Dynamic Study Or Operation Conditions For Low Energy Consumption And High Drying Rate During Freezing Drying Of Cooked Beef Slice

Freeze drying is welcomed by consumers because it can maximize the retention of food and edible quality, but many food manufacturers step back owing to the high energy consumption. That also lead the Freeze drying only use for the high added value products. The study on the freeze drying process of heat and mass transfer, the relationship between operating parameters and the physical property at home and abroad are only the interpretation of the freeze drying process ignore optimize control study. The results of the study on statistical optimization model in recent years can only be used for the same type of the same material, and then the applicable scope is narrow. This thesis use cooked beef slices as raw material and divided the whole process of freeze drying into three stages. Then study and optimized analysis influence of the three drying chamber pressures and material thickness on the drying rate and drying energy consumption, in order to explore the ways of guaranteeing the drying rate while reducing the energy consumption of freeze drying. The influence of experimental parameters on the power of cold trap, vacuum pump and heating plate is studied, and the forecasting model of freeze dry energy consumption is established, with the result that saving energy consumption and time for the research of freeze drying. Study the relationship of sublimation drying coefficient, analytical drying coefficient and the ratio of latent heat of vaporization on the total heating with the experimental parameters, and establish and verify coefficient database to expand the applicability established high rate dynamic prediction model. Combined the prediction model of energy consumption and high rate, and we can realize prediction the dynamic variety of material temperature, moisture and energy consumption in freeze drying process. Provide theoretical guidance for freeze-drying process optimizing control and energy saving. The results were as follows:(1)The effect of drying chamber pressure on the drying rate is different from the heat and mass transfer requirements in the freeze-drying process. Studies have shown that the control relationship of cooked beef slices is:stage I is mass transfer controlled process, stage III is heat transfer controlled process and stage II is controlled by the interaction of heat and mass transfer, but the effect of mass transfer is slightly larger than heat transfer. So improve the drying rate in stage I low drying chamber should be used, stage III should use relatively high drying chamber pressure, phase II adopt moderate pressure.(2)The experiment obtained the optimal operation conditions for high rate and low consumption by a comprehensive scoring method. The optimization experiment result saved 21% energy consumption in the case of ensuring the drying rate dropped only 4.6% compared with the optimization results of high drying rate, that mean more benefit to maximize profits for manufacturers.(3)The research results on the relationship between the powers of the system of freeze dryer with the experimental parameters show that:cold trap power affected by the chamber pressure, the heating power is affected by the heating temperature and chamber pressure. According to this, established the energy consumption forecast model of freeze drying process, thus saving a lot of energy and time for the research work of freeze drying by means of predicted the energy consumption.(4)Sublimation drying coefficient is affected by pre-freezing method, pre-freezing rate, heating temperature, drying chamber pressure and material thickness. Analytical drying coefficient and the ratio of latent heat of vaporization on the total heating is only influence by material thickness. At last we established sublimation drying coefficient database and analysis of drying correlation coefficient database on the heating temperature is 80℃ respectively. The database can provide a parameters source for freeze drying.(5)The verification experiment is carry out to base on the database, the experimental results show that, the dynamic predict value of material temperature absolute error value is less than 5℃. The predict the moisture of material value for different thickness of the and pressure conditions the relative error between measured value and predict value is smaller (<10%).The extend model could be used to predict the material surface temperature, freezing temperature and moisture content of cooked beef slice within the material thickness of 6-30mm, chamber pressure 10～120Pa change layer.