chemically reacting flows
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2022 ◽  
Author(s):  
Thomas S. Brown ◽  
Harbir Antil ◽  
Rainald Lohner ◽  
Deepanshu Verma ◽  
Fumiya Togashi

2021 ◽  
pp. 23-39
Author(s):  
Thomas S. Brown ◽  
Harbir Antil ◽  
Rainald Löhner ◽  
Fumiya Togashi ◽  
Deepanshu Verma

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nikhil Kalkote ◽  
Ashwani Assam ◽  
Vinayak Eswaran

Purpose The purpose of this study is to present and demonstrate a numerical method for solving chemically reacting flows. These are important for energy conversion devices, which rely on chemical reactions as their operational mechanism, with heat generated from the combustion of the fuel, often gases, being converted to work. Design/methodology/approach The numerical study of such flows requires the set of Navier-Stokes equations to be extended to include multiple species and the chemical reactions between them. The numerical method implemented in this study also accounts for changes in the material properties because of temperature variations and the process to handle steep spatial fronts and stiff source terms without incurring any numerical instabilities. An all-speed numerical framework is used through simple low-dissipation advection upwind splitting (SLAU) convective scheme, and it has been extended in a multi-component species framework on the in-house density-based flow solver. The capability of solving turbulent combustion is also implemented using the Eddy Dissipation Concept (EDC) framework and the recent k-kl turbulence model. Findings The numerical implementation has been demonstrated for several stiff problems in laminar and turbulent combustion. The laminar combustion results are compared from the corresponding results from the Cantera library, and the turbulent combustion computations are found to be consistent with the experimental results. Originality/value This paper has extended the single gas density-based framework to handle multi-component gaseous mixtures. This paper has demonstrated the capability of the numerical framework for solving non-reacting/reacting laminar and turbulent flow problems. The all-speed SLAU convective scheme has been extended in the multi-component species framework, and the turbulent model k-kl is used for turbulent combustion, which has not been done previously. While the former method provides the capability of solving for low-speed flows using the density-based method, the later is a length-scale-based method that includes scale-adaptive simulation characteristics in the turbulence modeling. The SLAU scheme has proven to work well for unsteady flows while the k-kL model works well in non-stationary turbulent flows. As both these flow features are commonly found in industrially important reacting flows, the convection scheme and the turbulence model together will enhance the numerical predictions of such flows.


2017 ◽  
Vol 27 (12) ◽  
pp. 2768-2774
Author(s):  
Rainald Löhner ◽  
Fumiya Togashi ◽  
Joseph David Baum

Purpose A common observation made when computing chemically reacting flows is how central processing unit (CPU)-intensive these are in comparison to cold flow cases. The update of tens or hundreds of species with hundreds or thousands of reactions can easily consume more than 95% of the total CPU time. In many cases, the region where reactions (combustion) are actually taking place comprises only a very small percentage of the volume. Typical examples are flame fronts propagating through a domain. In such cases, only a small fraction of points/cells needs a full chemistry update. This leads to extreme load imbalances on parallel machines. The purpose of the present work is to develop a methodology to balance the work in an optimal way. Design/methodology/approach Points that require a full chemistry update are identified, gathered and distributed across the network, so that work is evenly distributed. Once the chemistry has been updated, the unknowns are gathered back. Findings The procedure has been found to work extremely well, leading to optimal load balance with insignificant communication overheads. Research limitations/implications In many production runs, the procedure leads to a reduction in CPU requirements of more than an order of magnitude. This allows much larger and longer runs, improving accuracy and statistics. Practical implications The procedure has allowed the calculation of chemically reacting flow cases that were hitherto not possible. Originality/value To the authors’ knowledge, this type of load balancing has not been published before.


2017 ◽  
Vol 96 (5) ◽  
Author(s):  
T. Elperin ◽  
N. Kleeorin ◽  
M. Liberman ◽  
A. N. Lipatnikov ◽  
I. Rogachevskii ◽  
...  

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