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

同轴离心式喷嘴噪声引发燃烧不稳定分析和预测

doi: 10.13224/j.cnki.jasp.20200404

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

基金项目: 国家自然科学基金（51606138）

详细信息

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。

中图分类号: V231.1
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出版历程
- 收稿日期: 2020-09-21
- 刊出日期: 2021-11-28

Analysis and prediction of noise-induced combustion instabilities of coaxial swirl injector

Science and Technology on Liquid Rocket Engine Laboratory，Xi'an Aerospace Propulsion Institute， China Aerospace Science and Technology Corporation，Xi'an 710100，China

摘要

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。
- 同轴离心式喷嘴 /
- 噪声引发不稳定 /
- Hopf分叉 /
- 临界慢化 /
- 在线预测
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.
- coaxial swirl injector /
- noise-induced instability /
- Hopf bifurcation /
- critical slowing down /
- online prediction

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参考文献(21)

[1]	POINSOT T.Prediction and control of combustion instabilities in real engines[J].Proceedings of the Combustion Institute,2016,36:1-28.
[2]	LIEUWEN T.Online combustor stability margin assessment using dynamic pressure data[J].Journal of Engineering for Gas Turbines and Power,2005,127（3）:478-482.
[3]	YI T,GUTMARK E J.Online prediction of the onset of combustion instabilities based on the computation of damping ratios[J].Journal of Sound and Vibration,2008,310（1）:442-447.
[4]	NAIR V,THAMPI G,SUJITH R I.Intermittency route to thermoacoustic instability in turbulent combustors[J].Journal of Fluid Mechanics,2014,756:470-487.
[5]	NAIR V,SUJITH R I.Multifractality in combustion noise:predicting an impending combustion instability[J].Journal of Fluid Mechanics,2014,747:635-655.
[6]	MURUGESAN M,SUJITH R I.Detecting the onset of an impending thermoacoustic instability using complex networks[J].Journal of Propulsion and Power,2016,32:707-12.
[7]	GODAVARTHI V,UNNI V R,GOPALAKRISHNAN E A,et al.Recurrence networks to study dynamical transitions in a turbulent combustor[J].Chaos:An Interdiisciplinary Journal of Nonlinear Science,2017,27（6）:063113.1-063113.10.
[8]	HASHIMOTO T,SHIBUYA H,GOTODA H,et al.Spatiotemporal dynamics and early detection of thermoacoustic combustion instability in a model rocket combustor[J].Physical Review:E,2019,99（3）:032208.1-032208.7.
[9]	SARKAR S,CHAKRAVARTHY S R,RAMANAN V,et al.Dynamic data-driven prediction of instability in a swirl-stabilized combustor[J].International Journal of Spray and Combustion Dynamics,2016,8（4）:235-253.
[10]	XIONG S,MONDAL S,RAY A.Detection of thermoacoustic instabilities via nonparametric bayesian markov modeling of time-series data[J].Journal of Dynamic Systems,Measurement,and Control,2018,140（2）:024501.1-024501.7.
[11]	MONDAL S,GHALYAN N F,RAY A,et al.Early detection of thermoacoustic instabilities using hidden markov models[J].Combustion Science and Technology,2019,191（7/8/9）:1309-1336.
[12]	KOBAYASHI TT,MURAYAMA S,HACHIJO T,et al.Early detection of thermoacoustic combustion instability using a methodology combining complex networks and machine learning[J].Physical Review Applied,2019,11（6）:064034.1-064034.7.
[13]	SCHEFFER M,BASCOMPTE J,BROCK W A,et al.Early-warning signals for critical transitions[J].Nature,2009,461（7260）:53-59.
[14]	DAKOS V,CARPENTER S R,BROCK W A,et al.Methods for detecting early warnings of critical transitions in time series illustrated using simulated ecological data[J].PLoS One,2012,7（7）:e41010.1-e41010.20.
[15]	GOPALAKRISHNAN E A,SHARMA Y,JOHN T,et al.Early warning signals for critical transitions in a thermoacoustic system[J].Scientific Reports,2016,6:35310.1-35310.10.
[16]	AN Q,STEINBERG A M,JELLA S,et al.Early warning signs of imminent thermoacoustic oscillations through critical slowing down[J].Journal of Engineering for Gas Turbines and Power,2019,141（5）:054501.1-054501.4.
[17]	王延涛，薛帅杰，杨岸龙，等.同轴喷嘴自发激励高频燃烧不稳定性试验研究[J].宇航学报，2015，36（12）:1414-1420.
[18]	SEEKELL D A,CARPENTER S R,PACE M L.Conditional heteroskedasticity as a leading indicator of ecological regime shifts[J].American Naturalist,2011,178:442-451.
[19]	SAURABH A,KABIRAJ L,STEINERT R,et al.Noise-induced dynamics in the subthreshold region in thermoacoustic systems[J].Journal of Engineering for Gas Turbines and Power,2017,139（3）:031508.1-031508.6.
[20]	WAUGH I,JUNIPER M.Triggering in a thermoacoustic system with stochastic noise[J].International Journal of Spray and Combustion Dynamics,2011,3（3）:225-241.
[21]	LIEUWEN T C.Experimental investigation of limit-cycle oscillations in an unstable gas turbine combustor[J].Journal of Propulsion and Power,2002,18:61-67.