High-Fidelity atomization simulation of kerosene swirl injector using Multi-Resolution framework

物理 喷油器 煤油 航空航天工程 分辨率(逻辑) 机械 忠诚 核工程 热力学 电气工程 人工智能 计算机科学 工程类
作者
Meng Zhang,Xiang Lv,Fangmian Dong,Shuai Zhou,Yuanzhe Liu,Peijin Liu,Hongjun Liu
出处
期刊:Physics of Fluids [American Institute of Physics]
卷期号:37 (3) 被引量:10
标识
DOI:10.1063/5.0258236
摘要

Swirl injectors play a pivotal role in the combustion components of liquid rocket engines, underscoring the paramount importance of accurate atomization modeling. In this study, we use a coupled Eulerian-Lagrangian approach to conduct high-precision simulations of fully developed atomization. These simulations are rigorously compared with experimental atomization patterns observed under cold conditions and during ignition phases. The results exhibit a remarkable consistency in atomization patterns and the spatiotemporal evolution of droplet morphology. The simulations yield high-resolution three-dimensional atomization images, capturing intricate perturbation wave structures whose evolution periods closely align with experimental findings. The resultant vortex structure field vividly depicts the evolution of these perturbation waves from the injector's interior to its exterior. The periodic intervals of unstable waves are governed by the impact of the upward gas swirl on the edge line of the injector's straight section. Furthermore, the simulated flow field structure validates the theoretical flow field diagram derived from experimental data reported in the literature. The simulation methodology successfully provides statistically reliable droplet size information. As operating conditions intensify, the droplet size-velocity distribution transitions from an L-shaped pattern to a triangular clump-like configuration. This transition underscores the method's capability to precisely simulate both primary and secondary atomization, along with the intricate evolution and distribution patterns of the atomization field across a diverse range of conditions, with both high speed and precision. Our findings demonstrate that the Eulerian-Lagrangian approach offers a robust framework for understanding and forecasting the complex atomization in liquid rocket engines, advancing atomization tech in aerospace.
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