Browsing by Author "Ali, Aatif"

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    A Novel Analysis of Generalized Perturbed Zakharov–Kuznetsov Equation of Fractional-Order Arising in Dusty Plasma by Natural Transform Decomposition Method
    (Hindawi, 2022-06) Alhazmi, Sharifah E.; Abdelmohsen, Shaimaa A. M.; Alyami, Maryam Ahmed; Ali, Aatif; Asamoah, Joshua Kiddy K.; 0000-0002-7066-246X
    The natural transform decomposition method (NTDM) is a relatively new transformation method for finding an approximate differential equation solution. In the current study, the NTDM has been used for obtaining an approximate solution of the fractional-order generalized perturbed Zakharov–Kuznetsov (GPZK) equation. The method has been tested for three nonlinear cases of the fractional-order GPZK equation. The absolute errors are analyzed by the proposed method and the q-homotopy analysis transform method (q-HATM). 3D and 2D graphs have shown the proposed method’s accuracy and effectiveness. NTDM gives a much-closed solution after a few terms.
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    Heat transfer analysis of reactive boundary layer flow over a wedge in a nanofluid using Buongiorno’s model
    (AIP Advances, 2024-10) Jan, Saeed Ullah; Ali, Aatif; Sharaf, Mohamed; Asamoah, Joshua Kiddy K.; 0000-0002-7066-246X
    heat transfer of nanofluids. This study investigates the effects of three different chemical reactions—Arrhenius, bimolecular, and sensitized reactions—using Buongiorno’s model. Through similarity transformations, the system of partial differential equations (PDEs) is converted into ordinary differential equations, which are then solved by combining the shooting method with the Runge–Kutta–Fehlberg numerical technique. The findings show that the skin friction coefficient is greatly increased by raising the pressure gradient and stretching/contracting wedge parameters. On the other hand, as the thermophoresis parameter, Brownian motion parameter, activation energy, and Lewis number increase, the Nusselt number decreases, signifying a decrease in the efficiency of heat transfer. A higher Sherwood number, on the other hand, indicates increased mass transfer and is brought about by increases in the Lewis number, thermophoresis parameter, activation energy, and Falkner–Skan power-law parameter. These findings provide important information for maximizing heat and mass transfer in nanofluid systems. Key values for the skin friction coefficient, local Nusselt number, and the Sherwood number are given in tabular form, and the results are graphically represented.
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    Intelligent computing for electromagnetohydrodynamic bioconvection flow of micropolar nanofluid with thermal radiation and stratification: Levenberg–Marquardt backpropagation algorithm
    (AIP Advances, 2024-03) Khan, Zeeshan; Alfwzan, Wafa F.; Ali, Aatif; Nisreen, Innab; Zuhra, Samina; Islam, Saeed; Asamoah, Joshua Kiddy K.; 0000-0002-7066-246X
    The Levenberg–Marquardt (LM) backpropagation optimization algorithm, an artificial neural network algorithm, is used in this study to perform integrated numerical computing to evaluate the electromagnetohydrodynamic bioconvection flow of micropolar nanofluid with thermal radiation and stratification. The model is then reduced to a collection of boundary value problems, which are solved with the help of a numerical technique and the proposed scheme, i.e., the LM algorithm, which is an iterative approach to determine the minimum of a nonlinear function defined as the sum of squares. As a blend of the steepest descent and the Gauss–Newton method, it has become a typical approach for nonlinear least-squares problems. Furthermore, the stability and consistency of the algorithm are ensured. For validation purposes, the results are also compared with those of previous research and the MATLAB bvp4c solver. Neural networking is also utilized for velocity, temperature, and concentration profile mapping from input to output. These findings demonstrate the accuracy of forecasts and optimizations produced by artificial neural networks. The performance of the bvp4c solver, which is used to reduce the mean square error, is used to generalize a dataset. The artificial neural network-based LM backpropagation optimization algorithm operates using data based on the ratio of testing (13%), validation (17%), and training (70%). This stochastic computing work presents an activation log-sigmoid function based LM backpropagation optimization algorithm, in which tens of neurons and hidden and output layers are used for solving the learning language model. The overlapping of the results and the small computed absolute errors, which range from 10−3 to 10−10 and from 106 to 108 for each model class, indicate the accuracy of the artificial neural network-based LM backpropagation optimization algorithm. Furthermore, each model case’s regression performance is evaluated as if it were an ideal model. In addition, function fitness and histogram are used to validate the dependability of the algorithm. Numerical approaches and artificial neural networks are an excellent combination for fluid dynamics, and this could lead to new advancements in many domains. The findings of this research could contribute to the optimization of fluid systems, resulting in increased efficiency and production across various technical domains.
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    Mathematical modeling for the transmission potential of Zika virus with optimal control strategies
    (Springer , 2022-01) Ali, Aatif; Iqbal, Quaid; Asamoah, Joshua Kiddy K.; Islam, Saeed; 0000-0002-7066-246X
    In this paper, we formulate a new Zika virus model in light of both mosquito and human transmission along with the human awareness in the host population. Initially, we assumed that the virus is transmitted to humans through a mosquito bite and then transmits to his or her sexual partner. Further, we investigated the mathematical results and stability analysis and proved that the model is asymptotically stable both locally and globally. We applied the Castillo-Chavez approach for establishing global stability. Similarly, we presented the existence of endemic equilibrium and demonstrate that the model is locally and globally asymptotically stable using a suitable Lyapunov function at endemic state, upon backward bifurcation analysis we proposed that no bifurcation exists for our model. The sensitivity analysis is carried out and verified that the probability per biting of the susceptible mosquito with the infected human is the most sensitive parameter. Furthermore, we developed a Zika control model and incorporated three controls. These controls are prevention through bed nets and mosquito repellents, treatment of Zika patients, and the spray of insecticides on mosquitoes. The graphical results of the model with control and without control are obtained through a numerical scheme. The infection caused by the Zika virus would be more efficiently eliminated using the new idea of human awareness and bilinear incidence presented in this paper.
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    Motile micro-organism based trihybrid nanofluid flow with an application of magnetic effect across a slender stretching sheet: Numerical approach
    (AIP Advances, 2023-03) Elsebaee, Fayza Abdel Aziz; Bilal, Muhammad; Mahmoud, Samy Refahy; Balubaid, Mohammed; Shuaib, Muhammad; Asamoah, Joshua Kiddy K.; Ali, Aatif; 0000-0002-7066-246X
    The steady magnetohydrodynamic ternary hybrid nanofluid flow over a slender surface under the effects of activation energy, Hall current, chemical reactions, and a heat source has been reported. A numerical model is developed to increase the rate of energy transfer and boost the efficiency and outcome of heat energy dissemination for a diverse range of biological applications and commercial uses. The rheological properties and thermal conductivity of the base fluids are improved by framing an accurate combination of nanoparticles (NPs). The ternary hybrid nanofluid has been prepared, in the current analysis, by the dispersion of magnesium oxide, titanium dioxide (TiO2), and cobalt ferrite (CoFe2O4) NPs in the base fluid. The physical phenomena have been expressed in the form of a system of nonlinear PDEs, which are degraded to a dimensionless system of ODEs through the similarity replacement and numerically solved by employing the MATLAB software package bvp4c. The graphical and tabular results are estimated for velocity, mass, and energy curves vs distinct physical factors. It has been noticed that the variation in the magnetic effect enhances the energy profile while the increasing number of ternary nanocomposites (MgO, TiO2, and CoFe2O4) in water lowers the energy curve. Furthermore, the effect of both Lewis and Peclet numbers weakens the motile microbe’s profile.
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    New Variant of SARS-CoV-2 Dynamics with Imperfect Vaccine
    (Hindawi, 2022-04) Faniran, Taye Samuel; Ali, Aatif; Al-Hazmi, Nawal E.; Asamoah, Joshua Kiddy K.; Nofal, Taher A.; Adewole, Matthew O.; 0000-0002-7066-246X
    )e occurrence of a new strain of SARS-CoV-2 cannot be ruled out. )erefore, this study seeks to investigate the possible effects of a hypothetical imperfect anti-COVID-19 vaccine on the control of not only the first variant of SARS-CoV-2 but also the second (new) variant of SARS-CoV-2. We further examine the rates and a, escape of quarantined infectious individuals from isolation centers. )e control Rc and basic reproduction numbers R0 are computed which gives assess to obtain asymptotic stability of disease-free equilibrium point globally and the existence of a unique persistent equilibrium solution. Numerical results reveal that people infected with the second strain who are vaccinated with an imperfect vaccine are under control but the prevalence of the second variant enhances the prevalence of the first variant. )us, discovering a vaccine that is effective (to a good extent) for the prevention of variant 2 (new variant) is necessary for the control of COVID-19. Numerical results also reveal that increase in the rate at which individuals infected with the first variant escape the isolation center gives rise to the population infected with the first variant and lowers the peak of the population infected with the second variant. )is is probably because individuals infected with the second variant appear to be more careful with their lives and get vaccinated more than individuals infected with the first variant.
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    Numerical investigation of forced convective MHD tangent hyperbolic nanofluid flow with heat source/sink across a permeable wedge
    (AIP Advances, 2024-05) Assiri, Taghreed A.; Bilal, Muhammad; Mahmoud, Emad E.; Ali, Aatif; Asamoah, Joshua Kiddy K.; Adnan; 0000-0002-7066-246X
    The combined effect of wedge angle and melting energy transfer on the tangent hyperbolic magnetohydrodynamics nanofluid flow across a permeable wedge is numerically evaluated. Electronic gadgets produce an excessive amount of heat while in operation, so tangent hyperbolic nanofluid (THNF) is frequently used to cool them. THNF has the potential to dissipate heat more efficiently, thereby lowering the possibility of excessive heat and malfunctioning components. The effects of thermal radiation and heat source/sink are also examined on the flow of THNF. The flow has been formulated in the form of PDEs, which are numerically computed through the MATLAB solver BVP4c. The numerical results of BVP4c are relatively compared to the published work for validity purposes. It has been detected that the results are accurate and reliable. Furthermore, from the graphical results, it has been perceived that the rising impact of the Weissenberg number accelerates the velocity and thermal profile. The effect of the power-law index parameter drops the fluid temperature, but enhances the velocity curve. The variation in the wedge angle boosts the shearing stress and energy propagation rate, whereas the increment of Wi declines both the energy transfer rate and skin friction.
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    Numerical Investigation of Fractional-Order Kawahara and Modified Kawahara Equations by a Semianalytical Method
    (Hindawi, 2022-02) Alhejaili, Weaam; Alhazmi, Sharifah E.; Nawaz, Rashid; Ali, Aatif; Asamoah, Joshua Kiddy K.; Zada, Laiq; 0000-0002-7066-246X
    In this work, the optimal homotopy asymptotic method (OHAM) has been used to find approximate solutions to the nonlinear fractional-order Kawahara and modified Kawahara equations. The method convergence is controlled by a flexible function known as the auxiliary function. The values of the unknown arbitrary constants in the auxiliary function are computed using the Caputo derivative fractional-order and the well-known approach of least squares. Fractional-order derivatives are taken in the Caputo sense with numerical values in the closed interval ½0, 1 . The suggested method is directly applied to fractional-order Kawahara and modified Kawahara equations, with no need for small or large parameter assumptions. The numerical results obtained by the proposed method are compared to the new iterative method (NIM). Results reveal that the proposed method converges faster to the exact solution than other methods in the literature
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    Numerical Investigation of Fractional-Order Kawahara and Modified Kawahara Equations by a Semianalytical Method
    (Hindawi, 2022-02) Alhejaili, Weaam; Alhazmi, Sharifah E.; Nawaz, Rashid; Ali, Aatif; Asamoah, Joshua Kiddy K.; Zada, Laiq; 0000-0002-7066-246X
    In this work, the optimal homotopy asymptotic method (OHAM) has been used to find approximate solutions to the nonlinear fractional-order Kawahara and modified Kawahara equations. The method convergence is controlled by a flexible function known as the auxiliary function. The values of the unknown arbitrary constants in the auxiliary function are computed using the Caputo derivative fractional-order and the well-known approach of least squares. Fractional-order derivatives are taken in the Caputo sense with numerical values in the closed interval ½0, 1 . The suggested method is directly applied to fractional-order Kawahara and modified Kawahara equations, with no need for small or large parameter assumptions. The numerical results obtained by the proposed method are compared to the new iterative method (NIM). Results reveal that the proposed method converges faster to the exact solution than other methods in the literature.
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    Numerical Investigation of Fractional-Order Kawahara and Modified Kawahara Equations by a Semianalytical Method
    (Hindawi, 2022-02) Alhejaili, Weaam; Alhazmi, Sharifah E.; Nawaz, Rashid; Ali, Aatif; Asamoah, Joshua Kiddy K.; Zada, Laiq; 0000-0002-7066-246X
    In this work, the optimal homotopy asymptotic method (OHAM) has been used to find approximate solutions to the nonlinear fractional-order Kawahara and modified Kawahara equations. The method convergence is controlled by a flexible function known as the auxiliary function. The values of the unknown arbitrary constants in the auxiliary function are computed using the Caputo derivative fractional-order and the well-known approach of least squares. Fractional-order derivatives are taken in the Caputo sense with numerical values in the closed interval ½0, 1 . The suggested method is directly applied to fractional-order Kawahara and modified Kawahara equations, with no need for small or large parameter assumptions. The numerical results obtained by the proposed method are compared to the new iterative method (NIM). Results reveal that the proposed method converges faster to the exact solution than other methods in the literature.
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    Rheological Model for Generalized Energy and Mass Transfer through Hybrid Nanofluid Flow Comprised of Magnetized Cobalt Ferrite Nanoparticles
    (Hindawi, 2022-04) Al-Mubaddel, Fahad S.; Allehiany, F. M.; Nofal, Taher A.; Alam, Mohammad Mahtab; Ali, Aatif; Asamoah, Joshua Kiddy K.; 0000-0002-7066-246X
    The goal of the current research is to evaluate a 3D stagnation point flow of Darcy Forchheimer’s hybrid nanofluid (NF) through a heated wavy flexible cylinder under the influence of slip conditions and varying thickness. A numerical model is developed for the purpose to magnify the energy and mass transmission rate and maximize the efficiency and performance of thermal energy conduction for a variety of commercial and biological purposes through methanol-based hybrid NF flow consisting of cobalt ferrite and copper nanoparticles. Due to their inclusive range of applications, copper and cobalt iron oxide nanoparticles are gaining a lot of attention in medical and technical research. The model has been articulated in the form of a set of PDEs, which are reduced by the resemblance substitutions to the system of ODEs. The obtained 1st-order differential equations are further processed by the computational strategy PCM. For the sake of accuracy and credibility, the values are verified with the bvp4c package. The findings are physically exhibited and analyzed. It has been observed that the induced magnetic field lessens with the upshot of the magnetic term and enhances under the action of magnetic Prandtl number M. The energy profile declines due to the variation of thermal jump constraint and boosts with the absorption and generation term.