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The condensation heat transfer coefficient of the multi-channel dryer, one of the key component of paper-making machine, directly determines the efficiency of heat energy utilization. However, the prediction of condensation heat transfer coefficient remains a challenge because the heat transfer characteristics in multi-channel dryer is a complex fundamental issue involving the thermal behavior of two-phase fluid systems. Herein, we successfully developed the four supervised machine learning models to predict the heat transfer coefficient of a multi-channel cylinder dryer under different working conditions. The multi-channel cylinder dryer experiments under different steam mass flux and cooling water mass flow rates were performed and the measured data is used as the input data for training. Interestingly, the four trained Bayesian-optimized machine models present the excellent capability of prediction for condensation heat transfer coefficient of multi-channel cylinder dryer, where the values of R2 for tested Bayesian-optimized-based SVR, ANN, linear SVR, and RF are 0.983, 0.997, 0.996, and 0.953, respectively. In addition, the feature importance of descriptors is quantified based on a random forest algorithm. Our study suggests that machine learning models can effectively predict the condensate heat transfer coefficient of two-phase fluid systems, which not only would be beneficial to optimizing the structures and operation parameters of multi-channel cylinder dryer in the industry but to develop a reasonable correlation of heat transfer coefficient in fundamental research. [ABSTRACT FROM AUTHOR]

Amaranth seeds can be popped by evaporation of contained moisture during heating. The relationships among the expansion ratio by popping and the type of heating media, gas temperature, initial moisture content of the seeds and heating time were clarified based on empirical study. And using a simple calculation model, the popping mechanism and effect of initial condensation of superheated steam were investigated. According to the results, the maximum volume of the seeds after popping was 8.7 times greater than that of raw seeds at optimal conditions. Compared with the case of hot air, the expansion ratio by superheated steam was slightly lower. [ABSTRACT FROM AUTHOR]