Reaction-diffusion Equations Research Articles

Speed selection for reaction diffusion equations in heterogeneous environments

Reaction-advection-diffusion equations, in periodic settings and with general type nonlinearities, admit a threshold known as the minimal speed of propagation. The minimal speed does not have an accessible formula when the nonlinearity is not of KPP type, for instance. The question becomes whether the minimal speed can be obtained through a linearization procedure or not. In this paper, we derive selection criteria for the minimal speed: a key feature of the nonlinear selection is unveiled. Moreover, we use upper/lower solution techniques in order to derive practical criteria determining the minimal speed in the presence of advection and a general type nonlinearity.

The role of convection in the existence of wavefronts for biased movements

We investigate a model, inspired by Johnston et al. (2017) to describe the movement of a biological population which consists of isolated and grouped organisms. We introduce biases in the movements and then obtain a scalar reaction–diffusion equation that includes a convective term as a consequence of the biases. We focus on the case the diffusivity makes the parabolic equation of forward–backward–forward type and the reaction term models a strong Allee effect, with the Allee parameter lying between the two internal zeros of the diffusion. In such a case, the unbiased equation (i.e., without convection) possesses no smooth traveling‐wave solutions; on the contrary, in the presence of convection, we show that traveling‐wave solutions do exist for some significant choices of the parameters. We also study the sign of their speeds, which provides information on the long term behavior of the population, namely, its survival or extinction.

Steady-state solutions for a reaction–diffusion equation with Robin boundary conditions: Application to the control of dengue vectors

AbstractIn this paper, we investigate an initial-boundary value problem of a reaction–diffusion equation in a bounded domain with a Robin boundary condition and introduce some particular parameters to consider the non-zero flux on the boundary. This problem arises in the study of mosquito populations under the intervention of the population replacement method, where the boundary condition takes into account the inflow and outflow of individuals through the boundary. Using phase plane analysis, the present paper studies the existence and properties of non-constant steady-state solutions depending on several parameters. Then, we prove some sufficient conditions for their stability. We show that the long-time efficiency of this control method depends strongly on the size of the treated zone and the migration rate. To illustrate these theoretical results, we provide some numerical simulations in the framework of mosquito population control.

Influence of physical interactions on spatiotemporal patterns.

Spatiotemporal patterns are often modeled using reaction-diffusion equations, which combine complex reactions between constituents with ideal diffusive motion. Such descriptions neglect physical interactions between constituents, which might affect resulting patterns. To overcome this, we study how physical interactions affect cyclic dominant reactions, like the seminal rock-paper-scissors game, which exhibits spiral waves for ideal diffusion. Generalizing diffusion to incorporate physical interactions, we find that weak interactions change the length- and time scales of spiral waves, consistent with a mapping to the complex Ginzburg-Landau equation. In contrast, strong repulsive interactions typically generate oscillating lattices, and strong attraction leads to an interplay of phase separation and chemical oscillations, like droplets co-locating with cores of spiral waves. Our work suggests that physical interactions are relevant for forming spatiotemporal patterns in nature, and it might shed light on how biodiversity is maintained in ecological settings.

Random attractors for a stochastic nonlocal delayed reaction–diffusion equation on a semi-infinite interval

Abstract The aim of this paper is to prove the existence and qualitative property of random attractors for a stochastic non-local delayed reaction–diffusion equation (SNDRDE) on a semi-infinite interval with a Dirichlet boundary condition at the finite end. This equation models the spatial–temporal evolution of the mature individuals for a two-stage species whose juvenile and adults both diffuse that lives on a semi-infinite domain and subject to random perturbations. By transforming the SNDRDE into a random evolution equation with delay, by means of a stationary conjugate transformation, we first establish the global existence and uniqueness of solutions to the equation, after which we show the solutions generate a random dynamical system. Then, we deduce uniform a priori estimates of the solutions and show the existence of bounded random absorbing sets. Subsequently, we prove the pullback asymptotic compactness of the random dynamical system generated by the SNDRDE with respect to the compact open topology, and hence obtain the existence of random attractors. At last, it is proved that the random attractor is an exponentially attracting stationary solution under appropriate conditions. The theoretical results are illustrated by application to the stochastic non-local delayed Nicholson’s blowfly equation.

Large deviations for the two-time-scale stochastic convective Brinkman-Forchheimer equations

The convective Brinkman-Forchheimer (CBF) equations are employed to characterize the motion of incompressible fluid in a saturated porous medium. This work investigates the small noise asymptotic of two-time-scale stochastic CBF equations in two and three dimensional bounded domains. More precisely, we establish a Wentzell-Freidlin type large deviation principle for stochastic partial differential equations that have slow and fast time-scales. The slow component is the stochastic CBF equations in two or three dimensions perturbed by a small multiplicative Gaussian noise, while the fast component is a stochastic reaction-diffusion equation with damping. The results are obtained by using a variational method (based on weak convergence approach) developed by Budhiraja and Dupuis, Khasminkii's time discretization approach and stopping time arguments. In particular, the findings from this study are also applicable to two-dimensional stochastic Navier-Stokes equations.

Exact solutions of hyperbolic reaction-diffusion equations in two dimensions

Exact solutions are constructed for a class of nonlinear hyperbolic reaction-diffusion equations in two-space dimensions. Reduction of variables and subsequent solutions follow from a special nonclassical symmetry that uncovers a conditionally integrable system, equivalent to the linear Helmholtz equation. The hyperbolicity is commonly associated with a speed limit due to a delay, \(\tau\), between gradients and fluxes. With lethal boundary conditions on a circular domain wherein a species population exhibits logistic growth of Fisher–KPP type with equal time lag, the critical domain size for avoidance of extinction does not depend on \(\tau\). A diminishing exact solution within a circular domain is also constructed, when the reaction represents a weak Allee effect of Huxley type. For a combustion reaction of Arrhenius type, the only known exact solution that is finite but unbounded is extended to allow for a positive \(\tau\). doi: 10.1017/S1446181123000093

The effect of grazing intensity on pattern dynamics of the vegetation system

The evolution of vegetation system in arid and semi-arid grazing areas is a complex dynamical system which depends not only on the rainfall, but also grazing intensity. Currently, most of the research focuses on the influence of rainfall, but the effects of grazing have not been fully understood. Simultaneously, the intraspecific competition delay widely exists in vegetation system. In this project, we develop a vegetation model coupled with the intraspecific competition delay, discuss the vegetation pattern caused by the combination of grazing intensity, rainfall and competition delay, by analyzing conditions of the occurrence of Turing instability. In particular, we propose a new theoretical method to deal with the Turing instability of delayed diffusion system when the system exists a zero eigenvalue and the corresponding transversity condition is not zero. Using the theory of dynamics, we can show: (i) a bistable region in which vegetation-existence and vegetation-extinction states coexist for relatively large grazing rate, in the corresponding ordinary differential system, while the vegetation-existence state is replaced by vegetation pattern state for non-delayed diffusion system, and the range of bistable region is extended as the increase of rainfall; (ii) spatial distribution structure and spatially mean density of vegetation patterns reveal that degradation of the vegetation becomes more and more obvious with the increase of grazing intensity; (iii) the bistable region corresponding to the delayed diffusion system is narrowed, and vegetation system undergoes regime shift from the pattern state to bare-soil state before reaching the threshold of grazing rate. Overall, this study yields a new theoretical perspective for pattern dynamics of delayed reaction–diffusion equation, and provides valuable insights into the study of vegetation system in grazing ecosystem.

Exponential stability of large-scale stochastic reaction-diffusion equations

In this paper, we consider a class of large-scale stochastic reaction-diffusion systems. To prove the exponential stability of the system, we introduce the corresponding isolated subsystems. We show that the exponential stability of the isolated systems implies the exponential stability of the large-scale stochastic reaction-diffusion system under some conditions. Furthermore, we discuss a special case where the large-scale stochastic reaction-diffusion system is described in a hierarchical form. In this case, we prove that the original system is exponentially stable if and only if the corresponding subsystems are exponentially stable.

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.

Inflammation propagation modeled as a reaction–diffusion wave

Inflammation is a physiological process aimed to protect the organism in various diseases and injuries. This work presents a generic inflammation model based on the reaction–diffusion equations for the concentrations of uninflamed cells, inflamed cells, immune cells and the inflammatory cytokines. The analysis of the model shows the existence of three different regimes of inflammation progression depending on the value of a parameter R called the inflammation number. If R>1, then inflammation propagates in cell culture or tissue as a reaction–diffusion wave due to diffusion of inflammatory cytokines produced by inflamed cells. If 0<R<1, then inflammation vanishes and the system converges to the stable inflammation-free equilibrium. Finally if R<0, inflammation also propagates as a reaction–diffusion wave, but the mechanism of propagation is different, it is determined by positive feedback between inflammation and immune response. From the biological point of view, these three regimes correspond to acute inflammation resolved due to the immune response, to the disappearance of inflammatory reaction, and to an auto-immune inflammatory reaction or cytokine storm. We focus on finding the wave speed and other characteristics of inflammation progression by analytical and numerical methods, in order to deduce a qualitative understanding of various inflammatory reactions.

The dose-related plateau effect of surviving fraction in normal tissue during the ultra-high-dose-rate radiotherapy

Objective. Ultra-high-dose-rate radiotherapy, referred to as FLASH therapy, has been demonstrated to reduce the damage of normal tissue as well as inhibiting tumor growth compared with conventional dose-rate radiotherapy. The transient hypoxia may be a vital explanation for sparing the normal tissue. The heterogeneity of oxygen distribution for different doses and dose rates in the different radiotherapy schemes are analyzed. With these results, the influence of doses and dose rates on cell survival are evaluated in this work. Approach. The two-dimensional reaction–diffusion equations are used to describe the heterogeneity of the oxygen distribution in capillaries and tissue. A modified linear quadratic model is employed to characterize the surviving fraction at different doses and dose rates. Main results. The reduction of the damage to the normal tissue can be observed if the doses exceeds a minimum dose threshold under the ultra-high-dose-rate radiation. Also, the surviving fraction exhibits the ‘plateau effect’ under the ultra-high dose rates radiation, which signifies that within a specific range of doses, the surviving fraction either exhibits minimal variation or increases with the dose. For a given dose, the surviving fraction increases with the dose rate until tending to a stable value, which means that the protection in normal tissue reaches saturation. Significance. The emergence of the ‘plateau effect’ allows delivering the higher doses while minimizing damage to normal tissue. It is necessary to develop appropriate program of doses and dose rates for different irradiated tissue to achieve more efficient protection.

Using remote sensing data within an optimal spatiotemporal model for invasive plant management: the case of Ailanthus altissima in the Alta Murgia National Park

We tackle the problem of coupling a spatiotemporal model for simulating the spread and control of an invasive alien species with data coming from image processing and expert knowledge. In this study, we implement a spatially explicit optimal control model based on a reaction–diffusion equation which includes an Holling II type functional response term for modeling the density control rate. The model takes into account the budget constraint related to the control program and searches for the optimal effort allocation for the minimization of the invasive alien species density. Remote sensing and expert knowledge have been assimilated in the model to estimate the initial species distribution and its habitat suitability, empirically extracted by a land cover map of the study area. The approach has been applied to the plant species Ailanthus altissima (Mill.) Swingle within the Alta Murgia National Park. This area is one of the Natura 2000 sites under the study of the ongoing National Biodiversity Future Center (NBFC) funded by the Italian National Recovery and Resilience Plan (NRRP), and pilot site of the finished H2020 project ECOPOTENTIAL, which aimed at the integration of modeling tools and Earth Observations for a sustainable management of protected areas. Both the initial density map and the land cover map have been generated by using very high resolution satellite images and validated by means of ground truth data provided by the EU Life Alta Murgia Project (LIFE12 BIO/IT/000213), a project aimed at the eradication of A. altissima in the Alta Murgia National Park.

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

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

Neural network approximation of optimal controls for stochastic reaction-diffusion equations.

We present a numerical algorithm that allows the approximation of optimal controls for stochastic reaction-diffusion equations with additive noise by first reducing the problem to controls of feedback form and then approximating the feedback function using finitely based approximations. Using structural assumptions on the finitely based approximations, rates for the approximation error of the cost can be obtained. Our algorithm significantly reduces the computational complexity of finding controls with asymptotically optimal cost. Numerical experiments using artificial neural networks as well as radial basis function networks illustrate the performance of our algorithm. Our approach can also be applied to stochastic control problems for high dimensional stochastic differential equations and more general stochastic partial differential equations.

Velocity diagram of traveling waves for discrete reaction–diffusion equations

Velocity diagram of traveling waves for discrete 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.

An ALE meshfree method for surface PDEs coupling with forced mean curvature flow

In this paper, we propose an arbitrary Lagrangian Eulerian (ALE) meshfree method that utilizes the radial basis function-finite difference (RBF-FD) method for solving diffusion-reaction equations on evolving surfaces. The surface evolution law is determined by a forced mean curvature flow (FMCF). We develop a parametric RBF-FD method to solving the FMCF, which has not been done previously in the framework of meshfree methods. The advantage of this parametric method is that it utilizes a suitable tangential velocity in the equation to maintain a fairly uniform distribution of nodes during the surface evolution. The tangential velocity also allows us to construct an ALE RBF-FD scheme for the surface PDEs, which performs better than the purely Lagrangian method. Furthermore, we discuss how to deal with the boundary conditions for both the FMCF and the PDEs on surfaces, and present a ghost node approach to efficiently discretize the boundary conditions. Some numerical experiments are shown, which not only demonstrate the effectiveness of the tangential velocity, but also illustrate two applications.

Modeling of Porous Catalytic Pellets with Various Morphologies Suspended in Batch Reactor and CSTR from Analytical Solutions of Reaction-Diffusion Equations

Modeling of Porous Catalytic Pellets with Various Morphologies Suspended in Batch Reactor and CSTR from Analytical Solutions of Reaction-Diffusion Equations

Seed predation-induced Allee effects, seed dispersal and masting jointly drive the diversity of seed sources during population expansion.

The environmental factors affecting plant reproduction and effective dispersal, in particular biotic interactions, have a strong influence on plant expansion dynamics, but their demographic and genetic consequences remain an understudied body of theory. Here, we use a mathematical model in a one-dimensional space and on a single reproductive period to describe the joint effects of predispersal seed insect predators foraging strategy and plant reproduction strategy (masting) on the spatio-temporal dynamics of seed sources diversity in the colonisation front of expanding plant populations. We show that certain foraging strategies can result in a higher seed predation rate at the colonisation front compared to the core of the population, leading to an Allee effect. This effect promotes the contribution of seed sources from the core to the colonisation front, with long-distance dispersal further increasing this contribution. As a consequence, our study reveals a novel impact of the predispersal seed predation-induced Allee effect, which mitigates the erosion of diversity in expanding populations. We use rearrangement inequalities to show that masting has a buffering role: it mitigates this seed predation-induced Allee effect. This study shows that predispersal seed predation, plant reproductive strategies and seed dispersal patterns can be intermingled drivers of the diversity of seed sources in expanding plant populations, and opens new perspectives concerning the analysis of more complex models such as integro-difference or reaction-diffusion equations.