Vehicle coating aging fine granularity calculation and fine granularity three-dimensional characterization method based on Arrhenius formula

Abstract

The invention discloses an automobile coating aging fine granularity calculation and fine granularity three-dimensional characterization method based on an Arrhenius formula. The method comprises the following steps: drawing a three-dimensional geometric model of an automobile; the method comprises the following steps: importing material characteristics of an automotive coating of an automobile into thermal analysis software, setting simulation condition parameters and selecting a basic solver; performing gridding division on the three-dimensional geometric model by utilizing gridding division software, and then completing simulation modeling; establishing an aging model of the vehicle coating based on an Arrhenius formula; sorting the temperature values and the received irradiation doses according to different moments, substituting the sorted temperature values and the received irradiation doses into an aging model, and calculating an aging coefficient value of the vehicle coating within cumulative time; displaying the aging coefficient values of all the test points on the vehicle coating as point cloud values to generate an aging coefficient distribution diagram; and based on the aging coefficient distribution diagram, in combination with actual measurement data of an outdoor exposure test, calculating a fitting relationship between the aging coefficient of the vehicle coating and the chromatic aberration value and a fitting relationship between the aging coefficient of the vehicle coating and the glossiness. The invention provides a quicker and more accurate evaluation means for material aging.

Description

Technical Field

[0001] The present invention relates to the technical field of aging simulation research of polymer materials, and particularly relates to a fine-grained calculation and fine-grained three-dimensional characterization method for vehicle coatings aging based on the Arrhenius formula. Background Art

[0002] Due to advantages such as light weight, high strength, and good corrosion resistance, polymer materials have been widely used in the automotive field. However, during processing, storage, and use, polymer materials are affected by comprehensive internal and external factors such as light, heat, oxygen, water, high-energy radiation, chemistry, and biological erosion, resulting in changes in their chemical composition and structure, and a gradual decline in physical properties, manifested as hardening, sticking, embrittlement, discoloration, loss of strength, etc., that is, the aging of polymer materials. Especially when a vehicle is exposed outdoors for a long time, it will be affected by factors such as ultraviolet rays, temperature changes, and humidity, leading to a gradual decline in material performance, and problems such as loss of gloss, discoloration, and coating cracking. These problems not only affect the appearance quality of the vehicle, but may also reduce the protective performance of the coating, accelerate the corrosion of the metal substrate, and thus shorten the service life of the vehicle.

[0003] Common aging test methods for automotive exterior coatings include natural exposure tests, artificial accelerated aging tests, solar tracking and concentrating accelerated aging tests, etc. However, these methods have problems such as long time consumption, high cost, and difficulty in accurate prediction. With the development of computer simulation technology, parameter values on the surface of automotive materials can be quickly obtained through simulation. As an empirical formula describing the change of chemical reaction rate with temperature, the Arrhenius formula has been widely used in material aging research. This formula predicts the aging behavior of materials at different temperatures by establishing the relationship between time and temperature. In the aging research of automotive polymer materials, the quantification method based on the Arrhenius formula can provide a fast and accurate evaluation means for material aging.

[0004] However, most of the existing aging models do not fully consider the comprehensive effects of multi-environmental factors such as irradiation intensity, and lack technical means for intuitively displaying the aging degree and speed. Summary of the Invention

[0005] To solve the above problems, the present invention is implemented according to the following technical solutions:

[0006] The present invention provides a fine-grained calculation and fine-grained three-dimensional characterization method for vehicle coatings aging based on the Arrhenius formula, and the method includes:

[0007] S100. Draw a three-dimensional geometric model of the vehicle through three-dimensional modeling software, and the three-dimensional geometric model includes the geometric structure of the vehicle coating;

[0008] S200. Import the material properties of the vehicle coating into the thermal analysis software, set the simulation condition parameters, and select the basic solver;

[0009] S300. After meshing the three-dimensional geometric model using the meshing software, complete the simulation modeling to obtain the continuous distribution results of the temperature value and received irradiation dose of the vehicle coating;

[0010] S400. Establish an aging model for the vehicle coating based on the Arrhenius formula;

[0011] S500. Organize the temperature value and received irradiation dose at different times and substitute them into the aging model to calculate the aging coefficient value of the vehicle coating within the cumulative time;

[0012] S600. Use a Web-based interactive data visualization application to display the aging coefficient values of all test points on the vehicle coating as point cloud values to generate an aging coefficient distribution map;

[0013] S700. Based on the aging coefficient distribution map and the measured gloss data of the outdoor exposure test, construct a polynomial regression analysis model to calculate the fitting relationships between the aging coefficient and color difference of the vehicle coating, and between the aging coefficient and gloss of the vehicle coating.

[0014] Preferably, in step S200, the simulation condition parameters include material parameters, meteorological parameters, environmental parameters, simulation duration, thermal field boundary conditions, and irradiation field boundary conditions.

[0015] Preferably, the aging model is:

[0016]

[0017] where I t is the radiation intensity received by the sample at time t, with the unit of J / m2; E a is the apparent activation energy, with the unit of kJ·mol-1; T t is the surface temperature of the sample at time t, with the unit of K; Δt is the value time interval, with the unit of s; R is the gas constant, 8.314 J·mol-1·K-1; A is the pre-exponential factor.

[0018] Preferably, in step S700, the fitting relationship is linear regression fitting or polynomial regression fitting.

[0019] Compared with the prior art, the beneficial effects of the present invention are:

[0020] A fine-grained calculation and fine-grained three-dimensional characterization method for vehicle coating aging based on the Arrhenius formula. By introducing three-dimensional modeling, grid division, thermal analysis simulation, and quantitative calculation based on the Arrhenius formula, a fine-grained simulation method for vehicle coating aging that can comprehensively consider the influence of multiple environmental factors is constructed. First, use three-dimensional modeling software to draw the three-dimensional geometric model of the vehicle, import the material properties of the vehicle coating, and combine with thermal analysis software for simulation modeling, which can accurately simulate the temperature distribution and irradiation reception of the vehicle coating in the actual use environment. This computer simulation-based method can not only quickly obtain the temperature and irradiation dose distribution on the coating surface, but also achieve fine-grained analysis of the coating aging process through grid division technology, thus overcoming the defects of long time consumption, high cost, and difficult accurate prediction of traditional test methods.

[0021] Furthermore, based on the Arrhenius formula, the present invention introduces the influence of irradiation intensity and establishes a more accurate vehicle coating aging model. By substituting the temperature value and irradiation dose obtained from the simulation into the aging model and calculating the aging coefficient within the cumulative time, the aging degree of the vehicle coating under different environmental conditions can be quantitatively evaluated. This method not only considers the key factor of temperature, but also fully combines the comprehensive effects of multiple environmental factors such as irradiation intensity, significantly improving the accuracy and reliability of aging prediction and making up for the deficiencies of existing aging models in multi-factor coupling.

[0022] In addition, through a Web-based interactive data visualization application program, the present invention visually displays the aging coefficient of the vehicle coating in the form of a point cloud map to generate an aging coefficient distribution map. This innovation enables users to visually observe the distribution differences of coating aging at different positions, quickly locate the areas with severe aging, and thus provide a scientific basis for the maintenance and repair of the coating. At the same time, based on the aging coefficient distribution map, the present invention further calculates the fitting relationship between the vehicle coating aging coefficient and color difference, glossiness, and establishes a quantitative connection between the aging coefficient and appearance performance indicators. This connection enables the aging coefficient to be indirectly evaluated through the more easily measurable color difference and glossiness, providing a new technical means for quickly and efficiently evaluating the aging state of vehicle coatings in practical applications and greatly improving the practicality and convenience of aging evaluation.

[0023] In summary, the present invention not only innovates and improves the existing research methods for vehicle coating aging technically, but also has significant advantages in practical applications. Through accurate simulation modeling, fine-grained aging analysis, intuitive visualization display, and quantitative connection between the aging coefficient and appearance performance indicators, the present invention provides an efficient, accurate, and economical solution for the aging research and application of vehicle coatings, which can effectively shorten the aging evaluation cycle, reduce research costs, and provide strong technical support for the design, optimization, and maintenance of vehicle coatings. Brief Description of the Drawings

[0024] The following further elaborates on the specific embodiments of the present invention in conjunction with the accompanying drawings, where:

[0025] Figure 1 is the technical schematic diagram of the present invention;

[0026] Figure 2 is the three-dimensional characterization result of a specific embodiment of the present invention;

[0027] Figure 3 is the prediction result of the aging dominant indicators (color difference, glossiness) of a specific embodiment of the present invention. Specific Embodiments

[0028] To enable those skilled in the art of this technology to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0029] The terms used in this application are only for the purpose of describing specific embodiments and are not intended to limit this application. Unless otherwise defined, the technical terms or scientific terms used in this specification should have the ordinary meaning understood by those of ordinary skill in the art to which this application belongs. The "first", "second" and similar terms used in this specification and the claims do not denote any order, quantity or importance, but are only used to distinguish different technical features.

[0030] The following describes the preferred embodiments of the present invention in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only for the purpose of illustrating and explaining the present invention and are not used to limit the present invention.

[0031] As shown in the figure, a method for fine-grained calculation and fine-grained three-dimensional characterization of vehicle coating aging based on the Arrhenius formula according to the present invention includes:

[0032] S100. Draw a three-dimensional geometric model of the vehicle through three-dimensional modeling software, and the three-dimensional geometric model includes the geometric structure of the vehicle coating.

[0033] It is understandable that the purpose of drawing a 3D geometric model of a car using 3D modeling software is to provide an accurate and detailed virtual model basis for subsequent simulation analysis. Through 3D modeling, the actual structure and coating distribution of the car can be accurately restored, ensuring that the simulation process can truly reflect the forces, lighting, and environmental impacts on the coating at different positions. The establishment of the 3D model not only improves the accuracy of the simulation but also provides the necessary geometric information for subsequent meshing and thermal analysis. In addition, using 3D modeling software enables flexible adjustment of the model details, such as the thickness, shape, and distribution of the coating, so as to better simulate different types of automotive coatings. This precise modeling method lays a solid foundation for the entire simulation process, making the subsequent simulation results more credible and practical.

[0034] S200. Import the material properties of the automotive coating into the thermal analysis software, and set the simulation condition parameters and select the basic solver.

[0035] Furthermore, the simulation condition parameters include material parameters, meteorological parameters, environmental parameters, simulation duration, thermal field boundary conditions, and irradiation field boundary conditions.

[0036] It should be noted that the purpose of importing the material properties of the automotive coating into the thermal analysis software, setting the simulation condition parameters, and selecting the basic solver is to provide the necessary physical and environmental parameters for the simulation process to ensure that the simulation results can truly reflect the aging behavior of the automotive coating in actual use. By importing material properties such as thermal conductivity, specific heat capacity, and radiation absorption rate, the thermal analysis software can accurately calculate the temperature distribution and thermal response of the coating under different environmental conditions. At the same time, setting simulation condition parameters such as meteorological parameters (temperature, humidity, wind speed), environmental parameters (light intensity, ultraviolet intensity), and the boundary conditions of the thermal field and irradiation field can comprehensively simulate the aging conditions of the automotive coating in the outdoor environment. In addition, selecting a suitable basic solver can improve the calculation efficiency and accuracy of the simulation, ensuring reliable results within a reasonable time. The implementation of this step enables the simulation process to comprehensively consider the impacts of various factors on the aging of the automotive coating, thus providing accurate data support for subsequent calculation and analysis of the aging coefficient.

[0037] S300. After meshing the 3D geometric model using the meshing software, complete the simulation modeling to obtain the continuous distribution results of the temperature values and received irradiation amounts of the automotive coating.

[0038] It should be noted that meshing is the process of decomposing a complex three-dimensional model into multiple small units. The purpose of step S300 is to make the simulation calculation more efficient and accurate. By dividing the model into fine grid cells, the temperature changes and irradiation reception conditions of the vehicle coating at different positions can be captured more meticulously, thereby enabling a fine-grained analysis of the coating aging process. This fine-grained simulation can reveal the differences in coating aging in local areas and provide richer data support for the subsequent calculation of aging coefficients. In addition, meshing can also improve the calculation efficiency of the simulation. By reasonably dividing the grid cells, the consumption of computing resources can be significantly reduced while ensuring the calculation accuracy. Finally, the temperature and irradiation distribution results generated in this step provide key input data for the establishment of the vehicle coating aging model and are an indispensable part of the entire simulation method.

[0039] S400. Establish an aging model for vehicle coatings based on the Arrhenius formula.

[0040] Specifically, the aging model is:

[0041] where I t is the radiation intensity received by the sample at time t, with the unit of J / m2; E a is the apparent activation energy, with the unit of kJ·mol-1; T t is the surface temperature of the sample at time t, with the unit of K; Δt is the value time interval, with the unit of s; R is the gas constant, 8.314 J·mol-1·K-1; A is the pre-exponential factor.

[0042] It should be noted that the Arrhenius formula is an empirical formula that describes the variation of chemical reaction rate with temperature and is widely used in the research of material aging. By introducing the Arrhenius formula, the present invention can quantitatively describe the aging rate of vehicle coatings under different temperature and irradiation conditions. The establishment of this model takes into account the influence of these two key factors, temperature and irradiation intensity, on coating aging, making the calculation of aging coefficients more scientific and accurate. Compared with traditional aging models, this model not only considers the important factor of temperature but also combines the influence of irradiation intensity, and can more comprehensively reflect the aging behavior of vehicle coatings in the actual use environment. This aging model based on the Arrhenius formula provides a theoretical basis for the subsequent calculation of aging coefficients, making the aging assessment more accurate and reliable, and providing strong technical support for the research and application of vehicle coatings.

[0043] S500. Organize the temperature values and received irradiation amounts according to different times and substitute them into the aging model to calculate the aging coefficient value of the vehicle coating within the cumulative time.

[0044] It should be noted that the purpose of step S500 is to convert the temperature and irradiation data obtained from the simulation into aging coefficients with practical significance through quantitative analysis. The aging coefficient is a key indicator for measuring the aging degree of the coating. By substituting the temperature and irradiation data at different times into the aging model, the aging rate and cumulative aging degree of the coating within different time periods can be calculated. This method can not only provide dynamic information on the coating aging process, but also intuitively reflect the aging state of the coating throughout the simulation cycle through the cumulative aging coefficient. Compared with traditional aging tests, this method can predict the long-term aging behavior of the coating in a short time, greatly shortening the time cycle of aging assessment and reducing the research cost. In addition, by accurately calculating the aging coefficient, the present invention provides a quantitative, efficient and reliable means for the aging assessment of vehicle coatings, which helps to optimize the design of coating materials and improve the aging resistance of coatings.

[0045] S600. Use a web-based interactive data visualization application to display the aging coefficient values of all test points on the vehicle coating as point cloud values to generate an aging coefficient distribution map.

[0046] It should be noted that the purpose of step S600 is to present complex simulation data in an intuitive and visual way, enabling users to quickly and clearly understand the aging distribution of the vehicle coating. By showing the aging coefficient in the form of a point cloud diagram, users can intuitively observe the differences in the aging degree of the coating at different positions, so as to quickly locate the areas with severe aging. This visualization method not only improves the readability and usability of the data, but also provides a scientific basis for the maintenance and repair of the coating. In addition, the web-based interactive application enables users to view and analyze the aging distribution map anytime and anywhere on different devices, greatly improving the sharing and convenience of the data. In this way, the present invention not only improves the efficiency of aging assessment, but also provides an intuitive and efficient visualization tool for the aging research and practical application of automotive coatings.

[0047] S700. Based on the aging coefficient distribution map and the measured glossiness data of the outdoor exposure test, construct a polynomial regression analysis model to calculate the fitting relationships between the aging coefficient of the vehicle coating and the color difference value, as well as between the aging coefficient of the vehicle coating and the glossiness.

[0048] It should be noted that the purpose of step S700 is to establish a quantitative relationship between the aging coefficient and the actually measurable appearance performance indicators (such as color difference and gloss), so as to provide a more convenient and efficient method for aging assessment in practical applications. Through the fitting relationship, users can indirectly evaluate the aging degree of the coating by measuring the two intuitive appearance indicators of the color difference and gloss of the coating. This method not only simplifies the process of aging assessment, but also improves the efficiency and practicality of the assessment. Combining the measured data of color difference and gloss in the whole vehicle outdoor exposure test. In practical applications, color difference and gloss are easily measurable parameters. Using the measured data in the outdoor exposure test, a polynomial regression analysis model is used to establish the quantitative internal relationship between the aging index (WSV) and the actual characterization indicators of aging (color difference, gloss). Users can quickly judge the aging state of the coating without complex simulation calculations, thus providing strong support for the maintenance, repair and quality control of the coating. In addition, this quantitative relationship also provides a new perspective for the study of coating aging, helps to deeply understand the internal relationship between the coating aging process and the change of appearance performance, and further promotes the development and application of vehicle coating technology.

[0049] Preferably, in step S700, the fitting relationship is linear regression fitting or polynomial regression fitting.

[0050] In a specific embodiment, the implementation steps are as follows:

[0051] (1) Referring to a certain brand and model of automobile, use CAD drawing software to draw a three-dimensional geometric model, which includes the geometric structure of the vehicle coating;

[0052] (2) Sort out the material properties of the vehicle coating in the three-dimensional geometric model and import them into the CAE software. Set the material, meteorological, environmental parameters and simulation duration, and set the boundary conditions of the thermal field and the irradiation field of Erhai Lake, and select the basic solver;

[0053] (3) Use grid drawing software to perform grid division on the three-dimensional geometric model, complete the simulation modeling, and obtain the continuous distribution results of the temperature value and the received irradiation amount of the vehicle coating;

[0054] (4) Establish an aging model of the vehicle coating based on the Arrhenius formula:

[0055]

[0056] where I t is the radiation intensity received by the sample at time t, with the unit of J / m2; E a is the apparent activation energy, with the unit of kJ·mol-1; T tis the surface temperature of the sample at time t, with the unit of K; Δt is the value time interval, with the unit of s; R is the gas constant, R = 8.314 J·mol-1·K-1; A is the pre-exponential factor;

[0057] (5) Use the Python software tool to organize the temperature values and received irradiation amounts of the vehicle coatings obtained from the simulation, and substitute them into the aging model according to different times to calculate the aging coefficient values of the vehicle coatings within the cumulative time;

[0058] (6) Build a web-based interactive data visualization application program through the Python software, and display the aging coefficient values of all test points on the vehicle coating calculated in step (5) as point cloud values to generate an aging coefficient distribution map;

[0059] (7) Based on the aging coefficient distribution map generated in step (6), calculate the fitting relationships between the aging coefficient and the color difference value, and between the aging coefficient and the glossiness of the vehicle coating.

[0060] As described above, it is only a preferred embodiment of the present invention, and there is no limitation in any form to the present invention. Therefore, any modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A method for calculating and characterizing the aging of automotive coatings based on the Arrhenius formula, characterized in that: The method comprises: S100, drawing a three-dimensional geometric model of the automobile using three-dimensional modeling software, wherein the three-dimensional geometric model includes a geometric structure of the automobile coating; S200, importing the material properties of the vehicle coating into thermal analysis software, setting simulation condition parameters and selecting a basic solver; S300, meshing the three-dimensional geometric model using meshing software to complete simulation modeling and obtain continuous distribution results of the temperature value and received radiation amount of the vehicle coating; S400, establish an aging model for automotive coatings based on the Arrhenius formula; S500, sorting the temperature value and the received radiation amount at different times and inputting them into the aging model to calculate the aging coefficient value of the vehicle coating within the accumulated time; S600, using a web-based interactive data visualization application, the aging coefficient values ​​of all test points on the automotive coating are displayed as point cloud values ​​to generate an aging coefficient distribution map; S700: Based on the aging coefficient distribution diagram and the measured gloss data of the outdoor exposure test, a polynomial regression analysis model is constructed to calculate the fitting relationship between the aging coefficient of the automotive coating and the color difference value, and between the aging coefficient of the automotive coating and the gloss.

2. According to claim 1, a fine-grained calculation and fine-grained three-dimensional characterization method for automotive coating aging based on the Arrhenius formula is characterized by: In step S200, the simulation condition parameters include material parameters, meteorological parameters, environmental parameters, simulation time, thermal field boundary conditions and radiation field boundary conditions.

3. The fine-grained calculation and fine-grained three-dimensional characterization method for automotive coating aging based on the Arrhenius formula according to claim 1 is characterized in that: The aging model is: Among them, I t is the radiation intensity received by the sample at time t, in J / m2; E a is the apparent activation energy, in kJ·mol-1; T t is the surface temperature of the sample at time t, in K; Δt is the sampling time interval, in s; R is the gas constant, 8.314 J·mol-1·K-1; A is the prefactor.

4. The method for fine-grained calculation and fine-grained three-dimensional characterization of automotive coating aging based on the Arrhenius formula according to claim 1 is characterized by: In step S700, the fitting relationship is a linear regression fitting or a polynomial regression fitting.

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