Material life prediction method, prediction system and computer readable medium

Abstract

The invention relates to a material life prediction method, a prediction system and a computer readable medium. The prediction method comprises the following steps: obtaining simulation results of crystal plasticity finite element models corresponding to a to-be-predicted material under loads of pure low-cycle fatigue, creep fatigue and high-low-cycle composite creep fatigue, and at least one group of actual test results corresponding to the to-be-predicted material under the loads of pure low-cycle fatigue, creep fatigue and high-low-cycle composite creep fatigue; according to the simulation result and the test result, determining a critical value of a fatigue indication factor, a critical value of a creep indication factor and parameters related to the creep indication factor under loads of pure low-cycle fatigue, creep fatigue and high-low-cycle composite creep fatigue; and establishing a life prediction equation based on crystal plasticity by utilizing a linear damage accumulation criterion, and predicting the cycle life of the to-be-predicted material under the cyclic load test condition.

Description

Technical Field

[0001] The invention relates to a material life prediction method, a prediction system and a computer-readable medium. Background Art

[0002] As humans pay more and more attention to environmental protection and sustainable social development, key equipment in the fields of petrochemicals, power generation, aerospace, etc. are facing more demanding working environments to achieve higher production efficiency. In particular, the premature failure of equipment caused by complex damage interactions has attracted great interest from industries and research institutions around the world. Low-cycle fatigue caused by start-up and shutdown, high-cycle fatigue caused by vibration of assembly gaps, and creep loads borne during stable operation, this complex alternating load has posed new challenges to traditional life and reliability technical methods. At present, pure low-cycle fatigue damage driven by a single factor and creep fatigue damage driven by two factors can no longer reflect the real complex failure mechanism of high-temperature rotating parts. The composite creep fatigue of high and low cycles, that is, the high-cycle fatigue with a certain number of cycles superimposed on the load-keeping stage in each cycle, not only conforms to the actual working conditions, but also can obtain different degrees of multi-damage interactions by adjusting the test parameters.

[0003] The current life prediction models for fatigue and creep fatigue are mainly based on the theory of continuous damage mechanics to describe the process of damage accumulation until fracture of materials under cyclic loads. This type of method focuses on the damage analysis of components or components at the macro level, and cannot describe the stress-strain response and damage mechanism evolution at the micro level. In addition, the existing macro life prediction models only target damage types driven by a single factor or two factors. For complex multi-load composite working conditions, the prediction accuracy of the existing macro life prediction models can no longer meet the requirements of high-temperature component reliability assurance. Therefore, it is necessary to study the cyclic life under high and low cycle composite creep fatigue loads, especially to invent a multi-load life prediction method based on crystal plasticity theory.

[0004] At present, most of the life prediction methods based on crystal plasticity theory focus on fatigue life prediction driven by a single factor and creep fatigue life prediction driven by two factors. Now there is an urgent need for a life prediction method that can achieve the unification of multiple load conditions, especially a creep fatigue life prediction method for high and low cycle composites, to meet the needs of life prediction under different loads. Summary of the invention

[0005] An object of the present invention is to provide a material life prediction method.

[0006] An object of the present invention is to provide a material life prediction system.

[0007] An object of the present invention is to provide a computer readable medium.

[0008] According to one aspect of the present invention, a material life prediction method includes: obtaining simulation results of the crystal plasticity finite element model corresponding to the material to be predicted under the loads of pure low-cycle fatigue, creep fatigue and high-low-cycle composite creep fatigue, and at least one group of actual test results corresponding to each; determining the critical value of the fatigue indication factor, the critical value of the creep indication factor and parameters related to the creep indication factor under the loads of pure low-cycle fatigue, creep fatigue and high-low-cycle composite creep fatigue according to the simulation results and the test results; establishing a life prediction equation based on crystal plasticity using a linear damage accumulation criterion to predict the cycle life of the material to be predicted under cyclic load test conditions.

[0009] According to another aspect of the present invention, a material life prediction system includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above prediction method when executing the computer program.

[0010] According to another aspect of the present invention, a computer readable medium has a computer program thereon, and the program is executed by a processor to implement the steps in the prediction method described above that can be implemented by the computer program.

[0011] The advanced effects of the present invention include at least: only three parameters need to be determined to accurately predict the cycle life under various loads and their combined working conditions, the required parameters are few, the application range is wide, and a unified life prediction method for multiple load conditions is realized, especially a creep fatigue life prediction method for high and low cycle composites, to meet the needs of life prediction under different loads, and the prediction accuracy is good. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The above and other features, properties and advantages of the present invention will become more apparent through the following description in conjunction with the accompanying drawings and embodiments, in which:

[0013] Figure 1 FIG. 4 is a flow chart of a material life prediction method according to an embodiment of the present invention.

[0014] Figure 2 It is a schematic diagram of the variation of the critical values ​​of fatigue and creep indicator factors with the total strain range of a prediction method according to an embodiment.

[0015] Figure 3 The figure is a relationship diagram between a creep indicator factor critical value and a creep indicator factor at a specific cycle in a prediction method of an embodiment.

[0016] Figure 4 FIG. 4 is a diagram showing prediction results of a prediction method according to an embodiment. DETAILED DESCRIPTION

[0017] The following discloses various different implementation methods or embodiments of the subject technical solution. To simplify the disclosure, specific examples of various elements and arrangements are described below. Of course, these are only examples and are not intended to limit the scope of protection of the present invention.

[0018] At the same time, the present application uses specific words to describe the embodiments of the present application. For example, "one embodiment", "an embodiment", and / or "some embodiments" refer to a certain feature, structure or characteristic related to at least one embodiment of the present application. Therefore, it should be emphasized and noted that "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more in different positions in this specification does not necessarily refer to the same embodiment. In addition, some features, structures or characteristics in one or more embodiments of the present application can be appropriately combined.

[0019] It is understood that flow charts are used in the present application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that, according to the actual situation, the previous or following operations are not necessarily performed precisely in order. Other operations may also be added to these processes, or one or more operations may be removed from these processes.

[0020] refer to Figure 1 As shown, in some embodiments, the material life prediction method may include the following steps:

[0021] S1. Obtain simulation results of the crystal plasticity finite element model corresponding to the material to be predicted under the loads of pure low-cycle fatigue, creep fatigue and high-low-cycle combined creep fatigue, and at least one set of corresponding actual test results.

[0022] Specifically, the finite element model can be established by using the crystal plasticity constitutive equation. Specifically, the crystal plasticity constitutive parameters are obtained by the trial parameter method. The electron backscatter diffraction information of the material to be tested can be converted into nodes and units in an input file that can be read by ABAQUS through the matlab language, and the grain orientation file is assigned to each unit as a material constant through the matlab language; then, the periodic boundary conditions and different loading conditions of the crystal plasticity finite element model are obtained by writing an ABAQUS script program, so that the finite element simulation under any cyclic load can be realized.

[0023] The crystal plasticity constitutive equation mainly includes the following formulas, among which the main control equation of the deformation rate gradient is expressed as

[0024]

[0025] In formula (1), L p represents the inelastic deformation rate gradient, F prepresents the inelastic deformation gradient, represents the plastic slip rate of the αth slip system, s α The unit vector representing the slip direction of the αth slip system, m α represents the unit vector in the normal direction of the αth slip system, and N represents the number of slip systems.

[0026] The flow criterion equation in the crystal plasticity constitutive equation is expressed as

[0027]

[0028] In formula (2), represents the reference plastic slip rate, k represents the Boltzmann constant, T represents the Boltzmann constant, F0 represents the thermal activation free energy, τ α represents the decomposed shear stress of the αth slip system, B α represents the back stress of the αth slip system, S α represents the slip resistance of the αth slip system, τ0, p and q represent material constants. The slip resistance evolution equation in the crystal plasticity constitutive equation is expressed as

[0029]

[0030] In formula (3), h αβ represents the hardening matrix between slip systems α and β, S sat represents the saturated slip resistance, and S0 represents the initial slip resistance.

[0031] The static recovery term is introduced into the back stress equation of the crystal plasticity constitutive equation and is expressed as

[0032]

[0033] In formula (4), h B represents the back stress hardening constant, r D represents the dynamic recovery coefficient related to the sliding resistance, r S Represents the static recovery coefficient of back stress.

[0034] The specific method for obtaining at least one corresponding set of actual test results can be that the pure fatigue test adopts symmetrical triangular wave loading [national standard GB / T 26077-2010], and the creep fatigue test adopts upper trapezoidal wave loading (i.e. applying tensile load) [American standard ASTM E2714-13]; the strain-controlled high- and low-cycle composite creep fatigue test introduces high-cycle fatigue load in the above-mentioned creep fatigue tensile load stage.

[0035] S2. According to the simulation results and the test results, determine the critical value of the fatigue indication factor under the load of pure low-cycle fatigue, creep fatigue and high-low-cycle combined creep fatigue, the critical value of the creep indication factor and parameters related to the creep indication factor.

[0036] Specifically, the maximum cumulative energy dissipation in the finite element model can be extracted, and the maximum cumulative energy dissipation W can be regarded as the indicator factor for determining crack initiation in the material under test during cyclic loading. The evolution law of the indicator factor under different loads with the number of cycles and strain amplitude can be explored. Then, according to the evolution law of the indicator factor under different loads with the number of cycles and strain amplitude, it can be divided into fatigue indicator factor W F and creep indicator factor W C , where the fatigue indicator factor W F is a load-independent parameter, while the creep indicator factor W C is a load-related parameter and decreases significantly with the increase of strain amplitude. According to the evolution law of these two indicator factors and a set of test life, the critical value W of the fatigue indicator factor under different loads can be determined. F,crit , the critical value of creep indicator factor W C,crit And the parameter M related to the creep indication factor.

[0037] A specific step may be to regard the maximum cumulative energy dissipation W as an indicator factor for determining crack initiation of the material to be tested during cyclic loading, and the indicator factor increases linearly with the increase of the number of cycles under different loading conditions.

[0038] According to the damage type, the cumulative energy dissipation can be divided into fatigue indicator factor and creep indicator factor. The fatigue indicator factor is a parameter that is independent of the loading conditions. Therefore, the critical value of the fatigue indicator factor is W. F,crit It can be calculated according to the following formula

[0039] W F,crit =N i ·W F,cyc (5)

[0040] In formula (5), N i is the cycle life obtained from the test, W F,cyc It is the fatigue indicator factor obtained by simulation at a specific cycle.

[0041] However, the creep indicator factor is a parameter related to loading conditions. The critical value of the creep indicator factor is exponentially related to the creep indicator factor under a certain cycle.

[0042] W C,crit =N i ·(W C,cyc )M (6)

[0043] In formula (6), W C,cyc is the creep indicator factor obtained by simulation under a specific cycle, and M is a parameter related to the creep indicator factor.

[0044] S3. A life prediction equation based on crystal plasticity is established using a linear damage accumulation criterion to predict the cycle life of the material under cyclic load test conditions.

[0045] Specifically, the linear damage accumulation criterion can be used to establish a life prediction equation based on crystal plasticity, assuming that when the damage accumulates to 1, the material fails.

[0046]

[0047]

[0048]

[0049]

[0050] In formulas (7)-(10), and They represent the low-cycle fatigue damage, high-cycle fatigue damage and creep damage in the jth cycle, respectively. and They respectively represent the low-cycle fatigue indicator factor, high-cycle fatigue indicator factor and creep indicator factor obtained in the j-th cycle of simulation.

[0051] In S3, since the fatigue indicator factor and creep indicator factor both increase linearly with the number of cycles, the cycle life of the material under different cyclic load tests can be predicted.

[0052]

[0053] In order to further illustrate the life prediction method introduced above, a specific material is used to illustrate the life prediction of a nickel-based high-temperature alloy (GH4169) under different load conditions at 650°C.

[0054] Pure low-cycle fatigue, creep fatigue and high-low-cycle composite creep fatigue were selected for verification. Table 1 shows the test data of nickel-based superalloy (GH4169) at 650°C. The strain rate of cyclic loading and unloading is 4×10 -3 / s. These include 4 groups of pure fatigue tests with strain control ranging from 1.0% to 2.0%, 7 groups of creep fatigue tests with strain control, with the pull-holding time ranging from 60s to 1800s, and 7 groups of high- and low-cycle composite creep fatigue tests, with the high-cycle fatigue strain range ranging from 0.2% to 0.4% and the high-cycle fatigue frequency of 1Hz.

[0055] First, according to step S2 of a multi-load life prediction method based on crystal plasticity theory of the present invention, it is necessary to determine the evolution law of the fatigue indicator factor and the creep indicator factor under different loads, such as Figure 2 As shown, the fatigue indicator factor is a parameter independent of loading, while the creep indicator factor is a parameter related to loading; then according to step S2 of the present invention, since the creep indicator factor is a parameter related to loading, it is necessary to determine the critical value W of the fatigue indicator factor F,crit , creep indicator factor critical value W C,crit And the parameter M related to the creep indicator factor, we get W F,crit =24878MJ / m 3 , W C,crit =6180MJ / m 3 , M = 5.48. Finally, according to step S3 of the life prediction method of the present invention, a life prediction equation is established.

[0056] Table 1 Test data of nickel alloy material GH4169 at 650℃

[0057]

[0058] Depend on Figure 4 It can be seen from the results that no matter it is low cycle fatigue or low cycle fatigue or creep fatigue or high and low cycle composite creep fatigue test, most of the life predicted by the present invention is within the 2-fold error band, and the test results are close to the predicted results. It can be seen that the life prediction method of multiple load composites shown in the above embodiment can well predict the cycle life of the nickel alloy material GH4169 at 650°C. Therefore, the method introduced in the above embodiment can well predict the cycle life under multiple load composite working conditions, and the prediction accuracy is high.

[0059] It can be understood that the above embodiments can also be implemented in a system, that is, the present application also provides a material life prediction system, including a memory for storing instructions executable by a processor; a processor for executing the instructions to implement the prediction method as introduced in the above embodiments.

[0060] Preferably, in some embodiments, the system also includes a database having simulation results of the crystal plasticity finite element model corresponding to the material to be predicted under loads of pure low-cycle fatigue, creep fatigue, and high-low-cycle combined creep fatigue, and at least one corresponding set of actual test results.

[0061] It should be noted that the above-mentioned memory, processor, and database are not limited to a specific memory, processor, or database. For example, in some cases, both the memory and the processor can have a distributed structure. For example, they can include a memory and a processor located at the test equipment end and the backend cloud, respectively, and the test equipment end and the backend cloud jointly implement the above-mentioned life prediction method. Furthermore, in an embodiment adopting a distributed structure, each step can adjust the specific execution terminal according to actual conditions, and the specific scheme of each step implemented in a specific terminal should not limit the scope of protection of the present invention.

[0062] Another aspect of the present application further provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the steps of the prediction method described in the above embodiment are implemented. Please refer to the above description for details, which will not be repeated here.

[0063] In addition, it can be understood that the above-mentioned computer-readable storage medium can also be in a system form, that is, it includes multiple computer-readable storage sub-media, so as to jointly implement the steps of the prediction method described above through multiple computer-readable storage media.

[0064] In summary, the beneficial effects of the material life prediction method, prediction system and computer-readable medium introduced in the above embodiments include but are not limited to that only three parameters need to be determined to accurately predict the cycle life under various loads and their combined working conditions. Few parameters are required and the scope of application is wide, so a unified life prediction method for multiple load conditions can be realized, especially a creep fatigue life prediction method for high and low cycle composites, to meet the needs of life prediction under different loads, and the prediction accuracy is good.

[0065] The various illustrative logic modules and circuits described in conjunction with the embodiments disclosed herein may be implemented or executed with a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. The processor may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in cooperation with a DSP core, or any other such configuration.

[0066] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software module may reside in a RAM memory, a flash memory, a ROM memory, an EPROM memory, an EEPROM memory, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to a processor so that the processor can read and write information from / to the storage medium. In an alternative, a storage medium may be integrated into a processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In an alternative, the processor and the storage medium may reside in a user terminal as discrete components.

[0067] In one or more exemplary embodiments, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented as a computer program product in software, each function may be stored on or transmitted by a computer-readable medium as one or more instructions or codes. Computer-readable media include both computer storage media and communication media, including any media that facilitates the transfer of a computer program from one place to another. Storage media may be any available media that can be accessed by a computer. As an example and not limitation, such a computer-readable medium may include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, disk storage or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of an instruction or data structure and can be accessed by a computer. Any connection is also properly referred to as a computer-readable medium. For example, if the software is transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwaves, the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwaves are included in the definition of the medium. Disk and disc as used herein include compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc, wherein disk often reproduces data magnetically, while disc reproduces data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.

[0068] Although the present invention is disclosed as above in terms of preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art may make possible changes and modifications without departing from the spirit and scope of the present invention. Therefore, any modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solution of the present invention shall fall within the scope of protection defined by the claims of the present invention.

Claims

1. A material life prediction method, characterized in that: include: Obtaining simulation results of the crystal plasticity finite element model corresponding to the material to be predicted under the loads of pure low-cycle fatigue, creep fatigue, and high-low-cycle combined creep fatigue, and at least one set of actual test results corresponding to each; According to the simulation results and the test results, the critical value of the fatigue indication factor under the load of pure low-cycle fatigue, creep fatigue and high-low-cycle combined creep fatigue, the critical value of the creep indication factor and the parameters related to the creep indication factor are determined; The linear damage accumulation criterion is used to establish a life prediction equation based on crystal plasticity to predict the cycle life of the material under cyclic loading test conditions.

2. The prediction method according to claim 1, characterized in that: The step of obtaining simulation results of the crystal plasticity finite element model corresponding to the material to be predicted under the loads of pure low cycle fatigue, creep fatigue and high and low cycle combined creep fatigue includes: establishing the finite element model through the crystal plasticity constitutive equation.

3. The prediction method according to claim 2, characterized in that: The crystal plasticity constitutive equation includes the following formula, where the main governing equation of the deformation rate gradient is expressed as In the formula, L p represents the inelastic deformation rate gradient, F p represents the inelastic deformation gradient, represents the plastic slip rate of the αth slip system, s α The unit vector representing the slip direction of the αth slip system, m α represents the unit vector in the normal direction of the αth slip system, and N represents the number of slip systems; The flow criterion equation in the crystal plasticity constitutive equation is expressed as In the formula, represents the reference plastic slip rate, k represents the Boltzmann constant, T represents the Boltzmann constant, F0 represents the thermal activation free energy, τ α represents the decomposed shear stress of the αth slip system, B α represents the back stress of the αth slip system, S α represents the slip resistance of the αth slip system, τ0, p and q represent material constants; The slip resistance evolution equation in the crystal plasticity constitutive equation is expressed as In the formula, h αβ represents the hardening matrix between slip systems α and β, S sat represents the saturated slip resistance, S0 represents the initial slip resistance; The static recovery term is introduced into the back stress equation of the crystal plasticity constitutive equation and is expressed as In the formula, h B represents the back stress hardening constant, r D represents the dynamic recovery coefficient related to the sliding resistance, r S Represents the static recovery coefficient of back stress.

4. The prediction method according to claim 1, characterized in that: According to the simulation results and the test results, the steps of determining the critical value of the fatigue indicator factor under the load of pure low-cycle fatigue, creep fatigue and high-low-cycle combined creep fatigue, the critical value of the creep indicator factor and the parameters related to the creep indicator factor include: The maximum cumulative energy dissipation is regarded as the indicator factor for determining crack initiation in the material under test during cyclic loading. This indicator factor increases linearly with the increase of the number of cycles under different loading conditions. According to the damage type, the accumulated energy dissipation is divided into fatigue indicator factor and creep indicator factor.

5. The prediction method according to claim 4, characterized in that: According to the simulation results and the test results, the steps of determining the critical value of the fatigue indicator factor under the load of pure low-cycle fatigue, creep fatigue and high-low-cycle combined creep fatigue, the critical value of the creep indicator factor and the parameters related to the creep indicator factor include: Critical value of fatigue indicator factor W F,crit Calculate according to the following formula W F,crit =N i ·W F,cyc In the formula, N i is the cycle life obtained from the test, W F,cyc It is the fatigue indicator factor obtained by simulation at a specific cycle; According to the exponential relationship between the critical value of the creep indicator factor and the creep indicator factor at a certain cycle, W C,crit =N i ·(W C,cyc ) M In the formula, W C,cyc is the creep indicator factor obtained by simulation at a specific cycle, and M is a parameter related to the creep indicator factor.

6. The prediction method according to claim 1, characterized in that: The linear damage accumulation criterion is used to establish a life prediction equation based on crystal plasticity. The steps of predicting the cycle life of the material to be predicted under cyclic load test conditions include: The linear damage accumulation criterion is used to establish a life prediction equation based on crystal plasticity. It is assumed that when the damage accumulates to 1, the material fails and satisfies the following formula: In the above formula, and They represent the low-cycle fatigue damage, high-cycle fatigue damage and creep damage in the j-th cycle, respectively. and They respectively represent the low-cycle fatigue indicator factor, high-cycle fatigue indicator factor and creep indicator factor obtained in the j-th cycle of simulation.

7. The prediction method according to claim 6, characterized in that: The life prediction equation based on crystal plasticity is established by using a linear damage accumulation criterion, and the step of predicting the cycle life of the material to be predicted under the cyclic load test conditions also includes: The cycle life of the material to be predicted under different cyclic load tests is predicted by the following formula:

8. A material life prediction system, characterized in that: include: a memory for storing instructions executable by a processor; A processor, configured to execute the instructions to implement the prediction method according to any one of claims 1 to 7.

9. The prediction system according to claim 8, characterized in that It also includes a database having simulation results of the crystal plasticity finite element model corresponding to the material to be predicted under the loads of pure low-cycle fatigue, creep fatigue and high-low-cycle combined creep fatigue, and at least one corresponding set of actual test results.

10. A computer readable medium having a computer program thereon, characterized in that The program is executed by a processor to implement the steps in the prediction method according to any one of claims 1 to 7 that can be implemented by a computer program.

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