Related Experiment Video
Updated: Sep 13, 2025

Evolution of Staircase Structures in Diffusive Convection
Published on: September 5, 2018
Dynamical analysis and solutions of coupled 4D fractional differential systems with applications to predictability
Xiaoyu Chen1, Hongtao Fan1, Yajing Li1
1College of Science, Northwest A&F University, Yangling 712100, Shanxi, People's Republic of China.
Abstract:
For coupled two-dimensional fractional differential systems, a new two-step fractional-order Runge-Kutta method is proposed in this paper, which can reach a convergence order of 2α, with α being the fractional-order number. Further, we extend the two-step fractional-order Runge-Kutta algorithm to any coupled n-dimensional fractional differential system while maintaining convergence and consistency. To demonstrate the validity of the proposed method, numerical experiments are given for a four-dimensional fractional Lorenz system, and the dynamics of the four-dimensional fractional Lorenz system is analyzed using Lyapunov characteristic exponents, bifurcation diagrams, chaos diagrams, and C0 complexity. The results demonstrate that the system exhibits a diverse dynamical behavior and a broader range of fractional orders [0.43, 1] is accessible to the periodic orbit at the same parameter, compared to previous findings [He et al., Math. Methods Appl. Sci. 39, 2965-2973 (2016)]. Finally, we use global attractor radius and attractor radius to investigate the predictability of the coupled fractional-order ocean-atmosphere system [Li et al., Clim. Dyn. 51, 2359-2374 (2018)]. The results show that both global attractor radius and attractor radius decrease with decreasing fractional order, and the smaller the initial perturbation, the longer it takes to reach the attractor radius, but the attractor radius to the global attractor radius is not significantly correlated with the initial perturbation. These findings suggest that the predictability of the coupled fractional ocean-atmosphere system is limited by the presence of long-range memory effects captured in the fractional-order differential equations. By offering quantitative assessments of predictability, these approaches enhance our understanding of the intricate dynamics within such systems and can support informed decision-making in addressing and mitigating the effects of climate change on the global atmosphere and oceans.
More Related Videos
13:07Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression
Published on: January 15, 2022
13:27Exploring the Effects of Atmospheric Forcings on Evaporation: Experimental Integration of the Atmospheric Boundary Layer and Shallow Subsurface
Published on: June 8, 2015
Related Concept Videos
Linear Approximation in Time Domain
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
Differential Form of Maxwell's Equations
Types of Damping
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Navier–Stokes Equations
One-Degree-of-Freedom System
A one-degree-of-freedom system is defined by an independent variable that determines its state and behavior. One example of a one-degree-of-freedom system is a simple harmonic oscillator, such as a...