Show/Hide Menu
Hide/Show Apps
anonymousUser
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Açık Bilim Politikası
Açık Bilim Politikası
Frequently Asked Questions
Frequently Asked Questions
Browse
Browse
By Issue Date
By Issue Date
Authors
Authors
Titles
Titles
Subjects
Subjects
Communities & Collections
Communities & Collections
SLW model for computational fluid dynamics modeling of combustion systems: Implementation and validation
Date
2016-01-01
Author
Ozen, Guzide
Selçuk, Nevin
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
1
views
0
downloads
Spectral Line-Based Weighted Sum of Gray Gases (SLW) model was implemented to Computational Fluid Dynamics (CFD) Solver, ANSYS FLUENT. Discrete Ordinate Method (DOM) available in ANSYS FLUENT was used as Radiative Transfer Equation (RTE) Solver. ANSYS FLUENT with SLW was applied to the prediction of incident heat fluxes for three test problems; two containing isothermal homogenous/nonhomogenous water vapor and one isothermal water vapor/carbon dioxide mixture. Predictive accuracy of SLW in ANSYS FLUENT was assessed by benchmarking its predictions against those of ray tracing (RT) with Statistical Narrow-Band (SNB) and Method of Lines (MOL) solutions of DOM with SLW. Comparisons reveal that the results of CFD code are in good agreement with the benchmark solutions. This finding proves that the use of DOM with SLW in CFD codes would provide more accurate solutions in studies involving gas combustion, where accuracy in spectral radiative properties plays dominant role in heat flux predictions.
Subject Keywords
Gray-gases model
,
Oxy-fuel combustion
,
Blackbody distribution function
,
Emitting-scattering media
,
Radiative heat-transfer
,
Weighted-sum
,
Rectangular furnaces
,
Enclosures
,
Performance
,
Mixtures
URI
https://hdl.handle.net/11511/30288
Journal
NUMERICAL HEAT TRANSFER PART B-FUNDAMENTALS
DOI
https://doi.org/10.1080/10407790.2016.1173499
Collections
Graduate School of Natural and Applied Sciences, Article