Simulation method for low pressure pin assisted impregnation of fiber reinforced composite prepreg

Abstract

The application discloses a kind of fiber reinforced composite material prepreg low-pressure pin assisted impregnation simulation method, comprising: using simulation software to the fiber reinforced composite material impregnation of pin assisted impregnation system is simulated full process, realizes the full process simulation and penetration degree prediction of continuous fiber reinforced composite material low-pressure pin assisted impregnation process by flow region division, multi-scale simulation coupling mode;Representative volume unit and interface representative unit simplified by the application can greatly reduce the calculation resources consumed by simulation, and the simulation results can obtain the flow evolution and wetting performance of the whole process, providing strong support for impregnation device design and process parameter optimization.

Description

Technical Field

[0001] This invention relates to the field of permeation flow in the low-pressure pin-assisted impregnation process of continuous fiber reinforced composite materials, and specifically to a simplified method for impregnation flow and a full-process modeling and simulation method. Background Technology

[0002] Composite materials have long been widely used as alternatives to metals in various fields due to their excellent mechanical properties and low density. As an intermediate state between raw materials and finished products, the impregnation effect of composite prepregs is crucial to the mechanical properties of parts. Currently, there are various methods for preparing composite prepregs using fiber filaments and one or more resin bases as raw materials. Taking the preparation of thermoplastic resin-based composite prepregs as an example, the preparation methods can be divided into solution impregnation, melt impregnation, and powder impregnation. Pin-assisted atmospheric pressure melt impregnation, as a method for preparing prepregs using resins with low viscosity in the molten state, offers advantages such as good economic efficiency, simple equipment, short preparation cycle, and continuous production capability.

[0003] The pin-assisted atmospheric pressure impregnation system has complex process parameters. The geometry of the impregnation system, the number of pins, the resin material, and the temperature all affect the performance of the prepreg. Therefore, in actual production, a significant amount of time and resources are typically spent exploring suitable impregnation process parameters to balance production efficiency and prepreg quality. The main reason for this problem is the difficulty in predicting the wetting flow in pin-assisted systems, and the unclear mechanism by which the impregnation system process parameters affect the permeation flow process. Therefore, there is an urgent need for a low-cost and efficient method to quickly determine the impregnation process parameters for impregnation systems of different specifications. Utilizing a full-process simulation method can not only facilitate further research on the wetting flow mechanism but also replace a large number of repetitive experiments in impregnation system development and impregnation process parameter determination. Summary of the Invention

[0004] To address the aforementioned problems, this invention provides a full-process simulation method for a low-pressure pin-assisted impregnation system for prepregs. Typically, the difficulty in simulating the entire process of a pin-assisted impregnation system lies in the transfer of flow field parameters at different stages and the correction of simulation boundary conditions. The method of this invention achieves full-process simulation and wettability prediction of the fiber cross-section impregnation process within the melt impregnation tank through a combination of local steady-state simulation, empirical parameter fitting, and overall transient simulation.

[0005] To achieve the above technical objectives, this invention provides a full-process simulation method for low-pressure pin-assisted impregnation of continuous fiber reinforced composite prepregs, comprising the following steps:

[0006] S1: Establish a geometric model of the flow region in the impregnation tank, define the physical property parameters of the molten resin, divide the mesh, define the boundary conditions to perform steady-state simulation, obtain the pressure field and temperature field, and calculate the initial transient pressure distribution on the fiber bundle path.

[0007] S2: Divide the fiber bundle impregnation area into an immersion area, a wedge-shaped area, and a contact area. Based on the pin geometry and fiber bundle geometry, establish a three-dimensional model of the wedge-shaped area of ​​the fiber bundle near the pin. Use dynamic mesh technology to impart relative motion velocity to the fiber bundle and perform steady-state flow simulation on the wedge-shaped area to obtain the pressure distribution of the simulation area and obtain the pressure correction amount of the wedge-shaped area.

[0008] S3: Based on the empirical model of fiber bundle and pin contact, determine the pressure correction amount in the contact area:

[0009] The maximum pressure Pm is calculated based on the tension.

[0010]

[0011] In the formula, T is the tension force, w is the fiber bundle width, and R is the pin radius;

[0012] Calculate the lubrication coefficient Lf

[0013]

[0014] In the formula, η is the resin viscosity, U is the traction rate, T is the tension force, and w is the fiber bundle width;

[0015] The pressure correction Pp is calculated using Pp = LfPm;

[0016] S4: The wedge region pressure correction amount and contact region pressure correction amount obtained in steps S2 and S3 are superimposed on the initial transient pressure distribution obtained in step S1 at the corresponding time to complete the correction.

[0017] S5: Establish a two-dimensional fiber representative volume element model, divide the mesh, and perform steady-state simulation under a certain pressure gradient to calculate the viscous resistance coefficient;

[0018] S6: Establish a geometric model of the fiber cross-section representative unit. According to the simulation settings, it includes a permeation flow zone with the regional attribute of porous medium and an initial filling zone with the regional attribute of fluid. The porous medium flow zone is defined based on the viscosity coefficient calculated in step S5. The flow boundary conditions are defined based on the corrected transient pressure boundary conditions obtained in step S4 and the uncorrected transient pressure boundary conditions obtained in step S1. The transient simulation is completed to obtain the impregnation evolution process and realize the prediction of the permeation effect.

[0019] Preferably, the impregnation is carried out using a thermoplastic resin.

[0020] Preferably, in step S1, the boundary conditions include temperature boundary conditions defined according to the temperature control method and pressure boundary conditions defined according to the resin replenishment method.

[0021] Preferably, in step S2, the fiber bundle geometric parameters include the width and thickness of the fiber bundle. The width of the fiber bundle is determined based on actual measurements, and the thickness of the fiber bundle is calculated based on the actual obtained fiber volume fraction.

[0022] Preferably, in step S2, the temperature boundary condition in the steady-state flow simulation is determined by the temperature field obtained in step S1, the pressure boundary condition is determined by the pressure field obtained in step S1, the pressure boundary condition is defined as a fixed value, the magnitude of which is the average pressure of the corresponding region, and the momentum boundary condition is determined by the traction speed in the process parameters.

[0023] Preferably, in step S1, the physical properties of the molten resin include the resin viscosity. The viscosity-shear rate curves at different temperatures are obtained using a rotational rheometer, and a viscosity model is obtained by fitting the curves.

[0024] Preferably, in step S5, the grid is divided and steady-state simulation is performed under a certain pressure gradient. The average flow velocity at the outlet is calculated, and the relationship between the pressure drop per unit length and the average flow velocity at the outlet under different inlet pressures is plotted and fitted to obtain the slope k. Based on the viscosity model obtained in step S1, the average viscosity μ of the flow region is calculated by simulation using average temperature and shear rate.

[0025] The formula for calculating the viscosity coefficient is:

[0026]

[0027] In the formula, cvr is the viscous resistance coefficient, and k is the slope of the pressure drop per unit length - average outlet velocity graph fitting. This represents the average viscosity of the flow region.

[0028] Preferably, in step S6, the left and right sides of the representative unit geometric model are set as Pressure Inlet, the top and bottom sides are set as Symmetry, the rectangular area adjacent to the pressure inlets on both sides is the PatchArea pre-filled with resin during calculation initialization, and the middle rectangular area is the porous medium permeation flow area.

[0029] Preferably, in step S6, the geometric model of the fiber section representative unit is divided into upper boundary and lower boundary according to whether it is in direct contact with the pin. The upper boundary is in direct contact with the wedge region and the pin, so the modified transient pressure boundary condition obtained in step S4 is used; the lower boundary uses the unmodified transient pressure boundary condition obtained in S1.

[0030] Preferably, in step S6, the simulation time is set to the total time for the fiber bundle cross section to completely pass through the melt impregnation tank at a given traction speed, and the iteration step size is set to adaptive.

[0031] The advantages and positive effects of this invention are as follows:

[0032] (1) Based on the traditional permeation flow simulation method, this invention proposes a full-process, multi-scale permeation simulation process. This method can meet the process parameter optimization of impregnation devices with different geometries and different pin arrangements.

[0033] (2) Based on the characteristics of permeation flow along the fiber path, the present invention divides the simulation area and realizes the correction and transmission of simulation parameters, which can simulate the permeation flow phenomenon in the pin-assisted impregnation tank more realistically and coherently, which can provide assistance for the optimization of process parameters and provide a complete flow evolution process for the study of permeation mechanism.

[0034] (3) This invention utilizes the porous medium assumption to calculate the flow characteristics of fiber-represented volume units and fiber-represented cross-section units. Compared with the direct simulation method, it greatly reduces the consumption of computing resources, helps to shorten the design cycle of the impregnation tank structure, and accelerates the process parameter optimization iteration process. Attached Figure Description

[0035] Figure 1 This is a flowchart simulating the entire process of low-pressure pin-assisted impregnation of the continuous fiber reinforced composite prepreg of the present invention;

[0036] Figure 2 This is a geometric model of the melt impregnation tank of the present invention and an extracted geometric model of the flow channel;

[0037] Figure 3 The graph shows the PLA viscosity and shear rate changes obtained experimentally in this invention, as well as the fitting results of the CROSS model.

[0038] Figure 4 This is a diagram showing the initial transient pressure boundary condition distribution of the present invention.

[0039] Figure 5 This is a diagram showing the flow region division of the present invention;

[0040] Figure 6 This is a three-dimensional model diagram of the wedge-shaped region of the present invention;

[0041] Figure 7 This is a pressure correction distribution diagram for the wedge-shaped region of the present invention;

[0042] Figure 8 This is the pressure distribution diagram after the revision of this invention;

[0043] Figure 9 This is a diagram of the two-dimensional fiber representative volume unit of the present invention;

[0044] Figure 10 This is a diagram defining the boundary types and flow regions of this invention.

[0045] Figure 11 This is a diagram showing the transient pressure distribution at the boundary of the present invention.

[0046] Figure 12 This is a diagram illustrating the evolution of the flow morphology during the impregnation process of this invention.

[0047] Figure 13 This is a graph showing the evolution of the degree of wetting in this invention over time;

[0048] Figure 14 This is a graph showing the evolution of the inlet flow velocity of the upper and lower pressures over time in this invention. Detailed Implementation

[0049] The present invention will now be described in further detail with reference to the accompanying drawings and examples.

[0050] The present invention provides a full-process simulation method for low-pressure pin-assisted impregnation of continuous fiber-reinforced composite prepregs. Through parameter transfer and boundary condition correction in multi-scale, multi-region, and multi-type simulations, it achieves simulation of the impregnation evolution process and prediction of impregnation effects. This method can shorten the optimization time for process parameters of the low-pressure pin-assisted impregnation system and reduce the design iteration cost of the impregnation tank. The simulation process is as follows: Figure 1 As shown, the implementation of this invention will be described in six steps below.

[0051] S1: Based on the geometry of the impregnation tank, establish the corresponding flow region model, define the physical properties of the molten resin, mesh and define boundary conditions, and perform steady-state simulation:

[0052] Import the impregnation tank geometry model into SolidWorks modeling software, and obtain the geometry model of the flow region through solid Boolean operations, such as... Figure 2 As shown, the ANSYS MESH module is used to generate the mesh and verify mesh independence.

[0053] The resin used was PLA resin manufactured by Nature Works. Viscosity-shear rate curves at different temperatures were obtained using a rotational rheometer, and the cross viscosity model was fitted using ORIGING software. Figure 3 As shown. An ANSYS UDF was written to define the resin viscosity. The UDF program used is (taking 200 degrees Celsius as an example):

[0054] #include"udf.h"

[0055] #include"math.h"DEFINE_PROPERTY(cell_viscosity,c,t)

[0056] {

[0057] real s_r=C_STRAIN_RATE_MAG(c,t);

[0058] real t1 = 0.01357;

[0059] real A1 = 1410.13859;

[0060] real A2 = 191.45014;

[0061] real m = 1.05675;

[0062] real vis;

[0063] real temp=1+pow(t1*s_r,m); vis=A2+(A1-A2) / temp; return vis;

[0064] }

[0065] Based on the design of the impregnation tank, the flow boundary type is defined. The pin surface and the inner wall of the melt impregnation tank are both set to WALL type, the fiber inlet and fiber outlet are both set to PRESSURE OUTLET type, and the resin replenishment port is set to MASSFLOW INLET type.

[0066] Steady-state simulations were performed to obtain the global pressure and temperature fields within the melt impregnation tank. The pressure distribution along the fiber movement path within the melt impregnation tank was extracted, and the initial transient pressure distribution was calculated based on a fiber bundle traction rate of 17.7 mm / s. The results are as follows: Figure 4 As shown.

[0067] S2: Based on flow characteristics, the fiber bundle impregnation area is divided into an immersion area, a wedge-shaped area, and a contact area. The immersion area is where the fiber bundle is far from the pin and immersed in resin; the wedge-shaped area is where the fiber bundle is near the pin; and the contact area is where the fiber bundle is in direct contact with the pin. The distribution of each area is as follows: Figure 5 As shown.

[0068] A three-dimensional model of the wedge-shaped region adjacent to the pin is established based on the pin's geometry and the fiber bundle's geometric parameters, such as... Figure 6As shown, the width of the fiber bundle is determined based on actual measurements, the thickness of the fiber bundle is calculated using the actual fiber volume fraction, the temperature boundary condition is determined by the temperature field obtained in step S1, the pressure boundary condition is determined by the pressure field obtained in step S1, the pressure boundary condition is defined as a fixed value, the magnitude of which is the average pressure of the corresponding region, and the momentum boundary condition is determined by the traction velocity in the process parameters. A moving velocity of 17.7 mm / s is applied to the fiber using dynamic mesh technology, the gauge pressure is calculated to be 0, and the steady-state flow simulation of the wedge region is completed. The pressure distribution of the simulation region is obtained, and the pressure correction amount of the wedge region is obtained by extracting the pressure distribution along the fiber path in the wedge region. Figure 7 ).

[0069] S3: Based on the empirical model of fiber bundle and pin contact, the pressure correction amount in the contact area is determined by process parameters such as tension force.

[0070] The maximum pressure Pm is calculated based on the tension.

[0071]

[0072] In the formula, T is the tension force, w is the fiber bundle width, and R is the pin radius;

[0073] Calculate the lubrication coefficient Lf

[0074]

[0075] In the formula, η is the resin viscosity, U is the traction rate, T is the tension force, and w is the fiber bundle width;

[0076] Calculate the pressure correction Pp

[0077] Pp=LfPm(3)

[0078] The calculated pressure correction for the contact area is 843494 Pa.

[0079] S4: By measuring the length of different impregnation zones and the traction rate, the time it takes for the fiber bundle cross-section to pass through each impregnation zone and the time to reach different impregnation zones are calculated. Using ORIGIN software, the wedge-shaped region pressure correction and contact region pressure correction obtained in steps S2 and S3 are superimposed onto the initial transient pressure distribution obtained in step S1 at the corresponding time to complete the correction. The corrected pressure distribution is as follows: Figure 8 As shown.

[0080] S5: Use DIGIMAT to create a two-dimensional fiber-represented volume element and mesh it, such as Figure 9 As shown, its volume fraction is determined by actual requirements. The top and bottom boundary conditions are set to WALL, and the left and right boundary conditions are set to PRESSURE INLET and PRESSURE OUTLET respectively.

[0081] In ANSYS, a new Fluent simulation was created, and the parameterized simulation was set with the inlet pressure as the variable. The pressure values ​​were set to 5000 Pa, 10000 Pa, and 15000 Pa to complete the single-phase steady-state simulation. In the CFD-POST module, the average velocity voutlet at the outlet was calculated using areaAve(Velocity)@outlet, and the relationship between the pressure drop per unit length and the average velocity at the outlet under different inlet pressures was plotted. The slope was found by fitting a linear function using ORIGIN. The average viscosity of the flow region was obtained by using the resin viscosity model in step S1 and calculated using the average temperature and shear rate parameters of the simulation results. The viscosity coefficient was calculated using equation (4).

[0082]

[0083] In the formula, cvr is the viscous resistance coefficient, and k is the slope of the pressure drop per unit length - average outlet velocity graph fitting. This represents the average viscosity of the flow region.

[0084] S6: Use the ANSYS-ICEM module to establish a geometric model of the fiber cross-section representative element and draw a structured mesh. According to the simulation settings, this includes a permeation flow region with the region attribute of porous media and an initial filling region with the region attribute of fluid. Specific boundary types and flow region definitions are provided (where the left and right sides of the representative element are set to Pressure Inlet, the top and bottom sides are set to Symmetry, the rectangular area adjacent to the pressure inlets on both sides is the Patch Area pre-filled with resin during calculation initialization, and the middle rectangular area is the porous media permeation flow region). Figure 10 As shown. Regarding the selection of the multiphase flow model, since the permeation flow process involves two immiscible fluids with clearly defined boundaries, the VOF-explict model is used to obtain a more accurate two-phase interface. Simultaneously, the PorousMedium module needs to be added to the permeation flow region, and the viscous resistance coefficient calculated in S5 is used to define the porous medium region.

[0085] Regarding the boundary conditions, since the movement of the fiber filament within the impregnation system can be approximated as a translational movement of the fiber bundle cross-section along the fiber bundle path, the two sides of the geometric model can be divided into upper and lower boundaries based on whether they are in direct contact with the pin. The upper boundary is in direct contact with the wedge-shaped region and the pin, therefore the modified transient pressure boundary conditions obtained in step S4 are used; the lower boundary uses the unmodified transient pressure boundary conditions obtained in S1. The final transient pressure distribution on the two boundaries is as follows: Figure 11 As shown. The transient boundary list is read using the Fluent command line. The command used is:

[0086] FILE / READ-TRANSIENT-TABLE / "bianjie.txt"

[0087] The simulation time was set to the total time it takes for the fiber bundle cross section to completely pass through the melt impregnation tank at a given traction speed. The iteration step size was set to adaptive. The PISO solver was selected and multiple flow optimization solver parameters were set to complete the transient simulation.

[0088] Data post-processing is performed within the CFD-POST module to obtain the evolution of the flow morphology during impregnation. Figure 12 To analyze the degree of impregnation and the wetting mechanism, independent variables representing the degree of impregnation and the resin flow rate at each boundary need to be defined in CFD-POST. The custom command line used is:

[0089] DOI=areaAve(Pla.Volume Fraction)@composite symmetry 1

[0090] Bianjie1 velocity=lengthAve(Velocity)@Line 1

[0091] Bianjie2 velocity=lengthAve(Velocity)@Line 2

[0092] Line 1 and Line 2 represent the junction lines between the permeation flow region and the initial resin-filled region, respectively. Images showing the evolution of the wetting degree over time are obtained. Figure 13 Images showing the evolution of inlet velocity at both upper and lower pressures over time (e.g.) Figure 14 ).

[0093] In summary, this invention achieves full-process simulation and penetration prediction of the low-pressure pin-assisted impregnation process for continuous fiber-reinforced composite materials through flow region division and multi-scale simulation coupling. It can model and simulate the entire impregnation flow process of pin-assisted low-pressure impregnation systems with different geometries and numbers of pins, considering the flow characteristics of different flow regions. Furthermore, the simplified representative volume and interface representative units used in this invention significantly reduce the computational resources required for simulation. The simulation results can capture the flow evolution and wetting performance throughout the process, providing strong support for impregnation device design and process parameter optimization.

[0094] Except for the technical features described in the specification, all other technologies are known to those skilled in the art. Descriptions of well-known components and technologies are omitted in this invention to avoid redundancy and unnecessary limitation. The embodiments described above do not represent all embodiments consistent with this application. Various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of this invention are still within the protection scope of this invention.

Claims

1. A method of simulating low pressure pin assisted impregnation of a fibre reinforced composite prepreg, characterised in that, The method comprises the following steps: S1: a geometry model of a flow area of an impregnation tank is established, physical property parameters of molten resin are defined, a grid is divided, boundary conditions are defined for steady-state simulation, a pressure field and a temperature field are obtained, and an initial transient pressure distribution on a fiber bundle path is calculated; S2: the fiber bundle impregnation area is divided into an immersion area, a wedge-shaped area, and a contact area, a three-dimensional model of the wedge-shaped area adjacent to the fiber bundle and the pin is established according to the pin geometry and the fiber bundle geometry parameters, the wedge-shaped area is subjected to steady-state flow simulation by giving the fiber bundle a relative motion speed through dynamic grid technology, a pressure distribution in the simulation area is obtained, and a pressure correction amount of the wedge-shaped area is obtained; S3: the pressure correction amount of the contact area is determined according to an empirical model of the contact between the fiber bundle and the pin: The maximum pressure Pm is calculated according to the tension force: In the formula, T is the tension force, w is the width of the fiber bundle, and R is the radius of the pin. The lubrication coefficient Lf is calculated: In the formula, η is the viscosity of the resin, U is the traction rate, T is the tension force, and w is the width of the fiber bundle. The pressure correction amount Pp is calculated by Pp = LfPm. S4: the pressure correction amount of the wedge-shaped area and the pressure correction amount of the contact area obtained in steps S2 and S3 are superimposed on the initial transient pressure distribution obtained in step S1 at the corresponding moment to complete the correction; S5: a two-dimensional fiber representative volume element model is established, a grid is divided, and steady-state simulation is performed under a certain pressure gradient, and a viscous resistance coefficient is calculated; S6: a fiber cross-section representative element geometry model is established, according to the simulation settings, it includes a permeation flow area with a porous medium attribute and an initial filling area with a fluid attribute, wherein the porous medium flow area is defined according to the viscous resistance coefficient calculated in step S5, the flow boundary condition is defined according to the corrected transient pressure boundary condition obtained in step S4 and the uncorrected transient pressure boundary condition obtained in step S1, the transient simulation is completed, the impregnation evolution process is obtained, and the permeation effect prediction is realized.

2. The fiber-reinforced composite prepreg low-pressure pin-assisted infusion simulation method according to claim 1, characterized in that, The impregnation adopts a thermoplastic resin.

3. The fiber reinforced composite prepreg low pressure pin assisted infusion simulation method according to claim 1, wherein, In step S1, the boundary conditions include a temperature boundary condition defined according to a temperature control mode and a pressure boundary condition defined according to a resin supplement mode.

4. The fiber-reinforced composite prepreg low-pressure pin-assisted infusion simulation method according to claim 1, characterized in that, In step S2, the fiber bundle geometry parameters include the width and thickness of the fiber bundle, the width of the fiber bundle is determined according to actual measurement, and the thickness of the fiber bundle is calculated by actually obtaining the fiber volume fraction.

5. The fiber-reinforced composite prepreg low-pressure pin-assisted infusion simulation method according to claim 1, characterized in that, In step S2, the temperature boundary condition in the steady-state flow simulation is determined by the temperature field obtained in step S1, the pressure boundary condition is determined by the pressure field obtained in step S1, the pressure boundary condition is defined as a fixed value, the size is the average pressure of the corresponding area, and the momentum boundary condition is determined by the traction speed in the process parameters.

6. The fiber-reinforced composite prepreg low-pressure pin-assisted infusion simulation method according to claim 1, characterized in that, In step S1, the physical property parameters of the molten resin include the resin viscosity, and the resin viscosity is obtained by using a rotary rheometer to obtain a viscosity-shear rate curve at different temperatures and fitting to obtain a viscosity model.

7. The fiber-reinforced composite prepreg low-pressure pin-assisted infusion simulation method according to claim 6, characterized in that, In step S5, the grid is divided and steady simulation is performed under a certain pressure gradient, the average flow velocity at the outlet is calculated, the relationship between the pressure drop per unit length and the average flow velocity at the outlet under different inlet pressures is plotted, and the slope k is fitted; according to the viscosity model obtained in step S1, the average viscosity μ of the flow region is calculated by simulating the average temperature and shear rate; The formula for calculating the drag coefficient is: where cvr is the viscous drag coefficient, k is the slope of the pressure drop per unit length versus average outlet flow velocity plot, is the average viscosity of the flow region.

8. The fiber-reinforced composite prepreg low-pressure pin-assisted infusion simulation method according to claim 1, characterized in that, In step S6, the left and right sides of the representative unit geometric model are set as Pressure Inlet, and the upper and lower sides are set as Symmetry. The rectangular area adjacent to the pressure inlet on both sides is the Patch Area for pre-filling resin during calculation initialization, and the middle rectangular area is the porous medium permeation flow area.

9. The fiber-reinforced composite prepreg low-pressure pin-assisted infusion simulation method according to claim 1, characterized in that, In step S6, the fiber cross-section representative unit geometric model is divided into upper and lower boundaries according to whether it is in direct contact with the pin. The upper boundary is in direct contact with the wedge-shaped area and the pin, so the modified transient pressure boundary condition obtained in step S4 is used. The lower boundary uses the unmodified transient pressure boundary condition obtained in S1.

10. The fiber-reinforced composite prepreg low-pressure pin-assisted infusion simulation method according to claim 1, characterized in that, In step S6, the simulation time is set to the total time for the fiber bundle cross-section to completely pass through the melt impregnation tank under a given pulling speed, and the iteration step is set to adaptive.

Images