同轴离心式喷嘴噪声引发燃烧不稳定分析和预测

杨尚荣; 王勇; 杨宝娥

doi:10.13224/j.cnki.jasp.20200404

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同轴离心式喷嘴噪声引发燃烧不稳定分析和预测

燃烧、传热、传质 | 更新时间：2025-04-07

- 同轴离心式喷嘴噪声引发燃烧不稳定分析和预测
- Analysis and prediction of noise⁃induced combustion instabilities of coaxial swirl injector
- 航空动力学报 2021年36卷第11期页码：2317-2324
- 作者机构：
  
  中国航天科技集团有限公司西安航天动力研究所液体火箭发动机技术重点实验室，西安 710100
- 作者简介：
  
  杨尚荣（1986-），男，高级工程师，博士，研究领域为液体火箭发动机喷雾燃烧。
- 基金信息：
  
  国家自然科学基金(51606138)
- DOI：10.13224/j.cnki.jasp.20200404
  中图分类号：
- 稿件说明：
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杨尚荣, 王勇, 杨宝娥. 同轴离心式喷嘴噪声引发燃烧不稳定分析和预测[J]. 航空动力学报, 2021,36(11):2317-2324.

Shangrong YANG, Yong WANG, Baoe YANG. Analysis and prediction of noise⁃induced combustion instabilities of coaxial swirl injector[J]. Journal of Aerospace Power, 2021, 36(11): 2317-2324.
杨尚荣, 王勇, 杨宝娥. 同轴离心式喷嘴噪声引发燃烧不稳定分析和预测[J]. 航空动力学报, 2021,36(11):2317-2324. DOI： 10.13224/j.cnki.jasp.20200404.

Shangrong YANG, Yong WANG, Baoe YANG. Analysis and prediction of noise⁃induced combustion instabilities of coaxial swirl injector[J]. Journal of Aerospace Power, 2021, 36(11): 2317-2324. DOI： 10.13224/j.cnki.jasp.20200404.

摘要

以氧化剂和燃料的混合比作为系统控制参数，研究同轴离心式喷嘴燃烧动力学过程。混合比增加和减少过程中，燃烧噪声和振荡燃烧状态间转变的混合比不同，说明系统出现了亚临界Hopf分叉现象，且在双稳定区内出现了燃烧噪声引发的振荡燃烧。利用临界慢化理论，分析3种表征参数：延迟为1自相关系数、方差和条件异方差（CH）对噪声引发不稳定的预警效果。结果表明：延迟为1自相关系数在噪声引发不稳定前出现明显的上升趋势且非随机现象，具有较可靠的指示作用。方差对噪声引发不稳定性的预示性较差。条件异方差在不稳定发生前振荡上升，可以作为辅助判断条件。基于Kendall秩相关系数趋势评估方法，提出一种在线预测噪声引发不稳定的判断准则，具有较好的适应性和可靠性。

Abstract

The combustion dynamics of a coaxial swirl injector was investigated with the mixture ratio of oxidant and fuel as the system control parameter.The mixture ratios at which the transitions between combustion noise and oscillatory state occurred were different for the forward path and for the reverse path.This difference indicated that the transition to the oscillatory state observed was subcritical Hopf bifurcation in nature.Noise⁃induced instabilities were observed in the bistable regime.The viability of three early warning measures such as lag⁃1 autocorrelation，variance and conditional heteroskedasticity （CH） to predict transition in the combustor was analyzed based on critical slowing down theory.It was found that lag⁃1 autocorrelation showed an increasing trend as the critical point was approached，enabling to predict catastrophic transitions as early warning signals.Variance may be less generic as an indicator of noise⁃induced instability.Significant CH showed an increasing trend，which can be used as an auxiliary judgment condition.An online prediction method of good adaptability and reliability for noised⁃induced instability based on Kendall rank correlation coefficient was proposed.

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references

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