CN113252465A - M-H method-based heat-resistant steel creep life prediction method - Google Patents
M-H method-based heat-resistant steel creep life prediction method Download PDFInfo
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- 229910000859 α-Fe Inorganic materials 0.000 claims description 2
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- 229910052751 metal Inorganic materials 0.000 description 2
- 239000002184 metal Substances 0.000 description 2
- 239000007769 metal material Substances 0.000 description 2
- VYZAMTAEIAYCRO-UHFFFAOYSA-N Chromium Chemical compound [Cr] VYZAMTAEIAYCRO-UHFFFAOYSA-N 0.000 description 1
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Abstract
The invention discloses a method for predicting creep life of heat-resistant steel based on an M-H method, which comprises the following steps: s1, carrying out a creep test on the creep test sample, and acquiring creep performance data of the heat-resistant steel at the creep test temperature; s2, calculating P corresponding to different test stress sigma at the temperature according to the creep performance dataM‑HA value; s3, for PM‑HPerforming parametric curve fitting on the values to obtain a main fitting parameter curve of the improved M-H method at the temperature; s4, obtaining P corresponding to different low stress values at the temperature according to the obtained fitting parameter main curveM‑HThe creep life corresponding to different low stresses at the temperature is further worked out; s5, repeating the steps S1-S4 to obtain creep rupture lives corresponding to different low stresses at other temperatures. The method overcomes the defect that the creep life of the material low-stress area is excessively predicted, provides reliable basis for maintaining and replacing materials in engineering, and has the advantages of wide application range, high prediction precision and high reliability.
Description
Technical Field
The invention relates to the field of high-temperature materials and structural strength, in particular to a creep life prediction method of heat-resistant steel based on an M-H method.
Background
The accurate prediction of the service life of thermal power and nuclear power high-temperature materials is a precondition for guaranteeing the safe service of engineering materials and structures. High-chromium heat-resistant steel, especially heat-resistant steel with chromium content of 9% -12%, is a main choice or replacement material for main parts of thermal power plants due to its outstanding creep resistance, good corrosion resistance and high-temperature oxidation resistance. The high-temperature creep rupture of the high-temperature creep rupture has great influence on the safety and normal production of a thermal power plant. At present, the creep rupture life is obtained through a high-stress short-range creep test in engineering, and then the creep rupture life under actual service low stress is obtained through extrapolation, but the creep life of a material low-stress area is over-predicted by the method.
As operating temperatures increase, the likelihood of creep failure of high temperature equipment and high temperature mechanisms in modern industries and the severity of accidents due to creep failure also increase. Therefore, it is of great practical significance to correctly predict the creep life of a material, both from economic and safety considerations.
Currently, the most widely used creep life prediction method is a time-temperature parameter method represented by the Larson-Miller method. The method relates creep temperature, stress and time by Larson-Miller parameters to form a Larson-Miller parameter equation:
PL-M＝T(CL-M+lgtr) (1)
wherein, PL-MIs the Larson-Miller parameter; t is creep test temperature in K (Kelvins); c0、C1、C2、C3、C4Is a material constant; sigma is creep test stress; cL-MAs constant, for high-chromium martensitic heat-resistant steels, C L-M20 or 33 for ferritic steel, CL-MCasting high alloys of 17 or 31 for austenitic steels and Ni-Cr-Fe, CL-M15 or 36.
The equation has good comprehensiveness, but the formula (2) has many parameters, a complex structure and low prediction precision, the creep life of a low-stress area of a material is over-predicted, more test data are needed during application, and the method is suitable for prediction within a range which is not more than 3 times of the test creep life.
Although the newly developed theta method in the last 80 th century can better describe the creep curve obtained by the test under the normal stress condition, the method cannot be applied if the load changes, has high requirement on temperature uniformity, and cannot be used for accurate long-life extrapolation. In recent years, various forms of modified theta equations are established, and good effects are achieved in the aspect of expressing a creep curve, but the parameters of the theta equations are very sensitive to the deformation process of creep and are dispersed in the relation with stress and temperature, so that a large amount of test data is also needed for predicting the creep life by using a theta mapping method.
The M-H parameter method (Manson-Haferd) relates creep temperature, stress and time to form an M-H parameter equation:
wherein, PM-HIs an M-H parameter; t is creep test, temperature in units of K (Kelvins); a is0、a1、a2、a3、a4Is a material constant; sigma is creep test stress; lgta、TaIs a constant. The equation has good comprehensiveness, but the formula (4) has a plurality of parameters and low prediction precision, excessively predicts the creep life of the low-stress area of the material, and is suitable for prediction within a range which is not more than 3 times of the test creep life.
Disclosure of Invention
The invention aims to solve the problems and the defects of the conventional creep life prediction technology and provide a method for more accurately and effectively predicting the creep life of a heat-resistant alloy, particularly the creep life of the heat-resistant alloy under low stress on the basis of a conventional creep strength test.
Therefore, the invention adopts the following technical scheme:
a creep life prediction method for heat-resistant steel based on an M-H method comprises the following steps:
s1, performing a creep test on the creep test sample according to the creep test specification, and acquiring creep performance data and creep rupture time of the heat-resistant steel when the creep test temperature is T;
s2, calculating P corresponding to different test stress sigma at the temperature according to the creep performance data obtained in the step S1M-HThe value, the calculation formula is as follows:
wherein:
PM-H: an M-H parameter;
trcreep rupture time in units of h;
t is creep test temperature in K;
lgtaand TaIs a constant;
s3, for the PM-HPerforming parametric curve fitting on the values to obtain a main fitting parameter curve of the improved M-H method at the temperature, wherein the mathematical expression is as follows:
σ＝a+b ecP，
wherein:
sigma is test stress, and the unit is MPa;
a. b and c are undetermined coefficients;
s4, obtaining P corresponding to different low stress values at the temperature according to the fitting parameter main curve obtained in the step S3M-HSubstituting the values into the formula (1) to obtain creep life corresponding to different low stresses at the temperature;
s5, repeating the steps S1-S4 to obtain creep rupture lives corresponding to different low stresses at other temperatures.
Wherein the test stress sigma is in the range of 80-220 MPa.
Lgt in the formula (1) when the heat-resistant steel is high-chromium heat-resistant steela＝15，Ta450; (ii) a Lgt in the formula (1) when the heat-resistant steel is ferrite steela＝31；Ta190; lgt in formula (1) when the heat-resistant steel is austenitic steel or Ni-Cr-Fe casting high alloya＝18，Ta＝520。
In step S2, the test is regressed by least squares regression using mathematical analysis softwareData lgtrAnd constant lgta、TaAnd the temperature T is calculated from a group of input software under different stresses at the temperatureM-H。
In step S3, mathematical analysis software is used to determine the parameters P under different stresses at constant temperatureM-HAnalyzing and fitting the data to obtain the coefficients a, b and c, and substituting the coefficients into the expression sigma a + b ecPAnd obtaining an improved fitting parameter main curve of M-H method regression.
The prediction method of the invention firstly establishes the stress and the M-H parameter P on the basis of the relation equation of the creep life and the temperature of the M-H parameter method, considering the beneficial effect of the high-temperature strength on the creep property and the influence of the stress on the creep mechanism of the materialM-HFitting equation of the relationship (b), namely fitting a main curve; fitting creep life data under constant temperature and different stresses by using a least square method through the model, determining the parameter value of the model, and obtaining the stress and the parameter PM-HThe relational expression of (1); the predicted creep life under low stress is obtained from the relational expression.
Compared with the prior art, the prediction method has the following beneficial effects:
1. the invention provides an improved main curve equation of an M-H method regression curve: a + b ecPThe equation has good reliability, and the prediction precision of the creep life of the heat-resistant alloy is improved;
2. the method can accurately predict the creep life of the low-stress area of the material, can predict the creep life of the heat-resistant steel of different materials at different temperatures and under different stresses, overcomes the defect of over-predicting the creep life of the low-stress area of the material, and provides reliable basis for maintaining and replacing the material in engineering;
3. the prediction method is simple and efficient, can realize effective creep life prediction only through multiple groups of high-stress creep test data in a certain range, and has good practicability;
4. the method is suitable for predicting the creep life of various metal materials such as heat-resistant steel, heat-resistant alloy, high-temperature alloy and the like, and has wide application range and high reliability.
5. The method can effectively estimate the service time of the high-temperature-resistant metal, reduce the harm and reduce the cost.
Drawings
FIG. 1 is stress and creep rupture life data for ASME grade P92 steel at 650 ℃;
FIG. 2 shows that P92 steel is subjected to M-H method model based fitting main curve and actual parameter value P at 650 DEG CM-HA comparison graph of (A);
FIG. 3 shows that P92 steel is fit with main curve and actual parameter value P based on Jiang Feng-Zhao Jie topic group method model at 650 DEG CM-HA comparison graph of (A);
FIG. 4 shows the fitting of a principal curve to an actual parameter value P of P92 steel at 650 ℃ based on the improved M-H method model of the present inventionM-HA comparison graph of (A);
FIG. 5 is a creep life extrapolation curve of ASME grade P92 steel at 650 ℃ based on M-H method, Jiang Feng-Zhao Jie project group method, modified M-H method, L-M method;
FIG. 6 is a graph showing the comparison between the creep rupture time predicted from ASME grade P92 steel at 650 ℃ based on the M-H method, Jiang Feng-Zhao subject group method, modified M-H method, and L-M method, and the actual creep rupture time.
Detailed Description
The prediction method of the present invention will be described in detail below with reference to the accompanying drawings and examples.
Example one
In this example, ASME (American Society of Mechanical Engineers) grade high-chromium heat-resistant steel P92 was selected as the object of study, the sampling direction of the creep test specimen was the inboard-short transverse direction (perpendicular to the extrusion direction of the extruded plate), and the specimen size was referred to GB/T2039-1997 test methods for tensile creep and endurance of metals.
The method for predicting the creep life of the heat-resistant steel based on the M-H method comprises the following steps:
s1, acquiring creep performance data: and carrying out creep test on the creep test sample according to the specification of the creep test standard under the conditions that the creep test temperature T is 650 ℃ and the test stress range is 220-80 MPa, and obtaining 68 effective creep data under different stresses sigma, wherein the data distribution diagram is shown in figure 1.
S2, calculating the corresponding P under different test stress sigma at 650 ℃ by the effective creep data according to the following formulaM-HValue (M-H parameter):
in the formula:
trcreep rupture time in units of h;
t is creep test temperature in K;
at this test temperature, the M-H constants (lgt) of these materials were determined according to the Japanese institute for metallic materialsa、Ta) Value of lgta＝450，Ta＝15；
Test data lgt was regressed by least squares regression using mathematical analysis softwarerAnd constant lgta、TaAnd the temperature T can be obtained by a group of input softwareM-H。
S3, applying mathematical analysis software to the obtained P under the same temperature and different stressesM-HFitting the values to obtain undetermined coefficients a, b and c, and substituting the undetermined coefficients into the following formula:
σ＝a+b ecP，
wherein:
sigma is test stress, and the unit is MPa;
a. b and c are undetermined coefficients;
p is the parameter of M-H method；
Obtaining an improved fitted main curve of M-H method regression:
σ＝219.0934-5506.5105*exp(162.8230*PM-H)
s4, obtaining P corresponding to different low stress values at the temperature according to the fitting parameter main curve obtained in the step S3M-HValue, substituted into equation (1), or as follows:
the creep life was determined for various low stresses at 650 ℃.
S5, repeating the steps S1-S4 to obtain creep rupture lives corresponding to different low stresses at other temperatures.
At 650 ℃, the creep life of the ASME grade P92 heat-resistant steel under the stress of 220-20MPa is predicted by adopting the prediction method of the invention and several traditional methods, and the corresponding actual parameter value PM-HThe fitting relational expression between the stress and the fitting is shown in table 1, and the comparison graph of the fitting main curve and the actual parameter value under the corresponding model is shown in fig. 2-4; the extrapolated creep life curves for each method are shown in FIG. 5; fig. 6 shows a graph comparing the creep rupture time predicted by each method with the actual creep rupture time.
TABLE 1
Wherein: σ is the test stress in MPa.
As can be seen from the above table, the correlation coefficient of the conventional L-M method and the fitting main curve of the M-H method are lower than that of the improved fitting main curve of the M-H method of the present invention, and although the correlation coefficient of the fitting main curve of the von-zhuyege topic group method is the highest, as can be seen from fig. 5, the extrapolated curve of creep life is higher than the actual creep life.
As can be seen from fig. 5 and 6, the conventional M-H method, the von-jeikes project group method, and the conventional L-M method over-predict the creep lifetime of the low stress region of the material, whereas the improved M-H method of the present invention predicts better low stress region results and the prediction error is within 2 times of the error.
As can be seen from FIG. 6, the data points predicted by the method of the present invention are mostly at tpTo the right of tr, but not at tp＝trThe right-hand point is also substantially at tp＝trLine vicinity, illustrating the predicted creep at low stress for the method of the inventionThe fracture life is lower than the existing low-stress actual creep fracture life, and the method has good prediction effect and great engineering significance.
Claims (7)
1. A creep life prediction method for heat-resistant steel based on an M-H method comprises the following steps:
s1, performing a creep test on the creep test sample according to the creep test specification, and acquiring creep performance data and creep rupture time of the heat-resistant steel when the creep test temperature is T;
s2, calculating P corresponding to different test stress sigma at the temperature according to the creep performance data obtained in the step S1M-HThe value, the calculation formula is as follows:
wherein:
PM-H: an M-H parameter;
trcreep rupture time in units of h;
t is creep test temperature in K;
lgtaand TaIs a constant;
s3, for the PM-HPerforming parametric curve fitting on the values to obtain a main fitting parameter curve of the improved M-H method at the temperature, wherein the mathematical expression is as follows:
σ＝a+b ecP，
wherein:
sigma is test stress, and the unit is MPa;
a. b and c are undetermined coefficients;
s4, obtaining P corresponding to different low stress values at the temperature according to the fitting parameter main curve obtained in the step S3M-HSubstituting the values into the formula (1) to obtain creep life corresponding to different low stresses at the temperature;
s5, repeating the steps S1-S4 to obtain creep rupture lives corresponding to different low stresses at other temperatures.
2. The method for predicting creep life of heat-resistant steel according to claim 1, wherein: the test stress sigma is 80-220 MPa.
3. The method for predicting creep life of heat-resistant steel according to claim 1, wherein: the heat-resistant steel is high-chromium heat-resistant steel lgt in formula (1)a＝15，Ta＝450。
4. The method for predicting creep life of heat-resistant steel according to claim 1, wherein: the heat-resistant steel is ferrite steel, lgt in formula (1)a＝31；Ta＝190。
5. The method for predicting creep life of heat-resistant steel according to claim 1, wherein: the heat-resistant steel is austenitic steel or Ni-Cr-Fe cast high alloy, lgt in formula (1)a＝18，Ta＝520。
6. The method for predicting creep life of heat-resistant steel according to any one of claims 1 to 5, wherein: in step S2, the mathematical analysis software is used to regress the test data lgt by least squares methodrAnd constant lgta、TaAnd the temperature T is calculated from a group of input software under different stresses at the temperatureM-H。
7. The method for predicting creep life of heat-resistant steel according to claim 6, wherein: in step S3, mathematical analysis software is used to determine the parameters P under different stresses at constant temperatureM-HAnalyzing and fitting the data to obtain the coefficients a, b and c, and substituting the coefficients into the expression sigma a + b ecPAnd obtaining an improved fitting parameter main curve of M-H method regression.
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| CN114563268A (en) * | 2022-02-22 | 2022-05-31 | 杭州电子科技大学 | Method for predicting creep property of high-temperature alloy based on soft constraint neural network model |
| CN115718061A (en) * | 2022-11-25 | 2023-02-28 | 中国特种设备检测研究院 | Method, system and equipment for evaluating corrosion layer of heat-resistant steel material |
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| CN114563268A (en) * | 2022-02-22 | 2022-05-31 | 杭州电子科技大学 | Method for predicting creep property of high-temperature alloy based on soft constraint neural network model |
| CN114563268B (en) * | 2022-02-22 | 2024-04-26 | 杭州电子科技大学 | Method for predicting creep performance of high-temperature alloy based on soft constraint neural network model |
| CN115718061A (en) * | 2022-11-25 | 2023-02-28 | 中国特种设备检测研究院 | Method, system and equipment for evaluating corrosion layer of heat-resistant steel material |
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