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Published on: June 1, 2016
Numerical Study of Stratified Flames Using Reynolds Averaged Navier Stokes Modeling
Mohammad Raghib Shakeel1, Esmail M A Mokheimer1,2,3
1Mechanical Engineering Department, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia.
Stratified flames were modeled using Reynolds averaged Navier-Stokes. Increasing stratification initially enhances burning and temperature, but shifts the flame downstream beyond a certain ratio.
Area of Science:
- Combustion science
- Computational fluid dynamics
- Turbulence modeling
Background:
- Stratified flames present complex combustion dynamics.
- Accurate numerical modeling is crucial for understanding flame behavior.
- Previous studies often relied on computationally intensive methods.
Purpose of the Study:
- To develop and validate a computationally efficient numerical model for stratified flames.
- To investigate the impact of varying stratification ratios on flame characteristics.
- To analyze the effects on temperature, combustion efficiency, and flame location.
Main Methods:
- Reynolds averaged Navier-Stokes (RANS) technique for numerical modeling.
- Validation against experimental data from the Cambridge dual annulus swirl burner.
- Utilized the RNG k-ε turbulence model and SG-35 skeletal chemical mechanism.
- Achieved a 99.75% reduction in computational time compared to LES.
Main Results:
- The model accurately predicted scalar and vector quantities.
- Intense burning near the bluff body observed at stratification ratios (SRs) of 1 and 2.
- Flame region shifted downstream for SR > 2 due to rich inner annulus mixtures.
- Maximum temperature increased by 24.1% from SR=1 to SR=2.
- Combustion efficiency improved by 267% at SR=2.
Conclusions:
- The RANS model with RNG k-ε and SG-35 provides an efficient and accurate tool for stratified flame simulation.
- Mild stratification (SR=2) optimizes temperature and combustion efficiency.
- Flame behavior is highly sensitive to the equivalence ratio and mixing dynamics in stratified flames.
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