An Exploration of Advanced SLW Modeling Approaches in Comprehensive Combustion Predictions. Issue 2 (25th January 2022)

• Record Type: Journal Article
• Authors: Badger, J.; Webb, B.W.; Solovjov, V.P.
• Is Part Of: Combustion science and technology. Volume 194:Issue 2(2022)
• Page Start: 225
• Page End: 241
• Publication Date: 2022-01-25
• Subjects: Gas radiation -- SLW model -- rank correlated SLW model -- reference approach SLW model -- locally correlated SLW model; Combustion -- Periodicals; Combustion engineering -- Periodicals; 541.36105
• DOI: 10.1080/00102202.2019.1678907
• Languages: English
• ISSNs: 0010-2202

Abstract

ABSTRACT: Recent work demonstrated the integration of the Spectral Line Weighted-Sum-of-Gray-Gases (SLW) model for advanced modeling of gas radiation in high temperature gases in a comprehensive combustion modeling prediction scheme. This prior work compared predictions using the Reference Approach SLW model with the Domain Based Weighted-Sum-of-Gray-Gases model used in Fluent. The present work reports on the implementation of the Rank Correlated SLW model and the Locally Correlated SLW model in the combustion scenario studied in the earlier publication, complementing the Reference Approach SLW model predictions reported previously. The predictions confirm the need for such advanced radiation modeling to accurately resolve the radiative flux divergence and temperature fields, particularly in localized regions of the flame zone where very large differences in temperature and radiative heating may be found relative to the more rudimentary modeling approach. Results also reveal the dependence of the predictions for the three SLW model variants on the number of gray gases employed in the simulations. The Reference Approach and Locally Correlated SLW model predictions exhibit rather significant dependence on the number of gray gases used. It is shown that the Rank Correlated SLW model is the most robust of all models, and demonstrates that it can achieve accurate solutions with as few as 3–5 gray gases.