Shape and diffusion instabilities of two non-spherical gas bubbles under ultrasonic conditions

Ultrasonic cavitation involves dynamic oscillation processes induced by small bubbles in a liquid under the influence of ultrasonic waves. This study focuses on the investigation of shape and diffusion instabilities of two bubbles formed during cavitation. The derived equations for two non-spherical gas bubbles, based on perturbation theory and the Bernoulli equation, enable the analysis of their shape instability. Numerical simulations, utilizing the modified Keller–Miksis equation,are performed to examine the shape and diffusion instabilities. Three types of shape instabilities, namely, Rayleigh–Taylor,Rebound, and parametric instabilities, are observed. The results highlight the influence of initial radius, distance, and perturbation parameter on the shape and diffusion instabilities, as evidenced by the R_0–P_a phase diagram and the variation pattern of the equilibrium curve. This research contributes to the understanding of multiple bubble instability characteristics, which has important theoretical implications for future research in the field. Specifically, it underscores the significance of initial bubble parameters, driving pressure, and relative gas concentration in determining the shape and diffusive equilibrium instabilities of non-spherical bubbles.

Pattern dynamics of network-organized system with cross-diffusion

Cross-diffusion is a ubiquitous phenomenon in complex networks, but it is often neglected in the study of reaction–diffusion networks. In fact, network connections are often random. In this paper, we investigate pattern dynamics of random networks with cross-diffusion by using the method of network analysis and obtain a condition under which the network loses stability and Turing bifurcation occurs. In addition, we also derive the amplitude equation for the network and prove the stability of the amplitude equation which is also an effective tool to investigate pattern dynamics of the random network with cross diffusion. In the meantime, the pattern formation consistently matches the stability of the system and the amplitude equation is verified by simulations. A novel approach to the investigation of specific real systems was presented in this paper. Finally, the example and simulation used in this paper validate our theoretical results.

Effect of random movement and cooperative hunting in the prey-predator system:A dynamical approach

Self-diffusion prerequisite is obtained as the spreading approach of biological populations.Cooperative hunting is a common behavior in predator populations that promotes predation and the coexistence of the prey-predator system.On the other side,the Allee effect among prey may cause the system to become unstable.In this paper,a difusive prey predator system with cooperative hunting and the weak Allee effect in prey populations is discussed.The linear stability and Hopf-bifurcation analysis had been used to examine the system's stability.From the spatial stability of the system,the conditions for Turing instability have been derived.The multiple-scale analysis has been used to derive the amplitude equations of the system.The stability analysis of these amplitude equations leads to the formation of Turing patterns.Finally,numerical simulations are used to analyze spatial patterns forming in 1-D and 2-D.The studies indicate that the model can generate a complex pattern structure and that self-diffusion has a drastic impacton species distribution.

Turing instability in a diffusive SIS epidemiological model

Modeling and simulation of infectious diseases help to predict the likely outcome of an epidemic. In this paper, a spatial susceptible-infective-susceptible （SIS） type of epidemiological disease model with self- and cross-diffusion are investigated. We study the effect of diffusion on the stability of the endemic equilibrium with disease-induced mortality and nonlinear incidence rate, In the absence of diffusion the stationary solution stays stable but becomes unstable with respect to diffusion and that Turing instability takes place. We show that a standard （self-diffusion） system may be either stable or unstable, cross-diffusion response can stabilize an unstable standard system or decrease a ＂ihlring space （the space which the emergence of spatial patterns is holding） compared to the ~lhlring space with self-diffusion, i.e. the cross-diffusion response is an important factor that should not be ignored when pattern emerges. Numerical simulations are provided to illustrate and extend the theoretical results.