Fluidization of non-spherical particles is very common in petroleum engineering.Understanding the complex phenomenon of non-spherical particle flow is of great significance.In this paper,coupled with two-fluid model,t...Fluidization of non-spherical particles is very common in petroleum engineering.Understanding the complex phenomenon of non-spherical particle flow is of great significance.In this paper,coupled with two-fluid model,the drag coefficient correlation based on artificial neural network was applied in the simulations of a bubbling fluidized bed filled with non-spherical particles.The simulation results were compared with the experimental data from the literature.Good agreement between the experimental data and the simulation results reveals that the modified drag model can accurately capture the interaction between the gas phase and solid phase.Then,several cases of different particles,including tetrahedron,cube,and sphere,together with the nylon beads used in the model validation,were employed in the simulations to study the effect of particle shape on the flow behaviors in the bubbling fluidized bed.Particle shape affects the hydrodynamics of non-spherical particles mainly on microscale.This work can be a basis and reference for the utilization of artificial neural network in the investigation of drag coefficient correlation in the dense gas-solid two-phase flow.Moreover,the proposed drag coefficient correlation provides one more option when investigating the hydrodynamics of non-spherical particles in the gas-solid fluidized bed.展开更多
Fluidized beds are widely used in many industrial fields such as petroleum,chemical and energy.In actual industrial processes,spherical inert particles are typically added to the fluidized bed to promote fluidization ...Fluidized beds are widely used in many industrial fields such as petroleum,chemical and energy.In actual industrial processes,spherical inert particles are typically added to the fluidized bed to promote fluidization of non-spherical particles.Understanding mixing behaviors of binary mixtures in a fluidized bed has specific significance for the design and optimization of related industrial processes.In this study,the computational fluid dynamic-discrete element method with the consideration of rolling friction was applied to evaluate the mixing behaviors of binary mixtures comprising spherocylindrical particles and spherical particles in a fluidized bed.The simulation results indicate that the differences between rotational particle velocities were higher than those of translational particle velocities for spherical and non-spherical particles when well mixed.Moreover,as the volume fraction of the spherocylindrical particles increases,translational and rotational granular temperatures gradually increase.In addition,the addition of the spherical particles makes the spherocylindrical particles preferably distributed in a vertical orientation.展开更多
基金the financial support by the National Natural Science Foundation of China(Grant No.51706055).
文摘Fluidization of non-spherical particles is very common in petroleum engineering.Understanding the complex phenomenon of non-spherical particle flow is of great significance.In this paper,coupled with two-fluid model,the drag coefficient correlation based on artificial neural network was applied in the simulations of a bubbling fluidized bed filled with non-spherical particles.The simulation results were compared with the experimental data from the literature.Good agreement between the experimental data and the simulation results reveals that the modified drag model can accurately capture the interaction between the gas phase and solid phase.Then,several cases of different particles,including tetrahedron,cube,and sphere,together with the nylon beads used in the model validation,were employed in the simulations to study the effect of particle shape on the flow behaviors in the bubbling fluidized bed.Particle shape affects the hydrodynamics of non-spherical particles mainly on microscale.This work can be a basis and reference for the utilization of artificial neural network in the investigation of drag coefficient correlation in the dense gas-solid two-phase flow.Moreover,the proposed drag coefficient correlation provides one more option when investigating the hydrodynamics of non-spherical particles in the gas-solid fluidized bed.
基金financially supported by the National Natural Science Foundation of China(Grant No.51706055).
文摘Fluidized beds are widely used in many industrial fields such as petroleum,chemical and energy.In actual industrial processes,spherical inert particles are typically added to the fluidized bed to promote fluidization of non-spherical particles.Understanding mixing behaviors of binary mixtures in a fluidized bed has specific significance for the design and optimization of related industrial processes.In this study,the computational fluid dynamic-discrete element method with the consideration of rolling friction was applied to evaluate the mixing behaviors of binary mixtures comprising spherocylindrical particles and spherical particles in a fluidized bed.The simulation results indicate that the differences between rotational particle velocities were higher than those of translational particle velocities for spherical and non-spherical particles when well mixed.Moreover,as the volume fraction of the spherocylindrical particles increases,translational and rotational granular temperatures gradually increase.In addition,the addition of the spherical particles makes the spherocylindrical particles preferably distributed in a vertical orientation.
