A method for evaluating the degradation of low-cycle fatigue performance of long-term service materials

Abstract

The present invention belongs to the technical field of low-cycle fatigue, and in particular, is a method for evaluating the degradation of low-cycle fatigue performance of long-term service materials, including the following specific steps: Step 1, determining the thermal parameters of low-cycle fatigue prediction and extrapolation materials, that is, selecting the predicted hot service temperature, duration and strain amplitude according to engineering requirements; Step 2, determining the elastic parameters of the material; Step 3, bringing the thermal parameters and elastic parameters into the prediction model, and performing fitting calculations, and fitting the fatigue life relationship curve according to the prediction model. The method for evaluating the degradation of low-cycle fatigue performance of long-term service materials can realize the prediction of the low-cycle fatigue life of the material under any hot service temperature, duration and strain amplitude according to the prediction model by understanding the elastic parameters of the material under any condition. The prediction method is simple in form, saves the number of samples and time, and still has good prediction results for long-term hot service.

Description

Technical Field

[0001] The invention relates to the technical field of low cycle fatigue, and in particular to a method for evaluating the degradation of low cycle fatigue performance of a long-time service material. Background Art

[0002] Pressure vessels are subject to internal fluctuating loads during service and are prone to fatigue fracture failure, which seriously affects the service life and safety of the equipment. The SN curve is currently used in the design to determine the fatigue limit of the material. However, due to the limited volume of samples available for service equipment and the long service life, how to accurately predict the fatigue life of the material and use the existing partial data to reasonably extrapolate the fatigue life under service conditions has always been a key and difficult issue in engineering.

[0003] A thorough understanding of the factors affecting low-cycle fatigue under hot service conditions will reveal that the impact of hot service on material properties is mainly concentrated on service temperature and service duration. Therefore, the introduction of a model of service temperature and service duration can predict fatigue life at any service temperature, service duration and strain amplitude, thereby achieving cost savings and reasonable extrapolation. The present invention intends to provide a method for predicting and extrapolating low-cycle fatigue life from the perspective of low-cycle fatigue thermal parameters of pressure vessel steel. Summary of the invention

[0004] Based on the above-mentioned existing technical problems, the present invention proposes a method for evaluating the degradation of low-cycle fatigue performance of long-term service materials.

[0005] The present invention proposes a method for evaluating the degradation of low-cycle fatigue performance of long-term service materials, which comprises the following specific steps:

[0006] Step 1: Determine the thermal service state parameters of low-cycle fatigue prediction and extrapolation materials, that is, select the predicted thermal service temperature, duration and strain amplitude according to engineering requirements.

[0007] Step 2: Determine the material elastic parameters.

[0008] Step 3: Bring the thermal parameters and elastic parameters into the prediction model, perform fitting calculations, and fit the fatigue life relationship curve according to the prediction model.

[0009] Step 4: Obtain the prediction model under the service condition to achieve the prediction and extrapolation of the low-cycle fatigue life of the material.

[0010] Preferably, the elastic parameters in step 2 include fatigue strength coefficient σ' f , elastic modulus E and fatigue strength index b.

[0011] Preferably, the formula for the prediction model fitting calculation in step three is:

[0012]

[0013] Among them, A∝ε t , A0∝ε t , k(T)=k0×exp(-Q / RT).

[0014] Preferably, in the prediction model fitting calculation formula in step three, A is the amplification factor, A0 is the intercept, and A+A0 is the plastic strain amplitude of the original material in the unserviced state.

[0015] Preferably, k(T) in the prediction model fitting calculation formula in step three is a thermal aging kinetic parameter.

[0016] Preferably, the Δε in the prediction model fitting calculation formula in step 3 is t / 2 is a low cycle fatigue stability ring or N f / 2 total strain amplitude.

[0017] Preferably, t in the prediction model fitting calculation formula in step three is the service time.

[0018] Preferably, k0 in the k(T) calculation formula is the pre-exponential factor, R is the gas constant, and T is the thermal service temperature.

[0019] The beneficial effects of the present invention are:

[0020] The prediction model proposed in the present invention can realize the rapid prediction of low-cycle fatigue life, and can realize the extrapolation of low-cycle fatigue performance of materials with different hot service temperatures, any strain amplitude and long-term hot service. By understanding the elastic parameters of the material under any condition, the prediction model can be used to predict the low-cycle fatigue life of the material at any hot service temperature, duration and strain amplitude. The prediction method is simple in form, saves the number of samples and time, and still has good prediction results for long-term hot service. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a flow chart of a method for evaluating the degradation of low-cycle fatigue performance of long-term service materials proposed by the present invention;

[0022] Figure 2 This is a schematic diagram of the correlation between the actual low-cycle fatigue life and the predicted life of a long-time hot service material under different aging conditions in a method for evaluating the low-cycle fatigue performance degradation of a long-time service material proposed in the present invention. DETAILED DESCRIPTION

[0023] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0024] Reference Figure 1 , a method for evaluating the degradation of low-cycle fatigue performance of long-term service materials, comprising the following specific steps:

[0025] Step 1: Determine the thermal service state parameters of low-cycle fatigue prediction and extrapolation materials, that is, select the predicted thermal service temperature, duration and strain amplitude according to engineering requirements.

[0026] Step 2: Determine the elastic parameters of the material, which include the fatigue strength coefficient σ' f , elastic modulus E and fatigue strength index b.

[0027] Step 3: Bring the thermal parameters and elastic parameters into the prediction model, perform fitting calculations, and fit the fatigue life relationship curve according to the prediction model.

[0028] Step 4: Obtain the prediction model under the service condition to achieve the prediction and extrapolation of the low-cycle fatigue life of the material.

[0029] The prediction model fitting calculation formula is:

[0030]

[0031] Among them, Δε t / 2 is a low cycle fatigue stability ring or N f / 2, A is the amplification factor, A0 is the intercept, A+A0 is the plastic strain amplitude of the original material in the unserviced state, t is the service time, and k(T) is the thermal aging kinetic parameter.

[0032] The calculation formula of thermal aging kinetic parameters is:

[0033] k(T)=k0×exp(-Q / RT).

[0034] Among them, k0 is the pre-exponential factor, R is the gas constant, and T is the thermal service temperature.

[0035] Example:

[0036] The present invention is further described below with reference to an embodiment.

[0037] like Figure 2 As shown, the specific steps are as follows:

[0038] Step 1: For a certain pressure vessel material, select a certain long-term service temperature and duration.

[0039] Step 2: Determine elastic parameters, including fatigue strength coefficient σ' f , elastic modulus E and fatigue strength index b.

[0040] Step 3: Bring the thermal parameters and elastic parameters into the prediction model for fitting calculation. The fitting result is shown in the following formula:

[0041] Δε t / 2=0.0050(2N f ) -0.097 +(0.030×ε t -6.76×10 -5 )×exp(-t / 989.34)+0.88×ε t -1.42×10 -3

[0042] Step 4: According to the prediction model, the predicted life under different service times and strain amplitudes at the service temperature is obtained. The predicted life is compared with the actual life and it is found that the prediction results are within the twice tolerance band.

[0043] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for evaluating the degradation of low-cycle fatigue performance of long-term service materials, comprising the following specific steps: Step 1: Determine the thermal parameters of low-cycle fatigue prediction and extrapolation materials, that is, select the predicted hot service temperature, duration and strain amplitude according to engineering requirements; Step 2: Determine the material elastic parameters; Step 3: Bring the thermal parameters and elastic parameters into the prediction model, perform fitting calculations, and fit the fatigue life relationship curve according to the prediction model; The formula for the prediction model fitting calculation in step 3 is: in, A∝ε t , A0∝ε t , k(T)=k0×exp(-Q / RT), A in the prediction model fitting calculation formula in step 3 is the amplification factor, A0 is the intercept, A+A0 is the plastic strain amplitude of the original material in the unserviced state, k(T) in the prediction model fitting calculation formula in step 3 is the thermal aging kinetic parameter, k0 in the k(T) calculation formula is the pre-exponential factor, R is the gas constant, and T is the thermal service temperature; Step 4: Obtain the prediction model under the service condition to achieve the prediction and extrapolation of the low-cycle fatigue life of the material.

2. The method for evaluating the degradation of low-cycle fatigue performance of long-term service materials according to claim 1, characterized in that: The elastic parameters in step 2 include fatigue strength coefficient σ' f , elastic modulus E and fatigue strength index b.

3. The method for evaluating the degradation of low-cycle fatigue performance of long-term service materials according to claim 1, characterized in that: Δε in the prediction model fitting calculation formula in step 3 t / 2 is a low cycle fatigue stability ring or N f / 2 total strain amplitude.

4. The method for evaluating the degradation of low-cycle fatigue performance of long-term service materials according to claim 1, characterized in that: The t in the prediction model fitting calculation formula in step three is the service time.

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