A computationally efficient P1 radiation model for modern combustion systems utilizing pre-conditioned conjugate gradient methods
Abstract
The iterative convergence of the P1 radiation model can be slow in optically thin scenarios when employing classical iterative methods. In order to remedy this shortcoming, an in-house P1 radiation model was interfaced with high performance, scalable, linear solver libraries. Next, the accuracies of P1 radiation model calculations was assessed by comparing its predictions against discrete ordinates (DO) model calculations for prototypical problems representative of modern combustion systems. Corresponding benchmark results were also included for comparison. Utilizing Pre-Conditioners (PC) to the Conjugate Gradients (CG) method, the convergence time of the P1 radiation model reduced by a factor of 30 for modest problem sizes and a factor of 70 for larger sized problems when compared against classical Gauss Seidel sweeps. Additionally, PC provided 50% computational savings compared to employing CG in a standalone mode. The P1 model calculation times were about 25–30% of the DO model calculation time. The time to solution also scaled linearly with an increase in problem size. The weighted sum of gray gases model employed in this study in conjunction with the P1 model provided good agreement against benchmark data with L2 error norms (defined relative to corresponding DO calculations) improving when isotropic intensities were prevalent.
- Authors:
-
- University of North Dakota, Grand Forks, ND (United States)
- Publication Date:
- Research Org.:
- Univ. of North Dakota, Grand Forks, ND (United States)
- Sponsoring Org.:
- USDOE Office of Fossil Energy (FE)
- OSTI Identifier:
- 1533557
- Alternate Identifier(s):
- OSTI ID: 1416641
- Grant/Contract Number:
- FE0026191
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Applied Thermal Engineering
- Additional Journal Information:
- Journal Volume: 119; Journal Issue: C; Journal ID: ISSN 1359-4311
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; 42 ENGINEERING; radiative transfer; iterative methods; WSGGM; oxy-combustion; P-1 model
Citation Formats
Krishnamoorthy, Gautham. A computationally efficient P1 radiation model for modern combustion systems utilizing pre-conditioned conjugate gradient methods. United States: N. p., 2017.
Web. doi:10.1016/j.applthermaleng.2017.03.055.
Krishnamoorthy, Gautham. A computationally efficient P1 radiation model for modern combustion systems utilizing pre-conditioned conjugate gradient methods. United States. https://doi.org/10.1016/j.applthermaleng.2017.03.055
Krishnamoorthy, Gautham. Tue .
"A computationally efficient P1 radiation model for modern combustion systems utilizing pre-conditioned conjugate gradient methods". United States. https://doi.org/10.1016/j.applthermaleng.2017.03.055. https://www.osti.gov/servlets/purl/1533557.
@article{osti_1533557,
title = {A computationally efficient P1 radiation model for modern combustion systems utilizing pre-conditioned conjugate gradient methods},
author = {Krishnamoorthy, Gautham},
abstractNote = {The iterative convergence of the P1 radiation model can be slow in optically thin scenarios when employing classical iterative methods. In order to remedy this shortcoming, an in-house P1 radiation model was interfaced with high performance, scalable, linear solver libraries. Next, the accuracies of P1 radiation model calculations was assessed by comparing its predictions against discrete ordinates (DO) model calculations for prototypical problems representative of modern combustion systems. Corresponding benchmark results were also included for comparison. Utilizing Pre-Conditioners (PC) to the Conjugate Gradients (CG) method, the convergence time of the P1 radiation model reduced by a factor of 30 for modest problem sizes and a factor of 70 for larger sized problems when compared against classical Gauss Seidel sweeps. Additionally, PC provided 50% computational savings compared to employing CG in a standalone mode. The P1 model calculation times were about 25–30% of the DO model calculation time. The time to solution also scaled linearly with an increase in problem size. The weighted sum of gray gases model employed in this study in conjunction with the P1 model provided good agreement against benchmark data with L2 error norms (defined relative to corresponding DO calculations) improving when isotropic intensities were prevalent.},
doi = {10.1016/j.applthermaleng.2017.03.055},
journal = {Applied Thermal Engineering},
number = C,
volume = 119,
place = {United States},
year = {Tue Mar 14 00:00:00 EDT 2017},
month = {Tue Mar 14 00:00:00 EDT 2017}
}
Web of Science
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