Optimal Control of Slurry Pressure during Shield Tunnelling Based on Random Forest and Particle Swarm Optimization

The control of slurry pressure aiming to be consistent with the external water and earth pressure during shield tunnelling has great significance for face stability,especially in urban areas or underwater where the surrounding environment is very sensitive to the fluctuation of slurry pressure.In this study,an optimal control method for slurry pressure during shield tunnelling is developed,which is composed of an identifier and a controller.The established identifier based on the random forest(RF)can describe the complex non-linear relationship between slurry pressure and its influencing factors.The proposed controller based on particle swarm optimization(PSO)can optimize the key factor to precisely control the slurry pressure at the normal state of advancement.A data set from Tsinghua Yuan Tunnel in China was used to train the RF model and several performance measures like R2,RMSE,etc.,were employed to evaluate.Then,the hybrid RF-PSO control method is adopted to optimize the control of slurry pressure.The good agreement between optimized slurry pressure and expected values demonstrates a high identifying and control precision.

Prediction of Pressure Drop of Slurry Flow in Pipeline by Hybrid Support Vector Regression and Genetic Algorithm Model

This paper describes a robust support vector regression （SVR） methodology, which can offer superior performance for important process engineering problems. The method incorporates hybrid support vector regression and genetic algorithm technique （SVR-GA） for efficient tuning of SVR meta-parameters. The algorithm has been applied for prediction of pressure drop of solid liquid slurry flow. A comparison with selected correlations in the lit- erature showed that the developed SVR correlation noticeably improved the prediction of pressure drop over a wide range of operating conditions, physical properties, and pipe diameters.

Study on the rheology of coal-oil slurries during heating at high pressure

Using the self-developed viscosity measuring device, the viscosity variations of coal-oil slurries with temperature increasing during coal-oil co-processing were studied. The results show that the viscosity of coal-oil slurries prepared by different kinds of oil varies differently during heating. The viscosity of the coal-oil slurry prepared by the catalytic cracking slurry （FCC） generally decreases during heating. However, the viscosity of the coal-oil slurry prepared by the high-temperature coal tar （CT） will peak at 338 ℃ during heating. The differences in viscosity variations of coal-oil slurries are analyzed. In addition to the temperature, the properties of the solvents and coal are the main influencing factors. Because the used coal contains a large number of polar functional groups, the swelling behavior of the coal in polar solvent （CT） is stronger than that in non-polar solvent （FCC）. The swelling effect of the coal can result in the appearance of the viscosity peak. Therefore, before 100 ~C, the solvent molecules entering into the coal pores is the main influencing factor of coal-oil slurries viscosity variations. After 100 ℃, the increasing of particle size of coal particles is the main influencing factor of coal-oil slurries viscosity variations.