叶轮
蜗壳
机械
消散
计算流体力学
物理
滑移系数
湍流
熵产生
离心泵
涡流
涡度
热力学
作者
Wei Pu,Leilei Ji,Wei Li,Weidong Shi,Fei Tian,Wei Huang,Yang Yang,Xiwei Xu,Ramesh K. Agarwal,Song Jiang
摘要
To investigate the energy dissipation mechanisms within the pump and improve the computational accuracy of the solid–liquid flow numerical simulations, in this study, an improved CFD-DEM (Computational Fluid Dynamics - Discrete Element Method) method has been presented. First, the improved method of CFD-DEM is introduced, which mainly considers the turbulent dissipation of particles in the near-wall region and velocity field reconstruction. Then, the simulation results before and after the method's enhancement are compared. Finally, the analysis of the energy characteristics of the liquid phase flow field in the solid–liquid flow is conducted. Research shows that the modified CFD-DEM method significantly improves the accuracy of the particle distribution predictions, with the numerical results for head and efficiency being much closer to experimental values. In the high-speed regions of the impeller flow field, primarily located behind the pressure side of the blades, the liquid phase flow velocity and pressure fluctuations are less affected by changes in solid phase concentration. In the fluid region of the centrifugal pump, the energy loss caused by entropy production is significantly concentrated in the volute and impeller regions. Specifically, the entropy production dissipation in the volute region accounts for the substantial portion of the total entropy production, approximately 67%–68%, while the entropy production dissipation in the impeller region accounts for about 19.7%–20.4%. As the solid phase concentration increases, the energy dissipation within the pump gradually rises, and the total vorticity at the impeller inlet also increases correspondingly, with the vorticity distribution being related to the number of blades. The findings provide a reference for further exploring solid–liquid flow within centrifugal pumps.
科研通智能强力驱动
Strongly Powered by AbleSci AI