In modern automatic control, the control valve plays a very important role. The proper distribution and control of flowing liquid, gas, or solid powder requires a control valve to complete. The low-pressure pneumatic conveying device uses a blower as a power source, and the fan is at the front end of the feeding device, and the powder in the silo continuously goes high through the feeding device.
In modern automatic control, the control valve plays a very important role. The proper distribution and control of flowing liquid, gas or solid powder requires a control valve to complete. The low-pressure pneumatic conveying device uses a blower as a power source, and the fan is at the front end of the feeding device, and the powder in the silo is continuously and uniformly fed to the high-speed airflow through the feeding device, so that the powder is transported in a suspended state. In the pneumatic conveying device, it is necessary to control the material flow rate through the control valve, determine the settling speed of the material and the mass of the material delivered per unit time, to control the reasonable conveying wind speed and mixing ratio, which are the key factors affecting the conveying capacity and efficiency of the entire conveying system. factor.
The author numerically simulates the internal flow field of the material flow control valve in the pneumatic conveying system. The research work provided provides the basis for the design and performance optimization of the valve and the setting of the control device part of the pneumatic conveying system.
CONTROL VALVE MODEL AND MESHING
Figure 1 shows the established speed control valve model. Considering the flow in the valve as a plane-symmetric structure, a three-dimensional axisymmetric model is established to save computing resources.
According to the geometric characteristics of the valve, the complex flow path and the throttle opening in the valve are partially refined in advance, and the mesh division is shown in Fig. 2. In the iterative process, the pressure gradient and velocity gradient are adaptive functions, and the mesh is adaptively refined, which helps to improve the accuracy of the solution.
