Composite material spray pipe design method based on online monitoring and simulation verification

Abstract

The invention belongs to the technical field of engine nozzle performance optimization, and particularly discloses a composite material nozzle design method based on online monitoring and simulation verification, which comprises the following steps: S1, establishing a preliminary design model; s2, identifying key control parameters to obtain a sample grade online monitoring scheme; s3, correcting the simulation parameters of the preliminary design model obtained in the S1; s4, carrying out nozzle structure solidification simulation analysis and preliminary optimization design to obtain a nozzle preliminary optimization model; and S5, spray pipe production, online data acquisition and analysis and simulation verification are carried out, and if online monitored test data and final product performance indexes meet design requirements, the optimization design model is completed. According to the composite material spray pipe design method based on online monitoring and simulation verification, on-line monitoring is conducted on multiple parameters in the spray pipe curing process while the structural weight of the spray pipe is not increased, and support is provided for mastering the temperature and strain change rule in the spray pipe curing process.

Description

Technical Field

[0001] The present invention relates to the technical field of engine nozzle performance optimization, and in particular to a composite nozzle design method based on online monitoring and simulation verification. Background Art

[0002] In recent years, with the development of advanced composite materials, structural design and simulation technology, as well as the urgent need for advanced power to improve the performance of solid rocket engine nozzles, nozzle technology has gradually developed towards lightweight, structural and functional integration, high reliability, and strong environmental adaptability. On this basis, a one-piece molded all-composite nozzle technology that has been cured multiple times has been developed. Compared with traditional solid rocket engine nozzles (which are formed by individually molding various parts with different functions and then assembled), this technology eliminates the macro-assembly interface of traditional nozzles, simplifies the process flow, significantly reduces production materials such as tooling and molds, improves the quality and reliability of the nozzle, and reduces production costs. However, there are also the following shortcomings that need to be addressed:

[0003] (1) The one-piece molded all-composite nozzle is a typical multi-material composite functional structure. According to its functional zoning, different types of fibers and resins are used to make prepregs. After winding or laying, they are pressurized and cured, and need to go through multiple curing processes. During the curing process, due to factors such as resin curing shrinkage and mismatch of thermal expansion coefficients between fibers and matrix resin, the structural strength increases, and the generation and distribution of residual stress accumulate and change continuously, which will produce structural curing residual stress and curing deformation. This residual stress affects the mechanical properties of the composite structure and may even cause structural defects such as delamination and matrix cracking, affecting the structural performance of the nozzle throughout the product life.

[0004] (2) Due to the complex physical and chemical process of composite nozzle curing and molding, the existing material data and curing process parameters are relatively scarce, resulting in insufficient simulation calculation accuracy and low credibility of simulation results, which cannot guide the design well. At present, traditional design methods based on experience and simulation are usually adopted in nozzle structure design. By increasing the safety margin and performing conservative design to ensure structural reliability, the manufacturing cost is high and the structural efficiency is low. In the face of the urgent demand for improving nozzle performance, it is urgent to develop more accurate and efficient optimization design methods to reduce the waste of structural safety redundancy costs and improve the performance of nozzles.

[0005] In order to obtain an accurate and efficient optimization design method for the nozzle, it is necessary to change the current situation where the material data and curing parameters of the nozzle curing process are incomplete. Through online monitoring, the key control parameters in the nozzle curing process can be identified, and on this basis, the simulation calculation model can be calibrated and verified, the simulation calculation model can be corrected, the simulation analysis accuracy can be improved, and finally an optimized nozzle design scheme can be obtained.

[0006] Existing methods for online monitoring of parameters during the curing process of multilayer composite materials primarily include fiber optics, ultrasound, electrical methods, and thermal methods. Each method can only monitor a subset of parameters, requiring selection and evaluation based on specific conditions. Furthermore, most of these testing methods remain in the laboratory research phase, primarily targeting flat specimens of composite laminates. Monolithic nozzles are manufactured using a tape wrapping process, and there is a lack of methods for online monitoring parameters during the multiple curing processes of heterogeneous nozzle components. Summary of the Invention

[0007] The purpose of the present invention is to provide a composite nozzle design method based on online monitoring and simulation verification. While not increasing the weight of the nozzle structure, it can monitor multiple parameters during the nozzle curing process online, providing support for understanding the temperature and strain change laws during the nozzle curing process.

[0008] To achieve the above objectives, the present invention provides a composite nozzle design method based on online monitoring and simulation verification, comprising the following steps:

[0009] S1. Establish a preliminary design model;

[0010] S2. Identify key control parameters and obtain sample-level online monitoring solutions;

[0011] S3: Online monitoring of representative basic sample levels, data collection and analysis, and simulation verification, to modify the simulation parameters of the preliminary design model obtained in S1;

[0012] S4. Conduct simulation analysis and preliminary optimization design of the nozzle structure to obtain a preliminary optimization model of the nozzle;

[0013] S5. Based on the preliminary nozzle optimization model, nozzle production, online data collection and simulation verification are carried out. If the online monitoring test data and the final product performance indicators meet the design requirements, the optimized design model is completed. Otherwise, repeat S3-S5 for iterative optimization until the design requirements are met.

[0014] Preferably, S1 is specifically:

[0015] The preliminary design of the nozzle scheme is carried out based on the empirically designed structural parameters and traditional finite element simulation to obtain a preliminary design model.

[0016] Preferably, S2 is specifically:

[0017] Based on the preliminary design model, the key control parameters affecting the product performance are identified, and representative basic specimens are prepared. The representative basic specimens include Class A specimens and Class B specimens. The Class A specimens are made separately from the multiple composite materials that constitute the nozzle structure, and the Class B specimens are made from the multiple composite materials that constitute the nozzle structure, which are combined and stacked in pairs.

[0018] Preferably, the representative basic sample is one of a flat plate, an L-shape or a conical shape.

[0019] Preferably, S3 is specifically:

[0020] A fiber Bragg grating sensor is implanted in the Class A specimen to collect the internal temperature data and strain change data of the real Class A specimen in the curing environment with the same curing process as the nozzle. At the same time, a curing simulation model of the corresponding Class A specimen is established, and simulation calculations are performed on the Class A specimen under the same molding process to obtain the internal temperature data and strain change data of the Class A specimen under the simulated conditions.

[0021] The location for implanting the fiber grating sensor can be selected from the representative location obtained through preliminary simulation calculations. The online monitoring data measured in the Class A specimen can be compared with the finite element simulation results, and the relevant physical properties of the Class A specimen simulated by the finite element can be corrected.

[0022] Preferably, the relevant physical property parameters include resin curing kinetic parameters, resin chemical shrinkage coefficient and composite material thermal physical property parameters.

[0023] Preferably, S3 is specifically:

[0024] Fiber Bragg grating sensors are implanted in Class B specimens to collect real temperature and strain change data inside and at the interface of the Class B specimen material in a curing environment with the same curing process as the nozzle. At the same time, a curing simulation model of the corresponding Class B specimen is established. Simulation calculations are performed on the Class B specimen under the same molding process to obtain temperature and strain change data inside the material under simulated conditions. The online monitoring data measured in the Class B specimen is compared with the finite element simulation results to correct the errors in the design parameters of the Class B specimen coupling.

[0025] Preferably, the design parameters of the type B sample coupling include interface thermal conductivity and interface contact properties.

[0026] Preferably, in S4, the preliminary optimization design adopts Taguchi optimization method.

[0027] Preferably, in S5, during the nozzle production process, sensors are implanted in the interlayers of the nozzle structure composite material, and sensors are further implanted in key locations where the internal stress is large and the risk of structural failure is high, as indicated by the curing simulation analysis results, to obtain test data for online monitoring during the nozzle pressurized curing molding process, the test data including the actual temperature and strain change data inside the material;

[0028] Based on the test data from the implanted fiber Bragg grating sensor, the errors in the thermophysical parameters of the composite materials, the interface contact properties, and the input errors in the interface thermal conductivity in the preliminary optimization model of the nozzle were corrected. The optimized design was carried out by combining the measured parameters with finite element simulation to form an optimized design model.

[0029] If the test data from online monitoring and the performance indicators of the final product meet the design requirements, the optimized design model is completed. Otherwise, S3-S5 are repeated for iterative optimization until the design requirements are met.

[0030] Therefore, the present invention adopts the above-mentioned composite nozzle design method based on online monitoring and simulation verification, and the beneficial effects are as follows:

[0031] (1) The present invention proposes for the first time a method for optimizing the design of a fully composite nozzle structure by combining online monitoring with simulation verification. This method does not increase the weight of the nozzle structure while improving the accuracy of the simulation model. The method for online monitoring of multiple parameters during the nozzle curing process based on optical fiber sensing technology is to place optical fibers in the in-plane direction and inter-layer interface direction of the multi-layer composite material structure of the nozzle during the nozzle preparation process, so as to perform online monitoring of multiple parameters during the nozzle curing process, thereby providing support for understanding the temperature and strain change laws during the nozzle curing process.

[0032] (2) The present invention can achieve full coverage of the nozzle curing process, and can arrange sensors in key areas of concern of various structural components of the nozzle according to structural design requirements without significantly affecting the mechanical properties of the composite nozzle.

[0033] (3) The present invention can be extended to the existing optimization design method of special-shaped composite material components that require multiple curing and molding. It is suitable for the structural optimization of one-piece molded nozzles prepared by winding (or other methods to replace cloth tape winding), and is suitable for the optimization design of all-composite nozzle structures (or special-shaped multi-layer composite material structures similar to nozzle structures) that undergo multiple curing processes. It has low cost and is easy to apply and promote.

[0034] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1This is a flow chart of Example 1 of a composite nozzle design method based on online monitoring and simulation verification of the present invention;

[0036] Figure 2 1 is a schematic structural diagram of a nozzle according to Embodiment 2 of a composite nozzle design method based on online monitoring and simulation verification of the present invention;

[0037] Figure 3 This is a schematic diagram of sensor layout on a composite material plate according to Example 2 of a composite material nozzle design method based on online monitoring and simulation verification of the present invention;

[0038] Figure 4 This is a lead-out schematic diagram of Example 2 of a composite nozzle design method based on online monitoring and simulation verification of the present invention;

[0039] Figure 5 This is a schematic diagram of the lead series connection of Example 2 of a composite nozzle design method based on online monitoring and simulation verification of the present invention;

[0040] Figure 6 It is a process and final effect diagram of Example 2 of a composite nozzle design method based on online monitoring and simulation verification of the present invention, wherein (a) is a schematic diagram of the interlayer sensor layout, (b) is a schematic diagram of the interlayer filling, (c) is a schematic diagram of the interlayer sensor lead extraction, and (d) is a schematic diagram of the overall packaging. DETAILED DESCRIPTION

[0041] The technical solution of the present invention is further described below with reference to the accompanying drawings and embodiments.

[0042] Unless otherwise defined, technical or scientific terms used in the present invention shall have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs.

[0043] This invention is funded by the “2023 Major Research Project of Hubei Province (JD) (2023BAA004)”.

[0044] Example 1

[0045] like Figure 1 As shown, a composite nozzle design method based on online monitoring and simulation verification includes the following steps:

[0046] S1. Establish a preliminary design model. Specifically:

[0047] The preliminary design of the nozzle scheme is carried out based on the empirically designed structural parameters and traditional finite element simulation to obtain a preliminary design model.

[0048] S2. Identify key control parameters and obtain a sample-level online monitoring plan. Specifically:

[0049] Based on the preliminary design model, key control parameters affecting product performance were identified, and representative basic specimens were prepared. These specimens included Type A specimens and Type B specimens. Type A specimens were fabricated from multiple composite materials constituting the nozzle structure, while Type B specimens were fabricated from multiple composite materials stacked in pairs. In this embodiment, the representative basic specimens were either flat, L-shaped, or conical.

[0050] S3: Online monitoring of representative basic sample level, data collection and analysis, and simulation verification, to modify the simulation parameters of the preliminary design model obtained in S1.

[0051] A fiber Bragg grating sensor is implanted in the Class A specimen to collect the internal temperature data and strain change data of the real Class A specimen in the curing environment with the same curing process as the nozzle. At the same time, a curing simulation model of the corresponding Class A specimen is established, and simulation calculations are performed on the Class A specimen under the same molding process to obtain the internal temperature data and strain change data of the Class A specimen under the simulated conditions.

[0052] The fiber Bragg grating sensors were implanted in representative locations determined through preliminary simulations. The online monitoring data from the Class A specimens was compared with the finite element simulation results, and the relevant physical property parameters of the Class A specimens from the finite element simulations were corrected. These relevant physical property parameters included the resin curing kinetics, the resin chemical shrinkage coefficient, and the composite material's thermal properties.

[0053] Fiber Bragg grating sensors are implanted in Class B specimens to collect actual temperature and strain change data inside and at the interface of the Class B specimen material in a curing environment with the same curing process as the nozzle. A curing simulation model of the corresponding Class B specimen is established, and simulation calculations are performed on the Class B specimen under the same molding process to obtain temperature and strain change data inside the material under simulated conditions. The online monitoring data measured in the Class B specimens are compared with the finite element simulation results, and the errors in the coupled design parameters of the Class B specimens are corrected. The coupled design parameters of the Class B specimens include interface thermal conductivity and interface contact properties.

[0054] S4. Carry out simulation analysis of nozzle structure curing and use Taguchi optimization method for preliminary optimization design to obtain the preliminary optimization model of the nozzle.

[0055] S5. During the nozzle production process, sensors are implanted between the layers of the nozzle structure composite material. Sensors are further implanted in key locations with high internal stress and high risk of structural failure, as indicated by the curing simulation analysis results. This allows for online monitoring of the nozzle during pressurized curing and molding, including actual temperature and strain change data within the material.

[0056] Based on the test data from the implanted fiber Bragg grating sensor, the errors in the thermophysical parameters of the composite materials, the interface contact properties, and the input errors in the interface thermal conductivity in the preliminary optimization model of the nozzle were corrected. The optimized design was carried out by combining the measured parameters with finite element simulation to form an optimized design model.

[0057] If the test data from online monitoring and the performance indicators of the final product meet the design requirements, the optimized design model is completed. Otherwise, S3-S5 are repeated for iterative optimization until the design requirements are met.

[0058] Example 2

[0059] Using the optimization design method of Example 1, taking the nozzle prototype as an example, the steps are as follows:

[0060] S1. Combining the structural parameters and working load boundary conditions designed with experience, the schematic diagram of the nozzle prototype is as follows: Figure 2 As shown, the ablation layer is wound obliquely at 20°, the thermal insulation layer is wound flat at 0°, and the composite material structure layer is formed by unidirectional tape laying with a laying angle of [45° / -45° / 0° / -45° / 45° / 90°]s.

[0061] S2. Identify key control parameters and obtain sample-level online monitoring solutions.

[0062] The ablative layer and thermal insulation layer are both formed by winding with cloth tape and need to be cured simultaneously. The composite material structure layer is formed by unidirectional tape laying and then cured again on the basis of the ablative layer and thermal insulation layer. Three Class A specimens and two Class B specimens were obtained. The key control parameters of the nozzle structure reliability were identified:

[0063] a) Interlayer stresses in the ablative and thermal insulation layers during the curing process. These include interlayer tensile stress in the ablative layer, interlayer shear stress in the ablative layer, interlayer tensile stress in the thermal insulation layer, interlayer shear stress in the thermal insulation layer, and interlayer tensile stress and shear stress in the ablative / thermal insulation layer. Excessive stress values ​​can lead to interlayer cracking and structural failure.

[0064] b) The internal stress of the composite material structure during the curing process and the interface deformation matching performance between the composite material structure and the thermal insulation layer. This includes the internal stress of the composite material structure during curing, the interfacial tensile stress between the composite material structure and the thermal insulation layer, and the interfacial shear stress between the composite material structure and the thermal insulation layer.

[0065] If the placement angle within the composite material layer results in high stress values, the composite material layer will crack and lose its load-bearing capacity. The mismatch in interface deformation between the composite material layer and the thermal insulation layer due to material and process differences can lead to interfacial debonding during the curing process, resulting in structural failure. Therefore, the key control parameters identified are the interlaminar stresses generated during the curing process between the nozzle ablative layer, the thermal insulation layer, and the composite material layer.

[0066] S3: Online monitoring of representative basic sample level, data collection and analysis, and simulation verification, to modify the simulation parameters of the preliminary design model obtained in S1.

[0067] A fiber Bragg grating sensor is implanted in the Class A specimen to collect the actual temperature and strain change data inside the Class A specimen material in a curing environment with the same curing process as the nozzle. At the same time, a corresponding curing simulation model of the Class A specimen is established, and simulation calculations are performed on the Class A specimen under the same molding process to obtain the temperature and strain change data inside the material under the simulated conditions. The location for implanting the fiber Bragg grating sensor is selected from a representative location identified through preliminary simulation calculations. Based on the online monitoring data measured in the specimen and compared with the finite element simulation results, the physical properties of the single-element composite material simulated by the finite element simulation (the relevant physical properties include resin curing kinetic parameters, resin chemical shrinkage coefficient, composite material thermal properties, etc.) are corrected.

[0068] Fiber Bragg grating sensors are implanted in Class B specimens to collect the actual temperature and strain change data inside and at the interface of the Class B specimen material in a curing environment with the same curing process as the nozzle. At the same time, a corresponding curing simulation model of the Class B specimen is established, and simulation calculations are performed on the Class B specimens under the same molding process to obtain the temperature and strain change data inside the material under the simulated conditions. The location for implanting the fiber Bragg grating sensor can be selected from the representative location identified by preliminary simulation calculations. Based on the online monitoring data measured in the specimen and compared with the finite element simulation results, the errors of the integrated coupling parameters of multiple composite materials (the integrated coupling parameters of multiple composite materials include interface thermal conductivity and interface contact properties) are corrected.

[0069] The representative basic specimen is a flat-plate composite structural member. In order to obtain the changing laws of temperature, interlaminar shear stress, and interlaminar tensile stress of the composite structural member during the curing process, and to provide a basis for the curing simulation effect and structural reliability evaluation of the composite structural member, an optical fiber online monitoring test of the composite flat-plate specimen during the curing process was carried out. The specimen working conditions are shown in Table 1.

[0070] Table 1 Test specimen working conditions

[0071]

[0072]

[0073] Composite slabs were cured under various curing conditions, and fiber Bragg grating sensors were used to monitor interlaminar shear stress, interlaminar tensile stress, and temperature field changes. The fiber Bragg grating sensor placement was designed, with one fiber optic strain sensor and one fiber optic temperature sensor placed between the two composite slabs in each curing condition test piece. A fiber optic strain sensor was also placed along the Z-axis at the center of the two slabs. This sensor placement was used for monitoring the composite slabs under each curing condition.

[0074] The sensor layout needs to monitor the transverse and longitudinal stress between layers, and it is necessary to ensure that the sensor layout does not crosstalk. The sensor layout line is optimized. The sensor layout diagram is as follows Figure 3 As shown in the figure, the interlayer sensors are mainly concentrated in the center of the composite plate. Since the grating temperature sensor has a stress isolation structure and its size is significantly larger than that of the grating strain sensor, the layout position is moved to the periphery to ensure that the sensor leads are led out along the designed position. Figure 6 As shown in (a), after the X- and Y-direction temperature sensors and strain sensors are laid out, the leads are all led out along the Y direction. The Z-direction sensor is laid out at the center of the contact surface of the two composite material plates, and the sensor is kept between the two layers and is led out vertically along the Z direction along the center hole.

[0075] Due to the large size of the grating temperature sensor, if the upper composite material plate is directly covered on the top of the sensor, a large cavity will appear on the contact surface between the layers, affecting the curing effect. Therefore, the same material as the composite material plate under the corresponding working conditions is used for filling to make the interlayer flat to ensure a good curing effect of the composite material plate. The same material is used for filling until it is flush with the edge of the grating temperature sensor. The interlayer structure after filling is as follows: Figure 6 The composite flat plates are arranged in this way under all working conditions.

[0076] like Figure 4 The figure shows the schematic diagram of the sensor leads at various positions on the composite material flat plate. Each sensor lead is led out along the Y direction. The sensor leads are symmetrically arranged in the XOY plane. At the Y-direction lead-out position, each lead is symmetrically led out with the center line as the symmetry axis. The sensor leads on one side of the center line are marked with the corresponding sensor.

[0077] based on Figure 4 Schematic diagram of the lead-out of the optical fiber sensor. Design of the optical fiber sensor series circuit. Since the series circuit will increase the melting point of the optical fiber, considering the signal loss of the optical fiber, the number of sensors in each series circuit shall not exceed 3. The sensor circuit series connection method is as follows: Figure 5 As shown. Figure 5As shown in the sensor diagram corresponding to the middle lead, the red line includes the X-axis temperature sensor, Y-axis temperature sensor, and X-axis strain sensor, while the blue line includes the Y-axis strain sensor and Z-axis strain sensor. Each set of test pieces was tested by connecting the sensors in series to the demodulator in this manner.

[0078] After the fiber optic sensor is laid out between the composite material layers, the vacuum bag needs to be evacuated during the curing of the composite material. Since the fiber optic sensor is between the two composite material layers, the lead wire is in a suspended state and needs to be fixed and protected. A flexible inclined platform is built with silicone sheets to allow the optical fiber to be led out of the vacuum bag along the silicone inclined platform. The lead-out method is as follows: Figure 6 As shown in (c) in .

[0079] Since the Z-direction sensor is led out vertically, the vacuum bag can be squeezed to form a fold at the Z-direction sensor lead-out position. When vacuuming, the Z-direction sensor lead is kept vertically led out. The overall sensor lead package is as follows: Figure 6 As shown in (d) in .

[0080] S4. Conduct a curing simulation analysis of the nozzle structure and perform a preliminary optimization design using the Taguchi optimization method to obtain a preliminary optimized nozzle model. This preliminary optimization model includes the nozzle's structural layer layup angle scheme and interlaminar elastic layer parameter design scheme. Additional sensors can be implanted in critical areas with high internal stress and a higher risk of structural failure, as determined by the curing simulation.

[0081] S5. Nozzle online monitoring, data acquisition, analysis and simulation verification. Based on the preliminary optimization model of the nozzle, nozzle production and online data acquisition are carried out. During the nozzle production process, sensors are implanted between the layers of the composite material in the nozzle structure to obtain the actual temperature and strain change data inside the material during the nozzle pressurized curing molding process. Based on the sensor test data, the errors in the thermal physical parameters and interface contact parameters of various composite materials in the preliminary optimization model, as well as the input errors of environmental heat conduction, are corrected again. If the test data monitored by the fiber optic sensor and the final product performance indicators meet expectations, the optimized design model is completed.

[0082] Therefore, the present invention adopts the above-mentioned composite nozzle design method based on online monitoring and simulation verification, which does not increase the weight of the nozzle structure while performing online monitoring of multiple parameters during the nozzle curing process, providing support for understanding the temperature and strain change laws during the nozzle curing process.

[0083] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit the same. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solutions of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A composite nozzle design method based on online monitoring and simulation verification, characterized in that: The following steps are involved: S1. Establish a preliminary design model; S2. Identify key control parameters and obtain sample-level online monitoring solutions; S3: Online monitoring of representative basic sample levels, data collection and analysis, and simulation verification, to modify the simulation parameters of the preliminary design model obtained in S1; S4. Conduct simulation analysis and preliminary optimization design of the nozzle structure to obtain a preliminary optimization model of the nozzle; S5. Based on the preliminary nozzle optimization model, nozzle production, online data collection and simulation verification are carried out. If the online monitoring test data and the final product performance indicators meet the design requirements, the optimized design model is completed. Otherwise, repeat S3-S5 for iterative optimization until the design requirements are met.

2. The composite nozzle design method based on online monitoring and simulation verification according to claim 1 is characterized in that: S1 is specifically: The preliminary design of the nozzle scheme was carried out based on the empirically designed structural parameters and traditional finite element simulation to obtain a preliminary design model.

3. The composite nozzle design method based on online monitoring and simulation verification according to claim 2 is characterized in that: S2 is specifically: Based on the preliminary design model, the key control parameters affecting the product performance are identified, and representative basic specimens are prepared. The representative basic specimens include Class A specimens and Class B specimens. The Class A specimens are made separately from the multiple composite materials that constitute the nozzle structure, and the Class B specimens are made from the multiple composite materials that constitute the nozzle structure, which are combined and stacked in pairs.

4. The composite nozzle design method based on online monitoring and simulation verification according to claim 3 is characterized in that: The representative basic specimen is one of a flat plate, an L-shape or a conical shape.

5. The composite nozzle design method based on online monitoring and simulation verification according to claim 3 is characterized in that: S3 specifically: A fiber Bragg grating sensor is implanted in the Class A specimen to collect the internal temperature data and strain change data of the real Class A specimen in the curing environment with the same curing process as the nozzle. At the same time, a curing simulation model of the corresponding Class A specimen is established, and simulation calculations are performed on the Class A specimen under the same molding process to obtain the internal temperature data and strain change data of the Class A specimen under the simulated conditions. The location for implanting the fiber grating sensor can be selected from the representative location obtained through preliminary simulation calculations. The online monitoring data measured in the Class A specimen can be compared with the finite element simulation results, and the relevant physical properties of the Class A specimen simulated by the finite element can be corrected.

6. The composite nozzle design method based on online monitoring and simulation verification according to claim 5 is characterized in that: The relevant physical property parameters include resin curing kinetic parameters, resin chemical shrinkage coefficient and composite material thermal physical property parameters.

7. The composite nozzle design method based on online monitoring and simulation verification according to claim 3 is characterized in that: S3 specifically: Fiber Bragg grating sensors are implanted in Class B specimens to collect real temperature and strain change data inside and at the interface of the Class B specimen material in a curing environment with the same curing process as the nozzle. At the same time, a curing simulation model of the corresponding Class B specimen is established. Simulation calculations are performed on the Class B specimen under the same molding process to obtain temperature and strain change data inside the material under simulated conditions. The online monitoring data measured in the Class B specimen is compared with the finite element simulation results to correct the errors in the design parameters of the Class B specimen coupling.

8. The composite nozzle design method based on online monitoring and simulation verification according to claim 7 is characterized in that: The design parameters of the type B sample coupling include interface thermal conductivity and interface contact properties.

9. The composite nozzle design method based on online monitoring and simulation verification according to claim 1 is characterized in that: In S4, the preliminary optimization design adopts Taguchi optimization method.

10. A composite nozzle design method based on online monitoring and simulation verification according to claim 5 or 8, characterized in that: In S5, during the nozzle production process, sensors are implanted between the composite material layers of the nozzle structure. Sensors are then implanted in key locations where internal stress is high and the risk of structural failure is high, as indicated by the curing simulation analysis results. This allows for online monitoring of the nozzle during pressurized curing, including actual temperature and strain changes within the material. Based on the test data from the implanted fiber Bragg grating sensor, the errors in the thermophysical parameters of the composite materials, the interface contact properties, and the input errors in the interface thermal conductivity in the preliminary optimization model of the nozzle were corrected. The optimized design was carried out by combining the measured parameters with finite element simulation to form an optimized design model. If the test data from online monitoring and the performance indicators of the final product meet the design requirements, the optimized design model is completed. Otherwise, S3-S5 are repeated for iterative optimization until the design requirements are met.

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