Nonlinear forecast of heat transfer coefficient signal in fluidized bed evaporator

Abstract

The focus of this work is on the local nonlinear forecast of evolution behavior of heat transfer coefficient in an evaporator with vapor–liquid–solid external natural circulation flow. Time series of heat transfer coefficients are calculated from the measured signals of wall and fluid temperatures in the fluidized bed evaporator. The times series predicted by a model of datum driving developed on the basis of reconstruction of phase space, are compared to the obtained signals experimentally according to the time-averaged statistics characteristics, power spectral density functions, phase maps and invariants of chaotic attractor of evolution system including correlation dimension and Kolmogorov entropy. The predictions of average heat transfer coefficients show reasonable agreements, and those of the heat transfer coefficient fluctuations display tendency agreements. The time series predictions for vapor–liquid–solid flow boiling system is not as good as those for vapor–liquid flow boiling and gas–liquid bubble column systems from the point of view of the time trajectory, which indicates certain essential differences between these systems in fluctuation mechanism and nonlinear complexity.