Abstract We consider a family of variable time-stepping Dahlquist-Liniger-Nevanlinna (DLN) schemes, which is unconditionally non-linear stable and second order accurate, for the Allen-Cahn equation. The finite element methods are used for the spatial discretization. For the non-linear term, we combine the DLN scheme with two efficient temporal algorithms: partially implicit modified algorithm and scalar auxiliary variable algorithm. For both approaches, we prove the unconditional, long-term stability of the model energy under any arbitrary time step sequence. Moreover, we provide rigorous error analysis for the partially implicit modified algorithm with variable time-stepping. Efficient time-adaptive algorithms based on these schemes are also proposed. Several one- and two-dimensional numerical tests are presented to verify the properties of the proposed time-adaptive DLN methods.
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Mathematical and numerical analysis for PDE systems modeling intravascular drug release from arterial stents and transport in arterial tissue
This paper is concerned with the PDE (partial differential equation) and numerical analysis of a modified one-dimensional intravascular stent model. It is proved that the modified model has a unique weak solution by using the Galerkin method combined with a compactness argument. A semi-discrete finite-element method and a fully discrete scheme using the Euler time-stepping have been formulated for the PDE model. Optimal order error estimates in the energy norm are proved for both schemes. Numerical results are presented, along with comparisons between different decoupling strategies and time-stepping schemes. Lastly, extensions of the model and its PDE and numerical analysis results to the two-dimensional case are also briefly discussed.
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- Award ID(s):
- 2309626
- PAR ID:
- 10523287
- Publisher / Repository:
- AIMS Press
- Date Published:
- Journal Name:
- Mathematical Biosciences and Engineering
- Volume:
- 21
- Issue:
- 4
- ISSN:
- 1551-0018
- Page Range / eLocation ID:
- 5634 to 5657
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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