Yu Guangsuo

Development and demonstration plant operation of an opposed multi-burner coal-water slurry gasification technology

The features of the opposed multi-burner (OMB) gasification technology, the method and process of the research, and the operation results of a pilot plant and demonstration plants have been introduced. The operation results of the demonstration plants show that when Beisu coal was used as feedstock, the OMB CWS gasification process at Yankuang Cathy Coal Co. Ltd had a higher carbon conversion of 3%, a lower specific oxygen consumption of about 8%, and a lower specific carbon consumption of 2%–3% than that of Texaco CWS gasification at the Lunan Fertilizer Plant. When Shenfu coal was used as feedstock, the OMB CWS gasification process at Hua-lu Heng-sheng Chemical Co. Ltd had a higher carbon conversion of more than 3%, a lower specific oxygen consumption of about 2%, and a lower specific coal consumption of about 8% than that of the Texaco CWS gasification process at Shanghai Coking & Chemical Corporation. The OMB CWS gasification technology is proven by industrial experience to have a high product yield, low oxygen and coal consumption and robust and safe operation.

Experimental studying and stochastic modeling of residence time distribution in jet-entrained gasifier

The gasification technology of jet-entrained beds has been extensively applied to chemical production and the power generation. Residence time distribution (RTD) is required for modeling, design and optimization of jet-entrained gasifier. RTD in the gasifier was determined experimentally by impulse method. On the basis of the flow pattern, a stochastic model for RTD of materials in the gasifier has been developed, using Markov chain discrete formulation. The predicted results of Markov chain model give a reasonable fit of the experimental data, which shows that the process in the gasifier is stochastic and confirms that there are reflux and short-circuit in the gasifier and the flow pattern is inclined to perfect mixing.

The measurement of effective diffusivity for sulfur-tolerant methanation catalyst

Abstract The measurement of effective diffusivity for KD306 sulfur-tolerant methanation catalyst has been carried out using the ‘single pellet string reactor’ technique. The average tortuosity factor for KD306 catalyst was experimentally determined to be 7.2. The results of linearization method are in good agreement with the solutions of the parameter estimation method, which shows that the assumptions made in linearity processing are reasonable, and that the methods of linearization and parameter estimation can both be used to determine effective diffusivity efficiently.

The predictive model of bubble point based on neural network

The calculation of bubble point plays an important role in the chemical process of separation. Traditional methods are quite complicated, and they are also time-consuming tasks. In the paper, the bubble points in trays of a methanol distillation column are first calculated by process simulation software named Design II. Then, some of the data are used to train a backpropagation (BP) neural network and a radial basis function (RBF) neural network respectively. Finally neural networks are used to predict the left bubble points. The result indicates that the predicted data are in good agreement with the experimental data obtained by Design II, and the speed of the RBF neural network is better than that of the BP neural network.