CN112214875B - Method for evaluating real service temperature of workpiece through precipitated particle phase size - Google Patents

Method for evaluating real service temperature of workpiece through precipitated particle phase size Download PDF

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CN112214875B
CN112214875B CN202010952387.6A CN202010952387A CN112214875B CN 112214875 B CN112214875 B CN 112214875B CN 202010952387 A CN202010952387 A CN 202010952387A CN 112214875 B CN112214875 B CN 112214875B
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temperature
workpiece
particle phase
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CN112214875A (en
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高振桓
巩秀芳
王天剑
杨乐馨
聂丽萍
魏先平
袁小虎
孙友贝
管迎博
李定骏
隆彬
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DEC Dongfang Turbine Co Ltd
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    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
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    • G01N15/02—Investigating particle size or size distribution
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    • G06F2119/08—Thermal analysis or thermal optimisation

Abstract

The invention discloses a method for evaluating the real service temperature of a workpiece through the size of a precipitated particle phase, which comprises the following steps: 1) according to the size d of the precipitated particle phase of the heat-resistant alloy material workpiece in the pre-service state0And setting different temperatures T in the service temperature intervalnOf different durations tnSize d of precipitated particle phase under thermal exposure testnEstablishing an arithmetic model of temperature-time-precipitated particle size; wherein n represents the number of trials; 2) and measuring the size d of the precipitated particle phase in the workpiece after the workpiece is in service for a specific time T, and substituting the measured size d into the arithmetic model in the step 1) to obtain the estimated service temperature T. The method realizes service temperature evaluation of the material after thermal exposure by establishing a quantitative corresponding relation between temperature-time-organization, wherein the temperature range which is optimized in the thermal exposure test is 873-. The temperature evaluation precision is less than or equal to 15K, the evaluation result is reliable, and the method is suitable for engineering application.

Description

Method for evaluating real service temperature of workpiece through precipitated particle phase size
Technical Field
The invention belongs to the technical field of heat-resistant alloy materials for power stations, and particularly relates to a method for predicting and evaluating the actual service temperature of a material through the size of a precipitated particle phase of a heat-resistant alloy material after thermal exposure.
Background
The heat-resistant alloy material is used as a material for hot end parts of industrial power generation equipment, and is subjected to long-term high-temperature heat exposure and various damages such as long-term creep deformation, fatigue, high-temperature oxidation, hot corrosion and the like, so that the original structure and performance of the material are seriously influenced, and the damage to the structure and performance of the material is most obvious especially when the temperature is increased. Meanwhile, due to the nonuniformity of the real service temperature field of the hot end component and the complexity of the workpiece structure, the real temperature field is usually difficult to directly measure, and the detection, maintenance and service life evaluation of the temperature bearing component are difficult to obtain accurate temperature field data. Therefore, the research on the microstructure change rule of the heat-resistant alloy material under the real service condition is carried out, the corresponding relation between the service temperature, the service time and the service structure is obtained, and the method has important engineering significance for the design, detection, maintenance and service life evaluation of the temperature-bearing component.
Currently, the evaluation of the service temperature field of a workpiece by using a degraded microstructure has been reported. Such as: "an experimental evaluation of service temperature of high-temperature alloy turbine blade", publication No. CN105403502, introduces a technique for predicting a temperature field by primary gamma' phase volume fraction of a high-temperature alloy turbine blade, which is suitable for the evaluation of the service temperature of an aircraft engine blade above 900 ℃, but the evaluation application time is short, the service life cycle of the blade is 900 hours, the temperature evaluation precision of the method is +/-50 ℃, and the real service temperature at any time or the real service time at any service temperature cannot be evaluated. The service life of the ground gas turbine for the power station reaches 24000-50000 hours, and the service temperature range of the blade is 700-950 ℃, so the method reported in the publication No. CN105403502 is not applicable. The publication No. CN110411850 reports "an assessment method for service conditions of high-temperature alloy turbine blades", the method establishes the relationship among the service temperature, stress, gamma 'phase volume fraction, gamma' phase raft perfection degree and raft thickness of an aviation turbine blade DZ125 alloy through machine learning, wherein the stress and the temperature can be used as output variables of an artificial neural network, a prediction model of the method has no explicit relational expression, is inconvenient for engineering use, is only suitable for service temperature assessment within the service time of 1250h at the service temperature of more than 900 ℃, and needs a large amount of gamma 'phase volume fraction, gamma' phase raft perfection degree and raft thickness experimental data for machine learning. In addition, the gamma' phase is promoted to be raft-arranged, high temperature and stress are required, and the use condition of the ground gas turbine is not met.
Therefore, based on the heat-resistant alloy material for the power station, a method for establishing an explicit quantitative relation among the service temperature, the service time and the material organization is expected to solve the problems and predict the true service temperature of the material more accurately.
Disclosure of Invention
The technical problem solved by the invention is as follows: a method for predicting the actual service temperature of a material through the size of a precipitated particle phase of a heat-resistant alloy material after heat exposure is provided. The method realizes service temperature evaluation of the material after thermal exposure by establishing a quantitative corresponding relation between temperature-time-organization, wherein the temperature range which is optimized in the thermal exposure test is 873-. The temperature evaluation precision is less than or equal to 15K, the evaluation result is reliable, and the method is suitable for engineering application.
The technical scheme adopted by the invention is as follows:
a method for evaluating the actual service temperature of a workpiece through the size of a precipitated particle phase specifically comprises the following steps:
1) according to the size d of the precipitated particle phase of the heat-resistant alloy material workpiece in the pre-service state0And setting different temperatures T in the service temperature intervalnOf different durations tnSize d of precipitated particle phase under thermal exposure testnThen establishing an arithmetic model of temperature-time-precipitated particle size; where n represents the number of trials.
2) And measuring the size d of the precipitated particle phase in the workpiece after the workpiece is in service for the specific time T, substituting the measured size d into the arithmetic model in the step 1), and calculating to obtain the estimated service temperature T of the heat-resistant alloy material workpiece in service for the specific time T.
Different degrees of tissue damage may occur to materials exposed to heat for a long period of time, for example, coarsening of the gamma' phase precipitated particle phase for nickel-base superalloys and laves precipitated particle phase for W-containing heat-resistant steels. Therefore, the corresponding relation between temperature, time and structure can be established through the research on the evolution and quantification of the phase size of the precipitated particles, and the evaluation on the real service temperature of the workpiece is realized. The method specifically comprises the following steps:
assuming that the change in the size of the precipitated phase particles over time is related to the value of K, which is a complex function with respect to temperature, K ═ f (t), and can be expressed as:
K＝P1/[exp(P2T)·exp(P3T-1)·exp(P4T-2)·...·exp(PnT-m)]
where T is the service temperature, the high power down term of e (value ≈ 1) can be ignored, then:
K＝P1/[exp(P2T)·exp(P3T-1)]
the change in the phase size of the precipitated particles with respect to time t and parameter K can be expressed as:
d3-d0 3＝t·P1/[exp(P2T)·exp(P3T-1)]
wherein d is the size of the precipitated particles after service, d0The K value can be further simplified to be the size of the precipitated particles before service:
Figure BDA0002677430600000031
wherein, C1，C2And C3Is a constant.
The arithmetic model for the temperature-time-precipitated particle size was obtained as:
Figure BDA0002677430600000032
Figure BDA0002677430600000033
wherein T is the service specific time and T is the evaluation of the service specific time TEstimation of service temperature, d0The size of the precipitated particle phase is the size of the precipitated particle phase of the heat-resistant alloy material workpiece in the state before service, and d is the size of the precipitated particle phase of the heat-resistant alloy material workpiece after the heat-resistant alloy material workpiece is in service for a specific time t; c1，C2，C3Is a constant.
Preferably, the step 1) specifically comprises the following steps:
firstly, the size d of the precipitated particle phase of the heat-resistant alloy material workpiece in the state before service0Measuring, and setting different temperatures T in the service temperature intervalnAnd different time lengths tnAnd at the temperature TnAnd a time duration tnPrecipitated particle phase size dn(ii) a Performing at least two tests at different temperatures to obtain two groups of test group data;
② drawing according to the test data
Figure BDA0002677430600000041
And
Figure BDA0002677430600000042
a relationship diagram of (1), wherein tnDuration of the thermal exposure test to setnFor set Heat Exposure test temperature, dnAt this temperature TnAnd a time duration tnThe size of the precipitated particle phase; d0The size of the precipitated particle phase is the size of the precipitated particle phase of the heat-resistant alloy material workpiece in the pre-service state; c2And C3As a constant, solving for C by optimal straight line fitting2And C3D in the relation diagram3-d0 3And
Figure BDA0002677430600000043
the slope of the best fit line is C1。
Preferably, the heat-resistant alloy material workpiece in the step 1) is any one of a precipitation strengthening type high-temperature alloy or a precipitation strengthening type heat-resistant steel. The high-temperature alloy can adopt nickel-based alloy and the like.
Preferably, the service temperature interval in the step 1) is 873-.
Preferably, said C2And C3The value ranges are respectively as follows: c is more than or equal to 0.962≤0.99，0＜C3≤1.00。
Preferably, when the accuracy requirement is not high, C3Is convenient to use
Figure BDA0002677430600000044
Wherein T is the service specific time, T is the estimated service temperature of the service specific time T, d0The size of the precipitated particle phase is the size of the precipitated particle phase of the heat-resistant alloy material workpiece in the pre-service state; d is the size of the precipitated particle phase of the heat-resistant alloy material workpiece after the workpiece is in service for a specific time t; c1，C2Is a constant.
Preferably, the error characteristic of the estimated service temperature and the actual temperature is less than or equal to 15K.
The invention has the advantages that the temperature is established between the same service temperature of the precipitated particle phase in the heat-resistant alloy material tissue
Figure BDA0002677430600000045
Compared with the traditional method only capable of evaluating the service temperature interval, the method for evaluating the actual service temperature of the temperature-bearing component is more accurate and reliable, and can optimize the precision of evaluating the actual service temperature to be within 15K; the evaluation temperature range is relatively wide and is 873K-1273K; the application time range is long and is 0-50000 h; the material has wide application range and reliable evaluation result, and is suitable for engineering application.
Drawings
FIG. 1 is d in the heat exposure test of example 13-d0 3And t/C2 TFitting a relational graph;
FIG. 2 is d in the heat exposure test of example 23-d0 3And
Figure BDA0002677430600000051
and fitting the relational graph.
Detailed Description
The present invention will be further described with reference to the following description and examples, which include but are not limited to the following examples.
Example 1:
the service temperature field evaluation is carried out on the size of the gamma' phase in the directional solidification high-temperature alloy by adopting a thermal exposure test.
Firstly, the gamma' phase size d of the directionally solidified high-temperature alloy in the pre-service state is measured0Measuring the gamma' phase size d of the three phases after the three temperatures of 1073K/1123K/1173K are respectively exposed at four time points of 1000h/3000h/5000h/10000h, and taking C3When 1.00, take C2There is a best fit at 0.970, with a correlation coefficient of 0.995, where d3-d0 3And t/C2 TAs shown in Table 1, d3-d0 3And t/C2 TThe relationship is shown in FIG. 1. From d3-d0 3＝C1·t/(C2 T) Calculating C from the slope of the linear relation1Has a value of 2.380X 10-11Obtaining an arithmetic model of temperature-time-precipitated particle size as
Figure BDA0002677430600000052
Finally, measuring the gamma' phase dimension d of the workpiece to be predicted after the workpiece is in service for a specific time t, and measuring d and d0Substitution of value of t
Figure BDA0002677430600000053
And (5) solving an evaluation service temperature value. In this embodiment 1, it is known that the service temperature values are evaluated by using the method of the present invention at 1223K thermal exposure service time of 1000h, 3000h, 5000h and 10000h, and the evaluated service temperature is compared with the actual temperature, and the evaluation error is less than 15K, as shown in table 2.
TABLE 1 variation of gamma prime phase size at different heat exposure temperatures and different times for a directionally solidified superalloy of EXAMPLE 1
Serial number temperature/K Service time/hour d3-d0 3 t/C2 T
1 1073 0 0 0
2 1073 1000 35433342 7.16708E+17
3 1073 3000 79579143 2.15012E+18
4 1073 5000 99382383 3.58354E+18
5 1073 10000 198778652 7.16708E+18
6 1123 0 0 0
7 1123 1000 5685479 1.56289E+17
8 1123 3000 11674854 4.68868E+17
9 1123 5000 14655095 7.81446E+17
10 1123 10000 35838511 1.56289E+18
11 1173 0 0 0
12 1173 1000 62227503 3.28667E+18
13 1173 3000 214101610 9.86E+18
14 1173 5000 381449383 1.64333E+19
15 1173 10000 785181231 3.28667E+19
Table 2 prediction results and deviations of actual service temperature of directionally solidified superalloy in example 1
Figure BDA0002677430600000061
Example 2
Thermal exposure testing was used to make temperature field predictions for the primary gamma prime phase size in a cast superalloy.
First, the high temperature alloy of the casting is measuredPrimary gamma' phase size d in pre-service state of gold0Then, the gamma 'phase size d of each state after heat exposure at 973K/1073K/1123K is measured, and when C is reached, the gamma' phase size d is measured3＝0.03，C20.9858, with a best fit and a correlation coefficient of 0.9971, where
Figure BDA0002677430600000071
As shown in Table 3, d3-d0 3And
Figure BDA0002677430600000072
the relationship is shown in FIG. 2. By
Figure BDA0002677430600000073
Calculating C from the slope of the linear relation1Has a value of 3.586X 10-3An arithmetic model of temperature-time-precipitated particle size is obtained as
Figure BDA0002677430600000074
Finally, measuring the gamma' phase dimension d of the workpiece to be evaluated after the workpiece is in service for a specific time, and measuring d and d0Substitution of value of t
Figure BDA0002677430600000075
In this example 2, the temperature of a cast superalloy is known to be exposed to 1073K heat for 5000h, 8000h, 22884h and 40404h, and the temperature is evaluated by using the method of the present invention, and the evaluation service temperature is compared with the actual temperature, and the evaluation error is less than 15K, as shown in table 4.
TABLE 3. gamma.' phase size change at different heat exposure temperatures and times for one of the cast superalloys in example 2
Figure BDA0002677430600000076
TABLE 4 prediction of actual service temperature and deviation of cast superalloy in EXAMPLE 2
Figure BDA0002677430600000077
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. The invention extends to any novel feature or any novel combination of features disclosed in this specification and any novel method or process steps or any novel combination of features disclosed.

Claims (7)

1. A method for evaluating the actual service temperature of a workpiece through the size of a precipitated particle phase is characterized by comprising the following steps:
1) according to the size d of the precipitated particle phase of the heat-resistant alloy material workpiece in the pre-service state0And setting different temperatures T in the service temperature intervalnOf different durations tnSize d of precipitated particle phase under thermal exposure testnThen establishing an arithmetic model of temperature-time-precipitated particle size; wherein n represents the number of trials;
2) measuring the size d of the precipitated particle phase in the workpiece after the workpiece is in service for a specific time T, substituting the measured size d into the arithmetic model in the step 1), and calculating to obtain the estimated service temperature T of the heat-resistant alloy material workpiece in service for the specific time T;
wherein the arithmetic model of temperature-time-precipitated particle size is:
Figure FDA0003347505040000011
Figure FDA0003347505040000012
wherein T is the service specific time, T is the estimated service temperature of the service specific time T, d0The size of the precipitated particle phase is the size of the precipitated particle phase of the heat-resistant alloy material workpiece in the pre-service state; d is a phase rule of precipitated particles of the heat-resistant alloy material workpiece after the workpiece is in service for a specific time tCun, cun; c1，C2，C3Is a constant.
2. The method for evaluating the real service temperature of a workpiece through the size of the precipitated particle phase according to claim 1, wherein the step 1) comprises the following steps:
firstly, the size d of the precipitated particle phase of the heat-resistant alloy material workpiece in the state before service0Measuring, and setting different temperatures T in the service temperature intervalnAnd different time lengths tnAnd at the temperature TnAnd a time duration tnPrecipitated particle phase size dn(ii) a Performing at least two tests at different temperatures to obtain two groups of test group data;
② drawing according to the test data
Figure FDA0003347505040000013
And
Figure FDA0003347505040000014
a relationship diagram of (1), wherein tnDuration of the thermal exposure test to setnFor set Heat Exposure test temperature, dnAt this temperature TnAnd a time duration tnThe size of the precipitated particle phase; d0The size of the precipitated particle phase is the size of the precipitated particle phase of the heat-resistant alloy material workpiece in the pre-service state; c2And C3As a constant, solving for C by optimal straight line fitting2And C3The slope of the best fit straight line in the relational graph is C1。
3. The method for evaluating the actual service temperature of the workpiece through the size of the precipitated particle phase according to claim 1 or 2, wherein the workpiece made of the heat-resistant alloy material in the step 1) is any one of precipitation-strengthened high-temperature alloy or precipitation-strengthened heat-resistant steel.
4. The method for evaluating the actual service temperature of the workpiece according to the particle phase size of the precipitate in claim 1 or 2, wherein the service temperature interval in step 1) is 873-1273K, and the applicable time range is 0-50000 h.
5. The method of claim 2, wherein C is the temperature of the workpiece in service by the size of the precipitated particle phase2And C3The value ranges are respectively as follows: c is more than or equal to 0.962≤0.99，0＜C3≤1.00。
6. The method of claim 5, wherein C is the temperature of the workpiece in service3Taking out the mixture of 1.00, adding the mixture,
Figure FDA0003347505040000021
wherein T is the service specific time, T is the estimated service temperature of the service specific time T, d0The size of the precipitated particle phase is the size of the precipitated particle phase of the heat-resistant alloy material workpiece in the pre-service state; d is the size of the precipitated particle phase of the heat-resistant alloy material workpiece after the workpiece is in service for a specific time t; c1，C2Is a constant.
7. The method for evaluating the actual service temperature of the workpiece according to the precipitated particle phase size in claim 6, wherein the error characteristic of the evaluated service temperature and the actual temperature is less than or equal to 15K.
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