thermal conductivity and its hinging upon the nuanced orchestra of temperature distribution. Furthermore, it cast an illuminating spotlight on the incipient cascades of ohmic heating, significantly sculpting the heat exchange contours within fluidic streams. The controlling equations are turned into dimensionless partial differential equations via non-similarity transformations. subsequently, the local non-similarity approach is utilized to treat the dimensionless PDEs as ODEs, and bvp4c MATLAB tools are used to effectively solve them. Subsequently, graphical representations are provided to illustrate the changes in the velocity profile and temperature profile resulting from variations in parameters such as the Weissenberg number, porous parameter, thermal conductivity parameter, Magnetic parameter, and Eckert number. Under the given physical circumstances, the Nusselt number representing the temperature gradient and the local skin friction coefficient were determined. Notably, the heat transport mechanism is significantly affected by both thermal radiation and ohmic heating. Furthermore, the warming effects inside the thermal boundary layer are especially important for the Darcy parameter and magnetic parameter, which makes them of particular relevance in heat transfer issues. In the end, the results show how successful the suggested numerical technique is since it offers a thorough depiction of the flow and heat transfer processes.

Forced convection analysis of Williamson-based magnetized hybrid nanofluid flow through a porous medium: Nonsimilar modeling

The purpose of this work is to analyze the convective horizontal flow of Williamson-based magnetized hybrid nanofluid. The flow of Williamson fluid with heat transfer is stimulated in a porous media over a stretching surface. Two different type of nanoparticles such as, molybdenum disulfide ( Mo S 2 ) and copper (Cu) with engine oil (Eo) as base fluid are considered in this work. The convective flow of Williamson fluid is inspected based on Khanefer model. The governing system is transformed into nondimensionalized partial differential equations (PDE’s) by utilizing nonsimilar transformation. The transformed system is analytically approximated using local nonsimilarity (LNS) and perturbation approach which approximate the nondimensional PDE’s by nondimensional ordinary differential equations (ODEs). The LNS and perturbation ODEs are simulated utilizing finite difference-based algorithm bvp4c. The outcomes of simulation for heat transfer and convective flow over stretching surface incorporating the evolvement with local Nusselt number (Nu) for distinct values of prandtl number are compared with previous published numerical results. The appropriate range of governing nondimensionalized parameters is evaluated to detect the variance of physical quantities namely, velocity ( f ′ ( η ) ) of the fluid, temperature ( θ ′ ( η ) ) of the fluid, co-efficient of local Nusselt number (Nu) and co-efficient of local skin friction (Cf). The percentage difference between single nano-fluid and hybrid nano-fluids is made which are given in tabular form. To the best of author knowledge, nonosimilar study of hybrid-based magnetized Williamson nanofluid is not yet investigated. This work is anticipated to offer crucial information for the implementation of innovative heat transfer devices in the future and serve as an invaluable resource for researchers looking at the flow of nanofluids under various assumptions.

Dynamics of magnetized hybrid solid particles in a rotating cone with gradient descent optimization

Background Recent developments in nanoscience and nanotechnology have led to innovative hybrid nanofluids with superior thermal attributes to traditional nanofluids. These developments act as inspiration for the current framework, which focuses on an unsteady Casson hybrid nanofluid flow over a rotating cone in the presence of nonuniform heat source/sink factor. Methodology Two distinct shaped hybrid nanoparticles-hosted water is emphasized in the present work, namely spherical shaped CoF e 2 O 4 and cylindrical shaped Cu . The contribution of the heat source/sink variable is incorporated into the regulating equations utilizing boundary layer approximations. The resulting expressions of dimensionless forms of transmuted ODEs are computed through an NDSolve scheme. The performance of the pertinent parameters is accentuated to exhibit the relevance of the considered flow model. Furthermore, Multiple Linear Regression is introduced to generate appropriate formulations for the prediction of physical quantities on nanofluid and hybrid nanofluid. Core findings The volume fraction particles have a propensity to boost the temperature distribution, while the azimuthal and tangential factor follows the opposite trend in both the nanofluid and hybrid nanofluid. The skin friction coefficients rise for unsteady parameters, but the Nusselt number gets diminished due to the unsteadiness. The heat transfer rate of CoF e 2 O 4 nanoparticles hosted H 2 O is increased in Rudyak model than the Brinkman viscosity model by the involvement of an effective viscosity coefficient in terms of volume concentration of dispersed particles in nanofluid. Validation The outcomes are validated by comparing the present exploration with previously published investigations in certain instances. The multiple linear regression accurately anticipated the physical quantities with minimal error 10 − 2 . Applications An implementation of machine learning as an approach to do thermal evaluation with reliability and precision has emerged as a growing trend. The results of this investigation will benefit plenty of heat transfer applications, such as heat exchangers, heat pipes, and micro-channels.

On thermal performance of spine fin in magnetized hybrid fluid rooted with Cu and MoS4 nanoparticles

This study examines the thermal performance of diverse profiles of spine fins with variable thermal conductivity. A hybrid nanofluid comprising Cu, and MoS4 with water as the base fluid, is modeled mathematically. Both the cylindrical and concave parabolic profiles are taken into account. The comparative outcomes are inferred from numerical and semi-analytical methods. The non-dimensional temperature profiles are analyzed graphically while considering the fin tip to be insulated, and the effects of various thermal parameters are also investigated. We have observed that the heat transfer rate shows an opposite trend toward convective-conduction and porosity parameter. The study also revealed that the concave parabolic profile emits more heat in comparison with the cylindrical profile.

Spectral and Jet Properties of the Quasi-thermal-dominated GRB 210121A, GRB 210610B, and GRB 221022B

Some quasi-thermal (QT)-dominated gamma-ray bursts (GRBs) could be well described by a multicolor blackbody (mBB) function or a combined model of a BB plus a nonthermal (NT) component. In this analysis, two QT radiation-dominated bursts with known emission properties (GRB 210610B, likely from a hybrid jet, and GRB 210121A, with a spectrum consistent with nondissipative photospheric emission from a pure hot fireball) are used to make a comparison between these two models. To diagnose the magnetization properties of the central engine, the “top-down” approach proposed by Gao and Zhang is adopted. It is found that diagnoses based on these two models provide similar conclusions qualitatively; however, the model with mBB (or mBB+NT) may give more reasonable physical explanations. This implies that impacts from the GRB jet structure and geometrical broadening on the observed spectrum should be considered. However, conservatively, these methods may be not sensitive enough to distinguish between a pure hot fireball and a mildly magnetized hybrid jet. Some other information is necessary to provide more evidence when determining the jet properties for similar GRBs. Based on these considerations, we suggest that the photospheric emission of GRB 221022B is from a hot jet, where dissipation is caused by an internal shock mechanism due to the increasing Lorentz factor with time, which makes its prompt emission display typical evolution from thermal to NT.