An adaptive time-integration scheme for stiff chemistry based on Computational Singular Perturbation and Artificial Neural Networks
Name:
Adaptive_1-s2.0-S0021999121007701-main (1).pdf
Size:
4.552Mb
Format:
PDF
Description:
Accepted manuscript
Embargo End Date:
2023-11-29
Type
ArticleKAUST Department
Clean Combustion Research CenterComputational Reacting Flow Laboratory (CRFL)
Mechanical Engineering Program
Physical Science and Engineering (PSE) Division
Date
2021-11-30Online Publication Date
2021-11-29Print Publication Date
2022-02Embargo End Date
2023-11-29Submitted Date
2021-07-27Permanent link to this record
http://hdl.handle.net/10754/673852
Metadata
Show full item recordAbstract
We leverage the computational singular perturbation (CSP) theory to develop an adaptive time-integration scheme for stiff chemistry based on a local, projection-based, reduced order model (ROM) freed of the fast time-scales. Its construction is such that artificial neural networks (ANN) can be plugged-in as cheap surrogates of the local projection basis, which is a state function, to alleviate the computational cost, without sacrificing the geometrical and physical foundation of the method. In fact, the solver relies on the synthetic basis in place of the more expensive on-the-fly calculated basis, i.e. the eigenvectors of the Jacobian matrix of the chemical source term, to define the local slow invariant manifold (SIM) and the projection matrix, then integrates explicitly the projected, i.e., non-stiff, chemical source term.Citation
Malpica Galassi, R., Ciottoli, P. P., Valorani, M., & Im, H. G. (2021). An adaptive time-integration scheme for stiff chemistry based on Computational Singular Perturbation and Artificial Neural Networks. Journal of Computational Physics, 110875. doi:10.1016/j.jcp.2021.110875Sponsors
We acknowledge the fruitful discussions and the technical support kindly offered by Dr. Shivam Barwey and Professor Venkat Raman at the University of Michigan, Ann Arbor, MI, USA, and Dr. Mattia Soldan at KAUST, Saudi Arabia. R. Malpica Galassi acknowledges the financial support of the Fédération Wallonie-Bruxelles (FWB), Cellule Europe.Publisher
Elsevier BVJournal
Journal of Computational PhysicsAdditional Links
https://linkinghub.elsevier.com/retrieve/pii/S0021999121007701ae974a485f413a2113503eed53cd6c53
10.1016/j.jcp.2021.110875