A method for estimating material properties based on benchmark data

Abstract

The application provides a material performance estimation method based on benchmark data, and steps include: obtaining performance change data of a material to be evaluated in different sampling periods of natural environment test and accelerated test; obtaining performance deviation values of a benchmark material and the material to be evaluated at the same time of the two tests; establishing a deviation value correction coefficient in a natural environment; and estimating the performance of the material to be evaluated according to the obtained deviation values and the correction coefficient. The application establishes the deviation value for quantifying the performance difference between the material to be evaluated and the benchmark material, and determines the deviation value corresponding to the expected test time in the natural environment and the deviation value correction coefficient according to the benchmark material, so that the performance value of the material to be evaluated in the expected test time in the natural environment is quickly and accurately estimated by using short-term natural environment test data and laboratory accelerated test data.

Description

Technical Field

[0001] This invention belongs to the field of material performance evaluation technology, specifically relating to a method for predicting material performance based on benchmark data. Background Technology

[0002] Materials inevitably undergo performance degradation during use due to the long-term combined effects of various environmental factors, thus affecting the performance of equipment / products. The environmental resistance or degree of performance degradation of materials in the expected natural environment is a key decision-making basis for users in selecting the best materials for equipment / products and replacing existing materials. With increasingly stringent product performance requirements and rapid material development, there is an urgent need for methods that can quickly, accurately, and quantitatively predict material performance under expected natural environments.

[0003] Currently, most material performance evaluations employ either simple laboratory environmental testing or natural environment testing methods. While laboratory environmental testing is fast, it cannot fully simulate and reflect the damage behavior of equipment / products in actual service environments. Natural environment testing, on the other hand, has the advantage of reflecting the characteristics of real service environments, but its testing cycle is relatively long. Furthermore, the environmental resistance of materials is usually relative; that is, relative to a certain benchmark, material properties and their changes are more instructive for selection and application. Therefore, it is essential to develop a rapid and accurate quantitative prediction method for material properties that integrates benchmark material laboratory and natural environment adaptability benchmark data.

[0004] The previously developed method for evaluating the environmental adaptability of standard parts based on benchmark data (document CN2016110590413) proposed a method to assess the environmental adaptability of standard parts using benchmark data. This method estimates the performance value of the standard part to be evaluated based on the assumption that the performance ratio of the benchmark standard part under two environmental test conditions is equal to the performance ratio of the standard part to be evaluated under the same two environmental test conditions. During application, the inventors discovered that different materials exhibit varying degrees of performance change or rate of change under the same environmental test conditions, and that the differences in performance change between different materials vary with test time. This method failed to consider the differences in the impact of the same environmental test conditions on the performance of different materials, as well as the differences in performance at different times, thus affecting the reliability of the estimated results and the practical conformity and applicability of the evaluation method. Summary of the Invention

[0005] To address the problems existing in the prior art, this invention aims to provide a material performance prediction method based on benchmark data. This method can accelerate environmental testing and short-term natural environment testing through laboratory simulation in a short period of time, and use benchmark data on the environmental adaptability of benchmark materials to quantify and accurately predict the performance values ​​of the material to be evaluated under the expected natural environment.

[0006] The present invention adopts the following technical solution.

[0007] A method for predicting material properties based on benchmark data, comprising the following steps:

[0008] Step 1: Obtain performance change data of the material to be evaluated during different sampling periods in natural environment testing and accelerated testing;

[0009] Step 2: Obtain the performance deviation values ​​of the benchmark material and the material to be evaluated at the same time in both tests;

[0010] Step 3: Establish deviation correction coefficients under natural conditions;

[0011] Step 4: Estimate the performance of the material to be evaluated based on the obtained deviation value and its correction factor.

[0012] Further, step 1 includes: conducting natural environment tests on the material to be evaluated according to the natural environment testing method used for the benchmark material, conducting laboratory simulated accelerated environment tests on the material to be evaluated according to the laboratory simulated accelerated environment testing method used for the benchmark material, statistically analyzing the test results, and obtaining performance change data of the material to be evaluated at different sampling periods in the natural environment test and the accelerated test.

[0013] Furthermore, in step 2:

[0014] The deviation between the material to be evaluated and the benchmark material under accelerated laboratory testing conditions is calculated according to formula (Ⅰ).

[0015]

[0016] In the formula, k snt V represents the deviation between the nth benchmark material and the material to be evaluated during the t-th sampling period of accelerated laboratory testing. snt V represents the performance retention rate of the nth benchmark material during the t-th sampling cycle of accelerated laboratory testing. sxnt Let n be the performance retention rate of the material to be evaluated in the t-th sampling period of the accelerated laboratory test, where n = 1, 2, 3... and is an integer.

[0017] Calculate the deviation (measured value) between the material to be evaluated and the benchmark material under natural environmental test conditions according to formula (II).

[0018]

[0019] In the formula, k znt V represents the deviation (measured value) between the nth benchmark material and the material to be evaluated during the t-th sampling period of the natural environment test. znt V represents the performance retention rate of the nth benchmark sample during the t-th sampling period in the natural environment test. zxntLet n be the performance retention rate of the sample to be evaluated in the natural environment test during the t-th sampling period, where n = 1, 2, 3... and takes integer values.

[0020] Furthermore, step 3 includes:

[0021] The performance retention rate (V) of benchmark materials under accelerated laboratory testing conditions snt The x-axis represents the deviation (k) between the benchmark material and the material to be evaluated under accelerated laboratory testing conditions. snt Using y as the ordinate, establish the relationship equation between the retention rate of benchmark material properties and the deviation value, k sn =f(V sn );

[0022] Substituting the performance retention rate of the nth benchmark material over u sampling periods in the natural environment test into the aforementioned relational equation, the deviation values ​​between the benchmark material and the material to be evaluated under u natural environment test conditions are obtained. And calculate the deviation correction factor according to formula (Ⅲ),

[0023]

[0024] In the formula, k is the deviation correction factor derived based on the nth benchmark material. znt Let be the deviation (measured value) between the nth benchmark material and the material to be evaluated during the t-th sampling period of the natural environment test. This is the calculated deviation value between the nth benchmark material and the material to be evaluated during the tth sampling period of the natural environment test.

[0025] Furthermore, step 4 includes:

[0026] Calculate the performance estimate of the material to be evaluated under natural environmental testing time T according to formula (Ⅳ).

[0027]

[0028] In the formula, V zxn V is the estimated performance retention rate of the material to be evaluated based on the natural environment test time T (i.e., the predicted time) obtained according to the nth benchmark material. zn Let T be the performance retention rate of the nth benchmark material under natural environmental testing for time T. This is the calculated value of the deviation ratio between the nth benchmark material and the material to be evaluated during the natural environment test at time T. This is the deviation correction factor derived based on the nth benchmark material.

[0029] Beneficial effects: This invention provides a rapid and accurate method for predicting material properties based on benchmark data. By establishing a quantitative deviation value between the performance difference between the material to be evaluated and the benchmark material, and determining the deviation value and deviation correction coefficient corresponding to the expected test time under natural conditions based on the benchmark material, the method uses short-term natural environment test data and laboratory accelerated test data to rapidly and accurately predict the performance value of the material to be evaluated under the expected test time in natural environment. The error of the obtained material performance prediction results is less than 10% compared with the actual results of natural environment tests. Attached Figure Description

[0030] Figure 1 The figure shows the fitting curve of the retention rate and deviation ratio of the compression performance of the benchmark 3S-60 silicone rubber material under the laboratory thermal aging test in the example. Detailed Implementation

[0031] 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.

[0032] Example

[0033] A method for predicting material properties based on benchmark data, comprising the following steps:

[0034] Step 1: Obtain performance change data of the material to be evaluated under different sampling periods in natural environment test and accelerated test; conduct short-term natural environment test of the material to be evaluated according to the natural environment test method used for the benchmark material, and conduct laboratory simulated accelerated environment test of the material to be evaluated according to the laboratory simulated accelerated environment test method used for the benchmark material, and obtain the performance retention rate value of the material to be evaluated under different sampling periods in natural environment test and laboratory simulated accelerated test.

[0035] Step 2: Obtain the performance deviation values ​​of the benchmark material and the material to be evaluated at the same time in both tests;

[0036] The deviation between the material to be evaluated and the benchmark material under accelerated laboratory testing conditions is calculated according to formula (Ⅰ).

[0037]

[0038] In the formula, k snt V represents the deviation between the nth benchmark material and the material to be evaluated during the t-th sampling period of accelerated laboratory testing. snt V represents the performance retention rate of the nth benchmark material during the t-th sampling cycle of accelerated laboratory testing. sxntLet n be the performance retention rate of the material to be evaluated in the t-th sampling period of the accelerated laboratory test, where n = 1, 2, 3... and is an integer.

[0039] Calculate the deviation (measured value) between the material to be evaluated and the benchmark material under natural environmental test conditions according to formula (II).

[0040]

[0041] In the formula, k znt V represents the deviation (measured value) between the nth benchmark material and the material to be evaluated during the t-th sampling period of the natural environment test. znt V represents the performance retention rate of the nth benchmark sample during the t-th sampling period in the natural environment test. zxnt Let n be the performance retention rate of the sample to be evaluated in the natural environment test during the t-th sampling period, where n = 1, 2, 3... and is an integer.

[0042] Step 3, establish deviation correction coefficients under natural conditions:

[0043] Establish a fitting equation for the performance retention rate and deviation of the benchmark material under accelerated laboratory testing conditions, that is, using the performance retention rate (V) of the benchmark material under accelerated laboratory testing conditions as the basis for the equation. snt The x-axis represents the deviation (k) between the benchmark material and the material to be evaluated under accelerated laboratory testing conditions. snt Using y as the ordinate, establish the relationship equation between the retention rate of benchmark material properties and the deviation value, k sn =f(V sn );

[0044] Based on the established relationship equation k between the retention rate and deviation ratio of benchmark material properties sn =f(V sn Substituting the performance retention rate of the nth benchmark material over u sampling periods in the natural environment test into the above relational equation, we obtain the calculated deviation values ​​between the benchmark material and the material to be evaluated under u natural environment test conditions. Then calculate the deviation correction factor:

[0045]

[0046] In the formula, k is the deviation correction factor derived based on the nth benchmark material. znt The measured value is the deviation between the nth benchmark material and the material to be evaluated during the t-th sampling period of the natural environment test. This is the calculated deviation value between the nth benchmark material and the material to be evaluated during the tth sampling period of the natural environment test;

[0047] Step 4: Estimate the performance of the material to be evaluated based on the obtained deviation value and its correction factor.

[0048] Calculate the performance estimate of the material to be evaluated under natural environmental testing time T according to formula (Ⅳ).

[0049]

[0050] In the formula, V zxn V is the estimated performance retention rate of the material to be evaluated based on the nth benchmark material obtained from a natural environment test at time T. zn Let T be the performance retention rate of the nth benchmark material under natural environmental testing for time T. This is the calculated value of the deviation ratio between the nth benchmark material and the material to be evaluated during the natural environment test at time T. This is the deviation correction factor derived based on the nth benchmark material.

[0051] The measured results after a time period T of natural environment testing on the material to be evaluated are verified, and the evaluation error is calculated using the following formula:

[0052]

[0053] In the formula, E 0rr This represents the pre-evaluation error of the material's properties.

[0054] P v This is the preliminary evaluation result of the material's performance.

[0055] P r The results are from natural environment tests on the properties of the material to be evaluated.

[0056] This approach enables accelerated environmental testing in the laboratory and short-term natural environment testing within a short period of time. By utilizing the performance differences between benchmark materials and the materials to be evaluated, as well as benchmark data on the environmental adaptability of benchmark materials, it can accurately and quantitatively predict the performance of the materials to be evaluated. It features high accuracy and short testing time, and can quickly and accurately pre-evaluate the environmental adaptability of materials in natural environments. It can provide a rapid evaluation method for the selection and substitution of materials in equipment or products, and promote the innovative application of benchmark material environmental adaptability data.

[0057] It should be noted that the following points should be considered during the evaluation process.

[0058] 1. Selection of benchmark materials: The benchmark materials should be one or more materials of the same type as the material to be evaluated. If there are multiple benchmark materials of the same type available, it is recommended to select the benchmark material with similar initial performance to the material to be evaluated. In addition, the performance of the material to be evaluated should be between the performance of two or more benchmark materials. The test sample specifications, dimensions, testing performance and methods of the benchmark materials and the material to be evaluated should be consistent.

[0059] 2. Selection of environmental testing methods: The laboratory accelerated testing and natural environment testing of the material to be evaluated should be carried out in accordance with the laboratory simulation accelerated testing method and natural environment testing method used for the benchmark material. The laboratory accelerated testing method used has good simulation of natural environment testing, and the performance change trend of the material is basically consistent in the two environmental tests.

[0060] 3. Environmental test data processing: The performance change of the material is expressed by the performance retention rate, calculated using equation (VI):

[0061]

[0062] In the formula, V l L represents the retention rate of the sample's properties, in %; L0 represents the initial property value of the sample; L t This represents the performance value of the sample after a test time t.

[0063] To better understand the material property prediction method in this invention, examples are provided below for further explanation.

[0064] For materials of the same type, such as A1, A2, A3...Am, X, if benchmark data on the environmental and laboratory adaptability of materials A1, A2, A3...Am have been obtained, laboratory-simulated accelerated environmental tests and natural environmental tests should be conducted on the material to be evaluated, following the laboratory environmental testing methods and natural environmental testing methods used to obtain the benchmark data. By analyzing the deviation ratios and variation patterns of the performance of benchmark materials A1, A2, A3...Am and the material to be evaluated, X, in natural environment and laboratory-simulated accelerated tests, the performance of the material to be evaluated, X, in natural environment can be quantitatively evaluated.

[0065] We need to estimate the compression set of silicone rubber 6141 after 20 months of exposure in the Jiangjin warehouse. There are three benchmark rubber materials available: 3S-60 silicone rubber, 5171 nitrile rubber, and 5860 nitrile rubber. We will select 3S-60 silicone rubber, which is of the same type as the silicone rubber 6141 to be evaluated, as the benchmark material.

[0066] Since benchmark data for the natural environmental adaptability and laboratory environmental adaptability of 3S-60 silicone rubber have been obtained, the in-warehouse exposure test and the laboratory heat aging test with good simulation of 3S-60 silicone rubber were selected to conduct the natural environmental test and laboratory accelerated test of 6141 silicone rubber. The results of the laboratory heat aging test and the natural environmental test are shown in Table 1 and Table 2.

[0067] Table 1. Compression properties of benchmark rubber (3S-60 silicone rubber) and rubber to be evaluated (6141 silicone rubber) after heat aging tests.

[0068]

[0069] Table 2 Performance values ​​of benchmark rubber (3S-60 silicone rubber) and rubber to be evaluated (6141 silicone rubber) in the Jiangjin warehouse exposure test.

[0070]

[0071] According to formulas (I) and (II), the deviation ratios between the material to be evaluated and the benchmark material under natural environment test and laboratory accelerated test conditions are shown in Tables 3 and 4, respectively.

[0072] Table 3. Deviation values ​​of benchmark rubber and rubber to be evaluated under accelerated test conditions.

[0073] Test time / day <![CDATA[K sn ]]> Test time / day <![CDATA[K sn ]]> 1 0.978 37 1.025 2 0.994 41 1.030 3 1.002 49 1.033 4 1.007 54 1.029 6 1.009 59 1.029 9 1.003 65 1.040 12 1.003 71 1.042 15 0.998 78 1.049 18 1.001 86 1.038 21 1.002 95 1.042 25 1.011 105 1.051 29 1.001 115 1.078 33 1.013 126 1.064

[0074] Table 4 Deviation values ​​of benchmark materials and materials to be evaluated under natural environmental testing conditions.

[0075] Trial period / month <![CDATA[K zn ]]> 2 1.059 4 1.089 6 1.093 8 1.114

[0076] The fitting curve and equation for the retention rate and deviation ratio of compression properties of 3S-60 silicone rubber (benchmark rubber) under laboratory heat aging tests were established. Figure 1 Substituting the actual values ​​of the compression performance retention rate of 3S-60 silicone rubber in the short-term exposure test in Jiangjin (0.989, 0.9679, 0.9313, and 0.9026) into the above fitting relationship equation, the calculated deviation values ​​are 0.997, 1.001, 1.009, and 1.016.

[0077] The deviation correction factor is calculated according to formula (Ⅲ):

[0078]

[0079] The compression performance retention rate (V) of 3S-60 silicone rubber after 20 months of exposure in Jiangjin warehouse. zn Substituting (=0.8798) into the above fitting equation, the deviation value for the corresponding time is calculated to be 1.02087. According to equation (Ⅳ), the predicted performance value of the 6141 silicone rubber to be evaluated after 20 months of exposure in the Jiangjin warehouse is calculated as follows:

[0080]

[0081] The actual performance value of the 6141 silicone rubber to be evaluated after 20 months of exposure in the Jiangjin warehouse is 0.7341. The estimated error calculated according to formula (VI) is as follows.

[0082]

[0083] The predicted performance of the obtained material (6141 silicone rubber) has an error of 8.45% compared with the actual results of the natural environment test.

Claims

1. A method for benchmark data based material performance estimation, characterized by the steps of include: Step 1: Conduct natural environment tests on the material to be evaluated according to the natural environment testing method used for the benchmark material, and conduct laboratory simulated accelerated environment tests on the material to be evaluated according to the laboratory simulated accelerated environment testing method used for the benchmark material. Statistically analyze the test results and obtain performance change data of the material to be evaluated at different sampling periods in the natural environment test and the accelerated test. Step 2: Obtain the performance deviation values ​​of the benchmark material and the material to be evaluated at the same time in both tests; Step 3: Establish deviation correction coefficients under natural conditions; Step 4: Estimate the performance of the material to be evaluated based on the obtained deviation value and its correction factor; In step 2: The deviation between the material to be evaluated and the benchmark material under accelerated laboratory testing conditions is calculated according to formula (Ⅰ). In the formula, k snt V represents the deviation between the nth benchmark material and the material to be evaluated during the t-th sampling period of accelerated laboratory testing. snt V represents the performance retention rate of the nth benchmark material during the t-th sampling cycle of accelerated laboratory testing. sxnt Let n be the performance retention rate of the material to be evaluated in the t-th sampling period of the accelerated laboratory test, where n = 1, 2, 3... and is an integer. The deviation between the material to be evaluated and the benchmark material under natural environmental test conditions is calculated according to formula (II). In the formula, k znt V represents the deviation between the nth benchmark material and the material to be evaluated during the t-th sampling period of the natural environment test. znt V represents the performance retention rate of the nth benchmark sample during the t-th sampling period in the natural environment test. zxnt Let n be the performance retention rate of the sample to be evaluated in the natural environment test during the t-th sampling period, where n = 1, 2, 3... and is an integer. Step 3 includes: The performance retention rate (V) of benchmark materials under accelerated laboratory testing conditions snt The x-axis represents the deviation (k) between the benchmark material and the material to be evaluated under accelerated laboratory testing conditions. snt Using y as the ordinate, establish the relationship equation between the retention rate of benchmark material properties and the deviation value, k sn =f(V sn ); Substituting the performance retention rate of the nth benchmark material over u sampling periods in the natural environment test into the aforementioned relational equation, the deviation values ​​between the benchmark material and the material to be evaluated under u natural environment test conditions are obtained. And calculate the deviation correction factor according to formula (Ⅲ), In the formula, k is the deviation correction factor derived based on the nth benchmark material. znt Let be the deviation between the nth benchmark material and the material to be evaluated during the t-th sampling period of the natural environment test. This is the calculated deviation value between the nth benchmark material and the material to be evaluated during the tth sampling period of the natural environment test; Step 4 includes: Calculate the performance estimate of the material to be evaluated under natural environmental testing time T according to formula (Ⅳ). In the formula, V zxn V is the estimated performance retention rate of the material to be evaluated based on the nth benchmark material obtained from a natural environment test at time T. zn Let T be the performance retention rate of the nth benchmark material under natural environmental testing for time T. This is the calculated value of the deviation ratio between the nth benchmark material and the material to be evaluated during the natural environment test at time T. This is the deviation correction factor derived based on the nth benchmark material.

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