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John D. Stephens

Publications and source records attributed to John D. Stephens.

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Bounds-Constrained Finite Element Approximation of Time-Dependent Partial Differential Equations

Finite elements provide accurate and efficient methods for the numerical solution of partial differential equations by means of restricting variational problems to finite-dimensional approximating spaces. However, they do not, in general, guarantee enforcement of bounds constraints inherent in the original problem. We propose two approaches to enforcing bounds constraints for time-dependent problems. First, we propose general projective methods which result from a systematic modification of any abstract time-stepping scheme. Second, we present a monolithic technique for which we take a modified formulation of implicit single-stage Runge-Kutta methods and general implicit multistep methods as prototypical examples. By solving a constrained optimization problem, we are able to ensure that the bounds constraints are enforced by the approximate solution at the discrete time levels, obtaining (formally) high order methods both in space and time. Numerical examples for the linear heat and advection equations and nonlinear Allen-Cahn equation are given.

math.NA

Bounds-constrained finite element approximation of time-dependent partial differential equations

Finite element methods provide accurate and efficient methods for the numerical solution of partial differential equations by means of restricting variational problems to finite-dimensional approximating spaces. However, they do not guarantee enforcement of bounds constraints inherent in the original problem. Previous work enforces these bounds constraints by replacing the variational equations with variational inequalities. We extend this approach to collocation-type Runge-Kutta methods for time-dependent problems, obtaining (formally) high order methods in both space and time. By using a novel reformulation of the collocation scheme, we can guarantee that the bounds constraints hold uniformly in time. Numerical examples for a model of phytoplankton growth, the heat equation, and the Cahn-Hilliard system are given.

math.NA