Hybrid modeling of homogenous gas-phase combustion reactions

Brumback Terry E. () and Chen Chien-Pin ()
Additional contact information
Brumback Terry E.: Department of Chemical and Materials Engineering, University of Alabama, Huntsville, AL 35899, USA.
Chen Chien-Pin: Department of Chemical and Materials Engineering, University of Alabama, Huntsville, AL 35899, USA.

Monte Carlo Methods and Applications, 2011, vol. 17, issue 2, 133-154

Abstract: This paper presents a hybrid model (stochastic/deterministic) that describes the time evolution of chemical species in a homogenous gas-phase combustion reaction process at constant volume. First, the paper briefly introduces currently employed stochastic algorithms. Next, the development of the hybrid algorithm is detailed. The model is then validated and tested using a reduced reaction mechanism for methane combustion. The effect of user-input performance parameters on stochastic behavior and computational time is studied. The computational time of the algorithm compared to the stochastic simulation algorithm is then compared, and finally, the effect of multiple runs on auto-ignition time is investigated.

Keywords: Stochastic chemical kinetics; combustion; low-copy molecule modeling (search for similar items in EconPapers)
Date: 2011
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/mcma.2011.006 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bpj:mcmeap:v:17:y:2011:i:2:p:133-154:n:2

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/mcma/html

DOI: 10.1515/mcma.2011.006

Access Statistics for this article

Monte Carlo Methods and Applications is currently edited by Karl K. Sabelfeld

More articles in Monte Carlo Methods and Applications from De Gruyter
Bibliographic data for series maintained by Peter Golla ().