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The two-dimensional radiating mixed convective flowing in a nanofluid, together with the non-Darcy penetrable material over an inclined wavy surface is examined. The conversion from the wavy surface into a smooth surface is performed, via coordinate transformation. The early stage of a mathematical formulation is converted into a group of ordinary differential equations (ODEs), where these ODEs are resolved applying the bvp4c coding via MATLAB. The comparison of the current findings with the previously published studies proved that the current results are quite consistent, and the numerical bvp4c method is acceptable. The influence of relevant factors on nondimensional fluid flowing areas, heat and mass transmission rates is investigated and listed in the table as shown. The wavy surface and tendency angle have an effect of reducing the temperature and concentration in assisting flow. Additionally, the opposite direction is noted for opposing flow occurrences. [ABSTRACT FROM AUTHOR]

In this paper, we study a fourth-order nonlinear symmetric regularized long-wave equation which arises in several physical applications including ion sound waves in plasma. This model also describes nonlinear ion-acoustic and space-charge waves. Lie group analysis and the tanh-coth method is utilized for the construction of solitary wave solutions to the equation. Based on each symmetry, we reduce the considered partial differential equation into different ordinary differential equations. The obtained equations are solved and new solitary wave patterns are reported. To understand the physical interpretation, some solitary wave structures are exhibited graphically. Also, by using the multiplier approach, we constructed the local conservation laws of the considered equation. [ABSTRACT FROM AUTHOR]

With the effect of discrete time delay in deliberation, we propose and analyze a conceptual mathematical model for the tumor-immune interaction. The proposed model is delineated by a system of three coupled non-linear ordinary differential equations (ODEs), namely tumor cells, effector cells and cytokine Interleukin-2 (IL-2). Though simple, the model can have complicated dynamical behaviors. We have discussed the qualitative properties of the mathematical model including existence and positivity of the solutions. We find out tumor-free singular point and interior steady states in our mathematical model. We have studied the local stability analysis of the biological feasible steady states in both of the delayed and non-delayed system. By using transversality condition, we have analyzed Hopf bifurcation by using time delay τ as a bifurcation parameter. We have estimated the length of time delay parameter applying Laplace transformation for preserving the stability of period-1 limit cycle that provides the idea about the mode of action in controlling oscillations in the growth of tumor cells. We performed numerical simulations and explored their biological implications to validate our theoretical analysis. We have also drawn bifurcation diagram of delayed model with reference to the intrinsic growth rate α of tumor cell, deactivation rate d 1 of tumor cell, activation rate c 2 of effector cell and death rate d 2 of effector cell. Theoretical and numerical analysis show that in presence of IL-2 the effector cells can cause the tumor cell population to regress. [ABSTRACT FROM AUTHOR]

For obtaining numerical solutions of the system of ordinary differential equations (ODEs) of third order, a new numerical technique is proposed by using operational matrices of Bernstein polynomials. These operational matrices can be utilized to solve different problems of integral and differential equations. The System of third-order ODEs occur in various physical and engineering models. In this paper, an iterative algorithm is constructed by using operational matrices of Bernstein polynomials for solving the system of third order ODEs. The proposed technique provides a numerical solution by discretizing the system to a system of algebraic equations which can be solved directly. The method will be verified by using appropriate examples which are arising in Physics and some Engineering problems. The comparison of approximate and exact solution of the given examples is demonstrated with the help of tables and graphs. [ABSTRACT FROM AUTHOR]

In this paper, a generalized (3 + 1)-dimensional nonlinear evolution equation (NLEE) is proposed and examined. This investigated NLEE is undoubtedly a robust mathematical model in real-world applications. Because several essential and commonly used relative differential equations can be obtained by considering some specific choices in the given general form. In this way, many new solitary wave solutions are formally obtained via the generalized exponential rational function method (GERFM). The general idea of solving the equation in this method is to use an appropriate variable change that can transform the given partial differential equation into an ordinary differential equation. We then provide a general symbolic form for the solutions and determine the solution of the equation. To understand the dynamic concepts of numerical solutions better, several numerical simulations are included. The dependence of the properties of the solutions on the selection of the parameters in the equation can be examined in the results. Finally, the results verify the efficiency and reliability of the considered method. [ABSTRACT FROM AUTHOR]

The major purpose of this article is to exploit the strength of the Intelligent Back-propagated Neural Networks of Levenberg Marquardt Technique (IBNN-LMT) to study three-dimensional (3D) squeezed flow model of carbon nanotubes (SFM-CNTs) relying on water in a revolving network with a rigid ground wall. The impact of magnetohydrodynamic (MHD) and thermal radiation has been investigated. Similarity transformation is utilized to convert partial differential equations (PDEs) into ordinary differential equations (ODEs). For numerous nanofluids constructed of SWCNT and MWCNT, the influence of each parameter on velocity, temperature, Bejan number, and entropy production is estimated. The overall entropy optimization was also computed. The major outcome of this research is to examine the impacts of flowing parameters on CNTs when squeezing parameters are changed. Moreover, the estimated solution is evaluated for designed SFM-CNTs by using a testing method and comparing it to a standard solution that has been backed up by performance studies based on MSE convergence, error histogram, and regression studies. The velocity profile f (χ) along y-axis intensifies with the intensification in S , φ ,and A. Where Ω gives a dual performance with the increment in the function, as with the increase in M , f (χ) provides decreasing performance. The temperature function θ (χ) increase as the increment in S , Ec ,and Ec m and decrease with the increase in φ and R. The solution is accurate up to 4 to 10 decimal places which proves the worth and effectiveness of the proposed IBNN-LMT solver. [ABSTRACT FROM AUTHOR]

In present study, the nano-material flow of Ree-Eyring fluid model (NF-REFM) is examined by utilizing the technique of Levenberg Marquardt with backpropagated neural networks (TLM-BNNs). The flow is examined between two disks and the impacts of porosity and velocity slip are also analyzed. The partial differential equations (PDEs) representing the NF-REFM are transformed into system of ordinary differential equations (ODEs). Homotopy analysis method (HAM) is used to solve the ODEs and interpret the reference dataset for TLM-BNN. This dataset helps to compute the approximated solution of NF-REFM in MATLAB software. Regression analysis, Error histogram and MSE results, validates the performance of TLM-BNN. The flow effects on the velocity profile, temperature distribution and concentration profile are examined for different parameters. The results for entropy generation, Bejan number, Nusselt number, Sherwood number and skin friction coefficient are also discussed in this article. [ABSTRACT FROM AUTHOR]

In this article we observed the Darcy-Brinkman flow model in the existence of frictional heating and porous dissipation (DBFM) over a stretching sheet by employ the neural network backpropagated with Bayesian regularization technique (NNBP-BRT). NNBP-BRT has the ability to exhibit relatively complex relationships, which implies it can be used in numerical investigations to construct a robust framework. Bayesian regularization is a mathematical procedure that converts a nonlinear regression into a "well-posed" statistical equation in the ridge regression methodology. Partial differential equations (PDEs) are converted into ordinary differential equations (ODEs) by employ appropriate similarity transformation. The resulting system of nonlinear equations was numerically solved using the fourth-order Runge–Kutta approach with velocity and thermal slip assumptions. Here we utilized ND-Solve method to solve the ordinary differential equations and clarify the reference dataset for NNBP-BRT for different scenarios of DBFM by varying parameters. To compute the approximated solutions and error analysis plots of different scenarios of DBFM the reference dataset is utilized in MATLAB software using the command 'nftool'. The performance of NNBP-BRT is observed and obtained by observing the regression curves, histograms and MSE outcomes. The solution of DBFM is obtained by testing, validation and training process. Figures depict velocity profiles and temperature profiles for different variations of parameters. The effect of different flow parameters Brinkmann parameter, porosity parameter, Prandtl number and Eckert number on velocity profile and temperature profile are discussed and the results are presented graphically. [ABSTRACT FROM AUTHOR]