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Toward a simple and accurate Lagrangian-based error estimator for the BDF algorithms and adaptive time-stepping

Yazhou Wang (China State Key Laboratory of Power System and Generation Equipment, Department of Electrical Engineering, Tsinghua University, Beijing, China)
Dehong Luo (China Three Gorges Renewables (Group) Co., Ltd, Beijing, China)
Xuelin Zhang (Key Laboratory of Cryogenics, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing, China)
Zhitao Wang (China Huaneng Group Co., Ltd, Beijing, China)
Hui Chen (China Huaneng Group Co., Ltd, Beijing, China)
Xiaobo Zhang (Center of Mass Entrepreneurship and Innovation, State Grid Zhejiang Electric Power Co., Ltd, Hangzhou, China)
Ningning Xie (Institute of Science and Technology, China Three Gorges Corporation, Beijing, China)
Shengwei Mei (China State Key Laboratory of Power System and Generation Equipment, Department of Electrical Engineering, Tsinghua University, Beijing, China)
Xiaodai Xue (China State Key Laboratory of Power System and Generation Equipment, Department of Electrical Engineering, Tsinghua University, Beijing, China)
Tong Zhang (China State Key Laboratory of Power System and Generation Equipment, Department of Electrical Engineering, Tsinghua University, Beijing, China)
Kumar K. Tamma (Department of Mechanical Engineering, University of Minnesota, Minneapolis, Minnesota, USA)

International Journal of Numerical Methods for Heat & Fluid Flow

ISSN: 0961-5539

Article publication date: 14 September 2023

Issue publication date: 22 November 2023

84

Abstract

Purpose

The purpose of this paper is to design a simple and accurate a-posteriori Lagrangian-based error estimator is developed for the class of backward differentiation formula (BDF) algorithms with variable time step size, and the adaptive time-stepping in BDF algorithms is demonstrated for efficient time-dependent simulations in fluid flow and heat transfer.

Design/methodology/approach

The Lagrange interpolation polynomial is used to predict the time derivative, and then the accurate primary result is obtained by the Gauss integral, which is applied to evaluate the local error. Not only the generalized formula of the proposed error estimator is presented but also the specific expression for the widely applied BDF1/2/3 is illustrated. Two essential executable MATLAB functions to implement the proposed error estimator are appended for practical applications. Then, the adaptive time-stepping is demonstrated based on the newly proposed error estimator for BDF algorithms.

Findings

The validation tests show that the newly proposed error estimator is accurate such that the effectivity index is always close to unity for both linear and nonlinear problems, and it avoids under/overestimation of the exact local error. The applications for fluid dynamics and coupled fluid flow and heat transfer problems depict the advantage of adaptive time-stepping based on the proposed error estimator for time-dependent simulations.

Originality/value

In contrast to existing error estimators for BDF algorithms, the present work is more accurate for the local error estimation, and it can be readily extended to practical applications in engineering with a few changes to existing codes, contributing to efficient time-dependent simulations in fluid flow and heat transfer.

Keywords

Acknowledgements

This work was supported by The Science and Technology Project of China Three Gorges Corporation (Grant No. 202103404), Research on the International Standard for Compressed Air Energy Storage (Grant No. HNBZ21-I004) and The Mass Entrepreneurship and Innovation Project of State Grid Zhejiang Electric Power Co., Ltd. (Grant No. B711JZ220007).

Author contributions: Yazhou Wang and Dehong Luo contributed equally.

Citation

Wang, Y., Luo, D., Zhang, X., Wang, Z., Chen, H., Zhang, X., Xie, N., Mei, S., Xue, X., Zhang, T. and Tamma, K.K. (2023), "Toward a simple and accurate Lagrangian-based error estimator for the BDF algorithms and adaptive time-stepping", International Journal of Numerical Methods for Heat & Fluid Flow, Vol. 33 No. 12, pp. 4101-4127. https://doi.org/10.1108/HFF-03-2023-0161

Publisher

:

Emerald Publishing Limited

Copyright © 2023, Emerald Publishing Limited

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