Data model system for blending and curing thermosetting resin

Abstract

The invention discloses a data model system for blending and curing thermosetting resin, which comprises a mobile terminal (APP) used for providing an interface for a user to interact with the system; the neural network database is used for storing and managing related data of a neural network; according to the method, corresponding three-dimensional model modeling and external environment temperature setting are carried out according to the actual use shape of the thermosetting resin, so that the calculation result is more accurate, a large amount of analog simulation is carried out on different environment factors, all obtained simulation data are counted, and neural network training is carried out to optimize data; and the optimized data statistical model is converted and output as an APP of a user-defined interaction interface and a use mode, and an operator can correct the thermosetting resin blending and curing simulation model according to actual conditions to obtain a more accurate result.

Description

Technical Field

[0001] This invention relates to the field of data statistical modeling technology, specifically to a data modeling system for thermosetting resin blend curing. Background Technology

[0002] Thermosetting resins possess many excellent properties, such as superior mechanical properties, adhesive properties, corrosion resistance, low shrinkage, and electrical insulation. Therefore, thermosetting resins are widely used in the encapsulation of electronic components, integrated circuits, and transformers.

[0003] However, in traditional methods, thermosetting resins, after curing, form a network structure due to intermolecular cross-linking, resulting in a brittle texture. Therefore, single thermosetting resins have inherent limitations. Blending thermosetting resins can compensate for some of these limitations. Research on the curing of thermosetting resin blends is necessary in certain fields. Simulation methods can provide a comprehensive study of the curing of thermosetting resin blends. Analyzing the internal temperature and curing fields of thermosetting resins can assess the influence of various parameters on the curing process and curing effect, thereby identifying key factors and controllable indicators that affect the curing process and curing effect, and providing a basis for optimizing the curing process.

[0004] In summary, a data model system for thermosetting resin blend curing is needed to solve the above problems. Summary of the Invention

[0005] The purpose of this invention is to provide a data model system for the co-curing of thermosetting resins to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A data modeling system for thermosetting resin blend curing includes:

[0008] A mobile terminal (APP), which provides an interface for users to interact with the system;

[0009] A neural network database, used to store and manage data related to neural networks;

[0010] A curing kinetic model, which is used to describe the kinetic characteristics of thermosetting resins during the curing process;

[0011] A heat transfer model, which is used to describe the heat conduction and convective heat transfer during the curing process of thermosetting resins;

[0012] A thermosetting resin blending curing module is used to integrate a curing kinetics model and a heat transfer model and to numerically simulate the curing process of thermosetting resins.

[0013] As a preferred technical solution for a data model system for thermosetting resin blend curing, the establishment of the thermosetting resin blend curing module in the data model system for thermosetting resin blend curing includes the following steps:

[0014] S1. Obtain the material parameters for curing the blended thermosetting resin through experiments, and determine the data for simulating the curing process of the thermosetting resin;

[0015] S2. Establish the 3D model and mathematical model and set boundary conditions;

[0016] S3. Simulation calculations are used to determine the distribution and changes of the internal temperature field and degree of cure field of the thermosetting resin;

[0017] S4. Based on the numerical simulation results, establish a statistical model for thermosetting resin data through neural network training and prediction;

[0018] S5. After the thermosetting resin curing simulation is completed, the numerical simulation parameters and data statistical model are converted into a mobile terminal (APP) and interact with the mobile terminal (APP).

[0019] As a preferred technical solution for the data model system of thermosetting resin blend curing, the material parameters of the thermosetting resin blend curing obtained through experiments in step S1 above include the following steps:

[0020] S101. Blended thermosetting resin samples were obtained through experiments;

[0021] S102. Obtain the material parameters of the thermosetting resin during curing, including density, specific heat capacity, and thermal conductivity;

[0022] S103. Determine the parameters of the external environment in the experiment and consider the influence of the external environment on the experiment.

[0023] As a preferred technical solution for the data model system of thermosetting resin blend curing, step S2, which establishes the three-dimensional model and mathematical model and sets boundary conditions, includes the following steps:

[0024] S201. Establish a simple three-dimensional geometric model of the thermosetting resin based on the actual situation;

[0025] S202. Use heat transfer equations to describe the curing process of thermosetting resins, taking into account the Fourier heat conduction equation, transient heat transfer, and internal heat generation terms;

[0026] S203. Consider the convective heat transfer with the external environment during the curing process and set the corresponding mathematical expression.

[0027] As a preferred technical solution for the data model system of thermosetting resin blend curing, step S3, which involves simulating and calculating the distribution and changes of the internal temperature field and degree of cure field of the thermosetting resin, includes the following steps:

[0028] S301. Set the initial ambient temperature and internal heat source at the start of thermosetting resin curing;

[0029] S302. Mesh the established 3D model;

[0030] S303. Perform transient solution to calculate the distribution and changes of the temperature field and the degree of cure field;

[0031] S304. Describe the results, displaying them using cloud plots and dot plots.

[0032] As a preferred technical solution for the data model system of thermosetting resin blend curing, step S4, which establishes a statistical data model for thermosetting resin through neural network training and prediction, includes the following steps:

[0033] S401. Statistical analysis of determined material data parameters and simulation results under different 3D models and boundary conditions;

[0034] S402. Use the learning sample data obtained from the finite element simulation scheme to train the neural network;

[0035] S403. Obtain the improved data statistical model to predict various parameters during the curing process of thermosetting resins.

[0036] As a preferred technical solution for the data model system of thermosetting resin blend curing, step S5, which converts numerical simulation parameters and data statistical models into a mobile terminal (APP), includes the following steps:

[0037] S501. Based on the statistically obtained data, convert and output the simulation parameters and data statistical model to the mobile terminal (APP);

[0038] S502. The mobile terminal (APP) allows users to select different blended thermosetting resins;

[0039] S503. Users can create different geometric models, adjust the mesh generation results, and change material and boundary condition settings.

[0040] Compared with the prior art, the beneficial effects of the present invention are:

[0041] 1. This invention uses a three-dimensional model to create a corresponding shape for the actual use of thermosetting resins and sets the external ambient temperature, making the calculation results more accurate;

[0042] 2. This invention performs extensive simulations of different environmental factors, statistically analyzes all obtained simulation data, and trains neural networks to optimize the data;

[0043] 3. This invention evaluates the influence of various curing process parameters and the geometric dimensions of the object to be cured on the curing process and curing effect, thereby identifying key factors and controllable indicators that affect the curing process and curing effect, and providing a basis for optimizing the curing process;

[0044] 4. This invention converts the optimized data statistical model into an APP with a user-defined interactive interface and usage mode. Operators can modify the simulation model of thermosetting resin blend curing according to the actual situation to obtain more accurate results. Attached Figure Description

[0045] Figure 1 A data model system diagram for thermosetting resin blend curing is shown;

[0046] Figure 2 A flowchart illustrating the data model establishment method for thermosetting resin blend curing is shown. Detailed Implementation

[0047] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] Please see Figure 1 as well as Figure 2 The present invention provides a technical solution:

[0049] A data modeling system for thermosetting resin blend curing includes:

[0050] A mobile terminal (APP), which provides an interface for users to interact with the system;

[0051] A neural network database, used to store and manage data related to neural networks;

[0052] A curing kinetic model, which is used to describe the kinetic characteristics of thermosetting resins during the curing process;

[0053] A heat transfer model, which is used to describe the heat conduction and convective heat transfer during the curing process of thermosetting resins;

[0054] A thermosetting resin blending curing module is used to integrate a curing kinetics model and a heat transfer model and to numerically simulate the curing process of thermosetting resins.

[0055] Furthermore, the data model system for thermosetting resin blend curing, wherein the establishment of the thermosetting resin blend curing module includes the following steps:

[0056] S1. Obtain the material parameters for curing the blended thermosetting resin through experiments, and determine the data for simulating the curing process of the thermosetting resin;

[0057] S2. Establish the 3D model and mathematical model and set boundary conditions;

[0058] S3. Simulation calculations are used to determine the distribution and changes of the internal temperature field and degree of cure field of the thermosetting resin;

[0059] S4. Based on the numerical simulation results, establish a statistical model for thermosetting resin data through neural network training and prediction;

[0060] S5. After the thermosetting resin curing simulation is completed, the numerical simulation parameters and data statistical model are converted into a mobile terminal (APP) and interact with the mobile terminal (APP).

[0061] Furthermore, the process of obtaining the material parameters for curing the blended thermosetting resin through experiments in step S1 above includes the following steps:

[0062] S101. Blended thermosetting resin samples were obtained through experiments;

[0063] S102. Obtain the material parameters of the thermosetting resin during curing, including density, specific heat capacity, and thermal conductivity;

[0064] S103. Determine the parameters of the external environment in the experiment and consider the influence of the external environment on the experiment.

[0065] Furthermore, step S2, which establishes the three-dimensional model and mathematical model and sets boundary conditions, includes the following steps:

[0066] S201. Establish a simple three-dimensional geometric model of the thermosetting resin based on the actual situation;

[0067] S202. Use heat transfer equations to describe the curing process of thermosetting resins, taking into account the Fourier heat conduction equation, transient heat transfer, and internal heat generation terms;

[0068] S203. Consider the convective heat transfer with the external environment during the curing process and set the corresponding mathematical expression.

[0069] Furthermore, step S3, which involves simulating and calculating the distribution and changes of the internal temperature field and degree of cure field of the thermosetting resin, includes the following steps:

[0070] S301. Set the initial ambient temperature and internal heat source at the start of thermosetting resin curing;

[0071] S302. Mesh the established 3D model;

[0072] S303. Perform transient solution to calculate the distribution and changes of the temperature field and the degree of cure field;

[0073] S304. Describe the results, displaying them using cloud plots and dot plots.

[0074] Furthermore, step S4, which establishes a statistical model for thermosetting resin data through neural network training and prediction, includes the following steps:

[0075] S401. Statistical analysis of determined material data parameters and simulation results under different 3D models and boundary conditions;

[0076] S402. Use the learning sample data obtained from the finite element simulation scheme to train the neural network;

[0077] S403. Obtain the improved data statistical model to predict various parameters during the curing process of thermosetting resins.

[0078] Furthermore, step S5, which transforms the numerical simulation parameters and data statistical model into a mobile terminal (APP), includes the following steps:

[0079] S501. Based on the statistically obtained data, convert and output the simulation parameters and data statistical model to the mobile terminal (APP);

[0080] S502. The mobile terminal (APP) allows users to select different blended thermosetting resins;

[0081] S503. Users can create different geometric models, adjust the mesh generation results, and change material and boundary condition settings.

[0082] Example

[0083] The data model system for thermosetting resin blend curing consists of a mobile terminal, a neural network database, a curing kinetics model, a heat transfer model, and a thermosetting resin blend curing module. Its establishment process includes the following steps:

[0084] S1. Obtain the material parameters for curing the blended thermosetting resin through experiments, and determine the data for simulating the curing process of the thermosetting resin;

[0085] Specifically:

[0086] S101. Blended thermosetting resin samples were obtained through experiments;

[0087] S102. Obtain the material parameters of the thermosetting resin during curing, including density, specific heat capacity, and thermal conductivity;

[0088] S103. Determine the parameters of the external environment in the experiment and consider the influence of the external environment on the experiment;

[0089] S2. Establish the 3D model and mathematical model and set boundary conditions;

[0090] Specifically:

[0091] S201. Establish a simple three-dimensional geometric model of the thermosetting resin based on the actual situation;

[0092] S202. Use heat transfer equations to describe the curing process of thermosetting resins, taking into account the Fourier heat conduction equation, transient heat transfer, and internal heat generation terms;

[0093] S203. Considering the convective heat transfer with the external environment during the curing process, set the corresponding mathematical expression;

[0094] S3. Simulation calculations are used to determine the distribution and changes of the internal temperature field and degree of cure field of the thermosetting resin;

[0095] Specifically:

[0096] S301. Set the initial ambient temperature and internal heat source at the start of thermosetting resin curing;

[0097] S302. Mesh the established 3D model;

[0098] S303. Perform transient solution to calculate the distribution and changes of the temperature field and the degree of cure field;

[0099] S304. Describe the results, displaying them using contour plots and dot plots;

[0100] S4. Based on the numerical simulation results, establish a statistical model for thermosetting resin data through neural network training and prediction;

[0101] Specifically:

[0102] S401. Statistical analysis of determined material data parameters and simulation results under different 3D models and boundary conditions;

[0103] S402. Use the learning sample data obtained from the finite element simulation scheme to train the neural network;

[0104] S403. Obtain the improved data statistical model to predict various parameters in the thermosetting resin curing process;

[0105] S5. After the thermosetting resin curing simulation is completed, convert the numerical simulation parameters and data statistical model into a mobile terminal and allow the user to interact with the mobile terminal.

[0106] Specifically:

[0107] S501. Based on the statistically obtained data, convert and output the simulation parameters and data statistical model to the mobile terminal;

[0108] S502. The mobile terminal allows users to select different blended thermosetting resins;

[0109] S503. Users can create different geometric models, adjust the mesh generation results, and change material and boundary condition settings.

[0110] It should be noted that:

[0111] The steps for establishing a 3D model and a mathematical model and setting boundary conditions include:

[0112] A simple geometric three-dimensional model of the thermosetting resin is established based on the actual situation.

[0113] For the curing process of thermosetting resins, the heat transfer equation with temperature as the variable is based on the Fourier heat conduction equation, transient heat transfer, and internal heat generation terms, and is described by the following equation:

[0114]

[0115] In the formula, ρ, CP and k are the density, specific heat capacity and thermal conductivity of the thermosetting resin, respectively, u is the velocity vector, T is the absolute temperature, α is the degree of curing, ΔH is the heat of chemical reaction and t is the time;

[0116] For the curing process, thermosetting resin undergoes convective heat transfer with the external environment, and its mathematical expression is:

[0117]

[0118] In the formula, n is the boundary normal vector, h is the convective heat transfer coefficient, and Text is the external ambient temperature;

[0119] The solidification kinetics model is represented by a phenomenological model, which mainly uses semi-empirical formulas to represent the states before and after the reaction. The parameters in the equations are obtained through numerical simulation. This model does not consider the kinetic mechanism of the reaction process or the chemical composition of the system. Its mathematical expression is:

[0120]

[0121] In the formula, α is the degree of curing, dα / dt is the curing rate within a given time, A is the frequency factor, E is the activation energy, R is the gas constant, and m and n are the kinetic exponents of the reaction.

[0122] In practical applications, the above system allows users to convert and output statistically obtained data to a mobile terminal APP. The mobile terminal APP can freely switch between different blended thermosetting resins.

[0123] According to the staff's requirements, the mobile terminal APP establishes different geometric models, generates mesh division results for the geometric models, and freely adjusts the maximum and minimum unit sizes of the mesh.

[0124] When the actual situation differs, change the material and boundary condition settings;

[0125] After the calculation is completed, the user sees the output results, namely the display of the model and mesh, the temperature field and degree of cure field distribution during the thermosetting resin blending and curing process, and the curves of temperature and degree of cure changing over time at specific points.

[0126] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A data model system for the co-curing of thermosetting resin blends, characterized in that, include: A mobile terminal, wherein the mobile terminal is used to provide an interface for users to interact with the system; A neural network database, used to store and manage data related to neural networks; A curing kinetic model, which is used to describe the kinetic characteristics of thermosetting resins during the curing process; A heat transfer model, which is used to describe the heat conduction and convective heat transfer during the curing process of thermosetting resins; A thermosetting resin blending curing module is used to integrate a curing kinetics model and a heat transfer model and to numerically simulate the curing process of thermosetting resins.

2. The data model system for thermosetting resin blend curing according to claim 1, characterized in that, The establishment of the blended thermosetting resin curing module includes the following steps: S1. Obtain the material parameters for curing the blended thermosetting resin through experiments, and determine the data for simulating the curing process of the thermosetting resin; S2. Establish the 3D model and mathematical model and set boundary conditions; S3. Simulation calculations are used to determine the distribution and changes of the internal temperature field and degree of cure field of the thermosetting resin; S4. Based on the numerical simulation results, establish a statistical model for thermosetting resin data through neural network training and prediction; S5. After the thermosetting resin curing simulation is completed, the numerical simulation parameters and data statistical model are converted into a mobile terminal, which can then interact with the mobile terminal.

3. The data model system for thermosetting resin blend curing according to claim 2, characterized in that, The process of obtaining the material parameters for curing the blended thermosetting resin in step S1 above includes the following steps: S101. Blended thermosetting resin samples were obtained through experiments; S102. Obtain the material parameters of the thermosetting resin during curing, including density, specific heat capacity, and thermal conductivity; S103. Determine the parameters of the external environment in the experiment and consider the influence of the external environment on the experiment.

4. The data model system for thermosetting resin blend curing according to claim 3, characterized in that... Step S2, establishing the three-dimensional model and mathematical model and setting boundary conditions, includes the following steps: S201. Establish a simple three-dimensional geometric model of the thermosetting resin based on the actual situation; S202. Use heat transfer equations to describe the curing process of thermosetting resins, taking into account the Fourier heat conduction equation, transient heat transfer, and internal heat generation terms; S203. Consider the convective heat transfer with the external environment during the curing process and set the corresponding mathematical expression.

5. The data model system for thermosetting resin blend curing according to claim 4, characterized in that, The simulation calculation in step S3, which determines the distribution and changes of the internal temperature field and degree of cure field of the thermosetting resin, includes the following steps: S301. Set the initial ambient temperature and internal heat source at the start of thermosetting resin curing; S302. Mesh the established 3D model; S303. Perform transient solution to calculate the distribution and changes of the temperature field and the degree of cure field; S304. Describe the results, displaying them using cloud plots and dot plots.

6. The data model system for thermosetting resin blend curing according to claim 5, characterized in that, Step S4, which establishes a statistical model for thermosetting resin data through neural network training and prediction, includes the following steps: S401. Statistical analysis of determined material data parameters and simulation results under different 3D models and boundary conditions; S402. Use the learning sample data obtained from the finite element simulation scheme to train the neural network; S403. Obtain the improved data statistical model to predict various parameters during the curing process of thermosetting resins.

7. The data model system for thermosetting resin blend curing according to claim 6, characterized in that, Step S5, which transforms the numerical simulation parameters and data statistical model into a mobile terminal (APP), includes the following steps: S501. Based on the statistically obtained data, convert and output the simulation parameters and data statistical model to the mobile terminal (APP); S502. The mobile terminal (APP) allows users to select different blended thermosetting resins; S503. Users can create different geometric models, adjust the mesh generation results, and change material and boundary condition settings.

Images