Aquathermolysis of conventional heavy oil with superheated steam

This paper presents a new aquathermolysis study of conventional heavy oil in superheated steam. A new high temperature autoclave was designed, where volume and pressure could be adjusted. Aquathermolysis was studied on two different conventional heavy oil samples under different reaction times and temperatures. Experimental results show that aquathermolysis does take place for conventional heavy oil. As reaction time increases, the oil viscosity reduces. However, the reaction will reach equilibrium after a certain period of time and won＇t be sensitive to any further reaction time any more. Analysis shows that, while resin and asphaltenes decrease, saturated hydrocarbons and the H/C ratio increase after reaction. The main mechanism of aquathermolysis includes hydrogenization, desulfuration reaction of resin and asphaltenes, etc.

Thermal Hydraulic Design and Analysis of a Water-Cooled Ceramic Breeder Blanket with Superheated Steam for CFETR

The water-cooled ceramic breeder blanket（WCCB） is one of the blanket candidates for China fusion engineering test reactor（CFETR）.In order to improve power generation efficiency and tritium breeding ratio,WCCB with superheated steam is under development.The thermal-hydraulic design is the key to achieve the purpose of safe heat removal and efficient power generation under normal and partial loading operation conditions.In this paper,the coolant flow scheme was designed and one self-developed analytical program was developed,based on a theoretical heat transfer model and empirical correlations.Employing this program,the design and analysis of related thermal-hydraulic parameters were performed under different fusion power conditions.The results indicated that the superheated steam water-cooled blanket is feasible.

Characteristics and mathematical models of the thin-layer drying of paddy rice with low-pressure superheated steam

Drying paddy with low-pressure superheated steam(LPSS)can effectively increase theγ-aminobutyric acid content in paddy.This study aimed to investigate the characteristics and mathematical models(MMs)of thin-layer drying of paddy with LPSS.The experimentally obtained data werefitted by nonlinear regression with 5 MMs commonly used for thin-layer drying to calculate the goodness of fit of the MMs.Then,the thin-layer drying of paddy with LPSS was modeled with two machine learning methods as a Bayesian regularization back propagation(BRBP)neural network and a support vector machine(SVM).The results showed that paddy drying with LPSS is a reduced-rate drying process.The drying temperature and operating pressure have a significant impact on the drying process.Under the same pressure,increasing the drying temperature can accelerate the drying rate.Under the same temperature,increasing the operating pressure can accelerate the drying rate.The comparison of the model evaluation indexes showed that 5 common empirical MMs(Hederson and Pabis,Page,Midilli,Logarithmic,and Lewis)for thin-layer drying can achieve excellent fitting effects for a single experimental condition.However,the regression fitting of the indexes by calculating the coefficient(s)of each model showed that the empirical MMs produce poor fitting effects.The BRBP neural network-based model was slightly better than the SVM-based model,and both were significantly better than the empirical MM(the Henderson and Pabis model),as evidenced by a comparison of the training root mean square error(RMSE),testing RMSE,training mean absolute error(MAE),testing MAE,training R2,and testing R2 of the Henderson and Pabis model,the BRBP neural network model,and the SVM-based model.This results indicate that the MMs established by the two machine learning methods can better predict the moisture content changes in the paddy samples dried by LPSS.

Neuro-fuzzy generalized predictive control of boiler steam temperature

Power plants are nonlinear and uncertain complex systems. Reliable control of superheated steam temperature is necessary to ensure high efficiency and high load-following capability in the operation of modem power plant. A nonlinear generalized predictive controller based on neuro-fuzzy network （NFGPC） is proposed in this paper. The proposed nonlinear controller is applied to control the superheated steam temperature of a 200MW power plant. From the experiments on the plant and the simulation of the plant, much better performance than the traditional controller is obtained,

Effect of drying methods and parameters on the antioxidant properties of tea(Camellia sinensis)leaves

Background:Conventional drying using heated air oven is commonly used as a method for preserving the product but often affects the nutritional value,taste,and texture.However,the heat from the drying method can oxidize and destroy heat-sensitive compounds.Superheated steam(SHS)drying uses superheated steam instead of hot air or combustion gases in a direct dryer and was reported better at preserving the nutritional values of food products.Aim:To evaluate the effect of SHS drying on antioxidant properties of tea leaves.The study also compared SHS drying with conventional and freeze-drying methods.Results:Tea leaves dried using freeze drying retained the highest level of antioxidant properties compared to other drying methods.The leaves dried using SHS exhibited significantly higher radical scavenging activity,ORAC and FRAP values compared to oven drying method.At different drying temperatures(150℃and 175℃),oven dried leaves showed significantly higher(p<0.05)antioxidant properties than that of SHS dried ones.Tea leaves dried for 60,75,and 90 min using SHS showed significantly higher(p<0.05)FRAP and ORAC values,and also total phenolic content compared to oven dried tea leaves.Conclusion:Tea leaves dried using SHS drying method retained higher level of antioxidant properties compared to oven drying.The drying method also retained lower antioxidant properties as drying time increased.Further study involving SHS drying in food-related fields should be conducted to support its usefulness.