International Journal of Modeling, Simulation, and Scientific Computing

In this paper, we first construct an efficient scheme for nonlinear Caputo fractional differential equations with the initial value and the fractional degree $0<\alpha <1$. Then, the unconditional stability and the superlinear convergence with the order $1+\alpha$ of the proposed scheme are strictly proved and discussed. Due to the nonlocal property of fractional operators, the new scheme is time-consuming for long-time simulations. Thus, a fast implement of the proposed scheme is presented based on the sum-of-exponentials (SOE) approximation for the kernel $t^{\alpha -1}$ on the interval $[h,T]$ in the Riemann–Liouville integral, where $h$ is the stepsize. Some numerical experiments are provided to support the theoretical results of the new scheme and demonstrate the computational performance of its fast implement.

In this study, nonhomogeneous differential equation of the second order is considered, which contains fractional derivative (Bagley–Torvik equation), where the derivative order ranges within 1 and 2. This equation is applied in mechanics of oscillation processes. To study the equation, we use the Laplace transform, which allows us to obtain an image of the solution in an explicit form. Two typical kinds of functions of the right-hand side of the equation are considered. Numerical solutions are constructed for each of them. The solutions obtained are compared with experimental information on polymer concrete samples. The comparison allows for the conclusion about the adequacy of the numerical and analytical solutions to the nonhomogeneous Bagley–Torvik equation.

Bearing is among the most widely used components in rotating machinery. Its failure can cause serious economic losses or even disasters. However, the fault-induced impulses are weak especially for the early failure. As to the bearing fault diagnosis, a novel bearing diagnosis method based on scale-varying fractional-order stochastic resonance (SFrSR) is proposed. Signal-to-noise ratio of the SFrSR output is regarded as the criterion for evaluating the stochastic resonance (SR) output. In the proposed method, by selecting the proper parameters (integration step $H$, amplitude gain $K$ and fractional-order $\alpha$) of SFrSR, the weak fault-induced impulses, the noise and the potential can be matched with each other. An optimal fractional-order dynamic system can be generated. To verify the proposed SFrSR, numerical tests and application verification are conducted in comparison with the traditional scale-varying first-order SR (SFiSR). The results prove that the parameters $H,K$ and $\alpha$ affect the SFrSR effect seriously and the proposed SFrSR can enhance the weak signal while suppressing the noise. The SFrSR is more effective for bearing fault diagnosis than SFiSR.

In this paper, we give a formula for computing the eigenvalues of the Dirichlet problem for a differential equation of second-order with fractional derivatives in the lower terms. We obtained this formula using the perturbation theory for linear operators. Using this formula we can write out the system of eigenvalues for the problem under consideration.

In this paper, we consider the finite element method for two-dimensional nonlinear modified time-fractional fourth-order diffusion equation. In order to avoid using higher order elements, we introduce an intermediate variable $\sigma =\mathrm{\Delta }u$ and translate the fourth-order derivative of the original problem into a second-order coupled system. We discretize the fractional time derivative terms by using the $L1$-approximation and discretize the first-order time derivative term by using the second-order backward differentiation formula. In the fully discrete scheme, we implement the finite element method for the spatial approximation. Unconditional stability of the fully discrete scheme is proven and its optimal convergence order is obtained. Numerical experiments are carried out to demonstrate our theoretical analysis.

Numerical approximation for a linearized time fractional KdV equation with initial singularity using $L1$ scheme on graded mesh is considered. It is proved that the $L1$ scheme can attain order $2-\alpha$ convergence rate with appropriate choice of the grading parameter, where $\alpha$ $(0<\alpha <1)$ is the order of temporal Caputo fractional derivative. A fully discrete spectral scheme is constructed combing a Petrov–Galerkin spectral method for the spatial discretization, and its stability and convergence are theoretically proved. Some numerical results are provided to verify the theoretical analysis and demonstrated the sharpness of the error analysis.

In this paper, time-fractional Sharma–Tasso–Olver (STO) equation has been solved numerically through the Petrov–Galerkin approach utilizing a quintic B-spline function as the test function and a linear hat function as the trial function. The Petrov–Galerkin technique is effectively implemented to the fractional STO equation for acquiring the approximate solution numerically. The numerical outcomes are observed in adequate compatibility with those obtained from variational iteration method (VIM) and exact solutions. For fractional order, the numerical outcomes of fractional Sharma–Tasso–Olver equations are also compared with those obtained by variational iteration method (VIM) in Song et al. [Song L., Wang Q., Zhang H., Rational approximation solution of the fractional Sharma–Tasso–Olver equation, J. Comput. Appl. Math. 224:210–218, 2009]. Numerical experiments exhibit the accuracy and efficiency of the approach in order to solve nonlinear fractional STO equation.

In this paper, we have proposed the efficient numerical methods to solve a tumor-obesity model which involves two types of the fractional operators namely Caputo and Caputo-Fabrizio (CF). Stability and convergence of the proposed schemes using Caputo and CF fractional operators are analyzed. Numerical simulations are carried out to investigate the effect of low and high caloric diet on tumor dynamics of the generalized models. We perform the numerical simulations of the tumor-obesity model for different fractional order by varying immune response rate to compare the dynamics of the Caputo and CF fractional operators.

The problem of Mittag–Leffler stabilization (MLS) is studied for a class of nonlinear non-integer order systems. The stabilizer is constructed by using the Lyapunov function and backstepping algorithm. The continuous controller is designed to ensure that the state of the nonlinear fractional-order closed-loop system converges to the equilibrium. Two simulation examples are given to illustrate the effectiveness of the method.

In the present paper, invariant subspace method has been extended for solving systems of multi-term fractional partial differential equations (FPDEs) involving both time and space fractional derivatives. Further, the method has also been employed for solving multi-term fractional PDEs in $(1+n)$ dimensions. A diverse set of examples is solved to illustrate the method.

Practical performances of controller design methods strongly depend on relevancy of identified models. Fractional order system models promise advantage of more accurate modeling of real systems. This study presents a discussion on utilization of two fundamental numerical solution methods of fractional calculus in identification problems of One Noninteger Order Plus Time Delay with one pole (NOPTD-I) models. The identification process is carried out by estimating parameters of a NOPTD-I type transfer function template so that the step response of the NOPTD-I model can sufficiently fit experimental step response data. In the study, step responses of NOPTD-I models are numerically calculated according to two fundamental methods, which are Mittag-Leffler (ML) function and Grunwald–Letnikov (GL) definition. Particle swarm optimization (PSO) algorithm is used to perform data fitting. Illustrative examples are presented to evaluate model parameter estimation performances of these two methods for synthetically generated noisy test data. An experimental study is conducted for modeling pitch rotor of TRMS to compare experimental performances.

Image super-resolution methods-based existing edge indicating operators — namely Gauss curvature, mean curvature and gradient — cannot effectively identify the edges, ramps and flat regions and suffer from the loss of fine textures. To address these issues, this paper presents a fractional anisotropic diffusion equation based on a new edge indicator, named fractional-order difference curvature, which can characterize the intensity variations in images. We introduce the frequency-domain definition for fractional-order derivative by the Fourier transform, which is easy to implement numerically. The new edge indicator is better than the existing edge indicating operators in distinguishing between ramps and edges and can better handle the fine textures. Comparative results for natural images validate that the proposed method can yield a visually pleasing result and better values of MSSIM and PSNR.