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Low-cycle fatigue life prediction method based on high-temperature alloy machining surface integrity

A technology for fatigue life prediction and high-temperature alloys, which is applied in the direction of applying repetitive force/pulsation force to test material strength, measuring devices, and strength characteristics, etc., which can solve the problems affecting the accuracy of fatigue life prediction, cumbersome derivation process, and the size of grains on the surface of parts Influence and other issues, to achieve the effect of broad scientific research value and engineering application prospects, avoid duplication of experiments and data collection, save time and material expenditure

Pending Publication Date: 2020-09-18
SHANDONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0003] However, superalloys are very sensitive to stress concentration and strain rate. As a hot-end part, the service environment is complex and the load history is changeable in actual work. It will be subject to repeated coupling effects of mechanical stress and thermal stress, and it is very easy to cause low-cycle fatigue and failure.
The low-cycle fatigue failure of superalloy parts will cause equipment failure, cause serious economic losses, and even threaten the safety of operators. Therefore, it is urgent to accurately predict the low-cycle fatigue life of nickel-based superalloys
[0004] Existing low-cycle fatigue life prediction methods for superalloys can be divided into two categories: one is based on regression fitting of fatigue life test data of superalloy samples to predict fatigue life. A large number of tests are required, which is very time-consuming and expensive, and is limited to the application under the conditions within the test range; the other is based on the physical and mechanical properties of superalloy materials, and establishes an analytical model through theoretical reasoning for fatigue life analysis. Forecasting, the derivation process of this type of method is very cumbersome, and at the same time, the values ​​of many parameters in the model still need to be obtained through material performance testing, which is difficult to obtain and low in accuracy, thus affecting the accuracy of fatigue life prediction
Analysis and research have shown that the fatigue life of superalloys is also affected by the grain size of the surface of the part, and the existing fatigue life prediction methods have not considered the influence of this aspect

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  • Low-cycle fatigue life prediction method based on high-temperature alloy machining surface integrity
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  • Low-cycle fatigue life prediction method based on high-temperature alloy machining surface integrity

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Embodiment 1

[0049] The present invention is a method for predicting the low-cycle fatigue life of a high-temperature alloy sample based on the integrity of the machined surface. Taking the turned sample of GH4169 nickel-based superalloy as an example, the specific implementation steps of the low-cycle fatigue prediction method under high-temperature conditions are introduced in detail:

[0050] S1. The low-cycle fatigue test of GH4169 nickel-based superalloy at a constant temperature of 650°C was carried out using a servo hydraulic fatigue testing machine. The total axial strain was controlled between 0.2% and 0.6%, the strain ratio was -1, and the loading frequency was 20Hz. , the sample size as figure 2 shown. Obtain the data of fatigue life and total strain amplitude, and plot the relationship between fatigue life and total strain amplitude in the double logarithmic coordinate system image 3 .

[0051] S2. Select the sample for the fatigue test, cut it perpendicular to the sample i...

Embodiment 2

[0062] The invention is a low-cycle fatigue life prediction method for high-temperature alloy samples based on the integrity of the processed surface. Taking the GH4169 nickel-based high-temperature alloy finish turning-rolling combination processing sample as an example, the low-cycle fatigue prediction method under normal temperature conditions is introduced in detail. The implementation steps:

[0063] S1. The low-cycle fatigue test of the GH4169 nickel-based superalloy finish turning-rolling combination processing sample was carried out under normal temperature conditions using a servo hydraulic fatigue testing machine. The total axial strain was controlled between 0.2% and 0.6%, and the strain ratio was 0.1. The loading frequency is 90Hz, and the sample size is as follows figure 2 shown. Obtain the data of fatigue life and total strain amplitude, and plot the relationship between fatigue life and total strain amplitude in the double logarithmic coordinate system image...

Embodiment 3

[0075] The invention is a method for predicting the low-cycle fatigue life of a high-temperature alloy sample based on the integrity of the processed surface, but it also has guiding significance for the prediction of the low-cycle fatigue life of other alloy samples. Taking the TC4 high-temperature titanium alloy finish turning-rolling combination processing sample as an example, the specific implementation steps of the low cycle fatigue prediction method under normal temperature conditions are introduced in detail:

[0076] S1. The low-cycle fatigue test of the TC4 titanium alloy finish turning-rolling combined processing sample was carried out under normal temperature using a servo hydraulic fatigue testing machine. The total axial strain was controlled between 0.4% and 0.8%, and the strain ratio was 0.481. Frequency is 0.5Hz, fatigue limit σ -1 407Mpa, tensile strength σ b is 974Mpa, the sample size is as figure 2 shown. Obtain the data of fatigue life and total strain...

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Abstract

The invention discloses a low-cycle fatigue life prediction method based on high-temperature alloy processing surface integrity, and the method comprises the following steps: carrying out low-cycle fatigue test of a high-temperature alloy sample, obtaining the fatigue life and total strain amplitude data, and drawing a relation graph of the fatigue life and the total strain amplitude under a double logarithmic coordinate system; selecting a high-temperature alloy sample subjected to a low-cycle fatigue test, carrying out axial cutting sampling perpendicular to the sample, inlaying the sample into black inlaid resin, carrying out mechanical polishing to enable the roughness of the sampled surface to reach a micron level, and carrying out surface chemical corrosion to measure the average area root mean square of the surface; selecting a fatigue life test sample, and measuring the unevenness of the machined surface of the sample; and performing formula correction considering influence ofthe unevenness of the machined surface on the fatigue life prediction model, and establishing the high-temperature alloy sample low-cycle fatigue life prediction model based on the surface integrity.

Description

technical field [0001] The invention relates to the technical field of fatigue life prediction of high-temperature alloy samples, in particular to a low-cycle fatigue life prediction method based on the surface integrity of high-temperature alloy processing, which is suitable for high-temperature alloy materials used in aerospace, nuclear industry, chemical industry and other industries. Background technique [0002] Due to their excellent high temperature strength, hot corrosion resistance, high temperature oxidation resistance and fatigue resistance at high temperatures, superalloys are ideal for manufacturing working equipment in extreme service environments such as high temperature and high load, frequent high and low temperature alternation, and high-speed airflow scour. Key engineering material for hot end parts. Commonly used high-temperature alloys can be divided into three types of high-temperature alloys: nickel-based, cobalt-based and iron-based. Among them, nick...

Claims

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Application Information

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IPC IPC(8): G01N3/32G01N1/28G01N1/32G01N1/04
CPCG01N1/04G01N1/286G01N1/32G01N3/32G01N2001/2873G01N2203/0073
Inventor 刘战强姚共厚王鑫任小平王兵蔡玉奎
Owner SHANDONG UNIV
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