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基于Omega涡识别理论的自适应空化流动模型
屈念冲1,许开富1,项乐1,林荣浩2,党枭睿1
1.西安航天动力研究所,陕西 西安 710100;2.西安航天动力研究所 液体火箭发动机技术重点实验室,陕西 西安 710100
摘要:
液体火箭发动机涡轮泵内存在多种空化类型,其发生机理有所不同,现有数值计算方法通常采用同一套模型预测所有类型空化,导致预测精度不足。为提高复杂空化流动的计算精度,提出了自适应空化流动模型。基于先进的Omega涡识别理论和ZGB空化模型建立了相变系数自适应调整方法,以涡轮泵内两种典型空化(附着空化和泄漏涡空化)为对象,利用翼型实验对模型进行了验证。首先对比了几种涡识别方法的差异,发现Omega方法对阈值不敏感且物理意义明确,适合作为相变系数的取值依据;分析了相变系数对附着空化和泄漏涡空化的影响规律及两种典型空化的形成机理。结果表明:自适应模型相比ZGB模型,对泄漏涡空化的预测精度在大间隙下提升了约181%,小间隙提升了约27%,对附着空化的预测更接近实验结果;附着空化是吸力面脱落涡形成的原因,间隙泄漏流场的涡带和剪切层空化是由间隙泄漏涡和分离涡共同作用形成的。
关键词:  空化模型  Omega涡识别  相变系数  附着空化  叶顶间隙泄漏涡空化
DOI:10.13675/j.cnki.tjjs.2210076
分类号:V431
基金项目:
A self-adaptive cavitation model based on Omega vortex identification theory
QU Nianchong1, XU Kaifu1, XIANG Le1, LIN Ronghao2, DANG Xiaorui1
1.Xi’an Aerospace Propulsion Institute,Xi’an 710100,China;2.Science and Technology on Liquid Rocket Engine Laboratory,Xi’an Aerospace Propulsion Institute, Xi’an 710100,China
Abstract:
There are many complex types of cavitation in the turbopump of liquid rocket engine, and the occurrence mechanism is different. The existing cavitation numerical calculation methods usually use a set of models to predict all types of cavitation, which has certain deficiencies in the prediction accuracy of cavitation. To improve the calculation accuracy of complex cavitation flow, a self-adaptive cavitation model was proposed. Based on the advanced Omega vortex identification theory and ZGB cavitation model, a self-adaptive adjustment method for phase-transition coefficient was established. Two types of typical cavitation (attached cavitation and leakage vortex cavitation) in turbopumps were taken as the research objects, and the simulation method was verified by hydrofoil experiment data. Firstly, the differences of several vortex identification methods were compared. The result suggests Omega method is not sensitive to threshold and has clear physical meaning, which can be used as the value basis of the phase-transition coefficient. The effect of phase transition coefficient on attached cavitation and leakage vortex cavitation and mechanism of these two cavitations were analysed. The results show that compared with the ZGB model, the prediction accuracy of the self-adaptive model for leakage vortex cavitation is improved by 181% in the case of large clearance and 27% in the case of small clearance. The prediction of attached cavitation is closer to the experimental results. Attached cavitation is the reason of vortex shedding on suction surface. The vortex band and the shear layer cavitation of tip leakage flowfield are formed by the interaction of tip leakage vortex and separation vortex.
Key words:  Cavitation model  Omega vortex identification  Phase-transition coefficient  Attached cavitation  Tip leakage vortex cavitation