Method and apparatus for structural simulation analysis based on multi-component mixing of carboxymethyl cellulose

Abstract

This application provides a structural simulation analysis method and apparatus based on carboxymethyl cellulose multi-component mixing. The method includes: constructing multiple multi-component mixing models with the same external dimensions but different internal structures; performing fluid dynamics simulation on each multi-component mixing model to simulate the mixing process of multiple fluids and obtaining the corresponding mixing results; and determining the multi-component mixing model with the optimal mixing effect based on comparative analysis of the mixing results. This application, by constructing and simulating multiple multi-component mixing models with different internal structures in parallel and comparing and analyzing their mixing results based on fluid dynamics principles, can quickly and objectively select the mixing model with the optimal mixing efficiency.

Description

Technical Field

[0001] This application relates to the field of data analysis technology, and in particular to a structural simulation analysis method and apparatus based on a multi-component mixture of carboxymethyl cellulose. Background Technology

[0002] Carboxymethyl cellulose (CMC) gel composites are widely used in electrochemical energy storage electrode carriers, water treatment adsorption coatings, and flexible sensing media due to their hydrophilicity, biocompatibility, and biodegradability. The core purpose is to enhance the mechanical properties and functional characteristics of the gel through composite modification to meet the needs of engineering applications.

[0003] However, when CMC gels are blended with inorganic fillers, polymer matrices, and other materials, manual mixing is often used, which commonly results in poor compatibility, uneven dispersion, and weak interfacial bonding. During the extrusion molding stage, defects such as rheological instability and gel network damage easily occur, severely affecting product performance. Therefore, improving the mixing degree of CMC composite gels and designing efficient mixing and extrusion structures have become key challenges in CMC composite gel mixing technology. Summary of the Invention

[0004] To address the aforementioned problems in the prior art, this application provides a structural simulation analysis method and apparatus based on multi-component mixing of carboxymethyl cellulose, so as to quickly and accurately simulate the optimal structure of multi-component mixing.

[0005] To achieve the above objectives, the technical solution adopted in this application is as follows: In a first aspect, this application provides a structural simulation analysis method based on a multi-component mixture of carboxymethyl cellulose, including: Construct multiple multi-component hybrid models with the same external dimensions but different internal structures; Fluid dynamics simulations were performed on each multi-component mixing model to simulate the mixing process of multiple fluids and obtain the corresponding mixing results. The fluids included carboxymethyl cellulose gel. Based on the comparative analysis of the mixing results, the multi-component mixing model with the optimal mixing effect was determined.

[0006] The beneficial effect of this application is that by constructing and simulating multi-component hybrid models with various internal structures in parallel, and comparing and analyzing their hybridization results based on fluid dynamics principles, the hybrid model with the best hybridization performance can be quickly and objectively selected.

[0007] Optionally, the fluid dynamics simulation includes: Each multi-component hybrid model is meshed separately; A set of governing equations describing fluid flow and mixing is established, which includes the continuity equation with mass conservation, the momentum equation with momentum conservation, and the governing equations of the SST k-ω turbulence model. Set corresponding inlet velocity boundary conditions for the multiple fluids involved in the mixing; A pressure-based transient solver was selected for numerical calculation.

[0008] Optionally, the step of using a pressure-based transient solver for the solution calculation includes: A coupled algorithm is used to solve the continuity equation and the momentum equation simultaneously to handle the coupling relationship between the pressure field and the velocity field; The momentum equation and the governing equation of the SST k-ω turbulence model are spatially discretized using a second-order upwind scheme.

[0009] As can be seen from the above description, the computational efficiency of the simulation process and the physical fidelity of the results are fundamentally improved from the numerical solution level.

[0010] Optionally, obtaining the mixing result includes: By solving the set of governing equations, the velocity distribution data of the internal flow field of the corresponding multi-component mixing model and the concentration distribution data of the fluid are obtained.

[0011] Optionally, the continuity equation is: ; In the formula, ε q ρ is the volume fraction of phase q. q Let v be the density of phase q. q Let q be the velocity vector of phase q; The momentum equation is: ; In the formula, g is the acceleration due to gravity, β is the interphase drag coefficient, and τ q Let q be the stress tensor and p be the pressure. The formulas for solving the turbulent kinetic energy k and specific dissipation rate ω in the governing equations are as follows: ; ; In the formula, G k G is the turbulent kinetic energy production term caused by the average velocity gradient. ω Γ is the generating term of the specific dissipation rate ω. k and Γ ω Y represents the effective diffusion coefficient, which is the turbulent kinetic energy k and the specific dissipation rate ω, respectively. k and Y ω D represents the losses due to turbulent kinetic energy k and specific dissipation rate ω, respectively.ω This is a cross-diffusion term.

[0012] Optionally, the velocity distribution data and the concentration distribution data are obtained by extracting node information on a specified monitoring section in the fluid dynamics simulation. The monitoring section includes a cross section perpendicular to the flow direction and a longitudinal section containing the central axis of the needle.

[0013] Optionally, determining the multi-component mixing model with the optimal mixing effect based on the comparative analysis of the mixing results includes: Based on the velocity distribution data, the disturbance characteristics and mixing mechanism of different internal structures on the flow field are analyzed; Based on the concentration distribution data, a distribution uniformity index for quantitatively evaluating mixing uniformity is calculated. Based on the aforementioned flow field disturbance characteristics, mixing mechanism, and distribution uniformity index, the multi-component mixing model with the highest distribution uniformity index at the outlet section and whose flow field disturbance characteristics and mixing mechanism are most conducive to achieving radial mass exchange is determined to have the best mixing effect.

[0014] As described above, the final decision is made by integrating the disturbance mechanism revealed by the velocity field and the uniformity index calculated by the concentration field. This not only ensures that the selected optimal structure is the best in terms of quantitative indicators, but also confirms from the perspective of fluid dynamics that its intrinsic physical mechanism for enhancing mixing is the most effective.

[0015] Optionally, setting corresponding inlet velocity boundary conditions for the multiple fluids participating in the mixing includes: An inlet velocity of 0.065-0.070 m / s was set for the carboxymethyl cellulose gel, which serves as the first fluid. Set an inlet velocity of 0.088-0.095 m / s for the mixture as the second fluid.

[0016] Optionally, the multi-component mixing model includes: an unobstructed original structure, a stepped structure with stepped barriers inside, and a spiral structure with spiral guide vanes inside.

[0017] Secondly, this application provides a structural simulation and analysis device based on a multi-component mixture of carboxymethyl cellulose, comprising: one or more processors, and a memory; The memory stores computer-readable instructions that, when executed by the one or more processors, perform the steps of the method as described in the first aspect.

[0018] The structural simulation and analysis device based on the mixing of multiple components of carboxymethyl cellulose provided in the second aspect refers to the relevant description of the structural simulation and analysis method based on the mixing of multiple components of carboxymethyl cellulose provided in the first aspect. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the main process of the structural simulation analysis method based on multi-component mixing of carboxymethyl cellulose according to an embodiment of this application; Figure 2 This is a schematic diagram of the multi-component mixing model involved in the embodiments of this application; Figure 3 This is a schematic diagram of the velocity distribution cloud map of the X-section of the multi-component mixing model involved in the embodiments of this application; Figure 4 This is a schematic diagram of the velocity distribution contour plot of the Z-section of the multi-component mixing model involved in the embodiments of this application; Figure 5 This is a schematic diagram of the velocity distribution cloud map at different locations of the multi-component mixing model involved in the embodiments of this application; Figure 6 This is an X-section velocity vector diagram of the multi-component hybrid model involved in the embodiments of this application; Figure 7 This is a velocity vector diagram of the Z-section of the multi-component hybrid model involved in the embodiments of this application; Figure 8 This is an X-section concentration distribution cloud map of the multi-component mixing model involved in the embodiments of this application; Figure 9 This is a Z-section concentration distribution cloud map of the multi-component mixing model involved in the embodiments of this application; Figure 10 These are concentration distribution cloud maps at different locations in the multi-component mixture model involved in the embodiments of this application; Figure 11 This is a comparison of the distribution uniformity index of the multi-component mixing model involved in the embodiments of this application; Figure 12 This is a schematic diagram of the structure simulation and analysis device based on a multi-component mixture of carboxymethyl cellulose according to an embodiment of this application. Detailed Implementation

[0020] To better understand the above technical solutions, exemplary embodiments of this application will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of this application are shown in the drawings, it should be understood that this application can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this application can be understood more clearly and thoroughly, and that the scope of this application can be fully conveyed to those skilled in the art.

[0021] The embodiments of this application are applied to scenarios involving the mixing of multiple components. Existing technologies rely on physical samples to select the mixing structure, which suffers from long trial-and-error cycles and high costs.

[0022] Therefore, in various embodiments of this application, multiple multi-component mixing models with the same external dimensions but different internal structures are constructed; fluid dynamics simulations are performed on each multi-component mixing model to simulate the mixing process of multiple fluids and obtain the corresponding mixing results; based on the comparative analysis of the mixing results, the multi-component mixing model with the optimal mixing effect is determined. Thus, by constructing and simulating multiple multi-component mixing models with different internal structures in parallel, and comparing and analyzing their mixing results based on fluid dynamics principles, the mixing model with the optimal mixing efficiency can be quickly and objectively selected.

[0023] The present application will now be described in further detail with reference to the accompanying drawings and embodiments.

[0024] This application provides a structural simulation analysis method based on a multi-component mixture of carboxymethyl cellulose, such as... Figure 1 As shown, the method includes: Step S100: Construct multiple multi-component hybrid models with the same external dimensions but different internal structures.

[0025] In one example of this embodiment, the multi-component mixing model includes: an unobstructed original structure, a stepped structure with stepped barriers inside, and a spiral structure with spiral guide vanes inside.

[0026] Step S200: Perform fluid dynamics simulation on each multi-component mixing model to simulate the mixing process of multiple fluids and obtain the corresponding mixing results. The fluids include carboxymethyl cellulose gel.

[0027] Step S200 includes: Step S201: Perform mesh generation for each multi-component hybrid model.

[0028] Ansys SpaceClaim was used for geometric model construction, and Ansys Fluent meshing was used for mesh generation.

[0029] in, Figure 2 (a) is the original structure, 2(b) is the stepped structure, and 2(c) is the spiral structure. The upper part of each multi-component mixing model is the syringe inlet, and the lower part is the syringe outlet.

[0030] Step S202: Establish the governing equations describing fluid flow and mixing. The governing equations include the continuity equation for mass conservation, the momentum equation for momentum conservation, and the governing equations for the SST k-ω turbulence model.

[0031] The continuity equation is: ; In the formula, εq ρ is the volume fraction of phase q. q Let v be the density of phase q. q Let q be the velocity vector.

[0032] The momentum equation is: ; In the formula, g is the acceleration due to gravity, β is the interphase drag coefficient, and τ q Let q be the stress tensor and p be the pressure.

[0033] The formulas for solving the turbulent kinetic energy k and specific dissipation rate ω in the governing equations are as follows: ; ; In the formula, G k G is the turbulent kinetic energy production term caused by the average velocity gradient. ω Γ is the generating term of the specific dissipation rate ω. k and Γ ω Y represents the effective diffusion coefficient, which is the turbulent kinetic energy k and the specific dissipation rate ω, respectively. k and Y ω D represents the losses due to turbulent kinetic energy k and specific dissipation rate ω, respectively. ω This is a cross-diffusion term.

[0034] It should be noted that the phase q mentioned above refers to the fluid.

[0035] Step S203: Set corresponding inlet velocity boundary conditions for the multiple fluids involved in the mixing.

[0036] In this embodiment, step S203 includes: An inlet velocity of 0.065-0.070 m / s was set for the carboxymethyl cellulose gel, which serves as the first fluid. Set an inlet velocity of 0.088-0.095 m / s for the mixture as the second fluid.

[0037] Specifically, due to the high viscosity of CMC gel, in this example, the velocity of CMC gel is 0.068 m / s, indicating that the CMC gel material enters the channel first, followed by another mixture, B, at a velocity of 0.091 m / s. The two are uniformly mixed within the channel to form the composite material CMC / B. This allows for the establishment of X, Y, and Z planes to detect the flow behavior, with multiple planes established in the Y direction to observe the details of flow changes.

[0038] Step S204: Select a pressure-based transient solver for numerical calculation.

[0039] In this embodiment, step S204 includes: Step S2041: Use a coupled algorithm to solve the continuity equation and the momentum equation simultaneously to handle the coupling relationship between the pressure field and the velocity field.

[0040] Step S2042: Spatial discretization of the momentum equation and the governing equations of the SST k-ω turbulence model is performed using a second-order upwind scheme.

[0041] Step S205: By solving the set of governing equations, obtain the velocity distribution data and fluid concentration distribution data of the internal flow field of the corresponding multi-component mixing model.

[0042] In this embodiment, the velocity distribution data and concentration distribution data are obtained by extracting node information from a specified monitoring section in the fluid dynamics simulation. The monitoring section includes a cross section perpendicular to the flow direction and a longitudinal section containing the central axis of the needle.

[0043] Step S300: Based on the comparative analysis of the mixing results, determine the multi-component mixing model with the best mixing effect.

[0044] Step S300 includes: Based on velocity distribution data, we analyze the disturbance characteristics and mixing mechanism of different internal structures on the flow field.

[0045] Based on concentration distribution data, a distribution uniformity index is calculated to quantitatively evaluate the homogeneity of mixing.

[0046] Considering the overall flow field disturbance characteristics, mixing mechanism, and distribution uniformity index, the multi-component mixing model with the highest distribution uniformity index at the outlet section and whose flow field disturbance characteristics and mixing mechanism are most conducive to achieving radial mass exchange is determined to be the best in terms of mixing effect.

[0047] Therefore, by making the final decision based on the disturbance mechanism revealed by the comprehensive velocity field and the uniformity index calculated by the concentration field, we not only ensured that the selected optimal structure was the best in terms of quantitative indicators, but also confirmed from the perspective of fluid dynamics that its intrinsic physical mechanism for enhancing mixing was the most effective.

[0048] In a specific example of this application, hydrodynamic simulations were performed on the CMC gel and mixture in three structures, and the final mixing results are as follows: Figures 3 to 11 .

[0049] Figure 3 The image shows a comparison of velocity distribution contour maps for the three structures at the X-section. Figure 3 (a) It can be observed that the original fluid mainly flows from the middle of the syringe, with a high velocity in the central axis region and a low-velocity boundary layer near the wall due to viscosity. This distribution leads to insufficient radial mixing of the fluid. Figure 3(b) It can be observed that the flow velocity is relatively low in the middle section of the stepped structure at the X-section. This is mainly because the fluid avoids collisions with the steps, kinetic energy is dissipated, and the fluid flow direction is constantly changing. Figure 3 (c) It can be observed that the velocity distribution of the spiral structure is also relatively uniform, indicating that the spiral guide vanes effectively convert the kinetic energy of the axial flow into the rotational momentum of the fluid. This circumferential motion causes the fluid to continuously exchange positions in the radial direction, forming a uniform flow field.

[0050] Figure 4 This further illustrates the comparison of velocity distribution contour maps for the three structures at the Z-section. Figure 4 (b) It can be observed that the symmetry of the Z-axis velocity distribution in the stepped structure is significantly improved. The high-speed fluid continuously changes direction after passing through the stepped structure, which helps to achieve uniform fluid contact across the entire cross-section. Figure 4 (c) It can be found that the velocity distribution of the Z-section of the spiral structure is also uniform and symmetrical, which proves that the spiral-induced rotating flow has good axisymmetry.

[0051] Figure 5 The velocity distribution contour maps at different locations are shown, dynamically revealing the development of the mixing process. For the original structure, the velocity profile changes very little along the axial direction, making spontaneous mixing difficult. The stepped and spiral structures establish a stable rotating flow field from the inlet and maintain it until the outlet, demonstrating that both can mix the liquid well. This indicates that stepped channels can achieve more rapid and uniform mixing of CMC composite gels.

[0052] Figure 6 This demonstrates a comparison of the velocity vectors of the three structures at the X-section. Figure 6 (a) It can be observed that the vector directions of the original structure are parallel and consistent, indicating a simple unidirectional flow. From Figure 6 (b) It can be observed that the vector direction of the stepped structure deflects at the corners of the steps, demonstrating the flow splitting generated after the fluid impacts the wall. Figure 6 (c) It can be observed that the vector diagram of the spiral structure presents a spiral trajectory. The fluid does not move in a straight line, but rather moves along a spiral line at a certain angle to the axis under the guidance of the spiral blades. This three-dimensional spiral motion prolongs the actual flow path of the fluid, increases the contact opportunities and shearing effects between fluid micro-elements, and can effectively enhance the mixing of the two phases.

[0053] Figure 7 The Z-section vector diagram and the X-section conclusions corroborate each other. The original structure has the simplest streamlines, while the stepped structure exhibits a significant change in velocity direction, and the spiral structure displays a clear spiral trajectory streamline on the Z-section. This indicates that the outstanding performance of the stepped structure channels in improving the mixing of CMC-based composite gels stems from the alternating changes in velocity direction.

[0054] Figure 8 The diagram shows a comparison of the concentration distribution contour maps of the three structures at the X-section. At the X-section, a relatively uniform concentration distribution of all three structures can be observed at the syringe outlet.

[0055] Figure 9 The concentration distribution contour maps of the three structures at the Z-section are shown for comparison. The Z-section concentration contour map reveals the shortcomings of the original structure: the two components did not fully interweave in the Z direction, and obvious concentration partitioning is still visible. This means that although the original structure can achieve two-dimensional mixing at the X-section, it is still insufficiently mixed in the third dimension. In contrast, the stepped structure and the helical structure have equally uniform concentration distributions at the Z-section, achieving three-dimensional mixing. In particular, the channels of the stepped structure are more conducive to achieving rapid and uniform mixing of the CMC composite gel.

[0056] Figure 10 The diagrams show a comparison of concentration distribution contour maps for the three structures at different locations. For the original structure, the component interfaces blurred slowly with the flow, resulting in a sluggish mixing process. The stepped structure rapidly disrupted the initial interfaces, subsequently achieving rapid and uniform mixing of the CMC-based composite gel. The helical structure also exhibited a continuous and stable mixing enhancement process, with concentration uniformity steadily improving from the inlet to the outlet, ultimately reaching its optimal state at the outlet.

[0057] Figure 11 The diagram compares the uniformity indices of three different structures. The original structure has a flat and low uniformity index curve, indicating low mixing efficiency and inability to meet the demands of rapid mixing. The stepped structure's curve has a steep initial slope, indicating its strong disturbance capability in the initial mixing stage, rapidly disrupting the initial concentration field and achieving a significant leap in mixing efficiency. Subsequently, the uniformity index rises rapidly and reaches its maximum at the outlet, demonstrating that the stepped structure achieves efficient interphase mixing. The spiral structure also exhibits a curve with a stable and continuously rising slope. This indicates that the mixing driving force provided by the spiral structure persists throughout the entire flow field. With each step the fluid advances, the mixing efficiency increases, ultimately achieving a near-perfectly uniform mixing state at the outlet.

[0058] The comparative results show that the stepped structure performs best in achieving deep, uniform, and stable mixing during the CMC composite gel mixing process, followed by the spiral structure, while the original structure performs poorly.

[0059] This application precisely analyzes the stress distribution and rheological behavior of the composite system during extrusion. Based on finite element method (FEM) simulation, three hybrid extrusion screw structure models adapted to CMC composite gels were established. Then, machine learning was used to conduct hydrodynamic analysis on the mixing degree of the two-component coating particles within the three screw structures. Simulation analysis yielded the continuity, flowability, and mixing degree of the composite coating in the three screw structures. Comparative analysis of the simulation results showed that, under the same conditions, the stepped structure exhibited the best continuity, flowability, and mixing degree of the composite coating. Therefore, a stepped structure can be selected during the mixing process of CMC composite gels.

[0060] In one embodiment, such as Figure 12 As shown, this application also provides a structural simulation and analysis device 1200 based on a multi-component mixture of carboxymethyl cellulose, comprising: The communication interface 1201 allows for information exchange with other devices or network nodes.

[0061] One or more processors 1202 are connected to a communication interface 1201 to enable information interaction with other devices or network nodes, and to execute the methods provided by one or more technical solutions in the above embodiments when running computer programs.

[0062] Memory 1203 is used to store computer-readable instructions that can be executed on processor 1202. When executed by one or more processors 1202, the computer-readable instructions perform the steps of the software development method as described in the above embodiments.

[0063] The structural simulation and analysis device 1200 based on carboxymethyl cellulose multi-component mixture in this embodiment only shows a block diagram of a portion of the structure related to the present application solution, and does not constitute a limitation on the device to which the present application solution is applied. A specific device may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements, such as power supply, input / output interfaces, etc. Furthermore, the structural simulation and analysis device based on carboxymethyl cellulose multi-component mixture in this embodiment can operate on an operating system stored in memory 1203, such as Windows Server™, Mac OS X™, Unix™, Linux™, Free BSD™, or similar.

[0064] In addition, the specific descriptions of the technical effects and steps of the structure simulation analysis device based on carboxymethyl cellulose multi-component mixing in the above embodiments are all based on the relevant descriptions of the embodiments of the structure simulation analysis method based on carboxymethyl cellulose multi-component mixing.

[0065] Since the systems / devices described in the above embodiments of this application are systems / devices used to implement the methods of the above embodiments of this application, those skilled in the art can understand the specific structure and modifications of the system / devices based on the methods described in the above embodiments of this application, and therefore will not be repeated here. All systems / devices used in the methods of the above embodiments of this application fall within the scope of protection of this application.

[0066] Those skilled in the art will understand that embodiments of this application can be provided as methods, apparatus, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0067] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (devices), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions.

[0068] It should be noted that any reference numerals placed between parentheses in the claims should not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claims. The words "a" or "an" preceding a component do not exclude the presence of a plurality of such components. This application can be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In claims that enumerate several means, several of these means may be embodied by the same hardware. The use of the terms first, second, third, etc., is merely for convenience of expression and does not indicate any order. These terms can be understood as part of the component names.

[0069] Furthermore, it should be noted that in the description of this specification, the terms "one embodiment," "some embodiments," "embodiment," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0070] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the claims should be interpreted to include the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0071] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if these modifications and variations fall within the scope of the claims of this application and their equivalents, then this application should also include these modifications and variations.

Claims

1. A structural simulation and analysis method based on multi-component mixtures of carboxymethyl cellulose, characterized in that, include: Construct multiple multi-component hybrid models with the same external dimensions but different internal structures; Fluid dynamics simulations were performed on each multi-component mixing model to simulate the mixing process of multiple fluids and obtain the corresponding mixing results. The fluids included carboxymethyl cellulose gel. Based on the comparative analysis of the mixing results, the multi-component mixing model with the optimal mixing effect was determined.

2. The structural simulation and analysis method based on multi-component mixing of carboxymethyl cellulose according to claim 1, characterized in that, The fluid dynamics simulation includes: Each multi-component hybrid model is meshed separately; A set of governing equations describing fluid flow and mixing is established, which includes the continuity equation with mass conservation, the momentum equation with momentum conservation, and the governing equations of the SST k-ω turbulence model. Set corresponding inlet velocity boundary conditions for the multiple fluids involved in the mixing; A pressure-based transient solver was selected for numerical calculation.

3. The structural simulation and analysis method based on multi-component mixing of carboxymethyl cellulose according to claim 2, characterized in that, The selection of a pressure-based transient solver for solution calculation includes: A coupled algorithm is used to solve the continuity equation and the momentum equation simultaneously to handle the coupling relationship between the pressure field and the velocity field; The momentum equation and the governing equation of the SST k-ω turbulence model are spatially discretized using a second-order upwind scheme.

4. The structural simulation and analysis method based on multi-component mixing of carboxymethyl cellulose according to claim 2, characterized in that, The obtained mixture result includes: By solving the set of governing equations, the velocity distribution data of the internal flow field of the corresponding multi-component mixing model and the concentration distribution data of the fluid are obtained.

5. The structural simulation and analysis method based on multi-component mixing of carboxymethyl cellulose according to claim 2, characterized in that, The continuity equation is: ； In the formula, ε q ρ is the volume fraction of phase q. q Let v be the density of phase q. q Let q be the velocity vector of phase q; The momentum equation is: ； In the formula, g is the acceleration due to gravity, β is the interphase drag coefficient, and τ q Let q be the stress tensor and p be the pressure. The formulas for solving the turbulent kinetic energy k and specific dissipation rate ω in the governing equations are as follows: ； ； In the formula, G k G is the turbulent kinetic energy production term caused by the average velocity gradient. ω Γ is the generating term of the specific dissipation rate ω. k and Γ ω Y represents the effective diffusion coefficient, which is the turbulent kinetic energy k and the specific dissipation rate ω, respectively. k and Y ω D represents the losses due to turbulent kinetic energy k and specific dissipation rate ω, respectively. ω This is a cross-diffusion term.

6. The structural simulation and analysis method based on multi-component mixing of carboxymethyl cellulose according to claim 4, characterized in that, The velocity distribution data and the concentration distribution data are obtained by extracting node information from a specified monitoring section in the fluid dynamics simulation. The monitoring section includes a cross section perpendicular to the flow direction and a longitudinal section containing the central axis of the needle.

7. The structural simulation and analysis method based on multi-component mixing of carboxymethyl cellulose according to claim 4, characterized in that, The step of determining the multi-component mixing model with the optimal mixing effect based on the comparative analysis of the mixing results includes: Based on the velocity distribution data, the disturbance characteristics and mixing mechanism of different internal structures on the flow field are analyzed. Based on the concentration distribution data, a distribution uniformity index for quantitatively evaluating mixing uniformity is calculated. Based on the aforementioned flow field disturbance characteristics, mixing mechanism, and distribution uniformity index, the multi-component mixing model with the highest distribution uniformity index at the outlet section and whose flow field disturbance characteristics and mixing mechanism are most conducive to achieving radial mass exchange is determined to have the best mixing effect.

8. The structural simulation and analysis method based on multi-component mixing of carboxymethyl cellulose according to claim 2, characterized in that, The process of setting corresponding inlet velocity boundary conditions for the multiple fluids involved in mixing includes: An inlet velocity of 0.065-0.070 m / s was set for the carboxymethyl cellulose gel, which serves as the first fluid. Set an inlet velocity of 0.088-0.095 m / s for the mixture as the second fluid.

9. The structural simulation and analysis method based on multi-component mixing of carboxymethyl cellulose according to any one of claims 1 to 8, characterized in that, The multi-component mixing model includes: an unobstructed original structure, a stepped structure with stepped barriers inside, and a spiral structure with spiral guide vanes inside.

10. A structural simulation and analysis device based on a multi-component mixture of carboxymethyl cellulose, characterized in that, include: One or more processors, and memory; The memory stores computer-readable instructions that, when executed by the one or more processors, perform the steps of the method as described in any one of claims 1 to 9.

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