Nickel-based superalloy yield strength prediction model, modeling method, device and system

Abstract

The embodiment of the invention provides a nickel-based superalloy yield strength prediction model, a modeling method, a device and a system. The modeling method comprises the following steps: step 1, simplifying a gamma'precipitation strengthening model formula, and establishing a probability-related simplified gamma 'precipitation strengthening model; 2, according to the grain boundary strengthening contribution, the solid solution strengthening contribution and the simplified gamma'precipitation strengthening model, a yield strength model used in component design of the nickel-based high-temperature alloy is established; 3, temperature variables and parameters are introduced, and a novel yield strength model suitable for the full temperature range is established according to the yield strength model; 4, obtaining the coefficient of the novel yield strength model according to the yield strength data in the nickel-based superalloy component design; and 5, obtaining a yield strength model formula of the nickel-based superalloy according to the coefficient and the novel yield strength model. The method is suitable for predicting the yield strength of the nickel-based superalloy in a full temperature range.

Description

Technical Field

[0001] The present invention relates to the field of mechanical technology of alloy composition design, and in particular to a nickel-based high-temperature alloy yield strength prediction model, a nickel-based high-temperature alloy yield strength modeling method, a nickel-based high-temperature alloy yield strength modeling device and a nickel-based high-temperature alloy yield strength modeling system. Background Art

[0002] Nickel-based superalloys are widely used in hot-end components such as gas turbines and aircraft engines because they can maintain good strength, creep resistance, fatigue resistance, oxidation resistance and corrosion resistance in high temperature environments. The unique performance comes from the unique microstructure, which includes multi-modal size distribution of L12 precipitates γ' and face-centered cubic (FCC) matrix γ. The excellent yield strength of nickel-based superalloys mainly comes from grain boundary strengthening, solid solution strengthening and γ' precipitation strengthening. Many researchers have studied these three strengthening methods and established relatively good models.

[0003] Due to the extremely complex use environment of the engine, the geometric morphology of the parts made of nickel-based superalloys is also more complex. Although investment casting, as a traditional processing method, can be used for precision casting, the processing process is relatively complicated, the processing efficiency is relatively low, and there are certain limitations for the production of complex-shaped parts. Laser powder bed melting technology, as one of the additive manufacturing technologies, can process complex geometric shapes, can achieve fewer processing processes, has higher processing freedom and more efficient material utilization. However, considering the high temperature gradient, high cooling rate and cyclic heating-cooling process characteristics of laser powder bed melting technology, the microstructure of nickel-based superalloys formed by additive manufacturing will be different from that of nickel-based superalloys formed by traditional processes. Therefore, for the design of nickel-based superalloy components in additive manufacturing, it is necessary to model the yield strength of nickel-based superalloys for additive manufacturing forming processes. At the same time, the traditional nickel-based superalloy yield strength model does not consider the introduction of temperature variables to predict the yield strength of nickel-based superalloys at different temperatures. However, nickel-based superalloys are used in different usage scenarios, and the reference temperature of nickel-based superalloy components designed for different usage environments is often different.

[0004] Therefore, there is an urgent need for a new yield strength model that can be applied to the composition design of nickel-based high-temperature alloys over the entire temperature range to improve the efficiency of the composition design of nickel-based high-temperature alloys. Summary of the invention

[0005] Therefore, in order to overcome at least some of the defects and shortcomings existing in the prior art, embodiments of the present invention provide a nickel-based high-temperature alloy yield strength prediction model, a nickel-based high-temperature alloy yield strength modeling method, a nickel-based high-temperature alloy yield strength modeling device and a nickel-based high-temperature alloy yield strength modeling system.

[0006] Specifically, on the one hand, an embodiment of the present invention provides a nickel-based high-temperature alloy yield strength prediction model, characterized in that it includes: the calculation expression of the prediction model is:

[0007]

[0008] Where T is temperature, f γ is the volume fraction of γ phase, β i is the solid solution strengthening coefficient of the ith atom, x i is the concentration of the ith atom, f ′ Yes γ′ Phase volume fraction.

[0010] On the other hand, an embodiment of the present invention provides a method for modeling the yield strength of a nickel-based high-temperature alloy, comprising: step 1: simplifying the γ' precipitation strengthening model formula to establish a probability-related simplified γ' precipitation strengthening model; step 2: establishing a yield strength model for the composition design of a nickel-based high-temperature alloy based on grain boundary strengthening contribution, solid solution strengthening contribution and the simplified γ' precipitation strengthening model; step 3: introducing temperature variables and parameters, and establishing a new yield strength model suitable for the entire temperature range based on the yield strength model; step 4: obtaining coefficients of the new yield strength model based on the yield strength data in the composition design of the nickel-based high-temperature alloy; step 5: obtaining the yield strength model formula of the nickel-based high-temperature alloy based on the coefficients and the new yield strength model.

[0011] In a specific embodiment of the present invention, the step 4 specifically includes: step 4.1: obtaining the yield strength data and alloy composition data of nickel-based high-temperature alloys with different compositions at different temperatures; step 4.2: calculating the volume fraction of the γ matrix phase, the concentration of each solute atom in the γ matrix phase and the volume fraction of the γ' strengthening phase in the nickel-based high-temperature alloy at different temperatures based on the alloy composition data; step 4.3: obtaining the coefficient based on the temperature, the volume fraction of the γ matrix phase, the concentration of each solute atom in the γ matrix phase, the volume fraction of the γ' strengthening phase and the yield strength data.

[0012] In a specific embodiment of the present invention, the yield strength model formula of the nickel-based high-temperature alloy is:

[0013]

[0014] Where T is temperature, f γ is the volume fraction of γ phase, β i is the solid solution strengthening coefficient of the ith atom, x i is the concentration of the ith atom, f γ′ is the volume fraction of γ' phase.

[0016] In a specific embodiment of the present invention, step 1 specifically includes: introducing dislocations through the probability and average strength of the γ' precipitation phase through weak pair coupling mechanism, strong pair coupling mechanism and Orowan mechanism, simplifying the γ' precipitation strengthening model formula to obtain a simplified γ' precipitation strengthening model.

[0017] In a specific embodiment of the present invention, the simplified γ' precipitation strengthening model is:

[0018]

[0019] Where M is the Taylor factor, G is the shear model, b is the Burgers vector length, P w , P s and P o are the probabilities of dislocation passing through the γ' precipitate phase by weak pair coupling mechanism, strong pair coupling mechanism and Orowan mechanism, respectively, and r w 、r s and r o are the radius of the precipitate phase through which the dislocation passes by the weak pair coupling mechanism, the strong pair coupling mechanism and the Orowan mechanism, respectively, APB is the reverse boundary energy, f γ′ is the volume fraction of γ' phase.

[0020] In a specific embodiment of the present invention, the yield strength model formula in step 2 is:

[0021]

[0022] Among them, σ0 is the increase in basic yield strength, σ GB The increase in yield strength due to grain boundary strengthening, σ ss The increase in yield strength due to solid solution strengthening, σ γ′ To simplify the γ' precipitation strengthening model, k is the Hall-Page constant, d is the average grain size, and f is γ is the volume fraction of γ phase, β i is the solid solution strengthening coefficient of the ith atom, x i is the concentration of the ith atom, M is the Taylor factor, G is the shear model, b is the Burgers vector length, r w 、r s and r oare the radius of the precipitate phase through which the dislocation passes by the weak pair coupling mechanism, the strong pair coupling mechanism and the Orowan mechanism, respectively, APB is the reverse boundary energy, f γ′ is the volume fraction of γ' phase.

[0023] In a specific embodiment of the present invention, the new yield strength model applicable to the full temperature range in step 3 is:

[0024]

[0025] Among them, a, o, b, p, c, q, k, g, j and h are the coefficients to be fitted, T is the temperature, f γ is the volume fraction of γ phase, β i is the solid solution strengthening coefficient of the ith atom, x i is the concentration of the ith atom, f γ′ is the volume fraction of γ' phase.

[0026] On the other hand, an embodiment of the present invention also provides a nickel-based high-temperature alloy yield strength modeling device, including: a data acquisition module, used to obtain yield strength data and alloy composition data of nickel-based high-temperature alloys with different compositions at different temperatures; a thermodynamic calculation module, used to calculate the volume fraction of the γ matrix phase, the concentration of each solute atom in the γ matrix phase and the volume fraction of the γ' strengthening phase in the nickel-based high-temperature alloy at different temperatures according to the alloy composition data; a model optimization module, used to simplify the γ' precipitation strengthening model formula to obtain a probability-related simplified γ' precipitation strengthening model, and establish a yield strength model for the composition design of the nickel-based high-temperature alloy according to the grain boundary strengthening contribution, the solid solution strengthening contribution and the simplified γ' precipitation strengthening model, introduce temperature variables and parameters, establish a new yield strength model applicable to the full temperature range according to the yield strength model formula, and obtain the yield strength model formula of the nickel-based high-temperature alloy.

[0027] On the other hand, an embodiment of the present invention further provides a nickel-based high-temperature alloy yield strength modeling system, comprising: a processor and a memory connected to the processor, wherein the memory stores a computer program, and when the processor executes the computer program, the nickel-based high-temperature alloy yield strength modeling method as described above is executed.

[0028] From the above, it can be seen that the nickel-based high-temperature alloy yield strength modeling method provided in an embodiment of the present invention establishes a yield strength model in the composition design of the nickel-based high-temperature alloy according to the grain boundary strengthening contribution, the solid solution strengthening contribution and the simplified γ' precipitation strengthening model by simplifying the γ' precipitation strengthening model, introduces temperature variables and parameters, establishes a new yield strength model applicable to the entire temperature range, and obtains the correlation coefficient based on the yield strength data, thereby establishing a yield strength model formula for the nickel-based high-temperature alloy in the entire temperature range, which is applicable to the prediction of the yield strength of the nickel-based high-temperature alloy in the entire temperature range, so as to improve the efficiency of the nickel-based high-temperature alloy composition design. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0030] Figure 1 A schematic flow chart of a method for modeling the yield strength of a nickel-based high-temperature alloy provided in accordance with the first embodiment of the present invention.

[0031] Figure 2 Another schematic flow chart of the method for modeling the yield strength of nickel-based high-temperature alloys provided in the first embodiment of the present invention.

[0032] Figure 3 for Figure 1 Schematic diagram of the process of step 4 in FIG.

[0033] Figure 4 A model for grain boundary strengthening, solid solution strengthening and γ' precipitation strengthening mechanisms.

[0034] Figure 5 The yield strength modeling method of the nickel-based high-temperature alloy provided in an embodiment of the present invention has a prediction effect on the yield strength.

[0035] Figure 6 A schematic structural diagram of a nickel-based high-temperature alloy yield strength modeling device provided in accordance with the second embodiment of the present invention.

[0036] Figure 7 A schematic structural diagram of a nickel-based high-temperature alloy yield strength modeling system provided in the third embodiment of the present invention.

[0037] Figure 8 A schematic structural diagram of a storage medium provided in a fourth embodiment of the present invention. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments described in the present invention, all other embodiments obtained by ordinary technicians in this field without creative work belong to the protection scope of the present invention.

[0039] In the embodiments of the present invention, the descriptions of "first", "second", etc. are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" or "second" may explicitly or implicitly include at least one of the features.

[0040] [First embodiment]

[0041] The first embodiment of the present invention provides a nickel-based high-temperature alloy yield strength prediction model, and the calculation expression of the prediction model is:

[0042]

[0043] Where T is temperature, f γ is the volume fraction of γ phase, β i is the solid solution strengthening coefficient of the ith atom, x i is the concentration of the ith atom, f γ′ is the volume fraction of γ' phase.

[0045] See also Figure 1 A first embodiment of the present invention provides a nickel-based high-temperature alloy yield strength modeling method, which may specifically include the following steps:

[0046] S10, step 1: simplify the γ' precipitation strengthening model formula and establish a probability-related simplified γ' precipitation strengthening model;

[0047] S20, step 2: establishing a yield strength model for composition design of nickel-based high-temperature alloys according to the grain boundary strengthening contribution, the solid solution strengthening contribution and the simplified γ' precipitation strengthening model;

[0048] S30, step 3: introducing temperature variables and parameters, and establishing a new yield strength model applicable to the full temperature range according to the yield strength model;

[0049] S40, step 4: obtaining coefficients of the novel yield strength model according to yield strength data in the nickel-based high-temperature alloy composition design;

[0050] S50, step 5: obtaining a yield strength model formula of the nickel-based high-temperature alloy according to the coefficient and the new yield strength model.

[0051] Specifically, the yield strength model formula of the nickel-based high-temperature alloy described in this embodiment is:

[0052]

[0053] Where T is temperature, f γ is the volume fraction of γ phase, β i is the solid solution strengthening coefficient of the ith atom, x i is the concentration of the ith atom, f γ′ is the volume fraction of γ' phase.

[0055] Step 1: Simplify the formula of the γ' precipitation strengthening model and establish a probability-related simplified γ' precipitation strengthening model. Specifically, for example, the probability and average strength of dislocations passing through the γ' precipitation phase in the weak pair coupling mechanism, strong pair coupling mechanism and Orowan mechanism are introduced to simplify the formula of the γ' precipitation strengthening model to obtain a simplified γ' precipitation strengthening model.

[0056] Specifically, the original γ' precipitation strengthening model formula is modified and a probability-dependent precipitation strengthening mechanism is proposed to simplify the model. Figure 2 and Figure 3 As shown in the figure, the interaction mechanism between dislocation and precipitate depends on the radius of the common circular plane between the dislocation slip plane and the γ' precipitate. s The dislocation may pass through the precipitate in the form of weak pair coupling mechanism, strong pair coupling mechanism and Orowan mechanism. The Orowan mechanism is a form of precipitation strengthening in metal alloys. When the moving dislocation encounters an unshearable precipitate phase, its movement is blocked. By increasing the applied stress, the dislocation can bypass or shear the precipitate phase, thereby continuing to slide, resulting in Orowan strengthening behavior. In this regard, the present invention introduces P w , P s and (1-P w -P s ) represent the probability of dislocation passing through the γ' precipitate phase by weak pair coupling mechanism, strong pair coupling mechanism and Orowan mechanism respectively. and They represent the average strength of the weak pair coupling mechanism, strong pair coupling mechanism and Orowan mechanism respectively. The formulas are as follows:

[0057]

[0058] Among them, P w, P s and P o are the probabilities of dislocations passing through the γ' strengthened phase via weak pair coupling mechanism, strong pair coupling mechanism and Orowan mechanism, respectively. and are the average intensities provided by the weak pair coupling mechanism, the strong pair coupling mechanism, and the Orowan mechanism. and The simplified γ' precipitation strengthening model can be obtained as follows:

[0059]

[0060] Where M is the Taylor factor, G is the shear model, b is the Burgers vector length, P w , P s and P o are the probabilities of dislocation passing through the γ' precipitate phase by weak pair coupling mechanism, strong pair coupling mechanism and Orowan mechanism, respectively, and r w 、r s and r o are the radius of the precipitate phase through which the dislocation passes by the weak pair coupling mechanism, the strong pair coupling mechanism and the Orowan mechanism, respectively, APB is the reverse boundary energy, f γ′ is the volume fraction of γ' phase.

[0061] Step 2: Based on the grain boundary strengthening contribution, the solid solution strengthening contribution and the simplified γ' precipitation strengthening model, a yield strength model formula for the composition design of nickel-based high-temperature alloys is established. Specifically, the grain boundary strengthening and solid solution strengthening formulas are first listed, as follows:

[0062]

[0063] where k is the Hall-Page constant, d is the average grain size, and f γ is the volume fraction of γ phase, β i is the solid solution strengthening coefficient of the ith atom, x i is the concentration of the ith atom.

[0064] The grain boundary strengthening, solid solution strengthening and γ' precipitation strengthening models are combined, that is, formulas (2), (3) and (4) are combined to establish the yield strength model formula for the composition design of nickel-based high-temperature alloys. The specific formula is:

[0065]

[0066] Among them, σ0 is the increase in basic yield strength, σ GB The increase in yield strength due to grain boundary strengthening, σ ss The increase in yield strength due to solid solution strengthening, σ γ′To simplify the γ' precipitation strengthening model, k is the Hall-Page constant, d is the average grain size, and f is γ is the volume fraction of γ phase, β i is the solid solution strengthening coefficient of the ith atom, x i is the concentration of the ith atom, M is the Taylor factor, G is the shear model, b is the Burgers vector length, r w 、r s and r o are the radius of the precipitate phase through which the dislocation passes by the weak pair coupling mechanism, the strong pair coupling mechanism and the Orowan mechanism, respectively, APB is the reverse boundary energy, f γ′ is the volume fraction of γ' phase.

[0067] In this embodiment, the parameters that are insensitive to the composition can be replaced by constants, and then formula (5) can be expressed as follows:

[0068]

[0069] Where a, b and c are the coefficients to be fitted.

[0070] Further, step 3: introduce temperature variables and parameters, and establish a new yield strength model applicable to the full temperature range according to the yield strength model formula, so as to expand the applicable temperature range of the model formula. The new yield strength model applicable to the full temperature range is:

[0071]

[0072] Among them, a, o, b, p, c, q, k, g, j and h are the coefficients to be fitted, T is the temperature, f γ is the volume fraction of γ phase, β i is the solid solution strengthening coefficient of the ith atom, x i is the concentration of the ith atom, f γ′ is the volume fraction of γ' phase.

[0074] See also Figure 3 Step 4: Obtaining the coefficients of the new yield strength model according to the yield strength data in the nickel-based high-temperature alloy composition design, specifically comprising the following steps:

[0075] S41, step 4.1: obtaining yield strength data and alloy composition data of nickel-based high-temperature alloys with different compositions at different temperatures;

[0076] S42, step 4.2: calculating the volume fraction of the γ matrix phase, the concentration of each solute atom in the γ matrix phase and the volume fraction of the γ' strengthening phase in the nickel-based high-temperature alloy at different temperatures according to the alloy composition data;

[0077] S43, step 4.3: obtaining the coefficient according to the temperature, the volume fraction of the γ matrix phase, the concentration of each solute atom in the γ matrix phase, the volume fraction of the γ' strengthening phase and the yield strength data.

[0078] The coefficients are fitted by applying the above formula (7) to the design of the composition of the nickel-based high-temperature alloy as an example. The nickel-based high-temperature alloy in this embodiment can be, for example, an additively manufactured nickel-based high-temperature alloy. Of course, this embodiment is not limited to this. Specifically, the yield strength data of the nickel-based high-temperature alloys with different compositions at different temperatures are obtained, and the alloy composition data, temperature and yield strength data are recorded in detail. For example, the volume fraction of the γ matrix phase, the concentration of each solute atom in the γ matrix phase and the volume fraction of the γ' strengthening phase at the corresponding temperature can be obtained according to the alloy composition data at different temperatures. For example, the corresponding thermodynamic database and alloy composition data can be imported in succession through the high-throughput module in the thermodynamic software, and then the volume fraction of each phase and the concentration of each solute atom in each phase at different temperatures are calculated. The Result Analysis module in the thermodynamic software is used to batch process the calculation results to obtain the volume fraction of the γ matrix phase, the concentration of each solute atom in the γ matrix phase and the volume fraction of the γ' strengthening phase at the corresponding temperature. According to the above-obtained temperature, the volume fraction of the γ matrix phase, the concentration of each solute atom in the γ matrix phase and the volume fraction of the γ' strengthening phase and the yield strength data, the coefficients are fitted by combining the global optimization algorithm and the local optimization algorithm. Specifically, for example, each optimization can firstly perform a differential evolution algorithm, and then further optimize with the L-BFGS-B algorithm, and select the best result in multiple runs. In this way, better results can be provided. The yield strength model formula of the nickel-based high-temperature alloy finally obtained is:

[0079]

[0080] Where T is temperature, f γ is the volume fraction of γ phase, β i is the solid solution strengthening coefficient of the ith atom, x i is the concentration of the ith atom, f γ′ is the volume fraction of γ' phase.

[0082] See also Figure 4 , Figure 4 The following is a comparison chart of the predicted alloy yield strength and the actual alloy yield strength. Figure 4 It is not difficult to see that the nickel-based superalloy yield strength modeling method provided in this embodiment can better predict the yield strength of the nickel-based superalloy at different temperatures. In summary, the present invention can predict the yield strength of the nickel-based superalloy at room temperature to 1300K according to the alloy composition, providing favorable support for the composition design of the nickel-based superalloy in additive manufacturing.

[0083] [Second embodiment]

[0084] See also Figure 6 The second embodiment of the present invention provides a nickel-based high-temperature alloy yield strength modeling device 10, which may specifically include: a data acquisition module 100, a thermodynamic module 200 and a model optimization module 300.

[0085] The data acquisition module 100 is used to obtain the yield strength data and alloy composition data of nickel-based high-temperature alloys with different compositions at different temperatures;

[0086] Thermodynamic calculation module 200, used for calculating the volume fraction of the γ matrix phase, the concentration of each solute atom in the γ matrix phase and the volume fraction of the γ' strengthening phase in the nickel-based high-temperature alloy at different temperatures according to the alloy composition data;

[0087] The model optimization module 300 is used to simplify the γ' precipitation strengthening model formula to obtain a probability-related simplified γ' precipitation strengthening model, establish a yield strength model for the composition design of the nickel-based high-temperature alloy based on the grain boundary strengthening contribution, the solid solution strengthening contribution and the simplified γ' precipitation strengthening model, introduce temperature variables and parameters, establish a new yield strength model applicable to the entire temperature range based on the yield strength model formula, and obtain the yield strength model formula of the nickel-based high-temperature alloy.

[0088] The specific working process and technical effects of the various modules in the nickel-based high-temperature alloy yield strength modeling device 10 in this embodiment refer to the description of the first embodiment mentioned above.

[0089] [Third embodiment]

[0090] See also Figure 7 The third embodiment of the present invention provides a nickel-based high-temperature alloy yield strength modeling system 20. The nickel-based high-temperature alloy yield strength modeling system 20 includes a processor 400 and a memory 500 connected to the processor 400. The memory 500 may be, for example, a non-volatile storage cavity, and a computer program 510 is stored in the memory 500. The processor 400 may be, for example, an embedded processor. When the processor 400 executes the computer program 510, the nickel-based high-temperature alloy yield strength modeling method in the first embodiment is executed.

[0091] The specific working process and technical effects of the nickel-based high-temperature alloy yield strength modeling system 20 in this embodiment refer to the description of the first embodiment mentioned above.

[0092] [Fourth embodiment]

[0093] See also Figure 8 The fourth embodiment of the present invention provides a storage medium 30 storing a computer program 510.

[0094] The storage medium 30 is, for example, a non-volatile memory, such as: magnetic media (such as hard disks, floppy disks, and tapes), optical media (such as CDROM disks and DVDs), magneto-optical media (such as optical disks), and hardware devices (such as read-only memory (ROM), random access memory (RAM), flash memory, etc.) specially constructed to store and execute the computer program 510. The storage medium 30 stores the computer program 510, and the computer program 510 can be executed by the processor of the device where the storage medium 30 is located. The storage medium 30 can be executed by one or more processors or processing devices to execute the computer program 510 to implement the nickel-based high-temperature alloy yield strength modeling method in the aforementioned first embodiment.

[0095] In addition, it can be understood that the aforementioned embodiments are only exemplary descriptions of the present invention. Under the premise that the technical features do not conflict, the structures do not contradict, and the purpose of the present invention is not violated, the technical solutions of the various embodiments can be arbitrarily combined and used in combination.

[0096] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A nickel-based high-temperature alloy yield strength prediction model, characterized in that: include: The calculation expression of the prediction model is: Where T is temperature, f γ is the volume fraction of γ phase, β i is the solid solution strengthening coefficient of the ith atom, x i is the concentration of the ith atom, f γ′ is the volume fraction of γ' phase.

2. A method for modeling the yield strength of a nickel-based high-temperature alloy, characterized in that: include: Step 1: Simplify the γ' precipitation strengthening model formula and establish a probability-related simplified γ' precipitation strengthening model; Step 2: Establishing a yield strength model for the composition design of nickel-based high-temperature alloys based on the grain boundary strengthening contribution, the solid solution strengthening contribution and the simplified γ' precipitation strengthening model; Step 3: Introducing temperature variables and parameters, and establishing a new yield strength model applicable to the full temperature range according to the yield strength model; Step 4: Obtaining coefficients of the new yield strength model according to yield strength data in the nickel-based high-temperature alloy composition design; Step 5: Obtain the yield strength model formula of the nickel-based high-temperature alloy according to the coefficient and the new yield strength model.

3. The nickel-based high-temperature alloy yield strength modeling method according to claim 2, characterized in that: The step 4 specifically includes: Step 4.1: Obtain yield strength data and alloy composition data of nickel-based high-temperature alloys with different compositions at different temperatures; Step 4.2: Calculate the volume fraction of the γ matrix phase, the concentration of each solute atom in the γ matrix phase and the volume fraction of the γ' strengthening phase in the nickel-based high-temperature alloy at different temperatures according to the alloy composition data; Step 4.3: Obtaining the coefficient according to the temperature, the volume fraction of the γ matrix phase, the concentration of each solute atom in the γ matrix phase, the volume fraction of the γ' strengthening phase and the yield strength data.

4. The nickel-based high-temperature alloy yield strength modeling method according to claim 2, characterized in that: The yield strength model formula of the nickel-based high-temperature alloy is: Where T is temperature, f γ is the volume fraction of γ phase, β i is the solid solution strengthening coefficient of the ith atom, x i is the concentration of the ith atom, f γ′ is the volume fraction of γ' phase.

5. The nickel-based high-temperature alloy yield strength modeling method according to claim 2, characterized in that: The step 1 specifically includes: The probability and average strength of dislocations passing through the γ' precipitation phase by weak pair coupling mechanism, strong pair coupling mechanism and Orowan mechanism are introduced to simplify the formula of γ' precipitation strengthening model and obtain a simplified γ' precipitation strengthening model.

6. The nickel-based high-temperature alloy yield strength modeling method according to claim 5, characterized in that: The simplified γ' precipitation strengthening model is: Where M is the Taylor factor, G is the shear model, b is the Burgers vector length, P w , P s and P o are the probabilities of dislocation passing through the γ' precipitate phase by weak pair coupling mechanism, strong pair coupling mechanism and Orowan mechanism, respectively, and r w 、r s and r o are the radius of the precipitate phase through which the dislocation passes by the weak pair coupling mechanism, the strong pair coupling mechanism and the Orowan mechanism, respectively, APB is the reverse boundary energy, f γ′ is the volume fraction of γ' phase.

7. The nickel-based high-temperature alloy yield strength modeling method according to claim 6, characterized in that: The yield strength model formula in step 2 is: Among them, σ0 is the increase in basic yield strength, σ GB The increase in yield strength due to grain boundary strengthening, σ ss The increase in yield strength due to solid solution strengthening, σ γ′ To simplify the γ' precipitation strengthening model, k is the Hall-Page constant, d is the average grain size, and f is γ is the volume fraction of γ phase, β i is the solid solution strengthening coefficient of the ith atom, x i is the concentration of the ith atom, M is the Taylor factor, G is the shear model, b is the Burgers vector length, r w 、r s and r o are the radius of the precipitate phase through which the dislocation passes by the weak pair coupling mechanism, the strong pair coupling mechanism and the Orowan mechanism, respectively, APB is the reverse boundary energy, f γ′ is the volume fraction of γ' phase.

8. The modeling method according to claim 7, characterized in that: The new yield strength model applicable to the full temperature range in step 3 is: Among them, a, o, b, p, c, q, k, g, j and h are the coefficients to be fitted, T is the temperature, f γ is the volume fraction of γ phase, β i is the solid solution strengthening coefficient of the ith atom, x i is the concentration of the ith atom, f γ′ is the volume fraction of γ' phase.

9. A nickel-based high-temperature alloy yield strength modeling device, characterized in that: include: A data acquisition module is used to obtain the yield strength data and alloy composition data of nickel-based high-temperature alloys with different compositions at different temperatures; A thermodynamic calculation module is used to calculate the volume fraction of the γ matrix phase, the concentration of each solute atom in the γ matrix phase and the volume fraction of the γ' strengthening phase in the nickel-based high-temperature alloy at different temperatures according to the alloy composition data; The model optimization module is used to simplify the γ' precipitation strengthening model formula to obtain a probability-related simplified γ' precipitation strengthening model, establish a yield strength model for the composition design of nickel-based high-temperature alloys based on grain boundary strengthening contribution, solid solution strengthening contribution and the simplified γ' precipitation strengthening model, introduce temperature variables and parameters, establish a new yield strength model applicable to the entire temperature range based on the yield strength model formula, and obtain the yield strength model formula of the nickel-based high-temperature alloy.

10. A nickel-based high-temperature alloy yield strength modeling system, characterized in that: include: A processor and a memory connected to the processor, wherein the memory stores a computer program, and when the processor executes the computer program, the nickel-based high-temperature alloy yield strength modeling method according to any one of claims 2 to 8 is executed.

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