Nonlinear Bubbling Hydrodynamics in a Gas-Liquid Bubble Column with a Single Nozzle
Nonlinear Bubbling Hydrodynamics in a Gas-Liquid Bubble Column with a Single Nozzle
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DOI：
10.2202/1542-6580.1071
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发表时间：
2003-01
影响因子：
1.6
通讯作者：
Mingyan Liu
中科院分区：
文献类型：
--
作者：
Mingyan Liu
本文对单喷嘴气液鼓泡塔中的混沌鼓泡机理进行了研究。用于分析的信号是从放置在靠近喷嘴的泡罩塔中的压力传感器探针测量的压力波动的时间序列。为了研究鼓泡过程，对压力波动进行了统计分析、定性和定量的非线性分析。功率谱作为标准的统计措施提供了初步的证据，在气体流量的中间值起泡可能是混乱的性质。相图提供了一种定性的手段来分析从起泡时间信号重建的吸引子的精细几何结构。Kolmogorov熵的正有限估计提供了与混沌一致的行为的定量证据。除了以前的诊断工具，当地的非线性短期预测也被用来作为一个补充方法。结果表明，在一定的气体流量范围内，鼓泡过程表现出确定性的混沌行为。随着气体流量的增加，气泡的演化顺序依次为周期性气泡、初级和高级混沌气泡、喷射或随机气泡。然而，没有观察到明确的倍周期序列导致混沌行为。用非线性预测方法成功地预测压力信号的能力的急剧丧失提供了混沌气泡存在的最强证据。Kolmogorov熵和关联维数等非线性不变量的变化以及关联积分随操作条件的变化曲线，可作为鼓泡过程流型识别的潜在有效的定量工具。
In this work, the chaotic bubbling mechanism in a gas-liquid bubble column with a single nozzle was investigated. The signal for the analysis was the time series of pressure fluctuations measured from a pressure transducer probe placed in the bubble column close to the nozzle. In order to study the bubbling process, statistical analysis, qualitative and quantitative non-linear analyses were carried out for the pressure fluctuations. Power spectra used as standard statistical measures provided preliminary evidence that bubbling in the middle values of gas flow rates may be chaotic in nature. Phase plots provided a qualitative means of analyzing the fine geometry structure of the attractor reconstructed from the bubbling time signal. Positive finite estimates of the Kolmogorov entropy provided a quantitative evidence of behavior consistent with chaos. Besides previous diagnostic tools, the local non-linear short-term prediction was also used as a supplement method. It was found that the bubbling process exhibits a deterministic chaotic behavior in a certain range of the gas flow rate. When increasing the gas flow rate, the sequence of periodic bubbling, primary and advanced chaotic bubbling, and jetting or random bubbling were successively observed. However, no clear period doubling sequence leading to chaotic behavior was observed. The sharp loss of the ability to predict the pressure signal successfully with the non-linear prediction method provides a strongest evidence of the presence of the chaotic bubbling. The variations of the non-linear invariants, such as the Kolmogorov entropy and the correlation dimension together with the plot of the correlation integral with the operation conditions, might be developed as potential and effective quantitative tools for flow regime identification of the bubbling process.