Unconstrained ETD Methods on the Diffuse-Interface Model with the Peng-Robinson Equation of State

Unconstrained ETD Methods on the Diffuse-Interface Model with the Peng-Robinson Equation of State

Year:    2024

Author:    Menghuo Chen, Yuanqing Wu, Xiaoyu Feng, Shuyu Sun

Communications in Computational Physics, Vol. 35 (2024), Iss. 4 : pp. 973–1002

Abstract

In this study, we apply first-order exponential time differencing (ETD) methods to solve benchmark problems for the diffuse-interface model using the Peng-Robinson equation of state. We demonstrate the unconditional stability of the proposed algorithm within the ETD framework. Additionally, we analyzed the complexity of the algorithm, revealing that computations like matrix multiplications and inversions in each time step exhibit complexity strictly less than $\mathcal{O}(n^2),$ where $n$ represents the number of variables or grid points. The main objective was to develop an algorithm with enhanced performance and robustness. To achieve this, we avoid iterative solutions (such as matrix inversion) in each time step, as they are sensitive to matrix properties. Instead, we adopted a hierarchical matrix ($\mathcal{H}$-matrix) approximation for the matrix inverse and matrix exponential used in each time step. By leveraging hierarchical matrices with a rank $k ≪ n,$ we achieve a complexity of $O(kn{\rm log}(n))$ for their product with an $n$-vector, which outperforms the traditional $\mathcal{O}(n^2)$ complexity. Overall, our focus is on creating an unconditionally stable algorithm with improved computational efficiency and reliability.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/cicp.OA-2023-0256

Communications in Computational Physics, Vol. 35 (2024), Iss. 4 : pp. 973–1002

Published online:    2024-01

AMS Subject Headings:    Global Science Press

Copyright:    COPYRIGHT: © Global Science Press

Pages:    30

Keywords:    Diffuse-interface model exponential time differencing method hierarchical matrix.

Author Details

Menghuo Chen

Yuanqing Wu

Xiaoyu Feng

Shuyu Sun