汽-液-固流动沸腾系统混沌时间序列的遗传算法全局建模

与系统的平均特性建模研究相比，系统的时间序列建模工作更富挑战性，也更具有意义.最近的研究表明，汽-液-固三相流动沸腾系统的动力学行为具有混沌特征，因此，本文从非线性视角出发，开展系统物理量的时间序列建模研究.根据实验测得的反映系统非线性演化信息的汽-液-固三相流动沸腾系统的壁温时间序列数据，采用遗传算法全局建模方法，建立了描述该系统非线性动力学行为的时间序列迭代形式的数学模型，并将模型计算结果与实验数据进行了比较.结果表明，采用遗传算法全局建模方法所建立的模型，能够较好地描述汽-液-固三相流动沸腾系统的非线性动力学行为，模型计算值与实验数据吻合良好.

Modeling of chaotic signals based on genetic algorithms in vapor-liquid-solid boiling flow

Time series modeling is more difficult but more meaningful than the modeling on the average characteristics of the system. It has recently been shown that the fluctuation behavior in the system with vapor-liquid-solid boiling flow is chaotic. Hence, the time series modeling was studied in this work from the point of view of nonlinear hydrodynamics. Based on the time series data of wall temperature of heated tube in an evaporator with vapor-liquid-solid boiling flow, the genetic algorithm is used to develop global models by which the nonlinear hydrodynamic behavior of the system can be described in different operation conditions. The model equations were in the forms of iteration functions. Comparison and analysis of the data obtained from the model and those from the experiments were made. The results showed that the calculated values from the models were in good agreement with those measured in the experiments, and the hydrodynamic behavior of the vapor-liquid-solid three phase flow system can be well described by these models.