An accelerated computation of combustion with finite-rate chemistry using LES and an open source library for In-Situ-Adaptive Tabulation. (26th March 2017)

• Record Type: Journal Article
• Authors: Fooladgar, Ehsan; Chan, C.K.; Nogenmyr, Karl-Johan
• Is Part Of: Computers & fluids. Volume 146(2017)
• Page Start: 42
• Page End: 50
• Publication Date: 2017-03-26
• Subjects: Finite-rate chemistry -- LES PaSR Combustion Model -- In-Situ-Adaptive-Tabulation (ISAT) -- Cantera -- Open-source code -- Turbulent stratified flame; Fluid dynamics -- Data processing -- Periodicals; 532.050285
• DOI: 10.1016/j.compfluid.2017.01.008
• Languages: English
• ISSNs: 0045-7930

Abstract

Highlights: Reports a modified implementation of In-Situ-Adaptive Tabulation (ISAT) algorithm into OpenFoam, by replacing the Chemkin based thermo-chemical libraries with Cantera based libraries. Allows efficient coupling of detailed chemistry into combustion simulations without the use of commercial codes. Performs validation on 0D and 2D geometries of perfectly stirred reactor and a laminar premixed opposed jet using LES-FRC with complex chemistry. Abstract: In this paper, a modified version of the latest implementation of In-Situ-Adaptive-Tabulation (ISAT) algorithm, ISAT-CK7, is introduced and linked to OpenFOAM for accelerating chemical computation in simulating combustion with the finite chemistry (FRC) approach. In this new version, ISAT-CK7-Cantera, which is an open-source and free code, replaces Chemkin II in ISAT-CK7 as the thermo-chemical library. This new library facilitates using LES with FRC and detailed chemistry which has not been commonly done. In addition to successful validation of ISAT-CK7-Cantera in the simple 0D and 2D geometries, the resulting package, consisting of OpenFOAM, ISAT and Cantera, is used to evaluate the performance of LES-FRC with a partially stirred reactor combustion model and DRM19 skeletal mechanism against experimental data of the Darmstadt turbulent stratified flame. LES results show good to excellent agreement with the measured data.