Machine learning assisted modeling of mixing timescale for LES/PDF of high-Karlovitz turbulent premixed combustion

2022 ◽  
Vol 238 ◽  
pp. 111895
Author(s):  
Jinlong Liu ◽  
Haifeng Wang
2018 ◽  
Vol 35 (4) ◽  
pp. 365-372
Author(s):  
Jong-Chan Kim ◽  
Won-Chul Jung ◽  
Ji-Seok Hong ◽  
Hong-Gye Sung

Abstract The effects of turbulent burning velocities in a turbulent premixed combustion simulation with a G-equation are investigated using the 3D LES technique. Two turbulent burning velocity models – Kobayashi model, which takes into account the burning velocity pressure effect, and the Pitsch model, which considers the flame regions on the premixed flame structure – are implemented. An LM6000 combustor is employed to validate the turbulent premixed combustion model. The results show that the flame structures in front of the injector have different shapes in each model because of the different turbulent burning velocities. These different flame structures induce changes in the entire combustor flow field, including in the recirculation zone. The dynamic mode decomposition (DMD) method and linear acoustic analysis provide the dominant acoustic mode.


2020 ◽  
Vol 29 (4) ◽  
pp. 853-867
Author(s):  
Gang Luo ◽  
Haidong Dai ◽  
Lingpeng Dai ◽  
Yunlou Qian ◽  
Ce Sha ◽  
...  

PAMM ◽  
2006 ◽  
Vol 6 (1) ◽  
pp. 539-540
Author(s):  
Benjamin Rembold ◽  
Patrick Jenny

2014 ◽  
Vol 161 (12) ◽  
pp. 3085-3099 ◽  
Author(s):  
Zacharias M. Nikolaou ◽  
Nedunchezhian Swaminathan ◽  
Jyh-Yuan Chen

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