Abstract
We present a method to generate analytical coarse-grain cross sections for internal energy excitation and dissociation of nitrogen and apply it to the NASA Ames N2-N ab initio database. State-resolved cross sections from this database are reduced using the Uniform RoVibrational-Collisional bin model. With a 10-bin system as example we compare two sets of coarse-grain cross sections: one obtained by analytical inversion and another by direct binning. With analytical inversion we manage to compress the entire set of state-resolved data into a small set of parameters, sufficient to reconstruct the main features of the full database. This has the potential of massively reducing the computational cost in large-scale direct simulation Monte Carlo (DSMC) calculations, both concerning memory requirements and execution time. Combining this coarse-grain model with the N2-N ab initio database will enable much higher-fidelity DSMC simulation of nonequilibrium dissociation in shock-heated flows than is currently possible with conventional models.
Original language | English (US) |
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Article number | 110701 |
Journal | Chemical Physics |
Volume | 533 |
DOIs | |
State | Published - May 1 2020 |
Bibliographical note
Funding Information:Research of T.E. Magin was sponsored by the European Research Council Starting Grant #259354. The authors would like to thank Mr. Federico Bariselli for his contributions to the improvement of the URVC bin model.
Publisher Copyright:
© 2020 Elsevier B.V.
Keywords
- Coarse-grain models
- Direct simulation Monte Carlo (DSMC)
- Non-equilibrium flows
- Reaction cross sections