Paper detail

State-resolved coarse-grain cross sections for rovibrational excitation and dissociation of nitrogen based on ab initio data for the N2-N system

In this paper, we present a method to generate state-resolved reaction cross sections in analytical form for rovibrational energy excitation and dissociation of a molecular gas. The method is applied to an ab initio database for the N2-N system devel- oped at NASA Ames Research Center. The detailed information on N2 +N collisions contained in this database has been reduced by adapting a Uniform RoVibrational- Collisional bin model originally developed for rate coefficients. Using a 10-bin system as an example, a comparison is made between two sets of coarse-grain cross sections, obtained by analytical inversion and direct binning respectively. The analytical in- version approach is especially powerful, because it manages to compress the entire set of rovibrational-level-specific data from the Ames database into a much smaller set of numerical parameters, sufficient to reconstruct all coarse-grain cross sections for any particular N2 +N-collision pair. As a result of this approach, the computational cost in in large-scale Direct Simulation Monte Carlo (DSMC) flow simulations is sig- nificantly reduced, both in terms of memory requirements and execution time. The intended application is the simulation of high-temperature gas-dynamics phenomena in shock-heated flows via the DSMC method. Such conditions are typically encoun- tered in high-altitude, high-speed atmospheric entry, or in shock-tube experiments. Using this coarse-grain model together with ab initio rate data will enable more accu- rate modeling nonequilibrium phenomena, such as vibrationally-favored dissociation, an effect that is not well-captured by the conventional models prevalent in DSMC (i.e. Larsen-Borgnakke and Total Collision Energy).

preprint2018arXivOpen access
0citations
0reviews
0saves
Nocode
Nodataset
0institutions

Next steps

Decide what to do with this paper

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Institutions

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this graph slice

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form

No discussion yet. The first strong comment sets the tone.