Fractional Reaction-diffusion Equations Research Articles

On the generalized time fractional reaction–diffusion equation: Lie symmetries, exact solutions and conservation laws

In this paper, Lie symmetry analysis method is applied to the generalized time fractional reaction–diffusion equation. We obtain a conditional symmetric group and some conservation laws of the governing equation. The obtained Lie symmetries are used to reduce the studied fractional partial differential equation to some fractional ordinary differential equations with Riemann–Liouville fractional derivative or Erdélyi-Kober fractional derivative. Furthermore, we obtained asymptotic stable solutions and convergent power series solutions for the reduced equations. The dynamic behavior of these exact solutions is presented graphically.

Jacobi spectral method for the fractional reaction–diffusion equation arising in ecology

In this paper, we study fractional reaction–diffusion equation using Jacobi spectral method. Reaction–diffusion equation is used as model for spatial effects in ecology. In this method, the reaction–diffusion equation is changed to the systems of equations. Convergence analysis for the proposed spectral method is established from theoretical as well as numerical point of view. Some numerical examples are solved using proposed numerical method showing the feasibility of the method. The efficiency of the spectral method is shown by listing CPU time of computation.

An efficient numerical method based on Chelyshkov operation matrix for solving a type of time-space fractional reaction diffusion equation

An efficient numerical method based on Chelyshkov operation matrix for solving a type of time-space fractional reaction diffusion equation

Random dynamics for a stochastic nonlocal reaction-diffusion equation with an energy functional

<abstract><p>In this paper, the asymptotic behavior of solutions to a fractional stochastic nonlocal reaction-diffusion equation with polynomial drift terms of arbitrary order in an unbounded domain was analysed. First, the stochastic equation was transformed into a random one by using a stationary change of variable. Then, we proved the existence and uniqueness of solutions for the random problem based on pathwise uniform estimates as well as the energy method. Finally, the existence of a unique pullback attractor for the random dynamical system generated by the transformed equation is shown.</p></abstract>

Continuous data assimilation and feedback control of fractional reaction-diffusion equations

Continuous data assimilation and feedback control of fractional reaction-diffusion equations

Limiting dynamics for fractional stochastic reaction-diffusion equations driven by a Wong–Zakai approximation process on Rn

Limiting dynamics for fractional stochastic reaction-diffusion equations driven by a Wong–Zakai approximation process on Rn

Fractional Diffusion Equation under Singular and Non-Singular Kernel and Its Stability

The fractional reaction–diffusion equation has been used in many real-world applications in fields such as physics, biology, and chemistry. Motivated by the huge application of fractional reaction–diffusion, we propose a numerical scheme to solve the fractional reaction–diffusion equation under different kernels. Our method can be particularly employed for singular and non-singular kernels, such as the Riemann–Liouville, Caputo, Fabrizio–Caputo, and Atangana–Baleanu operators. Moreover, we obtained general inequalities that guarantee that the stability condition depends explicitly on the kernel. As an implementation of the method, we numerically solved the diffusion equation under the power-law and exponential kernels. For the power-law kernel, we solved by considering fractional time, space, and both operators. In another example, we considered the exponential kernel acting on the time derivative and compared the numerical results with the analytical ones. Our results showed that the numerical procedure developed in this work can be employed to solve fractional differential equations considering different kernels.

Analytical solution of the space-time fractional reaction-diffusion equation with variable coefficients

In this paper, we solve the problem of an inhomogeneous one-dimensional fractional differential reaction-diffusion equation with variable coefficients (1.1)-(1.2) by the method of separation of variables (the Fourier method). The Caputo derivative and the Riemann-Liouville derivative are considered in the time and space directions, respectively. We prove that the obtained solution of the boundary-value problem satisfies the given boundary conditions. We discuss the convergence of the series defining the proposed solution.

Highly Efficient Numerical Algorithm for Nonlinear Space Variable-Order Fractional Reaction–Diffusion Models

In this paper, we present a new highly efficient numerical algorithm for nonlinear variable-order space fractional reaction–diffusion equations. The algorithm is based on a new method developed by using the Gaussian quadrature pole rational approximation. A splitting technique is used to address the issues related to computational efficiency and the stability of the method. Two linear systems need to be solved using the same real-valued discretization matrix. The stability and convergence of the method are discussed analytically and demonstrated through numerical experiments by solving test problems from the literature. The variable-order diffusion effects on the solution profiles are illustrated through graphs. Finally, numerical experiments demonstrate the superiority of the presented method in terms of computational efficiency, accuracy, and reliability.

An iterative approach for solving fractional order Cauchy reaction-diffusion equations

An iterative approach for solving fractional order Cauchy reaction-diffusion equations

Large deviations of fractional stochastic equations with non-Lipschitz drift and multiplicative noise on unbounded domains

This paper is concerned with the large deviation principle of the non-local fractional stochastic reaction-diffusion equation with a polynomial drift of arbitrary degree driven by multiplicative noise defined on unbounded domains. We first prove the strong convergence of the solutions of a control equation with respect to the weak topology of controls, and then show the convergence in distribution of the solutions of the stochastic equation when the noise intensity approaches zero. We finally establish the large deviations of the stochastic equation by the weak convergence method. The main difficulty of the paper is caused by the non-compactness of Sobolev embeddings on unbounded domains, and the idea of uniform tail-ends estimates is employed to circumvent the obstacle in order to obtain the tightness of distribution laws of the stochastic equation and the precompactness of the control equation.

On the soliton solutions to the density-dependent space time fractional reaction–diffusion equation with conformable and M-truncated derivatives

On the soliton solutions to the density-dependent space time fractional reaction–diffusion equation with conformable and M-truncated derivatives

On Finite-Time Blow-Up Problem for Nonlinear Fractional Reaction Diffusion Equation: Analytical Results and Numerical Simulations

The study of the blow-up phenomenon for fractional reaction–diffusion problems is generally deemed of great importance in dealing with several situations that impact our daily lives, and it is applied in many areas such as finance and economics. In this article, we expand on some previous blow-up results for the explicit values and numerical simulation of finite-time blow-up solutions for a semilinear fractional partial differential problem involving a positive power of the solution. We show the behavior solution of the fractional problem, and the numerical solution of the finite-time blow-up solution is also considered. Finally, some illustrative examples and comparisons with the classical problem with integer order are presented, and the validity of the results is demonstrated.

Comparative analysis of three memory selection methods for time integration of Fractional Reaction-Diffusion Equations

By discretising in space, a non-linear time fractional reaction-diffusion equations (TFRDEs) can be converted into a system of time-fractional differential equations (TFDEs). The full memory method (FMM) and short memory method (SMM) are well-established memory selection methods used in the time integration of TFDEs. The main drawbacks of FMM and SMM are higher computational cost and uncontrollable error respectively. The only way to increase the accuracy of SMM is by increasing short memory length which causes an increase in computational cost. Especially when we apply these two methods to integrate TFRDEs, we have to solve a large system of TFDEs. Therefore, the drawbacks of these two methods affect seriously, when these are applied to solve TFRDEs. This paper aims to investigate the accuracy and efficiency of the memory selection method, Exponentially Decreasing Random Memory Method (EDRMM), and compare it with FMM and SMM when these methods apply to integrate TFRDEs. Based on these three memory selection methods, three semi-implicit numerical schemes namely semiimplicit scheme with full memory method (SI-FMM), semi-implicit scheme with short memory method (SI-SMM), and semi-implicit scheme with exponentially decreasing random memory method (SI-EDRMM)) are proposed and the accuracy and CPU time (computational time (CT)) of these three numerical schemes are compared. To do this comparison, these three numerical schemes are applied to four TFRDEs whose exact solutions are known. Numerical experiments confirm that the accuracy and efficiency of the SI-EDRMM are better than that of SI-SMM and the efficiency of SI-EDRMM is higher than that of SI-FMM. Therefore, EDRMM is better than SMM and FMM for the integration of TFRDEs.

A hybrid approach for piecewise fractional reaction–diffusion equations

In this paper, the Caputo and Atangana–Baleanu fractional derivatives are handled to introduce a type of piecewise fractional derivative. More precisely, a linear combination of the Caputo and Atangana–Baleanu fractional derivatives are considered in each sub-interval to define this fractional derivative. It is employed to generate another form of nonlinear reaction–diffusion equations. The orthonormal Legendre polynomials together with the orthonormal piecewise Legendre functions are used to make a hybrid algorithm for this new problem. In this way, an explicit formula for computing the piecewise fractional differentiation of the stated piecewise basis functions is obtained and applied in generating the method. The applicability and validity of the adopted procedure are examined through three examples.

Interpolated Coefficient Mixed Finite Elements for Semilinear Time Fractional Diffusion Equations

In this paper, we consider a fully discrete interpolated coefficient mixed finite element method for semilinear time fractional reaction–diffusion equations. The classic L1 scheme based on graded meshes and new mixed finite element based on triangulation is used for the temporal and spatial discretization, respectively. The interpolation coefficient technique is used to deal with the semilinear term, and the discrete nonlinear system is solved by a Newton-like iterative method. Stability and convergence results for both the original variable and its flux are derived. Numerical experiments confirm our theoretical analysis.

High‐order schemes and their error analysis for generalized variable coefficients fractional reaction–diffusion equations

In this manuscript, we develop and analyze two high‐order schemes, CFD and PQS , for generalized variable coefficients fractional reaction–diffusion equations. The generalized fractional derivative is characterized by a weight function and a scale function. We approximate it using generalized Alikhanov formula ( ) of order , where denotes the order of the generalized fractional derivative. Moreover, for spatial discretization, we use a compact operator in CFD scheme and parametric quintic splines in PQS scheme. The stability and convergence analysis of both schemes are demonstrated thoroughly using the discrete energy method in the ‐norm. It is shown that the convergence orders of the CFD and PQS schemes are and , respectively, where and represent the mesh spacing in the time direction and is the mesh spacing in the space direction. In addition, numerical results are obtained for three test problems to validate the theory and demonstrate the efficiency and superiority of the proposed schemes.

To study the effect of ER flux with buffer on the neuronal calcium.

Calcium signaling is decisive for cellular functions. This calcium random walk stipulates neuronal functions. Calcium concentration could provoke gene transcription, apoptosis, neuronal plasticity, etc. A malformation in calcium could change the neuron's intracellular behavior. Calcium concentration balancing is a complex cellular mechanism. This occurrence can be handled with the Caputo fractional reaction-diffusion equation. In this mathematical modeling, we have included the STIM-Orai mechanism and Endoplasmic Reticulum (ER) flux, Inositol Triphosphate Receptor (IPR), SERCA, plasma membrane flux, voltage-gated calcium entry, and different buffer interactions. A hybrid integral transform and Green's function approach were taken to solve the initial boundary problem. A closed-form solution of a Mittag-Leffler family function plotted using MATLAB software. Different parameters impact changes in the spatiotemporal behavior of the calcium concentration. Specific roles of organelles involved in Alzheimer's disease-affected neurons are computed. Ethylene glycol tetraacetic acid (EGTA), 1,2-bis(o-aminophenoxy)ethane N,N,N,N-tetraacetic acid (BAPTA), and S100B protein effects are also observed. In all simulations, we can say S100B and the STIM-Orai effect cannot be neglected. This model lights up the different approaches for calcium signaling pathway simulation. As a consequence, we determine that a generalized reaction-diffusion approach is a better fit realistic model.

A fourth order accurate numerical method for non-linear time fractional reaction–diffusion equation on a bounded domain

In the present work, a high-order numerical scheme is proposed and analyzed to solve the non-linear time fractional reaction–diffusion equation (RDE) of order α∈(0,1). The numerical scheme consists of a time-stepping cubic approximation for the time fractional derivative and a compact finite difference scheme to approximate the spatial derivative. After applying these approximations to time fractional RDE, we get a non-linear system of equations. An iterative algorithm is formulated to solve the obtained nonlinear discrete system. We analyze the unique solvability of the proposed compact finite difference scheme and discuss the stability using von Neumann analysis. Further, we prove that the scheme is convergent in the Euclidean norm with the convergence order 4−α in the temporal direction and 4 in the spatial direction using matrix analysis. Finally, the numerical experimentation is performed to demonstrate the authenticity of the proposed numerical scheme.

Glioblastoma multiforme growth prediction using a Proliferation-Invasion model based on nonlinear time-fractional 2D diffusion equation

The glioblastoma multiforme (GBM) is the fast-growing and aggressive type of tumor of the brain or spinal cord that is associated with high morbidity and mortality. Therefore, accurate knowledge of the tumor growth process in different time intervals seems necessary to adopt optimal treatment methods. In this study, with a combination of available early stages imaging data and using image processing methods, a time fractional reaction–diffusion equation based on the moving least squares method was implemented for predicting the growth of the GBM tumor model implemented in the mouse brain. The obtained results demonstrate that the Proliferation-Invasion model implemented by a time fractional form shows more agreement with the experimental results. As a result, using a fractional derivative of order α=0.9 results in the lowest prediction error of the tumor surface (less than 1%). In addition, to reducing the cost and side effects of theranostic methods, the presented model will have the possibility to consider the effects of therapeutic factors, such as hyperthermia, radiography, and surgery, on tumor growth. The ability to use the patient’s characteristics in diagnostic and treatment considerations and the development of personalized medicine can also be considered one of the capabilities of the presented model.