Discrete Maximum Principle Research Articles

A high order compact finite difference scheme for elliptic interface problems with discontinuous and high-contrast coefficients

The elliptic interface problems with discontinuous and high-contrast coefficients appear in many applications and often lead to huge condition numbers of the corresponding linear systems. Thus, it is highly desired to construct high order schemes to solve the elliptic interface problems with discontinuous and high-contrast coefficients. Let Γ be a smooth curve inside a rectangular region Ω. In this paper, we consider the elliptic interface problem −∇·(a∇u)=f in Ω∖Γ with Dirichlet boundary conditions, where the coefficient a and the source term f are smooth in Ω∖Γ and the two jump condition functions [u] and [a∇u·n→] across Γ are smooth along the interface Γ. To solve such elliptic interface problems, we propose a high order compact 9-point finite difference scheme and a high order local calculation for numerically computing the solution u and its gradient ∇u respectively on uniform Cartesian grids without changing coordinates into local coordinates. We numerically verify the sign conditions of our proposed compact finite difference scheme and prove the convergence rate by the discrete maximum principle. Our numerical experiments confirm the fourth order accuracy for computing the solution u in both l2 and l∞ norms of the proposed compact finite difference scheme on uniform meshes for the elliptic interface problems with discontinuous and high-contrast coefficients.

A generalized Eulerian-Lagrangian discontinuous Galerkin method for transport problems

We propose a generalized Eulerian-Lagrangian (GEL) discontinuous Galerkin (DG) method. The method is a generalization of the Eulerian-Lagrangian (EL) DG method for transport problems proposed in Cai et al. (2021) [5], which tracks solution along approximations to characteristics in the DG framework, allowing extra large time stepping size with stability. The newly proposed GEL DG method in this paper is motivated for solving linear hyperbolic systems with variable coefficients, where the velocity field for adjoint problems of the test functions is frozen to constant. In this paper, in a simplified scalar setting, we propose the GEL DG methodology by freezing the velocity field of adjoint problems, and by formulating the semi-discrete scheme over the space-time region partitioned by linear lines approximating characteristics. The fully-discrete schemes are obtained by method-of-lines Runge-Kutta methods. We further design flux limiters for the schemes to satisfy the discrete geometric conservation law (DGCL) and maximum principle preserving (MPP) properties. Numerical results on 1D and 2D linear transport problems are presented to demonstrate great properties of the GEL DG method. These include the high order spatial and temporal accuracy, stability with extra large time stepping size, and satisfaction of DGCL and MPP properties.

Optimal Open-Loop Control of Discrete Deterministic Systems by Application of the Perch School Metaheuristic Optimization Algorithm

A new hybrid metaheuristic method for optimizing the objective function on a parallelepiped set of admissible solutions is proposed. It mimics the behavior of a school of river perch when looking for food. The algorithm uses the ideas of several methods: a frog-leaping method, migration algorithms, a cuckoo algorithm and a path-relinking procedure. As an application, a wide class of problems of finding the optimal control of deterministic discrete dynamical systems with a nonseparable performance criterion is chosen. For this class of optimization problems, it is difficult to apply the discrete maximum principle and its generalizations as a necessary optimality condition and the Bellman equation as a sufficient optimality condition. The desire to extend the class of problems to be solved to control problems of trajectory bundles and stochastic problems leads to the need to use not only classical adaptive random search procedures, but also new approaches combining the ideas of migration algorithms and swarm intelligence methods. The efficiency of this method is demonstrated and an analysis is performed by solving several optimal deterministic discrete control problems: two nonseparable problems (Luus–Tassone and LiHaimes) and five classic linear systems control problems with known exact solutions.

Anti‐diffusive alternate‐directions schemes for the transport of step functions

AbstractThe purpose in this article is to design finite‐volume schemes on structured grids for the transport of piecewise‐constant functions (typically, indicator functions) with as low diffusion as possible. We first propose an extension of the so‐called Lagrange‐projection algorithm, or downwind scheme with an Ultrabee limiter, for the transport equation in one space dimension with a non‐constant velocity; as its constant velocity counterpart, this scheme is designed to capture the discontinuities separating two plateaus in only one cell, and is referred to as “anti‐diffusive.” It is shown to preserve the bounds of the solution. Then, for two and three dimensional problems, we introduce a conservative alternate‐directions algorithm, an show that this latter enjoys a discrete maximum principle, provided that the underlying one‐dimensional schemes satisfy a property which may be seen as a flux limitation, possibly incorporated a posteriori in any explicit scheme. Numerical tests of this alternate‐directions algorithm are performed, with a variety of one‐dimensional embedded schemes including the anti‐diffusive scheme developed here and the so called THINC scheme. The observed numerical diffusion is indeed very low. With the anti‐diffusive scheme, the above‐mentioned a posteriori limitation is necessary to preserve the solution bounds, but, in the performed tests, does not introduce any visible additional diffusion.

Energy relaxation approximation for compressible multicomponent flows in thermal nonequilibrium

This work concerns the numerical approximation with an explicit first-order finite volume method of inviscid, nonequilibrium, high-temperature flows in multiple space dimensions. It is devoted to the analysis of the numerical scheme for the approximation of the hyperbolic system in homogeneous form. We derive a general framework for the design of numerical schemes for this model from numerical schemes for the monocomponent compressible Euler equations for a polytropic gas. Under a very simple condition on the adiabatic exponent of the polytropic gas, the scheme for the multicomponent system enjoys the same properties as the one for the monocomponent system: discrete entropy inequality, positivity of the partial densities and internal energies, discrete maximum principle on the mass fractions, and discrete minimum principle on the entropy. Our approach extends the relaxation of energy (Coquel and Perthame in SIAM J. Numer. Anal. 35:2223–2249, 1998) to the multicomponent Euler system. In the limit of instantaneous relaxation we show that the solution formally converges to a unique and stable equilibrium solution to the multicomponent Euler equations. We then use this framework to design numerical schemes from three schemes for the polytropic Euler system: the Godunov exact Riemann solver, and the HLL and pressure relaxation based approximate Riemann solvers. Numerical experiments in one and two space dimensions on flows with discontinuous solutions support the conclusions of our analysis and highlight stability, robustness and convergence of the schemes.

Convergence Analysis of the Variational Operator Splitting Scheme for a Reaction-Diffusion System with Detailed Balance

We present a detailed convergence analysis for an operator splitting scheme proposed in [C. Liu et al.,J. Comput. Phys., 436, 110253, 2021] for a reaction-diffusion system with detailed balance. The numerical scheme has been constructed based on a recently developed energetic variational formulation, in which the reaction part is reformulated in terms of the reaction trajectory, and both the reaction and diffusion parts dissipate the same free energy. The scheme is energy stable and positivity-preserving. In this paper, the detailed convergence analysis and error estimate are performed for the operator splitting scheme. The nonlinearity in the reaction trajectory equation, as well as the implicit treatment of nonlinear and singular logarithmic terms, impose challenges in numerical analysis. To overcome these difficulties, we make use of the convex nature of the logarithmic nonlinear terms, which are treated implicitly in the chemical reaction stage. In addition, a combination of a rough error estimate and a refined error estimate leads to a desired bound of the numerical error in the reaction stage, in the discrete maximum norm. Furthermore, a discrete maximum principle yields the evolution bound of the numerical error function at the diffusion stage. As a direct consequence, a combination of the numerical error analysis at different stages and the consistency estimate for the operator splitting results in the convergence estimate of the numerical scheme for the full reaction-diffusion system.

Positive Scharfetter-Gummel finite volume method for convection-diffusion equations on polygonal meshes

In this paper, we develop and study a fully implicit positive finite volume scheme that allows an accurate approximation of the nonlinear highly anisotropic convection-diffusion equations on almost arbitrary girds. The key idea is to relate the oscillatory fluxes, including the convective ones, to the normal monotonic diffusive flux thanks to a technique used in the Scharfetter-Gummel discretizations. Then, we obtain a nonlinear two-point-like scheme with positive coefficients on primal and dual meshes. We check that the structure of the scheme naturally ensures the nonnegativity of the approximate solutions. We also establish energy estimates, which leads to a proof of existence of the numerical solutions. This analytical study is accompanied with a series of numerical results and simulations. They highlight the fulfillment of the discrete maximum principle, the optimal accuracy of our scheme, and its robustness with respect to the mesh and to high ratios of anisotropy.

DETERMINATION OF AN UNKNOWN DIFFUSION COEFFICIENT IN A PARABOLIC INVERSE PROBLEM

In this paper we studied the finite difference scheme for the solution of one dimensional parabolic inverse problem of finding the function and the unknown positive coefficient . The Backward time centered space (BTCS) which is unconditionally stable is studied and its convergent is proved using application of discrete maximum principle. Error estimates for and is studied and to give clear overview of the methodology several model problems are solved numerically. According to the experimental numerical results and the concluding remark are presented

Discrete Maximum Principle and Energy Stability of the Compact Difference Scheme for Two-Dimensional Allen-Cahn Equation

The Allen-Cahn model is discussed mainly in the phase field simulation. The compact difference method will be used to numerically approximate the two-dimensional nonlinear Allen-Cahn equation with initial and boundary value conditions, and then, a fully discrete compact difference scheme with second-order accuracy in time and fourth-order in space is established. And its numerical solution satisfies the discrete maximum principle under the constraints of reasonable space and time steps. On this basis, the energy stability of the scheme is investigated. Finally, numerical examples are given to illustrate the theoretical results.

An enhanced non-oscillatory BFECC algorithm for finite element solution of advective transport problems

In this paper, the so-called “back and forth error compensation correction (BFECC)” methodology is utilized to improve the solvers developed for the advection equation. Strict obedience to the so-called “discrete maximum principle” is enforced by incorporating a gradient-based limiter into the BFECC algorithm. The accuracy of the BFECC algorithm in capturing the steep-fronts in hyperbolic scalar-transport problems is improved by introducing a controlled anti-diffusivity. This is achieved at the cost of performing an additional backward sub-solution-step and modifying the formulation of the error compensation accordingly. The performance of the proposed methodology is assessed by solving a series of benchmarks utilizing different combinations of the BFECC algorithms and the underlying numerical schemes. Results are presented for both the structured and unstructured meshes.

Optimal maximum-norm estimate of the LDG method for singularly perturbed convection–diffusion problem

We consider the local discontinuous Galerkin (LDG) method with a generalized alternating numerical flux for a one-dimensional singularly perturbed convection–diffusion problem. The double-optimal local maximum-norm error estimate is derived on the quasi-uniform meshes for the first time. Here, “double-optimal” refers to the maximum-norm error estimate out of the boundary layer region being optimal and the width of the boundary layer being quasi-optimal. Furthermore, we improve the discrete maximum principle and global L1-error estimate established in the literature.

A mass-lumping finite element method for radially symmetric solution of a multidimensional semilinear heat equation with blow-up

This study presents a non-standard mass-lumping finite element method for computing the radially symmetric solution of a semilinear heat equation in N dimensional ball (). We provide two schemes, (ML–1) and (ML–2), and derive their error estimates through the discrete maximum principle. In the weighted norm, the convergence of (ML–1) was at the optimal order but that of (ML–2) was only at sub-optimal order. Nevertheless, scheme (ML–2) reproduces a blow-up of the solution of the original equation. In fact, in scheme (ML–2), we could accurately approximate the blow-up time. Our theoretical results were validated in numerical experiments.

Discrete maximum principle of a high order finite difference scheme for a generalized Allen–Cahn equation

We consider solving a generalized Allen-Cahn equation coupled with a passive convection for a given incompressible velocity field. The numerical scheme consists of the first order accurate stabilized implicit explicit time discretization and a fourth order accurate finite difference scheme, which is obtained from the finite difference formulation of the $Q^2$ spectral element method. We prove that the discrete maximum principle holds under suitable mesh size and time step constraints. The same result also applies to construct a bound-preserving scheme for any passive convection with an incompressible velocity field.

Mathematical modeling and optimal control strategy for the obesity epidemic

The aim of this work is to propose a discrete mathematical model to study the behavioral dynamics of a population affected by the disease of obesity. Thus, the population under study is divided into six compartments: susceptible (S), exposed (E), slightly obese (I1), moderately obese (I2), very obese (I3), and recovered (R). To fight this disease, we used four controls: Awareness through education and media, food and sports programs, medical treatment with drugs, and treatment with surgical intervention. The discrete time Pontryagin maximum principle is used to characterize the optimal controls. The numerical simulation via MATLAB confirms the performance of theoretical results.

On convergence of explicit finite volume scheme for one-dimensional three-component two-phase flow model in porous media

Abstract In this work, we develop and analyze an explicit finite volume scheme for a one-dimensional nonlinear, degenerate, convection–diffusion equation having application in petroleum reservoir. The main difficulty is that the solution typically lacks regularity due to the degenerate nonlinear diffusion term. We analyze a numerical scheme corresponding to explicit discretization of the diffusion term and a Godunov scheme for the advection term. L ∞ {L}^{\infty } stability under appropriate CFL conditions and BV {\rm{BV}} estimates are obtained. It is shown that the scheme satisfies a discrete maximum principle. Then we prove convergence of the approximate solution to the weak solution of the problem, and we mount convergence results to a weak solution of the problem in L 1 {L}^{1} . Results of numerical experiments are presented to validate the theoretical analysis.

Feedback Optimality Condition for Nonconvex Discrete Linear-Quadratic Optimal Control Problem

The paper analyzed a non-convex linear-quadratic optimization problem in a discrete dynamic system. We obtained necessary optimality condition with feedback controls which allow a descent of the functional cost. Such controls are generated by the quadratic majorant of the cost. In contrast to the discrete maximum principle, this condition does not require any convexity properties of the problem.

Uniformly Convergent Numerical Scheme for Singularly Perturbed Parabolic PDEs with Shift Parameters

In this article, singularly perturbed parabolic differential difference equations are considered. The solution of the equations exhibits a boundary layer on the right side of the spatial domain. The terms containing the advance and delay parameters are approximated using Taylor series approximation. The resulting singularly perturbed parabolic PDEs are solved using the Crank–Nicolson method in the temporal discretization and nonstandard finite difference method in the spatial discretization. The existence of a unique discrete solution is guaranteed using the discrete maximum principle. The uniform stability of the scheme is investigated using solution bound. The uniform convergence of the scheme is discussed and proved. The scheme converges uniformly with the order of convergenceON−1+Δt2, whereNis number of subintervals in spatial discretization andΔtis mesh length in temporal discretization. Two test numerical examples are considered to validate the theoretical findings of the scheme.

ANALOGUE OF THE DISCRETE MAXIMUM PRINCIPLE AND THE NECESSARY OPTIMALITY CONDITION OF SINGULAR CONTROLS IN ONE TWO-PARAMETRIC DISCRETE OPTIMAL CONTROL PROBLEM

A two-stage (stepwise) optimal control problem for linear two-parameter systems with distributed control functions is considered. The aim of the work is to establish the necessary optimality condition under the assumption that the convexity of the set of admissible controls is satisfied and the connection condition is nonlinear. Using increments of the quality functional in the form of two-dimensional linear inhomogeneous systems of difference equations, a formula is obtained that allows one to obtain both a discrete analogue of the Pontryagin maximum principle and to study the case of its degeneration. A theorem is formulated that is an analogue of the discrete Pontryagin maximum principle for the problem under consideration. In the case of special controls, the discrete maximum principle degenerates and, therefore, becomes ineffective, including in the verification sense. Therefore, it is necessary to have new necessary conditions for optimality. A special, in the sense of the Pontryagin maximum principle, case of a discrete maximum condition, under which admissible controls are considered special, is studied. A necessary condition for optimality of singular controls is established.

Maximum principle preserving finite difference scheme for 1-D nonlocal-to-local diffusion problems

In a recent paper (Du et al., 2018), a quasi-nonlocal coupling method was introduced to seamlessly bridge a nonlocal diffusion model with the classical local diffusion counterpart in a one-dimensional space. The proposed coupling framework removes interfacial inconsistency, preserves the balance of fluxes, and satisfies the maximum principle of diffusion problem. However, the numerical scheme proposed in that paper does not maintain all of these properties on a discrete level. In this paper we resolve this issue by proposing a new finite difference scheme that ensures the balance of fluxes and the discrete maximum principle. We rigorously prove these results and provide the stability and convergence analyses accordingly. In addition, we provide the Courant–Friedrichs–Lewy (CFL) condition for the new scheme and test a series of benchmark examples which confirm the theoretical findings.

Entropy stabilization and property-preserving limiters for ℙ1 discontinuous Galerkin discretizations of scalar hyperbolic problems

Abstract The methodology proposed in this paper bridges the gap between entropy stable and positivity-preserving discontinuous Galerkin (DG) methods for nonlinear hyperbolic problems. The entropy stability property and, optionally, preservation of local bounds for cell averages are enforced using flux limiters based on entropy conditions and discrete maximum principles, respectively. Entropy production by the (limited) gradients of the piecewise-linear DG approximation is constrained using Rusanov-type entropy viscosity. The Taylor basis representation of the entropy stabilization term reveals that it penalizes the solution gradients in a manner similar to slope limiting and requires implicit treatment to avoid severe time step restrictions. The optional application of a vertex-based slope limiter constrains the DG solution to be bounded by local maxima and minima of the cell averages. Numerical studies are performed for two scalar two-dimensional test problems with nonlinear and nonconvex flux functions.