A method and system for evaluating polymer material lifespan

Abstract

This invention provides a method and system for assessing the lifespan of polymer materials, comprising: determining the glass transition temperature of the polymer material; selecting at least four test temperatures based on the obtained glass transition temperature; determining the test time for the polymer material; determining the sampling cycle for the test; conducting a thermal aging test based on the obtained test temperature, sampling cycle, and test time; and measuring and statistically analyzing the test results data; optimizing the obtained test results data to minimize the error function; determining the physical quantities for assessing the lifespan of the polymer material; and predicting the lifespan of the polymer material based on the obtained physical quantities for assessing the lifespan. Using the scheme of this invention, the aging behavior of polymer materials can be studied quickly and accurately, and the assessed lifespan of the polymer material is almost consistent with the actual situation.

Description

Technical Field

[0001] This invention belongs to the field of polymer material life assessment technology, specifically relating to a polymer material life assessment method and a polymer material life assessment system. Background Technology

[0002] Polymer aging refers to the phenomenon where, during processing, storage, and use, the properties of polymer materials gradually deteriorate due to the combined effects of internal and external factors, eventually leading to their loss of usability. Polymer materials are widely used in various fields of national production and daily life. Studying the aging behavior of plastics can not only save costs and reduce the loss of raw materials and energy, but also effectively avoid safety hazards and ensure the safety of people's production and lives, thus having significant economic and social implications. Furthermore, research on the aging behavior of polymer materials can promote an understanding of the aging mechanism of polymer materials, grasp the objective laws governing changes in plastic structure, and thus correctly adopt various stabilization measures to extend their service life and promote the research and development of new materials and methods. In short, in-depth research on the aging behavior of polymer materials is crucial from both theoretical and practical perspectives.

[0003] Traditional methods for studying the aging behavior of polymer materials include accelerated aging tests, empirical equations, and correlation analysis between natural aging and artificial climate aging. Currently, a significant research achievement in this field is the method for handling the bending of the Arrhenius curve. This method assumes that the degradation reaction of a material at a series of temperatures is determined by two competing reactions, thus identifying a transition temperature, or activation energy inflection point, which divides the Arrhenius curve into two separate parts. The activation energy is lower in the lower temperature range and remains constant within this range. This method has yielded relatively good results in predicting performance changes for various organic polymer materials. However, when studying the aging of polycarbonate (PC) films at different temperatures in air and water, using the transition temperature principle to predict the lifespan of PC films at lower temperatures yields significantly inaccurate results.

[0004] In addition, the wear-out method can be used to study the service life of organic polymer materials at different temperatures: First, it is assumed that the degradation of organic polymer materials within a given temperature range can be simulated by a time-temperature equivalent model, and it is assumed that the dependence of aging index on time changes exponentially between the two temperatures. Then, the kinetic relationship of the performance with time obtained by aging the material at a low temperature for a period of time and then aging it at a high temperature can be used to obtain the extended curve of the performance change at low temperature through a time-temperature conversion model.

[0005] As mentioned earlier, many empirical formulas and theoretical models have been established for the aging behavior of polymer materials. However, the prominent problem is that the existing models and relationships lack universality for various environmental conditions and materials, are relatively complex to use, and the reliability of the obtained life prediction results needs further verification.

[0006] Studies have shown that the aging behavior of polymer materials involves two processes: post-curing and degradation. These two processes combine to create the unique aging behavior of polymer materials. Therefore, how to rapidly and accurately study the aging behavior (lifespan assessment) of polymer materials based on these two processes is a problem that needs to be solved. Summary of the Invention

[0007] The purpose of this invention is to provide a method and system for assessing the lifespan of polymer materials, which can at least quickly and accurately conduct research on the aging behavior (lifespan assessment) of polymer materials.

[0008] To achieve the above objectives, the present invention adopts the technical solution described below.

[0009] A method for assessing the lifespan of polymer materials, comprising the following steps:

[0010] Step 1: Determine the glass transition temperature of the polymer material;

[0011] Step 2: Based on the obtained glass transition temperature, select at least four test temperatures. The test temperatures must not exceed the glass transition temperature of the polymer material, and the four test temperature ranges should be close to or cover the working temperature. Close to means that the difference between the two is 10℃-30℃.

[0012] Step 3: Determine the testing time for the polymer materials and determine the sampling cycle according to formula (Ⅰ).

[0013] t't(h)=2 n-1 ……………………(Ⅰ)

[0014] In the formula, n = 1, 2, ..., and are integers, and t' represents the sampling period;

[0015] Step 4: Conduct a thermal aging test based on the obtained test temperature, sampling cycle, and test time, and measure and statistically analyze the test results data;

[0016] Step 5: Optimize the obtained experimental results data according to Equation (II) to minimize the error function φ, and obtain the values ​​of a, b, c, e1, f1, e2, and f2.

[0017]

[0018] In the formula, I iI represents the result data of the i-th experiment. i0 t represents the actual test value (i.e., the characteristic parameter of the test object). i T represents the time of the i-th test result data. i The temperature I represents the i-th test result data. i (t i T i ), 3…N and all are integers, representing an array of calculated values;

[0019] Step 6: Combine the obtained values ​​of a, b, c, e1, f1, e2, f2 and the working temperature of the polymer material, determine the physical quantities for assessing the lifespan of the polymer material according to formula (Ⅲ), and estimate the lifespan of the polymer material based on the obtained physical quantities for assessing the lifespan.

[0020]

[0021] In the formula, I is the physical quantity for life assessment, T is the working temperature of the polymer material, and t is the working time experienced by the polymer material.

[0022] As a preferred embodiment, the polymer material is a foam-type radar absorbing structure, nylon 66 or 6302 epoxy resin.

[0023] As a preferred embodiment, when the polymer material is a foam-type radar absorbing structure, the formula (Ⅲ) is simplified to formula (Ⅳ), that is, formula (Ⅳ) is obtained after simplifying formula (Ⅲ);

[0024]

[0025] In the formula, I is the physical quantity for life assessment, T is the working temperature of the polymer material, t is the time experienced by the polymer material, and K = 8.31.

[0026] This invention also provides a polymer material life assessment system, including a computer. The computer includes a memory, a processor, and a program stored in the memory and executable on the processor. When the processor executes the program, it performs the following steps / functions:

[0027] S1, read the input test result data;

[0028] S2, calculate the values ​​of a, b, c, e1, f1, e2, and f2 according to formula (Ⅱ);

[0029]

[0030] In the formula, I i I represents the result data of the i-th experiment. i0 t represents the actual test value. i T represents the time of the i-th test result data.i The temperature of the i-th test result data is represented by I, where i = 1, 2, 3...N and is an integer. i (t i T i ) represents an array formed from the calculation results.

[0031] S3, reads the input polymer material type, its working temperature data, and the experimental time data;

[0032] S4, read the values ​​of a, b, c, e1, f1, e2, and f2 obtained in step S2, calculate and output the physical quantities for assessing the lifespan of the polymer material according to equation (III).

[0033]

[0034] In the formula, I is the physical quantity for life assessment, T is the operating temperature of the polymer material, and t is the time experienced by the polymer material;

[0035] S5, Generate a lifetime chart for the polymer material based on the obtained lifetime assessment physical quantities.

[0036] Preferably, when the input polymer material is a foam-type radar absorbing structure, in step S4, the calculation model (Ⅳ) is directly called, and its life assessment physical quantities are calculated and output according to formula (Ⅲ).

[0037]

[0038] In the formula, I is the physical quantity for life assessment, T is the working temperature of the polymer material, t is the time experienced by the polymer material, and K = 8.31.

[0039] Beneficial effects: The solution of this invention enables rapid and accurate research on the aging behavior (lifespan assessment) of polymer materials, and the assessed lifespan of the polymer materials is almost consistent with the actual situation. Compared with the conventional Arrhenius formula, which can only describe the aging of polymer materials, this invention accurately describes the entire aging and post-curing process of polymer materials with a single model, without the need for manual judgment of the time period / point of entry into the aging process, thus exhibiting high accuracy and reliability. Attached Figure Description

[0040] Figure 1 This is a flowchart of the particle swarm optimization algorithm in Example 2;

[0041] Figure 2 This is the lifespan assessment chart for Nylon 66 in Example 2;

[0042] Figure 3 This is the lifespan assessment chart for the 6302 epoxy resin in Example 3;

[0043] Figure 4 This is a graph showing the calculation results of the time when the impact strength is less than 60% of the original value at 80℃ in Example 3. Detailed Implementation

[0044] The present invention will be further described below with reference to the accompanying drawings and specific embodiments. However, the following description of the embodiments is only for the purpose of helping to understand the principles and core ideas of the present invention, and is not intended to limit the scope of protection of the present invention. It should be noted that for those skilled in the art, improvements made to the present invention without departing from the principles of the present invention also fall within the scope of protection of the claims of the present invention.

[0045] Example 1

[0046] This embodiment assesses the lifespan of a foam-type radar absorbing structure.

[0047] A method for assessing the lifespan of a polymer material (foam-type radar absorbing structure), comprising the following steps:

[0048] Step 1: Determine the glass transition temperature of the polymer material. Specifically, the glass transition temperature of the foam-type radar absorbing structure is determined to be -25°C according to standard GB / T 11998-1989. The operating temperature of the foam-type radar absorbing structure is 0°C to 50°C.

[0049] Step 2: Based on the obtained glass transition temperature, select four test temperatures. The test temperatures and operating temperatures must not exceed the glass transition temperature of the polymer material, and the four test temperature ranges should be close to or cover the operating temperature. The four determined test temperatures are 50℃, 80℃, 110℃, and 140℃.

[0050] Step 3: Determine the testing time for the polymer materials and determine the sampling cycle according to formula (Ⅰ).

[0051] t't(h)=2 n-1 ……………………(Ⅰ)

[0052] In the formula, n = 1, 2, ..., and are integers, and t' represents the sampling period;

[0053] The sampling periods for the determined foam-type radar absorbing structure are 0 (original value), 72h, 144h, 288h, 432h, 864h, 1728h, and 2160h.

[0054] Step 4: Conduct the heat aging test according to the obtained test temperature, sampling cycle and test time. Specifically, conduct the heat aging test according to GB / T7141-2008 "Plastics Heat Aging Test Method", GB / T 2918-2018 "Standard Environment for Conditioning and Testing of Plastic Specimens" and rubber standards. The test results are shown in Table 1.

[0055] Table 1. Test results data for foam-type radar absorbing structures.

[0056]

[0057] Step 5: Optimize the obtained experimental results data according to Equation (II) to minimize the error function φ, and obtain the values ​​of a, b, c, e1, f1, e2, and f2.

[0058]

[0059] In the formula, I i I represents the result data of the i-th experiment. i0 t represents the actual test value. i T represents the time of the i-th test result data. i The temperature of the i-th test result data is represented by I, where i = 1, 2, 3...N and is an integer. i (t i T i () represents an array formed from the calculation results;

[0060] The optimization process can be performed using matelab software, and the processed data is shown in Table 2.

[0061] Analysis results of the experimental data obtained in Table 2

[0062] 50℃ 80℃ 110℃ 140℃ R 0.9627 0.9351 0.9974 0.9995 a 118.6735 218.0816 104.5835 812.2658 b 0.095589405 0.06568594 3.803384332 1.779780509 c 0.007634343 0.065743633 0.403790345 3.113409143 d 12.955 22.3848 0.349 0.094

[0063] In the process, to simplify calculations, ... and Simplification has been performed, assuming:

[0064]

[0065]

[0066] Therefore, equation (Ⅲ) simplifies to

[0067]

[0068] in:

[0069]

[0070]

[0071] Taking the average over a, we have:

[0072] a = 147

[0073] For d-regression, we have:

[0074] d = -0.2015T + 78.549

[0075] R 2 =0.9528

[0076] For E regression, we have:

[0077] E = -125.34T + 48529

[0078] R 2 =0.6196

[0079] For E' regression, we have:

[0080] E' = -185.64T + 73060

[0081] R 2 =0.9855

[0082] Therefore, the regularity function for the entire temperature range is:

[0083]

[0084] This regular function is also the simplified form (Ⅲ);

[0085] Step 6: Combine the obtained values ​​of a, b, and c with the working temperature of the polymer material, calculate the physical quantity (elongation at break) of the foam-type radar absorbing structure at each temperature according to formula (Ⅲ), i.e. the evaluation value. The results are shown in Table 3.

[0086]

[0087] In the formula, I is the physical quantity for life assessment, T is the working temperature of the polymer material, and t is the test time experienced by the polymer material.

[0088] Table 3. Physical quantities for life assessment (elongation at break) of foam-type radar absorbing structural components used in Hainan region.

[0089] October March June September December Evaluation value 70.6 86.74 78.43 64.54 51.85 Measured value 70.6 79.6 74.51 66 56 error% 0 8.97 5.26 -2 -7.41

[0090] As shown in Table 3, the life assessment values ​​of foam-type radar absorbing structures are close to the measured values, indicating good accuracy.

[0091] Example 2

[0092] A method for assessing the lifespan of a polymer material (Nylon 66) using impact strength as the physical quantity for lifespan assessment, comprising the following steps:

[0093] Step 1: Determine the glass transition temperature of nylon 66. Specifically, according to standard GB / T 11998-1989, the glass transition temperature of nylon 66 is determined to be 47°C. The working temperature of this nylon 66 is room temperature, and the impact strength (i.e., initial value) is 10.67.

[0094] Step 2: Based on the obtained glass transition temperature, select four test temperatures. The test temperatures and operating temperatures must not exceed the glass transition temperature of Nylon 66, and the four test temperature ranges should be close to or cover the operating temperature. The four determined test temperatures are 60℃, 90℃, 120℃, and 150℃.

[0095] Step 3: Determine the test time for Nylon 66, and determine the sampling period for the test according to formula (Ⅰ).

[0096] t't(h)=2 n-1 ……………………(Ⅰ)

[0097] In the formula, n = 1, 2, ..., and are integers, and t' represents the sampling period;

[0098] The determined sampling periods for Nylon 66 are 0 (original value), 6h, 12h, 24h, 48h, and 72h.

[0099] Step 4: Conduct the heat aging test according to the obtained test temperature, sampling cycle and test time. Specifically, conduct the heat aging test according to GB / T7141-2008 "Plastics Heat Aging Test Method", GB / T 2918-2018 "Standard Environment for Conditioning and Testing of Plastic Specimens" and rubber standards. The test results are shown in Table 4.

[0100] Table 4. Test results data for Nylon 66

[0101]

[0102] Step 5: Optimize the obtained experimental results data according to Equation (II) to minimize the error function φ;

[0103]

[0104] In the formula, I i I represents the result data of the i-th experiment. i0 t represents the actual test value. i T represents the time of the i-th test result data. i The temperature of the i-th test result data is represented by I, where i = 1, 2, 3...N and is an integer. i (ti T i () represents an array formed from the calculation results;

[0105] In this example, the optimization calculation uses the particle swarm optimization algorithm, with 500 particles, a maximum of 100,000 iterations, and a 7-dimensional search space. Each dimension has the following interval:

[0106] b=[0,10000]; c=[0,10000]; e1=[-10,10]; f1=[-1,1]; e2=[-10,10]; f2=[-1,1]; a=[-50,50];

[0107] The initial value is [1000, 1000, 1, 0, 1, 0, 10], and the calculation process is as follows: Figure 1 As shown, the calculation results (after processing) are: b = 6864.32990030601; c = 5565.46295463435; e1 = 0.349848475331552; f1 = 0.490632557709310; e2 = 3.59851067084827; f2 = -0.0278888319590752; a = 37.9238459730711;

[0108] Step 6: Combining the obtained values ​​of a, b, c, e1, f1, e2, and f2 with the operating temperature of Nylon 66, calculate the physical quantity (i.e., impact strength) of the polymer material at each temperature according to Equation (III).

[0109]

[0110] In the formula, I is the physical quantity for life assessment (i.e., impact strength), T is the working temperature of the polymer material, and t is the time experienced by the polymer material.

[0111] Based on the obtained physical quantity for life assessment (i.e., impact strength), a life assessment chart for Nylon 66 is obtained, as follows: Figure 2 As shown, by Figure 2 As can be seen from the center mark, at 25 degrees Celsius for 15 years (134,100 hours), the impact strength is 9.527, which is 10.71% lower than the original value of 10.67. Based on the failure criterion that the impact strength of component XX is lower than 60% of the original value, it is determined that the life of the sampled nylon 66 material is greater than 15 years.

[0112] Example 3

[0113] A method for life assessment of a polymer material (6302 epoxy resin) using impact strength as the physical quantity for life assessment, comprising the following steps:

[0114] Step 1: Determine the glass transition temperature of 6302 epoxy resin. Specifically, according to standard GB / T 11998-1989, the glass transition temperature of 6302 epoxy resin is determined to be 160℃. The working temperature of this 6302 epoxy resin is 0℃ to 65℃.

[0115] Step 2: Based on the obtained glass transition temperature, select four test temperatures. The test temperature and the working temperature must not exceed the glass transition temperature of 6302 epoxy resin, and the four test temperature ranges should be close to or cover the working temperature. The four test temperatures are 60℃, 90℃, 120℃, and 150℃.

[0116] Step 3: Determine the test time for 6302 epoxy resin, and determine the sampling cycle for the test according to formula (Ⅰ).

[0117] t't(h)=2 n-1 ……………………(Ⅰ)

[0118] In the formula, n = 1, 2, ..., and are integers, and t' represents the sampling period;

[0119] The sampling periods for 6302 epoxy resin were determined to be 0 (original value), 6h, 12h, 24h, 48h, and 72h.

[0120] Step 4: Conduct the heat aging test according to the obtained test temperature, sampling cycle and test time. Specifically, conduct the heat aging test according to GB / T7141-2008 "Plastics Heat Aging Test Method", GB / T 2918-2018 "Standard Environment for Conditioning and Testing of Plastic Specimens" and rubber standards. The test results are shown in Table 5.

[0121] Table 5. Test results data for 6302 epoxy resin

[0122]

[0123]

[0124] Step 5: Optimize the obtained experimental results data according to Equation (II) to minimize the error function φ;

[0125]

[0126] In the formula, I i I represents the result data of the i-th experiment. i0 t represents the actual test value. i T represents the time of the i-th test result data. i The temperature of the i-th test result data is represented by I, where i = 1, 2, 3...N and is an integer. i (t i Ti () represents an array formed from the calculation results;

[0127] The results of this optimization calculation (after processing) are as follows:

[0128] b=10000; c=7400.91128615322; e1=9.99999999999993; f1=0.102930939449 222; e2 = 4.47742098066899; f2 = -1.27049596934491; a = 0.263640000000000;

[0129] Step 6: Combining the obtained values ​​of a, b, c, e1, f1, e2, and f2 with the operating temperature of the 6302 epoxy resin, calculate the physical quantity (i.e., impact strength) for the life assessment of the 6302 epoxy resin at each temperature according to formula (Ⅲ).

[0130]

[0131] In the formula, I is the physical quantity for life assessment (i.e., impact strength), T is the working temperature of the polymer material, and t is the time experienced by the polymer material.

[0132] Based on the obtained physical quantity for life assessment (i.e., impact strength), a life assessment chart for 6302 epoxy resin is obtained, as shown below. Figure 3 As shown, by Figure 3 As can be seen from the marked point, at 25 degrees Celsius for 15 years (134,100 hours), the impact strength is 1.491, which is 5.03% lower than the original value of 1.57. According to the failure criterion that the impact strength of XX component is lower than 60% of the original value, it is determined that the life of the 6302 epoxy resin material sample is greater than 15 years.

[0133] Lifespan estimation: At 25℃, the aging degradation of nylon 66 over 15 years is greater than that of epoxy resin 6302. Therefore, based on the aging curve of nylon 66, the time when the impact strength is less than 60% of the original value at 80℃ is calculated. The calculation results are shown below. Figure 4 .See Figure 4 At the marked point, after 7200 hours and at a temperature of 80°C, the impact strength decreased to 6.291, which is 58.95% of the original value.

Claims

1. A method for assessing the lifespan of polymer materials, characterized by the following steps: include: Step 1: Determine the glass transition temperature of the polymer material; Step 2: Based on the obtained glass transition temperature, select at least four test temperatures. The test temperature and the working temperature must not be higher than the glass transition temperature of the polymer material, and the four test temperature ranges should be close to or cover the working temperature. Step 3: Determine the testing time for the polymer materials and determine the sampling cycle according to formula (Ⅰ). t’(h)=2 n-1 ……………………(Ⅰ) In the formula, n = 1, 2, ..., and are integers, and t' represents the sampling period; Step 4: Conduct a thermal aging test based on the obtained test temperature, sampling cycle, and test time, and measure and statistically analyze the test results data; Step 5: Optimize the obtained experimental results data according to Equation (II) to minimize the error function φ, and obtain the values ​​of a, b, c, e1, f1, e2, and f2. In the formula, I i I represents the result data of the i-th experiment. i0 t represents the actual test value. i T represents the time of the i-th test result data. i The temperature of the i-th test result data is represented by I, where i = 1, 2, 3...N and is an integer. i (t i T i () represents an array formed from the calculation results; Step 6: Combine the obtained values ​​of a, b, c, e1, f1, e2, f2 and the working temperature of the polymer material, calculate the physical quantity for assessing the lifespan of the polymer material according to formula (Ⅲ), and estimate the lifespan of the polymer material based on the obtained physical quantity for assessing the lifespan. In the formula, I is the physical quantity for life assessment, T is the operating temperature of the polymer material, and t is the time experienced by the polymer material.

2. The method for assessing the lifespan of polymer materials according to claim 1, characterized in that: The polymer material is a foam-type radar absorbing structure, nylon 66 or 6302 epoxy resin.

3. The method for assessing the lifespan of polymer materials according to claim 1, characterized in that: When the polymer material is a foam-type radar absorbing structural component, formula (III) is simplified to formula (IV). In the formula, I is the physical quantity for life assessment, T is the working temperature of the polymer material, t is the time experienced by the polymer material, and K = 8.

31.

4. A polymer material life assessment system, comprising a computer, the computer including a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it performs the following steps / functions: S1, read the input test result data; S2, using MATLAB software, calculate the values ​​of a, b, c, e1, f1, e2, and f2 according to formula (Ⅱ); In the formula, I i I represents the result data of the i-th experiment. i0 t represents the actual test value. i T represents the time of the i-th test result data. i The temperature of the i-th test result data is represented by I, where i = 1, 2, 3...N and is an integer. i (t i T i () represents an array formed from the calculation results; S3, reads the input polymer material type, its working temperature data, and the experimental time data; S4, read the values ​​of a, b, c, e1, f1, e2, and f2 obtained in step S2, calculate and output the physical quantities for assessing the lifespan of the polymer material according to equation (III). In the formula, I is the physical quantity for life assessment, T is the operating temperature of the polymer material, and t is the time experienced by the polymer material; S5, Generate a lifetime chart for the polymer material based on the obtained lifetime assessment physical quantities.

5. The polymer material life assessment system according to claim 4, characterized in that: When the input polymer material is read as a foam-type radar absorbing structure, in step S4, the calculation model (Ⅳ) is directly called, and its life assessment physical quantities are calculated and output according to formula (Ⅲ). In the formula, I is the physical quantity for life assessment, T is the working temperature of the polymer material, t is the time experienced by the polymer material, and K = 8.31.

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