Centrifugal blood pump impeller shape optimization design method based on parallel CFD numerical simulation

Abstract

The invention discloses a centrifugal blood pump impeller shape optimization design method based on parallel CFD numerical simulation. The method comprises the following steps: establishing a centrifugal blood pump model which comprises a blood pump shell and an internal impeller; dividing a network for the centrifugal blood pump model according to the required grid quantity, and encrypting the network at the key part to obtain a computational grid file; reading the computational grid file by using fluid dynamics calculation software, and obtaining a calculation area by establishing a control equation, determining initial conditions and boundary conditions, discretizing the control equation and solving calculation parameters in a given point manner; decomposing the calculation area and then executing parallel calculation to obtain a numerical simulation result of each time step in the calculation period; evaluating the comprehensive performance of the centrifugal blood pump model according to a numerical simulation result; and optimizing the shape of the impeller by combining a numerical simulation result and an engineering fluid mechanics theorem until a set performance standard is met. By means of the optimized impeller shape, the blood cell injury risk of ECMO equipment is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of blood pump impeller shape optimization, and more specifically, to a centrifugal blood pump impeller shape optimization design method based on parallel CFD numerical simulation. Background Art

[0002] Extracorporeal membrane oxygenation (ECMO) is mainly used to provide continuous extracorporeal respiration and circulation to patients with severe cardiopulmonary failure to maintain their lives. Figure 1 The operation process of the ECMO device shown in the figure, the device extracts venous blood from the patient's body and uses a centrifugal pump to drive the blood flow. The centrifugal pump plays a key role in this process. It drives the blood flow at a controllable speed to ensure stable circulation and prevent blood damage. Then, it enters the membrane oxygenator for gas exchange, removes carbon dioxide from the blood and adds oxygen. Finally, the temperature-regulated oxygen-rich blood is returned to the patient's artery or vein to provide continuous blood circulation and oxygenation support for critically ill patients to maintain vital signs. The essence of ECMO is a modified artificial heart-lung machine. The core parts are the membrane lung and the blood pump, which play the role of artificial lung and artificial heart respectively, and can provide long-term cardiopulmonary support for patients with severe cardiopulmonary failure. Among them, the blood pump that plays the role of artificial heart has received widespread attention and application. The centrifugal blood pump mainly provides power for the circulation of extracorporeal blood. There are various problems with the existing blood pumps. The comprehensive performance of the newly designed blood pump must meet requirements including extracorporeal blood pumping capacity, blood compatibility, and the degree of damage to red blood cells. In addition to laboratory testing, computational fluid dynamics (CFD) analysis is also commonly used for blood pump design verification. This method is faster, more time-saving and more cost-effective than laboratory in vitro testing.

[0003] The centrifugal blood pump is an indispensable component of the ECMO system, which mainly provides power for extracorporeal blood circulation. However, in practical applications, the centrifugal blood pump requires certain comprehensive performance. For example, it needs to have sufficient hydraulic performance to meet the power requirements for extracorporeal blood circulation, that is, it has good hemodynamic performance. For another example, it requires minimal impact on the blood, good blood compatibility, minimal damage to red blood cells, and reduced hemolysis. With the development of computational fluid dynamics (CFD), CFD technology is used to solve some structural and flow field problems in the design and optimization of blood pumps, thereby reducing the development cost and cycle of artificial hearts, namely blood pumps, which is of great significance to promoting the research and development of artificial hearts.

[0004] In the prior art, Sun et al. used the engineering fluid mechanics theorem to design the blood pump geometric model of the ECMO system, which is referred to as the benchmark model in this article. Figure 2 As shown, Figure 2 (a) is the front view of the centrifugal pump, Figure 2 (b) is the top view of the centrifugal pump, Figure 2 (c) is the top view of the impeller. The researchers conducted physical experiments on this model. The experiments tested that at 1550 revolutions per minute (rpm), the outlet flow rate was 3 liters per minute (L / min), verifying that the impeller of this model has good stability under high-speed rotation. The damage to blood in the ECMO system mainly occurs in the centrifugal blood pump. Therefore, before the blood pump enters clinical use, relevant performance evaluations must be carried out to meet the usage requirements. Currently, the application of CFD in the hemodynamic analysis of blood pumps is considered an important method for evaluating the blood compatibility of blood pumps before clinical use. CFD can accurately simulate the flow inside the blood pump and reduce the cost of blood pump development and laboratory experiment verification.

[0005] After analysis, the current geometric design and related physical experiments of blood pumps have the following defects:

[0006] 1) The drainage of the impeller flow channel of the blood pump in the benchmark model is poor, and its hydrodynamic performance is poor under high-speed rotation and causes large shear stress. Therefore, it is necessary to optimize the shape design of the impeller to reduce the shear stress and reduce the risk of blood cell damage in the ECMO device;

[0007] 2) Physical experiments require the production of expensive physical models, which have a long cycle and high development costs.

[0008] In summary, it is necessary to optimize the existing structural design of the blood pump to improve the comprehensive performance and reduce the cost of physical experiments. Summary of the Invention

[0009] The purpose of the present invention is to overcome the defects of the above-mentioned existing technologies and provide an optimized design method for the shape of the impeller of a centrifugal blood pump based on parallel CFD numerical simulation. The method includes the following steps:

[0010] Use 3D modeling software to establish a centrifugal blood pump model, which includes a blood pump housing and an internal impeller;

[0011] Divide the network of the centrifugal blood pump model according to the required grid size and encrypt the network at the set key parts to obtain a computational grid file;

[0012] Use computational fluid dynamics software to read the computational grid file, and obtain the computational domain by establishing control equations, determining initial conditions and boundary conditions, discretizing the control equations, and assigning solution calculation parameters;

[0013] Decompose the computational domain and perform parallel calculations to obtain the numerical simulation results at each time step within the computational period;

[0014] According to the numerical simulation results, evaluating the comprehensive performance of the centrifugal blood pump model;

[0015] The numerical simulation results are combined with the theorem of engineering fluid mechanics to optimize the impeller shape of the centrifugal blood pump model until the set performance standards are met.

[0016] Compared with the prior art, the advantage of the present invention is that, considering that physical experiments cannot effectively separate and analyze the liquid flow in the centrifugal pump, the present invention optimizes the impeller shape design to reduce shear stress through simulation using the open source computational fluid dynamics (CFD) toolkit OpenFOAM (Open Field Operation and Manipulation), thereby solving the problem of excessive shear stress caused by the impeller shape of the centrifugal pump of the extracorporeal membrane oxygenation (ECMO) device and reducing the risk of blood cell damage in the ECMO device.

[0017] Further features and advantages of the present invention will become apparent from the following detailed description of exemplary embodiments of the present invention with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention.

[0019] Figure 1 It is an operation flow chart of ECMO equipment in the prior art;

[0020] Figure 2 is a schematic diagram of the existing benchmark model;

[0021] Figure 3 is a schematic diagram of impeller dimensions and grids according to an embodiment of the present invention;

[0022] Figure 4 is a flow chart of a centrifugal blood pump impeller shape optimization design method based on parallel CFD numerical simulation according to one embodiment of the present invention;

[0023] Figure 5 Yes Figure 2 Schematic diagram of mesh division for numerical simulation experiments of the benchmark model;

[0024] Figure 6 is a schematic diagram of shear stress distribution on the impeller wall according to a numerical simulation result of an embodiment of the present invention;

[0025] Figure 7 is a schematic diagram of pressure field distribution according to a numerical simulation result of an embodiment of the present invention;

[0026] Figure 8is a schematic diagram of velocity field distribution according to a numerical simulation result of an embodiment of the present invention;

[0027] Fig. 9 Yes Figure 2 Schematic diagram of the flow change curve of the numerical simulation experiment based on the benchmark model. DETAILED DESCRIPTION

[0028] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that the relative arrangement of components and steps, numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present invention unless otherwise specifically stated.

[0029] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.

[0030] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered as part of the specification.

[0031] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limiting. Therefore, other examples of the exemplary embodiments may have different values.

[0032] It should be noted that like reference numerals and letters refer to similar items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0033] In general, the present invention provides a centrifugal blood pump impeller shape optimization design method based on parallel CFD numerical simulation, and designs two new impellers, respectively referred to as new model 1 and new model 2, see Figure 3 The impeller dimensions and meshes shown in Figure 3(a) are for the benchmark impeller. Figure 3 (b) is the impeller of the new model 1, Figure 3 (c) is the impeller of the new model 2. After parallel CFD numerical simulation, it is proved that the new impeller significantly reduces the shear stress. The software for CFD numerical simulation is open source and complete. The algorithm can be changed according to the calculation requirements, various customizations can be made, etc. At the same time, the parallel calculation method is used to quickly calculate large grids, which improves the calculation accuracy and speed.

[0034] Specifically, see Figure 4 As shown, the provided centrifugal blood pump impeller shape optimization design method based on parallel CFD numerical simulation includes the following steps:

[0035] Step S1, using three-dimensional modeling software to establish a centrifugal blood pump model, the model includes a blood pump housing and an internal impeller.

[0036] The centrifugal blood pump model is established by 3D modeling software, which includes the entire blood pump housing and the internal impeller. Figure 2 The blood pump geometric model is used as the benchmark model of the centrifugal blood pump.

[0037] Step S2, dividing the centrifugal blood pump model into a network according to the required mesh size, and encrypting the network at key locations to obtain a computational mesh file.

[0038] Meshing software can be used to divide the mesh according to the required mesh size, and the mesh can be encrypted at key locations such as the edge of the impeller to finally obtain the entire calculation mesh file.

[0039] For example, the blood pump model is meshed using unstructured tetrahedral grid units, and the grid calculation area is divided into a rotating area and a fixed area. The grids of the two areas are independent of each other, and the method for exchanging grid calculation information between the two areas can use an arbitrary grid interface method. The grid of the rotating area is completely wrapped around the outside of the impeller, and the rest is a fixed area.

[0040] Specifically, meshing software (such as SnappyHexMesh) can be used to divide the mesh according to the required mesh size. Since accurate calculation results are required, a finer mesh needs to be divided, and the mesh size is larger, so a parallel method is used to divide the mesh. Figure 5 The schematic diagram of the grid division of the benchmark model is shown in Figure 1, where the grid division results of the entire calculation area are shown in Figure 2. Figure 5 As shown in (a), the mesh is encrypted at key locations such as the edge of the impeller. Figure 5 As shown in (b). Since the structure of the calculation area is irregular and contains many complex curved shapes, the blood pump model is meshed using unstructured tetrahedral mesh units with a wider range of adaptability, and the mesh quality is guaranteed to meet the requirements.

[0041] In addition, since the blood pump only relies on the rotation of the impeller to drive the liquid flow in actual operation, the inlet and outlet of the blood pump are set as entrainment boundary conditions. Since the impeller in the blood pump performs a rotating rigid body motion, while the rest of the body is a stationary solid wall, the grid calculation area is divided into a rotating area and a fixed area, and the grids of the two areas are independent of each other. The method for exchanging grid calculation information between the two areas adopts the arbitrary grid interface method.

[0042] Step S3, using fluid dynamics calculation software to read the calculation grid file, and obtain the calculation area by establishing control equations, determining initial conditions and boundary conditions, discretizing the control equations, and giving solution calculation parameters.

[0043] In this step, the computational grid file is read using open source fluid dynamics computational software. The computational software includes the establishment of control equations, the establishment of initial conditions and boundary conditions, the discrete control equations, the given solution calculation parameters, etc. The discrete control equations include the initial conditions and boundary conditions after discretization.

[0044] In one embodiment, an open source fluid dynamics calculation software (such as OpenFOAM) is used to read the calculation grid file, and then the control equation is established, the initial conditions and boundary conditions are established, the control equation is discretized, the initial conditions and boundary conditions after discretization are obtained, and the control parameters for solving are given. For example, the control equation can use the Navier-Stokes equation, and introduce the k-omega SST turbulence model combined with the k-epsilon in the free flow and the k-omega model near the wall, and the finite volume method is used to discretize the control equation.

[0045] 1. Establishment of control equations

[0046] The blood flow field in the blood pump is an unsteady, incompressible Newtonian fluid, and its governing equation is described by the Navier-Stokes equations:

[0047]

[0048] Among them, U represents velocity, P represents pressure, ρ represents density, and μ represents viscosity.

[0049] Since the flow of blood in the blood pump is turbulent, turbulence is a very random, instantaneous flow state, and the flow velocity and flow direction will change every moment. And if you want to simulate turbulence very accurately, it takes a huge computational cost. Therefore, in this embodiment, a suitable turbulence model is introduced. Here, the k-omega SST turbulence model is selected. The k-omega SST turbulence model combines the k-epsilon in the free flow and the k-omega model near the wall. It does not use wall functions, so it is most accurate when solving the flow near the wall.

[0050] k-omega SST turbulence model:

[0051] Turbulent kinetic energy equation (k):

[0052]

[0053] Dissipation equation (ω):

[0054]

[0055] coefficient:

[0056] α=5 / 9,β=3 / 40,β* =9 / 100,δ=1 / 2,δ * =1 / 2

[0057] Where i, j = 1, 2, 3 represents the components of the x, y, and z axes in the three-dimensional coordinate system, U i represents the speed in the i direction, x j represents the displacement in the j direction, μ T represents the eddy viscosity coefficient, ω represents the dissipation rate, k represents the turbulent kinetic energy, μ represents the viscosity, τ ij represents the Reynolds stress.

[0058] 2. Determine initial conditions and boundary conditions

[0059] According to the physical experimental conditions, the inlet and outlet use the entrainment boundary condition, and the turbulence model uses the best k-omegaSST turbulence model. In addition, the impeller part is set as a rotating solid wall, and the rest of the blood pump part is set as a stationary solid wall.

[0060] 3. Discrete control equations, initial conditions and boundary conditions

[0061] For example, the governing equations are discretized using the finite volume method.

[0062] First, the time term in the equation is discretized by the Euler implicit method of velocity U with respect to time:

[0063]

[0064] Implicit discretization of convection terms:

[0065]

[0066] The Laplace term is implicitly discretized:

[0067]

[0068] Pressure term explicit discretization:

[0069]

[0070] Where superscript t represents the currently known time step, superscript * represents the prediction step to be sought, subscript f represents the value on the grid cell surface, subscripts P and N represent adjacent grid cells, Δt represents the time step, and S f Represents the surface vector of each face of the grid cell, V represents the volume of the grid cell, is the flux. I is the unit vector. ▽U * is the quantity defined at the body center, i.e., the velocity gradient at the mesh body center. (▽U * ) f is the quantity defined at the center of the surface, that is, the velocity gradient at the center of the grid surface.

[0071] 4. Given the solution calculation parameters

[0072] The control parameters are set according to the calculation boundary conditions, and the initial conditions at the inlet and outlet and the impeller are set. Given a discrete format, for example, the time first-order derivative term (unsteady term) format, gradient term format, divergence term format, Laplace term format, interpolation format, surface normal gradient format, etc. can be used.

[0073] Step S4, decomposing the calculation area and performing parallel calculations to obtain numerical simulation results for each time step within the calculation cycle.

[0074] In order to improve the computational efficiency, the computational area obtained in the above steps is decomposed and then parallelized. For example, open source fluid dynamics computing software is used to perform computations on a supercomputing platform with a large number of cores to obtain the numerical simulation results of each time step within the computational cycle, including the shear stress, pressure, and velocity distribution at various locations in the blood pump flow field. i

[0075] Figure 6 is a schematic diagram of the shear stress distribution on the impeller wall of the numerical simulation results, where Figure 6 (a) Corresponding to the baseline model, Figure 6 (b) corresponds to the new model 1, Figure 6 (c) Corresponding to the new model 2, the horizontal axis is the coordinates of the impeller wall point, dimensionless units, and the vertical axis is the shear stress, unit kPa. Figure 6 It can be seen that the wall shear stress of the baseline model exceeds 10kPa, which accounts for a large proportion, obviously exceeding the wall shear stress of the new model 1 and the new model 2. Therefore, the new model 1 and the new model 2 can effectively reduce the risk of blood cell damage, improve the safety of ECMO equipment, and have better fluid mechanics performance.

[0076] Figure 7 is a schematic diagram of the pressure field distribution of numerical simulation results, where Figure 7 (a) Corresponding to the baseline model, Figure 7 (b) Corresponding to the new model 1, Figure 7 (c) corresponds to the new model 2. Figure 7 It can be seen that the overall pressure distribution of the new model 1 and the new model 2 is basically below 8 kPa, while the pressure distribution of the baseline model is mostly around 10 kPa.

[0077] Figure 8 is a schematic diagram of the velocity field distribution of numerical simulation results, where Figure 8 (a) Corresponding to the baseline model, Figure 8 (b) Corresponding to the new model 1, Figure 8 (c) corresponds to the new model 2. Figure 8It can be seen that the baseline model, new model 1, and new model 2 have a maximum rotation speed of about 5.4 m / s at the tip of the impeller. Since the new model 1 and the new model 2 optimize the flow channel design of the impeller, they show better drainage effect.

[0078] Step S5, evaluating the comprehensive performance of the centrifugal blood pump according to the obtained numerical simulation results.

[0079] Based on the blood pump internal flow field data calculated above, the comprehensive performance of the designed centrifugal blood pump can be analyzed to determine whether the design should be further optimized until the requirements are met.

[0080] Step S6, combining the numerical simulation results with the theorem of engineering fluid mechanics to optimize the impeller shape.

[0081] For example, a new impeller shape is designed by combining the numerical simulation results with the engineering fluid mechanics theorem, and then returning to step S2, the new impeller designed is as follows: Figure 3 shown. Figure 3 (a) is the benchmark model. The rotor consists of 12 blades. The angle between each blade is 30 degrees. The gap between the blades is evenly distributed. The radius of the cavity in the middle of the rotor is 50 mm. Figure 3 (b) is the new model 1, the total number of blades and Figure 3 (a) The benchmark model remains consistent, consisting of 6 short blades and 6 long blades. The long blades extend upward and converge to the end point. The angle between each blade is 30 degrees, the blade flow channel gap is evenly distributed, and the radius of the rotor center cavity is 30 mm. Figure 3 (c) New Model 2 Figure 3 (b) Based on the new model 1, the 6 short blades will be extended to a total of 12 long blades. The angle between each blade is 30 degrees, the blade flow channel gap is evenly distributed, and the radius of the rotor middle cavity is 24 mm.

[0082] In summary, the present invention can decompose the calculation area by software, and then distribute each calculation area to an independent processor on the supercomputer. Each independent processor on the supercomputer uses a solver copy to perform parallel calculations on each calculation area, and information is exchanged during the calculation process to improve the calculation efficiency. After obtaining the blood pump flow field results of each time step in the calculation cycle of each calculation area, a merge process is performed to finally obtain the calculation result of the overall calculation area.

[0083] In order to further verify the effect of the present invention, numerical simulation and physical experimental verification were carried out, and the performance of the benchmark model and the designed new impeller model were analyzed and compared.

[0084] Since the blood pump is small in size and closed, the flow of liquid inside the blood pump cannot be observed in physical experiments. Figure 2 The benchmark model is simulated in parallel with CFD. Figure 5 is the grid division of the numerical simulation experiment of the benchmark model, where Figure 5 (a) is the grid division for the entire calculation area. Figure 5 (b) is the encrypted mesh for key parts such as impellers. Parallel CFD numerical simulation can reduce experimental costs and shorten experimental cycles. The numerical simulation can use the ORISE supercomputer of the Chinese Academy of Sciences: CPU: Hygon C86-7185 2.5GHz, 128GB RAM, 30 cores per node. The experiment used 30 nodes with a total of 900 cores to realize parallel CFD numerical simulation.

[0085] During the experiment, the three-dimensional, unsteady, incompressible continuity equation and momentum equation were used in the calculation of the flow field. The inlet and outlet boundary conditions of the blood pump were defined as entrainment boundary conditions, that is, the liquid flow was driven only by the rotation of the impeller. The impeller speed was set to 1550rpm, consistent with the physical experiment, that is, the speed was about 0.04 seconds / revolution. The start time of the numerical simulation was 0, the time step was 0.016 seconds, and the end time was 0.4 seconds.

[0086] Fig. 9 is the outlet flow rate variation curve of the numerical simulation result, where the horizontal axis is the time step, the unit is 0.016s, and the vertical axis is the flow rate, the unit is L / min. Fig. 9 It can be seen that the numerical simulation speed is set to 1550rpm under the same working conditions as the physical experiment. After 10 turns, the outlet flow rate is stable at 3L / min, which is consistent with the results of the physical experiment, proving the accuracy of the CFD numerical simulation method. In the experiment, the sliding grid method is used to simulate the rotation of the impeller, and the rotation is regarded as a rigid body motion. After the parameter conditions are determined as above, the numerical simulation is carried out, and the outlet flow rate is stable at 3L / min.

[0087] The experiment proves that the numerical simulation results of the benchmark model are consistent with the physical experimental results. And by comparing with the benchmark model impeller, the impeller new model 1 and new model 2 after shape optimization design effectively reduce the shear stress, verifying the feasibility and application value of the present invention.

[0088] In summary, compared with the prior art, the present invention has the following advantages:

[0089] 1) Two new impellers were designed by optimizing the shape of the blood pump impeller. Compared with the benchmark model blood pump, the numerical simulation results showed that the two new impellers had smaller shear stress, reducing the risk of blood cell damage in ECMO equipment and improving the safety of ECMO equipment;

[0090] 2) Physical experiments can only collect limited measurement data. The present invention uses CFD to visualize the shear stress, pressure, velocity and other data of the internal flow field of the blood pump. In the numerical simulation, the discrete solution of the Navier-Stokes equation, the introduction of the k-omega SST turbulence model, the inlet and outlet entrainment boundary conditions, the rotation area calculation, the parallel calculation and other computing technologies are successively used to improve the calculation efficiency and accuracy.

[0091] The present invention may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present invention.

[0092] Computer readable storage medium can be a tangible device that can hold and store instructions used by an instruction execution device. Computer readable storage medium can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination thereof. More specific examples (non-exhaustive list) of computer readable storage medium include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, for example, a punch card or a convex structure in a groove on which instructions are stored, and any suitable combination thereof. The computer readable storage medium used here is not interpreted as a transient signal itself, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagated by a waveguide or other transmission medium (for example, a light pulse by an optical fiber cable), or an electrical signal transmitted by a wire.

[0093] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0094] The computer program instructions for performing the operation of the present invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, Python, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed entirely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be personalized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present invention.

[0095] Various aspects of the present invention are described herein with reference to the flow charts and / or block diagrams of the methods, devices (systems) and computer program products according to embodiments of the present invention. It should be understood that each box of the flow chart and / or block diagram and the combination of each box in the flow chart and / or block diagram can be implemented by computer-readable program instructions.

[0096] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processor of the computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0097] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operating steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0098] The flow charts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the systems, methods and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a part of a module, a program segment or an instruction, and a part of the module, a program segment or an instruction contains one or more executable instructions for realizing the specified logical function. In some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions. It is well known to those skilled in the art that it is equivalent to implement it by hardware, implement it by software, and implement it by combining software and hardware.

[0099] Embodiments of the present invention have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements in the marketplace, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein. The scope of the present invention is defined by the appended claims.

Claims

1. A centrifugal blood pump impeller shape optimization design method based on parallel CFD numerical simulation, comprising the following steps: A centrifugal blood pump model is established by using three-dimensional modeling software, and the centrifugal blood pump model includes a blood pump housing and an internal impeller; Divide the centrifugal blood pump model into a network according to the required grid size, and encrypt the network at set key locations to obtain a computational grid file; The calculation grid file is read using fluid dynamics calculation software, and the calculation area is obtained by establishing control equations, determining initial conditions and boundary conditions, discretizing control equations, and solving calculation parameters for given points; After decomposing the calculation area, parallel calculation is performed to obtain numerical simulation results of each time step within the calculation cycle; According to the numerical simulation results, evaluating the comprehensive performance of the centrifugal blood pump model; The numerical simulation results are combined with the theorem of engineering fluid mechanics to optimize the impeller shape of the centrifugal blood pump model until the set performance standards are met.

2. The method according to claim 1, characterized in that: The grid division adopts unstructured tetrahedral grid units, and the grid calculation area is divided into independent rotating areas and fixed areas. The grid of the rotating area is wrapped around the outside of the impeller, and the rest is defined by the grid of the fixed area.

3. The method according to claim 1, characterized in that The control equation adopts the Navier-Stokes equation, which is expressed as: Among them, U represents velocity, P represents pressure, ρ represents density, and μ represents viscosity.

4. The method according to claim 1, characterized in that: The initial conditions and boundary conditions are established as follows: the inlet and outlet use entrainment boundary conditions; the turbulence model uses the k-omega SST turbulence model; the impeller of the centrifugal blood pump model is set as a rotating solid wall, and the rest of the model is set as a stationary solid wall.

5. The method according to claim 3, characterized in that: The discrete control equations include: The finite volume method is used to discretize the control equations, and the time term in the equation is discretized by the Euler implicit discretization of the velocity U with respect to time, which is expressed as: The convection term is implicitly discretized and expressed as: The Laplace term is implicitly discretized and expressed as: The pressure term is explicitly discretized and expressed as: Where superscript t represents the currently known time step, superscript * represents the prediction step to be calculated, subscript f represents the value on the grid cell surface, subscripts P and N represent adjacent grid cells, Δt represents the time step, and S f Represents the surface vector of each face of the grid cell, V represents the volume of the grid cell, is the flux, ▽U * is the velocity gradient at the center of the mesh.

6. The method according to claim 1, characterized in that The solution calculation parameters include: setting the initial conditions at the inlet and outlet and the impeller; giving a discrete format, including a time first-order derivative format, a gradient term format, a divergence term format, a Laplace term format, an interpolation format or a surface normal gradient format.

7. The method according to claim 1, characterized in that Decomposing the computation region and performing parallel computation includes: Decomposing the calculation region to obtain a decomposed calculation region; The decomposed calculation areas are distributed to independent processors of the supercomputer. Each independent processor uses a solver copy to perform parallel calculations on its own calculation area. Information is exchanged during the calculation process to obtain numerical simulation results for each time step within the calculation cycle of each calculation area. The results are then synthesized and processed to obtain the calculation results of the entire calculation area.

8. The method according to claim 1, characterized in that The key part is the impeller.

9. A computer-readable storage medium having a computer program stored thereon, wherein: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

10. A computer device comprising a memory and a processor, wherein a computer program capable of running on the processor is stored in the memory, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

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