High-degree-of-freedom artificial heart valve multi-objective geometric optimization design method

Abstract

The invention discloses a high-degree-of-freedom artificial heart valve multi-objective geometric optimization design method, and relates to the technical field of medical instruments, and the method comprises the following steps: carrying out parameterized geometric modeling on an artificial heart valve by adopting a variable-parameter geometric curve to obtain a valve leaflet geometric model of a polymer valve; importing the valve leaflet geometric model into simulation software for finite element simulation, wherein the simulation software has secondary development capability; finite element simulation is solved, and a simulation result is optimized by using a multi-objective optimization algorithm; and selecting an optimal valve parameter combination from the Pareto frontier as a final optimization result. Through a high-degree-of-freedom parametric modeling method, finite element simulation, a multi-objective optimization algorithm and an automatic design process are combined, rapid performance optimization of valve geometry is achieved, the method is not only suitable for artificial heart valve design, but also can be expanded to geometric construction and optimization of flexible medical instruments, and the method is suitable for popularization and application. And a new normal form is provided for the development of standardized and intelligent medical instruments.

Description

Technical Field

[0001] The present invention relates to the technical field of medical devices, and in particular to a multi-objective geometric optimization design method for an artificial heart valve with a high degree of freedom. Background Art

[0002] Prosthetic heart valves are key devices for treating valvular heart disease. In recent years, polymer prosthetic heart valves (PHVs) have become a research hotspot due to their biocompatibility and potential for automated manufacturing. However, their performance is limited by insufficient geometric design flexibility, low efficiency of single-objective optimization, and fragmented design processes.

[0003] Traditional valve geometry design often uses fixed-parameter models (such as parametric frameworks based on a small number of control points), which are difficult to adapt to individual needs. Optimization methods often rely on single-objective algorithms, which cannot balance conflicts between stress distribution, opening area, and fatigue performance. Furthermore, the modeling, simulation, and optimization processes require manual integration, severely restricting design efficiency.

[0004] Therefore, those skilled in the art are committed to developing a multi-objective geometric optimization design method for artificial heart valves with a high degree of freedom. Summary of the Invention

[0005] In view of the above-mentioned defects of the prior art, the technical problem to be solved by the present invention is that the existing valve geometric model relies on fixed parameters or a small number of control points, has low flexibility, and is difficult to quickly adapt to different anatomical requirements or optimization goals.

[0006] To achieve the above objectives, the present invention provides a high-degree-of-freedom multi-objective geometric optimization design method for an artificial heart valve, the method comprising the following steps:

[0007] S101: performing parametric geometric modeling on the artificial heart valve using a geometric curve with variable parameters to obtain a leaflet geometric model of the polymer valve;

[0008] S103: importing the leaflet geometric model into simulation software for finite element simulation, wherein the simulation software has secondary development capability;

[0009] S105: solving the finite element simulation and optimizing the simulation results using a multi-objective optimization algorithm;

[0010] S107: Select the optimal valve parameter combination in the Pareto front as the final optimization result.

[0011] Furthermore, in step S101, the artificial heart valve adopts a tri-leaflet valve, and the valve is modeled by a plurality of basic curves, wherein the basic curves include an attached edge curve, an abdominal curve and a free edge curve, wherein:

[0012] The attachment edge curve is formed by stretching a spline curve with one or more control points on the side view plane and intersecting the cylindrical surface;

[0013] The free edge curve is located at the horizontal plane where the highest point of the valve is located, and is composed of a spline curve. The free edge curve is set with multiple control point parameters;

[0014] The abdominal curve is generated by the spline curve with movable control points on the side view plane.

[0015] Furthermore, with the free edge curve and the attachment curve as boundaries and the abdominal curve as a guide line, a single leaflet is lofted out, and with the single leaflet as a solid and the Z axis as a rotation axis, a 120° rotation array is performed to obtain a complete leaflet geometric model.

[0016] Furthermore, the leaflet geometric model includes multiple variable parameters, and the variable parameters include: the coordinates of the abdominal curve control point, the coordinates of the attachment curve control point, the valve height, the gap between the leaflet and the central axis, and the gap between adjacent leaflets.

[0017] Furthermore, the spline curve uses a B-Spline curve, and the B-Spline curve is set as:

[0018]

[0019] in,

[0020]

[0021] U={u0,u1,u2,…,u m},u i ≤u i+1 ,i=0,1,…,m-1

[0022] Among them, C(u) is the B-Spline curve, N i,p (u) is the basis function of the i-th B-Spline curve with degree p, P i is the control point, U is the node vector, u i ∈U is the node, m is the number of nodes, and p is the number of times.

[0023] Furthermore, in step S103, during the finite element simulation process, a completely fixed constraint is set on the attachment edge of the leaflet, and the transvalvular pressure difference curve of the aortic valve in a normal human body is used as the physiological dynamic load boundary condition of the valve finite element simulation. The load is applied to the ventricular side surface of the polymer aortic valve, and the load loading direction is perpendicular to the ventricular side surface. The linear elastic constitutive model is used as the constitutive model of the leaflet.

[0024] Furthermore, in step S105, when solving the finite element simulation, a dynamic display solution method or a fluid-solid coupling solution method is used, wherein,

[0025] The dynamic display solution method loads the transvalvular pressure difference within one or more cardiac cycles on the ventricular side of the valve to make the valve open and close periodically, solves the mechanical equilibrium equation explicitly, and maintains quasi-static state during the calculation;

[0026] The fluid-solid coupling solution method adopts the immersed boundary method and performs relevant settings on the valve, blood vessel wall and blood flow domain.

[0027] Furthermore, in step S105, the multi-objective optimization algorithm includes multiple key performance indicators, an objective function is formed by the multiple key performance indicators, and the objective function is optimized. The key performance indicators include: maximum stress, deformation, open area, valve opening degree and fatigue life estimation.

[0028] Furthermore, the multi-objective optimization algorithm is configured as NSGA-II algorithm, swarm algorithm or gradient algorithm to complete the multi-objective optimization process.

[0029] Furthermore, the method drives the seamless connection of modeling, simulation and optimization tools through an automated interface protocol, secondary develops the finite element simulation process, and integrates it with the parametric geometric modeling process to achieve automated simulation and multi-objective optimization of multi-parameter polymer valves.

[0030] In a preferred embodiment of the present invention, compared with the prior art, the present invention has the following beneficial effects:

[0031] 1. This invention dynamically adjusts key dimensions of geometric morphology through variable parameters, covers the diversity of design space, supports rapid adaptation to different anatomical requirements, and greatly improves design flexibility;

[0032] 2. The present invention dynamically weighs multiple objectives based on simulation data, such as stress, strain, opening area and fatigue resistance performance indicators, generates a Pareto optimal solution set, improves comprehensive performance, such as fatigue life and opening area, and avoids single-objective bias.

[0033] The concept, specific structure and technical effects of the present invention will be further described below in conjunction with the accompanying drawings to fully understand the purpose, characteristics and effects of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a schematic flow chart of a design method of a preferred embodiment of the present invention;

[0035] Figure 2is a schematic diagram of a leaflet geometric model of a preferred embodiment of the present invention;

[0036] Figure 3 This is a schematic diagram of valve simulation optimization according to a preferred embodiment of the present invention;

[0037] Figure 4 It is a schematic diagram of the valve opening degree of a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0038] The following describes several preferred embodiments of the present invention with reference to the accompanying drawings to make its technical content clearer and easier to understand. The present invention can be embodied in many different forms of embodiments, and the scope of protection of the present invention is not limited to the embodiments mentioned herein.

[0039] In the drawings, components with identical structures are denoted by the same reference numerals, and components with similar structures or functions are denoted by similar reference numerals. The size and thickness of each component shown in the drawings are arbitrary and are not limited by the present invention. For clarity, the thickness of components in some places in the drawings is appropriately exaggerated.

[0040] like Figure 1 As shown, the existing valve geometry model relies on fixed parameters or a small number of control points. The parametric framework based on a small number of control points has low flexibility and is difficult to quickly adapt to different anatomical requirements or optimization goals. The present invention provides a high-freedom multi-objective geometric optimization design method for artificial heart valves, which combines finite element simulation, multi-objective optimization algorithm and automated design process to achieve rapid performance optimization of valve geometry.

[0041] The embodiment of the present invention provides a multi-objective geometric optimization design method for an artificial heart valve with a high degree of freedom, comprising the following steps:

[0042] S101: performing parametric geometric modeling on an artificial heart valve using a geometric curve with variable parameters to obtain a leaflet geometric model of the polymer valve.

[0043] like Figure 2 As shown, in this embodiment, the artificial heart valve adopts a tri-leaf valve, and the valve is modeled by multiple basic curves, including an attached edge curve, an abdominal curve and a free edge curve, wherein:

[0044] 1) Attachment edge curve: It is formed by stretching a spline curve with one or more control points on the side view plane and intersecting it with the cylindrical surface;

[0045] 2) Free edge curve: Located on the horizontal plane of the highest point of the valve, it is composed of a spline curve and has multiple control point parameters.

[0046] 3) Abdomen curve: generated by a spline curve with movable control points on the side view plane.

[0047] In this embodiment, when modeling the leaflet geometric model, the free edge curve and the attachment curve are used as boundaries, and the abdominal curve is used as a guide line to loft out a single leaflet; then, the single leaflet is used as an entity, the Z axis is used as the rotation axis, and a 120° rotation array is performed to obtain a complete leaflet geometric model.

[0048] In the modeling process of this embodiment, the leaflet geometry model is modeled using dynamic geometric parameterization. The model includes multiple variable parameters, thereby achieving a prosthetic heart valve with a high degree of freedom. These variable parameters include the coordinates of the abdominal curve control points, the coordinates of the attachment curve control points, the valve height, the gap between the leaflets and the central axis, and the gap between adjacent leaflets.

[0049] During the modeling process, the spline curve uses the B-Spline curve, and the B-Spline curve is set as follows:

[0050]

[0051] in,

[0052]

[0053] U={u0,u1,u2,…,u m},u i ≤u i+1 ,i=0,1,…,m-1

[0054] Among them, C(u) is the B-Spline curve, N i,p (u) is the basis function of the i-th B-Spline curve with degree p, P i is the control point, U is the node vector, u i ∈U is the node, m is the number of nodes, and p is the number of times.

[0055] S103: Importing the leaflet geometric model into simulation software for finite element simulation, where the simulation software has secondary development capabilities.

[0056] In this embodiment, during the finite element simulation process, a completely fixed constraint is set on the attachment edge of the leaflet, and the transvalvular pressure difference curve of the aortic valve in a normal human body is used as the physiological dynamic load boundary condition of the valve finite element simulation. The load is applied to the ventricular side surface of the polymer aortic valve, and the load loading direction is perpendicular to the ventricular side surface. The linear elastic constitutive model is used as the constitutive model of the leaflet.

[0057] S105: Solve the finite element simulation and optimize the simulation results using a multi-objective optimization algorithm.

[0058] When solving finite element simulations, use the dynamic display solution method or the fluid-structure interaction solution method, where:

[0059] Dynamic explicit solution method: A transvalvular pressure difference is applied to the ventricular side of the valve for one or more cardiac cycles, causing the valve to open and close periodically. The mechanical equilibrium equations are solved explicitly, and quasi-static conditions are maintained during the calculation.

[0060] Fluid-solid coupling solution method: The immersed boundary method is used, and relevant settings are made for the valve, blood vessel wall and blood flow domain.

[0061] In this embodiment, a multi-objective optimization algorithm is used to optimize the simulation results. The multi-objective optimization algorithm includes multiple key performance indicators, and the objective function is composed of multiple key performance indicators. The objective function is optimized to improve the comprehensive performance, such as fatigue life, opening area, etc., to avoid single-objective bias.

[0062] In the multi-objective optimization algorithm, the key performance indicators among the multi-objectives include: maximum stress, deformation, open area, valve opening degree and fatigue life estimation.

[0063] In this embodiment, the multi-objective optimization algorithm may select the NSGA-II algorithm, the swarm algorithm, or the gradient algorithm to complete the multi-objective optimization process and ensure the optimization effect.

[0064] S107: Select the optimal valve parameter combination in the Pareto front as the final optimization result.

[0065] According to the multi-objective optimization results, the optimal solution set and its corresponding performance indicators are obtained in the Pareto front. The maximum stress is closely related to the fatigue performance of the valve. The parameter combination with the minimum maximum stress can be selected as the final optimization result in the Pareto front of the optimization result.

[0066] In this embodiment, the optimization method provided by the present invention drives the seamless connection of modeling, simulation and optimization tools through an automated interface protocol, secondary develops the finite element simulation process, and integrates it with the parametric geometric modeling process to achieve automated simulation and multi-objective optimization of multi-parameter polymer valves. It can be integrated into a closed-loop design system, which can significantly shorten the design cycle and adapt to the rapid development needs of personalized medical devices.

[0067] Compared with the prior art, the embodiment of the present invention provides a multi-objective geometric optimization design method for an artificial heart valve with a high degree of freedom, which has the following characteristics:

[0068] 1. Existing valve geometry models rely on fixed parameters or a small number of control points, which are inflexible and difficult to quickly adapt to different anatomical requirements or optimization goals. The present invention implements dynamic geometric parametric modeling, dynamically adjusting key geometric dimensions (such as height and gap) through variable parameters, covering the diversity of the design space, supporting rapid adaptation to different anatomical requirements, and significantly improving design flexibility;

[0069] 2. The efficiency of multi-objective optimization in existing technologies is low. Existing optimization methods cannot systematically balance the conflicts between key valve performance indicators such as valve opening area, stress distribution and fatigue resistance, resulting in long design cycles and performance compromises. The present invention adopts a multi-objective collaborative optimization strategy to dynamically weigh objectives (such as stress, strain, opening area, and fatigue resistance indicators) based on simulation data to generate a Pareto optimal solution set, effectively improving comprehensive performance such as fatigue life and opening area, and avoiding single-objective bias;

[0070] 3. Existing technologies separate design and simulation. In existing design processes, geometric modeling and finite element simulation must be manually integrated, resulting in a low level of automation and hindering rapid iteration. This invention provides an integrated closed-loop design system that seamlessly connects modeling, simulation, and optimization tools through automated interface protocols. This system can significantly shorten the design cycle and meet the needs of rapid development of personalized medical devices.

[0071] The present invention will be described in detail below in conjunction with the preferred embodiments of the present invention.

[0072] like Figure 1 As shown, an embodiment of the present invention provides a multi-objective geometric optimization design method for an artificial heart valve with a high degree of freedom, including the following:

[0073] 1. Parametric geometric modeling of valves

[0074] In this embodiment, a three-leaf valve is used. Figure 2 As shown, the three basic curves of the valve are all modeled using geometric curves with variable parameters such as B-Spline.

[0075] For a given node vector

[0076] U={u0,u1,u2,…,u m},u i ≤u i+1 ,i=0,1,…,m-1

[0077] Then the i-th B-spline basis function N with degree p is i,p (u) is defined by the recursive formula as follows:

[0078] Initial conditions:

[0079]

[0080] Recursive formula:

[0081]

[0082] If the denominator is 0, the corresponding term is defined as 0.

[0083] The B-spline curve is defined as follows: given the control points P0, P1, ...P n and the node vector U, the B-spline curve of degree p is expressed as:

[0084]

[0085] like Figure 2 As shown, (a) is the design details of the free edge, (b) is the side view and design details of the attached edge, (c) is the design details of the abdominal curve, (d) is the complete design of the trileaflet valve, and (e) is the top view and front view of the valve. Figure 2 The three basic curves in include the attached edge curve, the belly curve and the free edge curve. Figure 2 (d) are FixedBoundary Edge, Belly Edge and Free Edge respectively.

[0086] 1) Attachment edge: draw a spline curve sketch with one (or more) control points (variable points) on the side view surface, and then stretch the surface to form a curve that intersects with the cylindrical surface.

[0087] 2) The free edge is located at the horizontal plane where the highest point of the valve is located and is composed of a spline curve with multiple control points and variable parameters.

[0088] 3) The abdominal curve is generated by a spline curve sketch with movable control points drawn on the side view plane.

[0089] The leaflet geometry model of the polymer valve can be drawn based on the basic curve of the valve. Using the free edge and the attachment curve as the boundary and the abdominal curve as the guide line, a single leaflet is obtained by lofting, such as Figure 2 As shown in the figure, a single leaflet is taken as a solid body and the z-axis is used as the rotation axis. A 120-degree rotation array is performed to obtain a complete leaflet geometric model of the polymer valve.

[0090] With this design, a variable-parameter polymer valve has seven variable parameters: the y and z coordinates of the abdominal curve control point, the y and z coordinates of the attachment curve control point, the valve height, the gap between the leaflets and the central axis, and the gap between adjacent leaflets. These seven variable parameters also correspond to seven degrees of freedom, forming a multi-degree-of-freedom valve geometry control system. These seven degrees of freedom have different variable ranges depending on the desired valve radius and the patient's vascular structure.

[0091] 2. Valve Simulation Process

[0092] The established leaflet geometry model is imported into secondary development simulation software such as ABAQUS2022 (Dassault Systèmes, France) to perform explicit dynamics solution or fluid-structure interaction solution.

[0093] Taking the dynamic display solution as an example, the polymer valve leaflets are fixed by the valve stent, so the attachment edge of the leaflets is completely fixed. The transvalvular pressure difference curve of the aortic valve in a normal human body is used as the physiological dynamic load boundary condition of the valve finite element simulation. The transvalvular curve is as follows: Figure 3 As shown in (b). The load is applied to the ventricular side surface of the polymer aortic valve, and the load loading direction is perpendicular to the surface. Figure 3 As shown in the figure, a linear elastic constitutive model is used as the constitutive model for the valve leaflets. The motion of the valve during one (or more, to ensure solution stability) cardiac cycle is calculated using an explicit solver. Specifically, a transvalvular pressure differential is applied to the ventricular side of the valve over the course of one cardiac cycle, causing the valve to periodically open and close. The calculations utilize an explicit solution of the mechanical equilibrium equations, maintaining a quasi-static state.

[0094] Taking fluid-structure interaction as an example, LS-DYNA software is used, and common fluid-structure interaction methods such as the immersed boundary method are adopted. Relevant settings are made for the valve, blood vessel wall, and blood flow domain (this setting can refer to the flow, pressure, and valve morphology data obtained from in vitro experiments).

[0095] A Python script was written to perform secondary development of the above simulation process and integrate it with the modeling process to achieve automated simulation of multi-parameter polymer valves.

[0096] 3. Optimization Algorithm

[0097] Establish Figure 3In (c), a finite element simulation-based polymer heart valve geometry optimization platform calculates parameterized valve geometry data in Python. A SolidWorks API secondary development program written in C# generates the valve geometry model file. This model file is imported into an ABAQUS Python script for finite element simulation. The simulation results are processed to determine maximum stress, mean stress, valve opening, or other optimization metrics. Optimization is then performed using a multi-objective optimization algorithm such as NSGA-II. The optimal valve parameter combination on the Pareto front is selected as the final optimization result.

[0098] The specific optimization process is as follows:

[0099] (1) Input

[0100] Including valve geometry control parameter set θ, maximum number of iterations T max , optimization algorithm O (such as NSGA-II).

[0101] 1 Initialization

[0102] Set the parameter space range θ∈Θ and initialize the population (if using genetic / evolutionary algorithm).

[0103] 2 For t = 1 to T max :

[0104] For each set of design parameters θ i ∈Θ:

[0105] 2.1 Parametric Modeling:

[0106] Generate valve geometry using CAD tools or custom modeling scripts:

[0107] G i =Geometry(θ).

[0108] 2.2 Finite element simulation

[0109] G i Input into a finite element solver (such as Abaqus);

[0110] Set material parameters, boundary conditions, and loading conditions;

[0111] Solve and get the response result R i =Simulate(G i ).

[0112] 2.3 Post-processing analysis:

[0113] Extract key performance indicators such as:

[0114] Maximum stress σ_max i ;

[0115] Deformation δ i ;

[0116] Open area A i ;

[0117] Valve opening degree GSF;

[0118] Fatigue life estimation L i ;

[0119] Composition of objective function vector: F i =[f1(θ i ),f2(θ i ),...,f_m(θ i )].

[0120] 2.4 Multi-objective optimization:

[0121] Perform selection, crossover, mutation and other operations according to the optimization algorithm O (if it is a swarm algorithm);

[0122] Or update θ according to the gradient information (if it is a gradient method);

[0123] Update the population or solution set to improve the objective function.

[0124] (2) Output

[0125] Pareto optimal solution set θ * And its corresponding performance index F * .

[0126] The valve opening degree (GSF) is determined by the top view area of ​​the valve leaflets when the valve is maximally open and closed. Figure 4 shown.

[0127] The calculation formula of GSF is as follows:

[0128]

[0129] Among them, S1 is the leaflet's top-view area when the valve is maximally open, and S2 is the leaflet's top-view area when the valve is closed.

[0130] The maximum stress is closely related to the fatigue performance of the valve. The parameter combination with the minimum maximum stress can be selected as the final optimization result in the Pareto front of the optimization results.

[0131] According to the above process, the maximum stress on the optimized valve can be reduced by 40%. The in vitro pulsating flow test of the valve before and after processing optimization shows that the effective opening area, regurgitation fraction and transvalvular pressure difference are improved, especially in terms of fatigue resistance. The number of accelerated fatigue test cycles of the optimized valve is 7 times that of the valve before optimization.

[0132] To address the challenges of existing valve geometry models, which rely on fixed parameters or a small number of control points, resulting in low flexibility and difficulty in rapidly adapting to diverse anatomical requirements or optimization goals, the present invention provides a high-degree-of-freedom, multi-objective geometric optimization design method for artificial heart valves. By combining finite element simulation, multi-objective optimization algorithms, and an automated design process, this method enables rapid performance optimization of valve geometry. This method is not only applicable to artificial heart valve design but can also be extended to the geometric construction and optimization of flexible medical devices, providing a new paradigm for standardized and intelligent medical device development.

[0133] The above describes in detail the preferred embodiments of the present invention. It should be understood that those skilled in the art can make numerous modifications and variations based on the concepts of the present invention without inventive effort. Therefore, any technical solutions that can be derived by those skilled in the art through logical analysis, reasoning, or limited experimentation based on the concepts of the present invention and the prior art should be within the scope of protection defined by the claims.

Claims

1. A high-degree-of-freedom multi-objective geometric optimization design method for artificial heart valves, characterized in that: The method comprises the following steps: S101: performing parametric geometric modeling on the artificial heart valve using a geometric curve with variable parameters to obtain a leaflet geometric model of the polymer valve; S103: importing the leaflet geometric model into simulation software for finite element simulation, wherein the simulation software has secondary development capability; S105: solving the finite element simulation and optimizing the simulation results using a multi-objective optimization algorithm; S107: Select the optimal valve parameter combination in the Pareto front as the final optimization result.

2. The method according to claim 1, wherein In step S101, the artificial heart valve adopts a tri-leaflet valve, and the valve is modeled by multiple basic curves, wherein the basic curves include an attached edge curve, an abdominal curve and a free edge curve, wherein: The attachment edge curve is formed by stretching a spline curve with one or more control points on the side view plane and intersecting the cylindrical surface; The free edge curve is located at the horizontal plane where the highest point of the valve is located, and is composed of a spline curve. The free edge curve is set with multiple control point parameters; The abdominal curve is generated by the spline curve with movable control points on the side view plane.

3. The method according to claim 2, wherein With the free edge curve and the attachment curve as boundaries and the abdominal curve as a guide line, a single leaflet is obtained by lofting. With the single leaflet as a solid and the Z axis as the rotation axis, a 120° rotation array is performed to obtain a complete leaflet geometric model.

4. The method according to claim 3, wherein The leaflet geometric model includes multiple variable parameters, including: the coordinates of the abdominal curve control point, the coordinates of the attachment curve control point, the valve height, the gap between the leaflet and the central axis, and the gap between adjacent leaflets.

5. The method according to claim 4, wherein The spline curve uses a B-Spline curve, and the B-Spline curve is set as: in, U={u0,u1,u2,…,u m },u i ≤u i+1 ,i=0,1,…,m-1 Among them, C(u) is the B-Spline curve, N i,p (u) is the basis function of the i-th B-Spline curve with degree p, P i is the control point, U is the node vector, u i ∈U is the node, m is the number of nodes, and p is the number of times.

6. The method according to claim 5, wherein In step S103, during the finite element simulation process, a completely fixed constraint is set on the attachment edge of the leaflet, and the transvalvular pressure difference curve of the aortic valve in a normal human body is used as the physiological dynamic load boundary condition of the valve finite element simulation. The load is applied to the ventricular side surface of the polymer aortic valve, and the load loading direction is perpendicular to the ventricular side surface. The linear elastic constitutive model is used as the constitutive model of the leaflet.

7. The method according to claim 6, wherein In step S105, when solving the finite element simulation, a dynamic display solution method or a fluid-solid coupling solution method is used, wherein: The dynamic display solution method loads the transvalvular pressure difference within one or more cardiac cycles on the ventricular side of the valve to make the valve open and close periodically, solves the mechanical equilibrium equation explicitly, and maintains quasi-static state during the calculation; The fluid-solid coupling solution method adopts the immersed boundary method and performs relevant settings on the valve, blood vessel wall and blood flow domain.

8. The method according to claim 7, wherein In step S105, the multi-objective optimization algorithm includes multiple key performance indicators, which constitute an objective function and are optimized. The key performance indicators include: maximum stress, deformation, open area, valve opening degree and fatigue life estimation.

9. The method according to claim 8, wherein The multi-objective optimization algorithm is configured as NSGA-II algorithm, swarm algorithm or gradient algorithm to complete the multi-objective optimization process.

10. The method according to claim 9, wherein The method drives the seamless connection of modeling, simulation and optimization tools through an automated interface protocol, secondary develops the finite element simulation process, and integrates it with the parametric geometric modeling process to achieve automated simulation and multi-objective optimization of multi-parameter polymer valves.

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