Enhanced discrete phase model for multiphase flow simulation of blood flow with high shear stress.

Shear stress is often present in the blood flow within blood-contacting devices, which is the leading cause of hemolysis. However, the simulation method for blood flow with shear stress is still not perfect, especially the multiphase flow model and experimental verification. In this regard, this study proposes an enhanced discrete phase model for multiphase flow simulation of blood flow with shear stress. This simulation is based on the discrete phase model (DPM). According to the multiphase flow characteristics of blood, a virtual mass force model and a pressure gradient influence model are added to the calculation of cell particle motion. In the experimental verification, nozzle models were designed to simulate the flow with shear stress, varying the degree of shear stress through different nozzle sizes. The microscopic flow was measured by the Particle Image Velocimetry (PIV) experimental method. The comparison of the turbulence models and the verification of the simulation accuracy were carried out based on the experimental results. The result demonstrates that the simulation effect of the SST k-ω model is better than other standard turbulence models. Accuracy analysis proves that the simulation results are accurate and can capture the movement of cell-level particles in the flow with shear stress. The results of the research are conducive to obtaining accurate and comprehensive analysis results in the equipment development phase.

Multiple parameters and target optimization of splitter blades for axial spiral blade blood pump using computational fluid mechanics, neural networks, and particle image velocimetry experiment.

The blood pump is an implantable device with strict performance requirements. Any effective structural improvement will help to improve the treatment of patients. However, the research of blood pump structure improvement is a complex optimization problem with multiple parameters and objectives. This study takes the splitter blade as the object of structural improvement. Computational fluid mechanics and neural networks are combined in research and optimization. And hydraulic experiments and micro particle image velocimetry technology were used. In the optimization study, the number of blades, axial length and circumferential offset are optimization parameters, and hydraulic performance and hemolytic prediction index are optimization targets. The study analyzes the influence of each parameter on performance and completes the optimization of the parameters. In the results, the optimal parameters of number of blades, axial length ratio, and circumferential offset are 2.6° and 0.41°, respectively. Under optimized parameters, hydraulic performance can be significantly improved. And the results of hemolysis prediction and micro particle image velocimetry experiments reflect that there is no increase in the risk of hemolytic damage. The results of this study provide a method and ideas for improving the structure of the axial spiral blade blood pump. The established optimization method can be effectively applied to the design and research of axial spiral blade blood pumps with complex, high precision, and multiple parameters and targets.

Structural improvement study of streamline design method, conical hub, and auxiliary blades for axial blood pump.

The blood pump is a medical device used to assist or replace the diseased heart. Research on the structure of blood pumps has been committed to achieving better hemolysis and hydraulic performance. The purpose of this study was to find some effective ways to improve design methods and hydraulic structures. The research contents of improvement include: (1) improved blade streamline design method; (2) conical impeller hub; (3) additional auxiliary blades. Characteristic analysis and parameter design were carried out on the above three aspects. The methods used in this study included Dynamics (CFD) simulation, hydraulic experiments, and Particle Image Velocimetry (PIV) experiments. The results showed that this improved streamline design method could improve the distortion of blades and ensure a smaller impeller length. And, in the enhanced design of the hub, it is designed to be conical with inlet and outlet diameters of 7.5 and 12.8 mm, respectively. Furthermore, the auxiliary blades between the main blades are analyzed and designed. The results have the best performance optimization effect when the length of the auxiliary blades is 55% of the main blades. In general, the structural improvements in this study achieved the effect of improving hydraulic performance and avoiding increased hemolysis. These methods can be considered as an effective means of improving blood pump performance.

Analysis of flow field and hemolysis index in axial flow blood pump by computational fluid dynamics-discrete element method.

To fully study the relationship between the internal flow field and hemolysis index in an axial flow blood pump, a computational fluid dynamics-discrete element method coupled calculation method was used. Through numerical analysis under conditions of 6000, 8000, and 10,000 r/min, it was found that there was flow separation of blood cell particles in the tip of the impeller and the guide vane behind the impeller. The flow field has a larger pressure gradient distribution, which reduces the lift ratio of the blood pump and easily causes blood cell damage. The study shows that the hemolysis index obtained by the computational fluid dynamics-discrete element method is 4.75% higher than that from the traditional computational fluid dynamics method, which indicates the impact of microcollision between erythrocyte particles and walls on hemolysis index and also further verifies the validity of the computational fluid dynamics-discrete element coupling method. Through the hydraulic and particle image velocimetry experiments of the blood pump, the coincidence between numerical calculation and experiment is analyzed from macro and micro aspects, which shows that the numerical calculation method is feasible.