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The nonlocal Allen-Cahn (NAC) equation is a generalization of the classic Allen-Cahn equation by replacing the Laplacian with a parameterized nonlocal diffusion operator, and satisfies the maximum principle as its local counterpart. In this…

Numerical Analysis · Mathematics 2019-02-14 Qiang Du , Lili Ju , Xiao Li , Zhonghua Qiao

For the past few years, scalar auxiliary variable (SAV) and SAV-type approaches became very hot and efficient methods to simulate various gradient flows. Inspired by the new SAV approach in \cite{huang2020highly}, we propose a novel…

Numerical Analysis · Mathematics 2022-04-14 Zhengguang Liu , Xiaoli Li

In this work, we propose a Crank-Nicolson-type scheme with variable steps for the time fractional Allen-Cahn equation. The proposed scheme is shown to be unconditionally stable (in a variational energy sense), and is maximum bound…

Numerical Analysis · Mathematics 2022-01-05 Hong-lin Liao , Tao Tang , Tao Zhou

We study the systematic numerical approximation of a class of Allen-Cahn type problems modeling the motion of phase interfaces. The common feature of these models is an underlying gradient flow structure which gives rise to a decay of an…

Numerical Analysis · Mathematics 2017-03-09 Anke Böttcher , Herbert Egger

We present in this paper construction and analysis of a block-centered finite difference method for the spatial discretization of the scalar auxiliary variable Crank-Nicolson scheme (SAV/CN-BCFD) for gradient flows, and show rigorously that…

Numerical Analysis · Mathematics 2018-12-06 Xiaoli Li , Jie Shen , Hongxing Rui

An adaptive implicit-explicit (IMEX) BDF2 scheme is investigated on generalized SAV approach for the Cahn-Hilliard equation by combining with Fourier spectral method in space. It is proved that the modified energy dissipation law is…

Numerical Analysis · Mathematics 2022-11-04 Yifan Wei , Jiwei Zhang , Chengchao Zhao , Yanmin Zhao

We construct first- and second-order time discretization schemes for the Cahn-Hilliard-Navier-Stokes system based on the multiple scalar auxiliary variables approach (MSAV) approach for gradient systems and (rotational) pressure-correction…

Numerical Analysis · Mathematics 2020-09-22 Xiaoli Li , Jie Shen

This paper is concerned with conditionally structure-preserving, low regularity time integration methods for a class of semilinear parabolic equations of Allen-Cahn type. Important properties of such equations include maximum bound…

Numerical Analysis · Mathematics 2022-11-09 Cao-Kha Doan , Thi-Thao-Phuong Hoang , Lili Ju , Katharina Schratz

The energy dissipation property of the Strang splitting method was first demonstrated for the matrix-valued Allen-Cahn (MAC) equation under restrictive time-step constraints [J. Comput. Phys. 454, 110985, 2022]. In this work, we eliminate…

Numerical Analysis · Mathematics 2025-08-07 Chaoyu Quan , Tao Tang , Dong Wang

The Smectic-A (SmA) phase is modeled by a modified Landau-de Gennes (mLdG) model proposed by Xia et al. [Phys. Rev. Lett., 126 (2021), 177801], in which a tensor order parameter $\mathbf{Q}$ for the orientational order is coupled with a…

Numerical Analysis · Mathematics 2026-04-21 Wenshuai Hu , Guanghua Ji , Xiao Li

In this paper, we propose and analyze a first-order and a second-order time-stepping schemes for the anisotropic phase-field dendritic crystal growth model. The proposed schemes are based on an auxiliary variable approach for the Allen-Cahn…

Numerical Analysis · Mathematics 2021-09-06 Minghui Li , Mejdi Azaiez , Chuanju Xu

We develop and analyze a highly efficient, second-order time-marching scheme for infinite-dimensional nonlinear geophysical fluid models, designed to accurately approximate invariant measures-that is, the stationary statistical properties…

Numerical Analysis · Mathematics 2025-10-08 Daozhi Han , Xiaoming Wang

The Allen-Cahn equation (ACE) inherently possesses two crucial properties: the maximum principle and the energy dissipation law. Preserving these two properties at the discrete level is also necessary in the numerical methods for the ACE.…

Numerical Analysis · Mathematics 2024-01-04 Ying Chen , Xi Liu , Zhenhua Chai , Baochang Shi

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…

Numerical Analysis · Mathematics 2021-04-27 Jie Shen , Xiangxiong Zhang

In this paper, we consider numerical approximations for the anisotropic Cahn-Hilliard equation. The main challenge of constructing numerical schemes with unconditional energy stabilities for this model is how to design proper temporal…

Numerical Analysis · Mathematics 2018-04-10 Xiaofeng Yang

We propose a new numerical technique to deal with nonlinear terms in gradient flows. By introducing a scalar auxiliary variable (SAV), we construct efficient and robust energy stable schemes for a large class of gradient flows. The SAV…

Numerical Analysis · Mathematics 2017-10-05 Jie Shen , Jie Xu , Jiang Yang

In this paper, we propose and analyze an efficient implicit--explicit (IMEX) second order in time backward differentiation formulation (BDF2) scheme with variable time steps for gradient flow problems using the scalar auxiliary variable…

Numerical Analysis · Mathematics 2022-04-04 Dianming Hou , Zhonghua Qiao

Two fast L1 time-stepping methods, including the backward Euler and stabilized semi-implicit schemes, are suggested for the time-fractional Allen-Cahn equation with Caputo's derivative. The time mesh is refined near the initial time to…

Numerical Analysis · Mathematics 2020-12-23 Bingquan Ji , Hong-lin Liao , Luming Zhang

This work uses a linear relaxation method to develop efficient numerical schemes for the time-fractional Allen-Cahn and Cahn-Hilliard equations. The L1+-CN formula is used to discretize the fractional derivative, and an auxiliary variable…

Numerical Analysis · Mathematics 2025-06-16 Hui Yu , Zhaoyang Wang , Ping Lin

The $L^2$ gradient flow of the Ginzburg-Landau free energy functional leads to the Allen Cahn equation that is widely used for modeling phase separation. Machine learning methods for solving the Allen-Cahn equation in its strong form suffer…

Machine Learning · Computer Science 2025-03-27 Revanth Mattey , Susanta Ghosh