Quasilinearization Method Research Articles

Exploring convective entropy optimization and activation energy impact on magneto-nanofluid flow over a vertical stretched plate with Hall current and nonlinear thermal radiation using SQLM

This paper investigates the profound impact of entropy generation and activation energy on the dynamics of hydromagnetic nanofluids, focusing on nonlinear thermal radiation, viscous and Ohmic dissipation, and Hall current effects over a linear stretching sheet. Various nanoparticles are incorporated into the nanofluid formulation using the thermophoresis and Brownian motion model. Through similarity transformation, the system of nonlinear equations is solved with high precision using the Spectral Quasilinearization Method (SQLM). Comprehensive analyses of velocity, cross-flow velocity, temperature, concentration, and entropy generation profiles are conducted for numerous physical parameters. Results indicate that velocity and cross-flow velocity increase with the Hall parameter while temperature and concentration profiles decrease. Both the velocity and cross-flow velocity profiles enhance for mixed convection parameters closer to the sheet, whereas the temperature and concentration profiles exhibit the contrary tendency. Prandtl number diminishes the profiles of horizontal velocity, cross-flow velocity and concentration distributions. Temperature distribution profile hikes for both the Brownian motion parameter and thermophoresis parameter. The activation energy parameter enhances the cross-flow velocity, with a corresponding decline in temperature distribution and a similar trend is observed in the concentration profile. Further, entropy generation profiles increase with higher Brinkman and Reynolds numbers while exhibiting mixed tendencies with the Schmidt number. These findings reveal that Hall current introduces complex interactions within the nanofluid flow, significantly influencing thermal, concentration, and entropy generation characteristics, particularly in magnetic fields and activation energy.

Qualitative Outcomes on Monotone Iterative Technique and Quasilinearization Method on Time Scale

In this paper, a nonlinear dynamic equation with an initial value problem (IVP) on a time scale is considered. First, applying comparison results with a coupled lower solution (LS) and an upper solution (US), we improved the quasilinearization method (QLM) for the IVP. Unlike other studies, we consider the LS and US pair of the seventh type instead of the natural type. It was determined that the solutions of the dynamic equation converge uniformly and monotonically to the unique solution of the IVP, and the convergence is quadratic. Moreover, we will use the delta derivative (Δγ) instead of the classical derivative (dγ) in the proof because it studies a time scale. In the second part of the paper, we applied the monotone iterative technique (MIT) coupled with the LS and US, which is an effective method, proving a clear analytical representation for the solution of the equation when the relevant functions are monotonically non-decreasing and non-increasing. Then an example is given to illustrate the results obtained.

Numerical solution for a generalized form of nonlinear cordial Volterra integral equations using quasilinearization and Legendre-collocation methods

In this article, we propose a numerical method for a general form of nonlinear cordial Volterra integral equations. We discuss conditions that under them the problem has solutions. Since the existence of solutions for the problem depends on the solvability of a scalar equation and also a linear form of the problem, then we employ quasilinearization technique in which solving a nonlinear problem is reduced to solve a sequence of linear equations. The existence of solutions of linear equations and their quadratically convergence to the solutions of the nonlinear problem is considered. For the numerical solution of the produced linear equations we apply Legendre-collocation method along with a regularization technique for the quadrature formulas. We discuss the error analysis of the collocation method considering that the cordial Volterra integral operators are noncompact. To test the efficiency and accuracy of the proposed method, the solution of different cases of numerical examples are reported.

Entropy generation and Cattaneo–Christov heat flux analysis of binary and ternary hybrid Maxwell nanofluid flows with slip and convective conditions

Hybrid nanomaterials significantly enhance thermal systems through improved thermal conductivity, efficient energy storage, and customized thermomechanical properties. Due to their superior thermophysical characteristics, binary/ternary hybrid nanofluids are crucial in fields such as industry, biomedicine, transportation, and pharmaceuticals. This study examines the hydromagnetic flows and heat transfer properties of binary (CuO+Fe3O4/sodium alginate) and ternary (CuO+Fe3O4+MoS2/sodium alginate) hybrid Maxwell nanofluids over a radially stretching rotating disk. The governing flow equations incorporate Cattaneo–Christov heat flux, mixed convection, velocity and thermal slips, nonlinear radiation, viscous dissipation, and Joule heating in a Darcy–Forchheimer porous medium. These axisymmetric partial differential equations are transformed into ordinary differential equations using similarity variables, and the spectral quasilinearization method (SQLM) is applied for numerical solutions. Results reveal the effects of relevant parameters on velocity, temperature, skin friction, and heat transfer rates. Novelty lies in the comparative analysis of flow behaviors and entropy production rates between binary and ternary hybrid Maxwell nanofluids. When the heat source is included, the Nusselt number increases by 12.9% for ternary nanofluids and 16.07% for binary nanofluids as the thermal relaxation number increases from 0.5 to 1.5. Furthermore, the ternary hybrid nanofluid shows greater resistance to Lorentz and porous medium forces and exhibits a higher temperature distribution and better thermal management capabilities compared to the binary hybrid nanofluid.

Accelerating Fourth-Generation Machine Learning Potentials Using Quasi-Linear Scaling Particle Mesh Charge Equilibration.

Machine learning potentials (MLPs) have revolutionized the field of atomistic simulations by describing atomic interactions with the accuracy of electronic structure methods at a small fraction of the cost. Most current MLPs construct the energy of a system as a sum of atomic energies, which depend on information about the atomic environments provided in the form of predefined or learnable feature vectors. If, in addition, nonlocal phenomena like long-range charge transfer are important, fourth-generation MLPs need to be used, which include a charge equilibration (Qeq) step to take the global structure of the system into account. This Qeq can significantly increase the computational cost and thus can become a computational bottleneck for large systems. In this Article, we present a highly efficient formulation of Qeq that does not require the explicit computation of the Coulomb matrix elements, resulting in a quasi-linear scaling method. Moreover, our approach also allows for the efficient calculation of energy derivatives, which explicitly consider the global structure-dependence of the atomic charges as obtained from Qeq. Due to its generality, the method is not restricted to MLPs and can also be applied within a variety of other force fields.

A highly accurate and efficient Genocchi‐based spectral technique applied to singular fractional order boundary value problems

This article focuses on an efficient and highly accurate approximate solver for a class of generalized singular boundary value problems (SBVPs) having nonlinearity and with two‐term fractional derivatives. The involved fractional derivative operators are given in the form of Liouville–Caputo. The developed algorithm for solving the generalized SBVPs consists of two main stages. The first stage is devoted to an iterative quasilinearization method (QLM) to conquer the (strong) nonlinearity of the governing SBVPs. Secondly, we employ the generalized Genocchi polynomials (GGPs) to treat the resulting sequence of linearized SBVPs numerically. An upper error estimate for the Genocchi series solution in the norm is obtained via a rigorous error analysis. The main benefit of the presented QLM‐GGPs procedure is that the required number of iteration in the first stage is within a few steps, and an accurate polynomial solution is obtained through computer implementations in the second stage. Three widely applicable test cases are investigated to observe the efficacy as well as the high‐order accuracy of the QLM‐GGPs algorithm. The comparable accuracy and robustness of the presented algorithm are validated by doing comparisons with the results of some well‐established available computational methods. It is apparently shown that the QLM‐GGPs algorithm provides a promising tool to solve strongly nonlinear SBVPs with two‐term fractional derivatives accurately and efficiently.

Generalized Quasilinearization Method for Caputo Fractional Differential Equations with Initial Conditions with Applications

Generalized Quasilinearization Method for Caputo Fractional Differential Equations with Initial Conditions with Applications

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].

New Results on the Quasilinearization Method for Time Scales

We have developed the generalized quasilinearization method (QM) for an initial value problem (IVP) of dynamic equations on time scales by using comparison theorems with a coupled lower solution (LS) and upper solution (US) of the natural type. Under some conditions, we observed that the solutions converged to the unique solution of the problem uniformly and monotonically, and the rate of convergence was investigated.

Overlapping grid multidomian spectral quasilinearization method for Williamson nanofluid with gyrotactic microorganisms flow past a radially stretching sheet

Overlapping grid multidomian spectral quasilinearization method for Williamson nanofluid with gyrotactic microorganisms flow past a radially stretching sheet

The impact of factor tax structure on firm innovation: evidence from China

ABSTRACT Labor and capital are two of the most fundamental factors of production, and the ratio of labor to capital tax can reflect the structure of factor tax. Despite the existing literature demonstrating the impact of taxation on enterprise innovation, few studies have addressed the effect of changes in factor tax structure on enterprise innovation. Using provincial tax data and listed company data from China between 2006 and 2017, this study empirically tests the impact of factor tax structure on enterprise innovation using the Poisson quasi-linear method. The findings indicate that a higher share of labor tax and a lower share of capital tax tend to inhibit enterprise innovation. Conversely, a higher tax compliance rate for labor tax and a lower compliance rate for capital tax are also unfavorable to enterprise innovation. A non-linear relationship is observed between factor tax structure and enterprise innovation, where a higher share of labor tax and a lower share of capital tax can promote enterprise innovation when exceeding a specific limit. The results of this study have theoretical and practical implications for improving factor tax structure, stimulating enterprise innovation, and promoting economic transformation toward higher quality.

Dynamics of magneto-bioconvection thermal casson nanofluid with activation energy and joule heating

As nanotechnology is expanding its application in engineering science, it provides ample opportunities to explore fluid properties with the help of nanoparticles for growing significance in different industries. Heat and energy management are the major concerned areas to the industries as well as researchers. This article carried out the investigation of gyrotactic microorganisms incorporated in Casson nanofluid, with activation energy, Hall, Joule heating, and other parameters. The major interest of this article was to explore the characteristic of the bioconvective magneto Casson nanofluid by analyzing the influence of the key parameters on the heat, flow, concentration and microbial concentration profiles. Thepreliminary borderline circumstances with prevailing partial differential equations by use of appropriate similarity variations were rewritten as ordinary differential equations (ODEs) and ultimate borderline environments correspondingly. Furthermore, we used the Spectral Quasi-Linearization (SQLM) method for the numerical calculation of ODEs to get the consequences of the key parameters. Analysis of the flow in both directions i.e. the tangential and circumferential, temperature, solutal, and microbial distribution with activation energy, and the ion-slip, Hall current, and other interesting parameters was done by their pictorial views. The quantities of physical attention were examined and reflected the flattering outcomes. The increasing Casson nanofluid parameter reduces the velocity outline of the flow while expanding the temperature outline, on the other side the microbial, and solutal profiles was enriched by the rising values of the activation energy constraint. The rising of temperature profile has been observed for the increasing values of the thermal radiation as well as buoyancy ratio parameters. The effect of different parameters on engineering interest quantities was also considered. The growing Casson fluid parameter, minimize the local Nusselt number approximately 43%, while the quantities of local Sherwood and local density of microbial increase by approximately 16% and 22%, correspondingly. The local Nusselt number decreases about 87%, however, the local quantities of Sherwood, and density of microbial increase by about 13% and 12%, respectively for increasing values of thermal radiation.

Lie group analysis and SQLM of entropy generation of MHD nonlinear radiative micropolar nanofluid flow with thermophoresis and Brownian motion

This study investigates the entropy generation in hydromagnetic mixed convection of a micropolar fluid flowing over a stretchable sheet, taking into account various influential factors such as nonlinear thermal radiation, Ohmic dissipation, uniform heat source/sink effects, chemical reaction, thermophoresis, and Brownian motion. The Spectral Quasilinearization Method (SQLM) is employed, which transforms nonlinear equations into a series of linearized ones, streamlining the solving process. Additionally, Lie group analysis is utilized to identify symmetries and derive similarity transformations crucial for converting partial differential equations into coupled ordinary differential equations, which are then solved numerically. A comprehensive sensitivity analysis is conducted on critical parameters, including the Darcy parameter, Biot number, Brinkman number, nonlinear convection parameter, and chemical reaction parameter. This analysis explores the impacts of these parameters on various flow profiles, such as velocity, temperature, microrotation, concentration, and entropy generation, enriching the depth and practical relevance of the findings. The results reveal that increasing the Brinkman and Reynolds numbers enhances entropy generation profiles while increasing the coupling parameter reduces them. The focus on entropy generation analysis provides valuable insights into energy utilization and system efficiency, particularly in micropolar fluid dynamics. Furthermore, the study underscores the practical implications of its findings by highlighting their relevance in evaluating the effectiveness of industrial processes, especially those related to energy conversion and heat transfer phenomena.

Entropy generation and activation energy on nonlinearly thermo-radiative and magnetohydrodynamic heat transfer of Jeffrey nanofluid with non-uniform heat source/sink using SQLM

ABSTRACT Entropy generation and activation energy analysis on MHD heat and mass transfer of Jeffrey nanofluid under the impact of nonlinear thermal radiation and heat source/sink (non-uniform) over a linearly stretching sheet has been investigated numerically using Spectral Quasilinearization Method (SQLM). The Brownian motion with thermophoretic effects has been utilized. The basic equations concerned with the problem are solved numerically. The impacts of different governing physical parameters are analyzed on the velocity, temperature, and concentration fields, along with entropy generation, and Bejan number profiles are analyzed graphically. It is found that the concentration profiles have a mixed tendency with magnetic parameters. In addition, the temperature profiles increase in the presence of Brownian motion with thermophoresis effects, whereas the composite behavior is noticed on the entropy generation profiles. It is also found that both the temperature and concentration profiles diminish for various values of Deborah number while the velocity profile increases. Also, it is noticed that both the temperature profiles increase for enhanced values of the space-dependent and time-dependent parameters. Due to activation energy, the Bejan number profiles decrease, whereas the entropy generation profiles increase far away from the expandable sheet but decrease closer to the sheet.

Spectral quasi-linearization approach for the swimming of motile microorganisms on the bio-convection Casson nanofluid flow over a rotating circular disk

The ability of motile microorganisms is used to design of biomedical nanofluidic devices that utilize for targeted drug delivery, to influence heat transfer in nanofluids that are applied to the optimization of cooling system, in biotechnological processes where precise control over fluid flow, etc. However, based upon the several facts, the current investigation lead to propose the heat transfer characteristic of motile microorganisms swimming in a flow of bio-convection nanofluid over a rotating circular disk. The proposed study explores the impacts of dissipative heat generated by the movement of microorganisms, thermal radiation, and chemical reactions. The impact of cross-diffusive property organized by the implementation of Brownian motion and thermophorsis energies the flow phenomena of bio-convection. The set of coupled nonlinear system of non-dimensional equations is obtained by the implementation of similarity rules and further quasi-linearization method is utilized for the solution of this system. The characteristics of diversified parameters are presented through graphs with the variation of the proposed factors within their certain limitations and thee discuss briefly. Further, the important outcomes of the study are presented as; the fluid velocity decelerates due to the enhanced non-Newtonian Casson parameter, whereas the radiating heat for the inclusion of thermal radiation and coupling parameter, that is, Eckert number boosts up the heat transport phenomena.

Stability analysis and numerical evaluations of a COVID-19 model with vaccination

A novel (nonlinear) mathematical model for the transmission of Coronavirus 19 (COVID-19) with eight compartments and considering the impact of vaccination is examined in this manuscript. The qualitative behavior of the system such as the boundedness of solutions, the basic reproduction number, and the stability of the equilibrium points is investigated in detail. Some domestic real data collected from the Kerman University of Medical Science (KUMC) is used to estimate the parameters of the proposed model. We predict the dynamical behavior of the system through numerical simulations based on a combined spectral matrix collocation methodology. In this respect, we first linearize the nonlinear system of equations by the method of quasilinearization (QLM). Hence, the shifted version of Chebyshev polynomials of the second kind (SCPSK) is utilized along with the domain-splitting strategy to acquire the solutions of the system over a long time interval. The uniform convergence and upper bound estimation of the SCPSK bases are proved in a rigorous manner. Moreover, the technique of residual error functions is used to testify the accuracy of the QLM-SCPSK method. The presented numerical results justify the robustness and good accuracy of the QLM-SCPSK technique. The achieved numerical orders of convergence indicate that the QLM-SCSK algorithm has exponential rate of convergence. Using the linearization technique in one hand and the domain-splitting strategy on the other hand, enable us to predict the behaviour of similar disease problems with high accuracy and maximum efficiency on an arbitrary domain of interest.

Thermohydrodynamics of Bödewadt hybrid-nanofluid flow in a horizontal magnetic field

Since disks, rotating or stationary, are integral in many thermal systems, such as rotating heat exchangers, thermoelectric coolers, solar energy systems, and geothermal plants, this study scrutinizes the thermohydrodynamics of rotating hybrid nanofluid flow over a stretchable disk at rest. Further, the shape of the nanoparticles and the choice of base fluid substantially impact the enhancement of the heat transfer rate in various such thermal systems. Therefore, the present investigation considers engineered colloids made of four distinct (sphere, cylinder, column, lamina) titania and copper nanoparticle shapes in two different base fluids: water and engine-oil. The problem is formulated mathematically in an externally applied horizontal magnetic field and incorporating a non-Fourier heat flux model in the presence of solar radiation. Analogous to the case of the conventional vertical magnetic field, a similarity solution is also possible when magnetic forces act horizontally, both towards and opposite to the direction of rotation. Thus, the governing partial differential equations (PDEs) are first reduced to a set of highly non-linear and coupled ordinary differential equations (ODEs) via similarity transformations. These resulting set of ODEs are then solved numerically using a rapid and efficient spectral quasilinearization method (SQLM). Obtained results show that lamina-shaped TiO2−Cu/ engine-oil hybrid-nanofluid is a better choice than the other shapes of nanoparticle suspension in water. The horizontally applied magnetic field exhibits a stronger influence on the flow and heat transfer characteristics when compared to a vertical magnetic field. Additionally increasing the thermal relaxation parameter αt from 0.1 to 0.35, the Nusselt number boost by 24.44%, 23.41%, 22.54%, and 17.93% for sphere, cylinder, column, and lamina nanoparticles of TiO2−Cu/water hybrid nanofluid. In the case of TiO2−Cu/engine-oil hybrid-nanofluid augmenting αt from 0.1 to 0.35, the Nusselt number rise by 23.95%, 22.83%, 21.82%, and 15.89% for sphere, cylinder, column, and lamina nanoparticles. Based on their increasing NS and Be values, the various shapes follow the sequence: lamina ¡ column ¡ cylinder ¡ sphere. Furthermore, entropy generation can be optimized through the augmentation of solar radiation factors QSR, δ, along with the reduction of the magnetic interaction parameter M, and by a proper selection of nanoparticle’s shape. Interestingly, dual solutions are observed for the case of a shrinking disk, i.e., for S<0, and a linear temporal stability analysis reveals that only one of these two branches, namely the first solution branch, is stable and the second branch unstable.

Quasilinearization variational iteration method for system of nonlinear ODEs

In this manuscript, we discuss a new technique for solving system of nonlinear differential equations, which is a modification of the variation iteration method (VIM) implemented using the quasilinearization method and Adomian’s polynomial. The quasilinearization variational iteration method (QVIM) is the name given to this proposed method. The proposed method’s convergence analysis in Banach space is also discussed here. Three application problems, including the Genesio-Tesi system, are considered to test the applicability of our approach. We also discuss the case study of the chaotic and non-chaotic solutions of the Genesio-Tesi system (GTS). The convergence behaviour of the method is studied for various values of parameter x. To assess the viability and efficacy of QVIM, we compare it to the existing well-known Adomian decomposition method. The results show that the proposed method is highly efficient and simple to implement.

Influence of magnetic field-dependent viscosity on Casson-based nanofluid boundary layers: A comprehensive analysis using Lie group and spectral quasi-linearization method

This study examines the effects of magnetic-field-dependent (MFD) viscosity on the boundary layer flow of a non-Newtonian sodium alginate-based Fe3O4 nanofluid over an impermeable stretching surface. The non-Newtonian Casson and homogeneous nanofluid models are utilized to derive the governing flow and heat transfer equations. Applying Lie group transformations to dimensional partial differential equations yields nondimensional ordinary differential equations, which are then numerically solved using the spectral quasi-linearization technique. The analysis primarily focuses on the impacts of the MFD viscosity parameter, nanoparticle volume fraction of Fe3O4, and magnetic parameters on the flow and heat transfer characteristics. The local skin friction and heat transfer rate behaviors influenced by viscosity changes due to the magnetic field are discussed. It is found that MFD viscosity significantly impacts flow and thermal energies, enhancing skin friction coefficients and reducing Nusselt numbers in the boundary layer region.

Analysis of heat and mass transfer of a non-linear convective heat generating fluid flow in a porous medium with variable viscosity

The present study addresses the significance of analyzing the heat and mass transfer characteristics of a non-linear convective fluid flow featuring variable viscosity within a porous medium. Our focus lies on understanding the impact of varying viscosity on the hydromagnetic coupling stress, particularly in the presence of internal heat generation. The fluid is confined within a porous medium, and convection cooling takes place at both wall of the fluid. A key assumption in our investigation is the nonlinearity nature of the buoyancy force, specifically when there is a substantial difference in temperature and concentration within the fluid and its surroundings, the buoyancy force becomes quadratic. The exploration of couple stress fluids, alongside considerations of temperature-dependent internal heat generation and mass transfer, contributes to advancing our understanding of thermal system performance. By accounting for nonlinearity in density, temperature, and concentration, the research aims to provide more accurate results than previous linear models, crucial for optimizing energy consumption in practical applications such as nuclear reactors and heat exchangers. Dealing with this type of problem often pose significant challenges, as they often lack analytical solutions, necessitating the use of more advanced numerical methods or approximation techniques. We employ Spectral Quasilinearisation Method (SQLM) to solve the coupled non-linear boundary value problems (PDE) arising from the model, momentum equation, energy equation, concentration equation, and entropy generation. The obtained results are then validated using the Runge–Kutta method and a good agreement is achieved. The findings for the dimensionless velocity, temperature, mass concentration and entropy generation are presented in graphics and in table manner, and effects of controlling parameters are extensively explained. The results highlight that an increase in variable viscosity leads to an enhancement in the velocity profile, while simultaneously reducing the temperature in the system. Furthermore, increments in the non-linear convection parameter and coupling stress parameter result in an appreciation of the velocity profile, temperature profile, and entropy generation rate.