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Title: Stability and convergence analysis of the exponential time differencing scheme for a Cahn–Hilliard binary fluid-surfactant model
Authors: Dong, Y
Li, X 
Qiao, Z 
Zhang, Z
Issue Date: Aug-2023
Source: Applied numerical mathematics, Aug. 2023, v. 190, p. 321-343
Abstract: In this paper, we focus on the Cahn–Hilliard type of binary fluid-surfactant model, which is derived as the H−1 gradient flow system of a binary energy functional of the fluid density and the surfactant density. By introducing two stabilization terms appropriately, we give a linear convex splitting of the energy functional, and then establish the exponential time differencing scheme with first-order temporal accuracy in combination with the Fourier spectral approximation in space. To guarantee the energy stability, we treat the nonlinear term partially implicitly in the equation for the fluid and evaluate the nonlinear term in the equation for the surfactant completely explicitly. The developed scheme is linear and decoupled, and the unconditional energy stability, the mass conservation, and the convergence are proved rigorously in the fully discrete setting. Various numerical experiments illustrate the stability and convergence of proposed scheme, along with the effectiveness in the long-time simulations.
Keywords: Binary fluid-surfactant model
Exponential time differencing scheme
Linear convex splitting
Unconditional energy stability
Optimal error estimate
Publisher: Elsevier B.V.
Journal: Applied numerical mathematics 
ISSN: 0168-9274
EISSN: 1873-5460
DOI: 10.1016/j.apnum.2023.05.004
Rights: © 2023 IMACS. Published by Elsevier B.V. All rights reserved.
© 2023. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
The following publication Dong, Y., Li, X., Qiao, Z., & Zhang, Z. (2023). Stability and convergence analysis of the exponential time differencing scheme for a Cahn–Hilliard binary fluid-surfactant model. Applied Numerical Mathematics, 190, 321–343 is available at https://doi.org/10.1016/j.apnum.2023.05.004
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