界面张力梯度驱动对流向湍流转捩的研究

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doi:10.6052/1000-0992-20-022

中国科学院力学研究所微重力重点实验室, 北京 100190
中国科学院大学工程科学学院, 北京 100049

基金项目:

国家自然科学基金资助项目 (11972353, U1738116).

详细信息

作者简介:

**E-mail: kq@imech.ac.cn
康琦, 研究员、博士生导师. 中国科学院微重力重点实验室主任, 国际宇航联(IAF)微重力专业委员会委员, 空间科学学会理事, 《空间科学学报》副主编. 长期从事微重力流体物理等方面研究, 在SJ-10, TG-2, Taiji-1等任务中完成多项空间实验.
*E-mail: likai@imech.ac.cn
李凯, 研究员、博士生导师. 中国科学院BR计划引进国外杰出人才, 中国科学院微重力重点实验室副主任, 国科大岗位教授. 长期从事微重力流体力学、传热与流动控制、计算流体力学等方面研究, 上述领域发表SCI期刊论文40余篇;

通讯作者:
李凯
康琦

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出版历程
- 收稿日期:2020-09-14
- 刊出日期:2021-03-25

Study on bifurcation to chaos of surface tension gradient driven flow

National Microgravity Laboratory, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China
School of Engineering Science, University of Chinese Academy of Sciences, Beijing 100049, China

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Corresponding author:LI Kai;KANG Qi

摘要

摘要:作为空间自然对流热质输运的基本形式, 界面张力梯度驱动对流是流动和传热强耦合的复杂非线性过程, 也是一个多控制参数耦合作用的过程, 表现出丰富的流动时空特征. 界面张力梯度驱动对流是微重力流体物理的重要研究内容和学科前沿, 同时在空间燃料输运过程和空间能源或热管利用等空间流体管理问题中均有重要应用. 本文综述了界面张力梯度驱动对流向湍流转捩研究的背景意义、地面实验、空间实验及数值模拟的研究现状, 重点介绍了从非线性动力学角度来研究转捩规律的具体方法, 目前最常见的手段是对观测量的时间序列进行分析, 通过频谱分析及相空间重构等方法计算时间序列的特征量, 从而判断流动模式, 这类方法理论成熟, 计算简单, 但需要对大量数据进行繁琐的处理; 另一种方法是通过数值计算分岔来研究对流在时空中的转捩模式, 这类方法可以直接计算出分岔点, 但是复杂之处在于需要求解大规模的线性或非线性方程组, 本文详细阐述了两种方法的理论背景, 应用状况及局限性, 探讨了将两种方法相互结合, 在研究中互为补充的可能, 并对今后的研究方向提出了建议.
- 界面张力梯度驱动对流/
- 微重力/
- 分岔/
- 混沌
Abstract:As the primary heat and mass transfer mechanism in space through natural convection, surface tension gradient-driven convection is a complex nonlinear process concerning strong coupling between fluid flow and heat transfer. It is also a multiple parameter coupling process that exhibits complex spatial-temporal characteristics. Therefore, the mechanism of the surface tension gradient-driven convection becomes a hotspot in microgravity fluid physics. It also has many important applications, such as in space fluid and energy management. In this paper, recent experimental and numerical results on the transition of surface tension gradient-driven convection are reviewed, especially the nonlinear analysis on the flow bifurcations to chaos. There are several numerical methods to obtain the corresponding bifurcation diagrams. One is to integrate the model forward in time starting from different parameters and initial values, and others are to calculate the asymptotic flow states and bifurcation points directly. The direct numerical simulation method and time series analysis are widely used, but searching for bifurcation points from a large number of data is burdensome. Bifurcation points can be computed directly with the numerical bifurcation method, but such calculations are more difficult to implement than the direct numerical method.
- surface gradient tension-driven convection/
- microgravity/
- bifurcation/
- chaos

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