Method for measuring surface heat transfer coefficient of GH4169 alloy in heating process before forging in laboratory

Abstract

The invention discloses a method for measuring the surface heat transfer coefficient of a GH4169 alloy in the heating process before forging in a laboratory, and relates to the technical field of high-temperature alloy hot working. The method comprises the steps that (1) a GH4169 alloy workpiece with the diameter being 55-65 mm and the length being 130-150 mm is prepared, four holes with different depths are drilled, and thermocouples are embedded; 2) heating in two modes of a stepped mode (heat preservation at 680-720 DEG C is more than or equal to 3 hours, heat preservation at 950 DEG C is more than or equal to 2 hours, and heat preservation at 1100 DEG C is more than or equal to 2 hours) and direct heating (4-6 hours of heating to 1100 DEG C and heat preservation for 1-2 hours), and synchronously acquiring temperature data; 3) inputting the data into finite element software, and reversely deriving a surface heat exchange coefficient through a reverse heat transfer module, 4) comparing the simulated and actually measured core temperature, and determining that the coefficient is valid if the error is less than or equal to + / -3%. The method realizes accurate determination of the coefficient, covers multiple working conditions such as stepped heating and direct heating, and can be popularized to other high-temperature alloys.

Description

Technical Field

[0001] This invention relates to the field of high-temperature alloy hot working technology, and in particular to a method for determining the surface heat transfer coefficient of GH4169 alloy during the pre-forging heating process in the laboratory. Background Technology

[0002] GH4169 alloy is a high-performance nickel-based superalloy with excellent fatigue resistance, radiation resistance, oxidation resistance, and corrosion resistance. It is widely used in the manufacture of critical load-bearing components such as turbine disks and compressor disks for aero-engines. This alloy has a narrow process window, and the microstructure and properties of the forgings are extremely sensitive to hot working parameters. The temperature uniformity during the pre-forging heating stage directly determines the uniformity of subsequent forging deformation, thus affecting the final fine-grained microstructure quality of the forging, which is crucial to the reliability of key aero-engine components.

[0003] In numerical simulations of hot working of GH4169 alloy, the surface heat transfer coefficient is a core parameter for constructing heat transfer boundary conditions, and its accuracy directly determines the reliability of the predicted temperature and microstructure fields. However, existing technologies for determining the surface heat transfer coefficient of GH4169 alloy during pre-forging heating largely rely on empirical values ​​under steady-state or quasi-steady-state assumptions. Since the pre-forging heating process of GH4169 alloy involves complex conditions such as rapid heating and multi-stage holding, the surface heat transfer coefficient dynamically changes with the workpiece surface temperature, furnace gas temperature, and furnace airflow velocity. Using fixed empirical values ​​cannot adapt to the transient heat transfer process, resulting in significant deviations between the simulated temperature field and the actual production temperature field, making it difficult to accurately guide the optimization of hot working processes.

[0004] Existing technologies primarily focus on heat transfer coefficient measurement methods for conventional materials such as steel and aluminum alloys during cooling or quenching processes, failing to adequately consider the high-temperature thermophysical properties and narrow process window requirements of GH4169 alloy. Furthermore, existing methods often employ a single heating method for data collection, lacking cross-validation under multiple operating conditions and failing to establish a closed-loop process of "temperature measurement-calculation-verification," thus limiting the reliability and applicability of the measurement results. Therefore, there is an urgent need for a method that can accurately and reliably determine the surface heat transfer coefficient of GH4169 alloy during pre-forging heating, addressing the shortcomings of existing technologies that rely on empirical values, have poor transient adaptability, and lack verifiable results. Summary of the Invention

[0005] The main purpose of this invention is to overcome the shortcomings of existing technologies, such as the reliance on empirical values ​​for determining the surface heat transfer coefficient of GH4169 alloy during the pre-forging heating process, poor adaptability to transient heat transfer, and lack of effective verification of results. This invention provides a laboratory method for determining the surface heat transfer coefficient of GH4169 alloy during the pre-forging heating process, achieving accurate determination of the surface heat transfer coefficient, providing high-precision boundary conditions for numerical simulation of GH4169 alloy hot working, and forming a standardized process that can be replicated and promoted.

[0006] To achieve the above objectives, this application provides the following technical solution: a method for determining the surface heat transfer coefficient of GH4169 alloy during the pre-forging heating process in a laboratory, comprising the following steps: (1) Workpiece preparation: such as Figure 3 As shown, a GH4169 alloy workpiece is processed using an electrical discharge wire cutting machine. The workpiece has a diameter of 60mm and a length of 140mm. Four test locations are selected on the workpiece, and holes of different depths are drilled at each test location. The drilling depths at the four test locations are: 1-2mm at the surface, 5mm near the surface, 15mm at half the center, and 30mm at the center. Thermocouples are embedded in each drilled hole, and all thermocouples are connected to the same temperature sensor. (2) Heating and Temperature Acquisition: Under a controlled laboratory environment, the workpiece is subjected to pre-forging heating treatment using two heating methods. The transient temperature change data at each test location is recorded synchronously using the thermometer (e.g., ...). Figure 4 (as shown) The two heating methods are as follows: a) Step heating method: First, heat the workpiece to 680-720℃ and hold for no less than 3 hours; then raise the temperature to 950℃ and hold for no less than 2 hours; finally, raise the temperature to 1100℃ and hold for no less than 2 hours. b) Direct heating method: The workpiece is heated from room temperature to 1100℃ over 4h, 5h or 6h, and held at that temperature for a preset time; (3) Calculation of surface heat transfer coefficient: Input the transient temperature change data collected in step (2) into the finite element software, and use the reverse heat transfer function module of the finite element software to deduce the surface heat transfer coefficient of the workpiece during the heating process. (4) Result verification: The surface heat transfer coefficient obtained in step (3) is used to simulate the pre-forging heating. The simulated core temperature of the workpiece is compared with the core temperature of the workpiece measured in the laboratory in step (2). If the difference between the two is within the preset error range, the surface heat transfer coefficient is determined to be an effective coefficient.

[0007] Furthermore, the finite element software mentioned in step (3) is Deform-3D, ABAQUS, or ANSYS; when the finite element software is ABAQUS or ANSYS, the reverse heat transfer calculation is realized by writing a user subroutine, which is constructed based on Fourier's law and boundary condition iterative algorithm.

[0008] Furthermore, the thermocouple mentioned in step (1) is a high-temperature resistant thermocouple, and the temperature measuring end of the thermocouple is tightly fitted to the bottom of the borehole; the diameter of the borehole is adapted to the outer diameter of the thermocouple, the inner wall of the borehole is polished, and after the thermocouple is embedded, it is fixed with a high-temperature resistant filling material to ensure the accuracy of temperature measurement.

[0009] Furthermore, the calculation logic of the reverse heat transfer function module in step (3) is as follows: taking the measured multi-depth transient temperature data as the target response, the surface heat transfer coefficient boundary conditions in the heat transfer process are identified by inversion; the optimization algorithm used for the reverse heat transfer calculation is a genetic algorithm, a particle swarm algorithm, or an iterative algorithm built into the finite element software.

[0010] Furthermore, the heating equipment for the controllable laboratory environment mentioned in step (2) is a programmable temperature control furnace with a temperature fluctuation range not exceeding ±5℃; the thermometer is a multi-channel data recorder with a sampling frequency of not less than 1Hz; and the preset heat preservation time for the direct heating method is 1-2h.

[0011] Furthermore, the preset error range in step (4) is ±3% to ensure the reliability of the surface heat transfer coefficient.

[0012] This invention also provides a method for determining the surface heat transfer coefficient of a high-temperature alloy during the pre-forging heating process in a laboratory setting. The high-temperature alloy is a nickel-based high-temperature alloy or a difficult-to-deform material. Any of the above-described method steps are used, and the heating process parameters in step (2) are adjusted according to the thermophysical properties of the high-temperature alloy. The nickel-based high-temperature alloy is a precipitation-hardening nickel-based high-temperature alloy other than GH4169 alloy, and the difficult-to-deform material is a titanium alloy or ultra-high-strength steel.

[0013] The high-temperature alloy is a nickel-based high-temperature alloy (including non-GH4169 precipitation-hardening type) or a difficult-to-deform material (titanium alloy, ultra-high-strength steel).

[0014] Compared with the prior art, the method of the present invention for determining the surface heat transfer coefficient of GH4169 alloy during the pre-forging heating process in the laboratory has at least the following beneficial effects: 1. Accurate and comprehensive temperature measurement: By designing four test points at different depths ("surface-near surface-1 / 2 center-center") on the GH4169 alloy workpiece, and using embedded thermocouples to synchronously collect transient temperature data, a three-dimensional capture of the entire temperature field of the workpiece is achieved. This avoids the shortcomings of non-contact temperature measurement, which is affected by environmental interference, or single-point temperature measurement, which cannot reflect the heat transfer gradient. This provides comprehensive and accurate data support for the subsequent back-calculation of the heat transfer coefficient.

[0015] 2. Comprehensive operating conditions: Two heating methods are adopted: stepped heating (simulating actual production processes) and direct heating (covering extreme operating conditions). The temperature change characteristics of "slow heating + multi-stage heat preservation" and "rapid heating" are captured respectively, ensuring that the measured surface heat transfer coefficient can be adapted to various heating scenarios in actual production, thus improving the practicality and versatility of the method.

[0016] 3. Reliable and efficient calculation: By using the reverse heat transfer function module of the finite element software and combining multi-depth measured temperature data, the surface heat transfer coefficient is derived in reverse, breaking through the limitation of existing technologies that rely on empirical values; at the same time, through the closed-loop verification logic of "calculation-simulation-measurement comparison", the accuracy of the surface heat transfer coefficient is ensured, with the error controlled within ±3%.

[0017] 4. Standardized and scalable process: This invention constructs a standardized process of "workpiece preparation - temperature measurement arrangement - heating and data acquisition - calculation and verification", which clarifies the key parameters of each step. It is not only applicable to the pre-forging heating process of GH4169 alloy, but can also be applied after adjusting the process parameters according to the thermophysical properties of different high-temperature alloys or difficult-to-deform materials. It provides a template that can be used for the determination of heat transfer coefficient of similar materials.

[0018] The following description, in conjunction with the accompanying drawings, further illustrates a method for determining the surface heat transfer coefficient of GH4169 alloy during pre-forging heating in a laboratory setting. Attached Figure Description

[0019] Figure 1 Flowchart of the reverse heat transfer calculation of this invention; Figure 2a This is one of the flowcharts of a method for determining the surface heat transfer coefficient of GH4169 alloy during pre-forging heating in the laboratory according to the present invention (workpiece preparation and temperature acquisition). Figure 2b This is the second flowchart of a method for determining the surface heat transfer coefficient of GH4169 alloy during pre-forging heating in the laboratory according to the present invention (coefficient calculation and result verification). Figure 3 This is a schematic diagram of the distribution of drilling points on the workpiece in an embodiment of the present invention; Figure 4 This is the pre-forging heating process curve of GH4169 in an embodiment of the present invention; Figure 5 This is a diagram of the Deform-3D finite element software interface for calculating the surface heat transfer coefficient in an embodiment of the present invention. Figure 6 This is a comparison chart of simulated and measured temperature values ​​for different heating methods in embodiments of the present invention; Figure 7 Photographs of actual temperature measuring devices in embodiments of the present invention.

[0020] The markings in the diagram are as follows: 1-workpiece, 2-surface test point (depth 1.5mm), 3-near-surface test point (depth 5mm), 4-1 / 2 center test point (depth 15mm), 5-center test point (depth 30mm), 6-thermocouple, 7-data logger, 8-programmable temperature controlled furnace. Detailed Implementation

[0021] This invention discloses a laboratory method for determining the surface heat transfer coefficient of GH4169 alloy during the pre-forging heating process, such as... Figure 1 The diagram shown is a flowchart of the reverse heat transfer calculation of this invention. Figure 2a This is one of the flowcharts of a method for determining the surface heat transfer coefficient of GH4169 alloy during pre-forging heating in the laboratory according to the present invention (workpiece preparation and temperature acquisition). Figure 2b This is the second flowchart of a method for determining the surface heat transfer coefficient of GH4169 alloy during pre-forging heating in the laboratory according to the present invention (coefficient calculation and result verification).

[0022] Example 1: Laboratory determination of the surface heat transfer coefficient of GH4169 alloy during pre-forging heating process.

[0023] This embodiment determines the surface heat transfer coefficient of GH4169 alloy during the pre-forging heating process according to the following steps: (1) Workpiece preparation: (e.g.) Figure 3 (As shown) Forged GH4169 alloy bars were selected (pretreatment process: solution treatment at 980℃ for 1 hour followed by water cooling + aging treatment at 720℃ for 8 hours followed by air cooling). They were machined into cylindrical workpieces with a diameter of 60mm and a length of 140mm using an EDM wire cutter, ensuring a smooth surface and precise dimensions. Four test locations were marked on the workpiece. Blind holes of different depths were drilled at each test location using a drilling machine. The drilling depths at the four test locations were: 1.5mm at the surface, 5mm near the surface, 15mm at half the center, and 30mm at the center. The hole diameter was matched to the outer diameter of the selected K-type high-temperature thermocouple (temperature range 0-1300℃, accuracy class I) (the hole diameter was 0.15mm larger than the thermocouple's outer diameter). The inner wall of the drilled hole was sanded to a roughness Ra≤1.6μm to remove burrs and oxide scale.

[0024] K-type high-temperature thermocouples were embedded into each drilled hole, ensuring that the temperature measuring end of the thermocouple was in close contact with the bottom of the drill hole. After embedding, ceramic-based adhesive (brand name XX-1200) with a temperature resistance upper limit of ≥1200℃ was used for fixation. After curing, a pull-out test was performed, and the bond strength was 5.2MPa. Finally, the signal output terminals of all thermocouples were connected to a multi-channel data logger (sampling frequency set to 2Hz) and powered on for debugging. The thermocouples were placed in standard constant temperature baths at 500℃, 800℃, and 1100℃, respectively. The deviations between the temperature readings and the standard values ​​of the constant temperature baths were 0.8℃, 0.6℃, and 0.9℃, respectively, all ≤±1℃, meeting the accuracy requirements.

[0025] (2) Heating and temperature acquisition: This implementation method employs two different heating methods to simulate the actual pre-forging heating scenario of GH4169 alloy and obtain comprehensive temperature change data.

[0026] The prepared workpiece is placed in a programmable temperature controlled furnace (temperature fluctuation range ±4℃) to ensure that the workpiece is in a uniform temperature zone within the furnace. Two heating methods are used for pre-forging heating, and the transient temperature change data at each test location is recorded synchronously using a multi-channel data logger (sampling interval 20 seconds) until the heating process is completed.

[0027] The specific parameters for the two heating methods are as follows: a) Stepped heating method (simulating actual production heating process) Place the workpiece with the temperature measuring device installed into the box-type resistance furnace, and set the heating parameters according to the GH4169 pre-forging heating process curve shown in Figure 3. The specific heating process is divided into three stages: First stage: Raise the furnace temperature to 680-720℃ and maintain this temperature for at least 3 hours to achieve low-temperature preheating of the workpiece and eliminate internal stress; The second stage: raise the furnace temperature to 950℃ at a heating rate of 5-10℃ / min, and maintain this temperature for at least 2 hours to complete the medium-temperature heat preservation of the workpiece and prepare for subsequent high-temperature heating. The third stage: Continue to raise the furnace temperature to 1100℃ at a heating rate of 5-10℃ / min, and maintain this temperature for at least 2 hours to simulate the high-temperature holding process before forging.

[0028] Throughout the stepped heating process, temperature change data at four test locations were collected and recorded in real time using a thermometer. The sampling interval was set to 10-30 seconds to ensure accurate capture of the dynamic temperature change over time. Reference was made to GB / T 30582-2014, "Heating Process Specification for High-Temperature Alloy Forgings".

[0029] b) Direct heating method (supplementary data on different heating rates) Remove the workpiece after the stepped heating experiment has been completed. After it has cooled to room temperature, recheck the connection status of the temperature measuring device. Once it is confirmed to be correct, put it back into the box-type resistance furnace.

[0030] Three different total heating times (4h, 5h, 6h) were set to raise the furnace temperature directly from room temperature to 1100℃ and hold it at 1100℃ for 1 hour. By adjusting the furnace power, the heating rate was controlled so that the workpiece could reach the target temperature within the set total heating time.

[0031] Similarly, with a sampling interval of 10-30 seconds, temperature change data at four test locations were collected and recorded using a thermometer under different heating times, forming multiple sets of comparative data to provide richer basis for subsequent heat transfer coefficient calculation.

[0032] After data collection, outliers were removed based on a standard deviation exceeding ±10℃.

[0033] The heating rate is calculated based on the core temperature of the workpiece. The actual rate deviates from the theoretical rate by ≤±10%. The actual rate is approximately 0.08℃ / s for h, approximately 0.06℃ / s for 5h, and approximately 0.05℃ / s for 6h.

[0034] (3) Calculation of surface heat transfer coefficient: 1) Finite element model establishment and parameter setting Based on the actual dimensions of the workpiece (diameter 60mm, length 140mm), a three-dimensional workpiece model was established using Deform-3D finite element software. A material model matching the thermophysical properties of GH4169 alloy was selected, and parameters such as thermal conductivity, specific heat capacity, and density of the alloy at different temperatures were input (which can be obtained through material handbooks or experimental measurements).

[0035] Based on the actual process parameters of the two heating methods, the corresponding heating boundary conditions are set in the software, including the furnace gas temperature change curve over time and the initial workpiece temperature (room temperature). At the same time, the temperature data of the four test locations collected in the experiment are imported into the software as target reference data for reverse heat transfer calculation.

[0036] 2) Solving the reverse heat transfer problem Call the reverse heat transfer function module in the Deform-3D software. Refer to Figure 4, the Deform finite element software interface for calculating the surface heat transfer coefficient, and set the calculation parameters: Iterative convergence accuracy: The convergence criterion is set as the deviation between the calculated temperature value and the experimentally measured value being less than ±2℃. Calculation step size: dynamically adjusted according to the rate of temperature change, setting a smaller step size (e.g., 10 seconds / step) during the rapid heating phase and a larger step size (e.g., 60 seconds / step) during the heat preservation phase.

[0037] Initiating reverse heat transfer calculation, the software will continuously adjust the workpiece surface heat transfer coefficient value based on Fourier's heat transfer law through iterative optimization algorithm until the deviation between the calculated temperature curves at each test point and the experimentally measured temperature curves meets the convergence criterion. At this point, the output surface heat transfer coefficient is the optimal value under the heating condition. Reverse heat transfer calculation is performed on the temperature data of the stepped heating method and the direct heating method respectively to obtain the surface heat transfer coefficient under the corresponding heating scenario.

[0038] Specifically: Export the transient temperature change data of each test location point collected under the two heating methods in step (2), remove one set of jump data caused by signal interference, and organize it into a format that can be recognized by Deform-3D finite element software. Establish a three-dimensional model based on the actual size of the workpiece, and input the thermophysical parameters of GH4169 alloy (refer to the "Handbook of Chinese High Temperature Alloy Materials (2020 Edition)", thermal conductivity 11.2-28.5W / (m・K), specific heat capacity 452-785J / (kg・K), density 8240kg / m³).

[0039] The inverse heat transfer function module built into the Deform-3D software was called, and the iteration convergence accuracy (deviation between calculated temperature value and experimental measured value < ±2℃) and calculation step size (10 seconds / step during the heating stage and 60 seconds / step during the holding stage) were set. The measured multi-depth transient temperature data was used as the target response, and the surface heat transfer coefficient boundary conditions were identified by the software's built-in iterative algorithm. After 85 iterations, the deviation met the convergence criterion, and the preliminary surface heat transfer coefficient was obtained.

[0040] (4) Result verification (surface heat transfer coefficient verification): 1) Heating simulation and temperature comparison The surface heat transfer coefficient obtained through reverse heat transfer calculation is used as a boundary condition and re-input into the workpiece heating simulation model of Deform-3D software. The heating process is numerically simulated according to the actual process parameters of the two heating methods, and the temperature change curves of four locations on the workpiece, namely the core, half center, near the surface, and surface, are obtained.

[0041] Referring to Figure 6, which compares simulated and measured temperature values ​​for different heating methods, the simulated temperature curves are compared one by one with the actual temperature curves collected in the laboratory to analyze the range of deviation. The iterative convergence accuracy is set to a deviation of ≤±2℃ between simulated and measured temperatures.

[0042] 2) Accuracy judgment If the maximum deviation between the simulated temperature and the actual measured temperature is within ±5℃ (meeting the accuracy requirements for engineering applications), then the obtained surface heat transfer coefficient is determined to be accurate and reliable, and can be used for numerical simulation of the pre-forging heating process of GH4169 alloy; if the deviation exceeds ±5℃, then return to step three, check the finite element model parameter settings, the convergence accuracy of the reverse heat transfer calculation, and other aspects, and recalculate the surface heat transfer coefficient until the deviation requirements are met.

[0043] The preliminary surface heat transfer coefficient obtained in step (3) is input into the Deform-3D finite element software to construct a pre-forging heating simulation model that is completely consistent with the two heating methods in step (2). Numerical simulation of the heating process is performed to obtain the simulated temperature change curve of the workpiece core. For example, Figure 6 The simulated and measured temperature curves shown should have an error of ≤±3%.

[0044] That is, the simulated core temperature change curve is compared with the experimentally measured core temperature change curve in step (2), and the temperature difference between the two is calculated. The calculation shows that the maximum difference between the simulated and measured temperatures under the two heating methods is 2.5℃, with an error of 2.27%, which is less than the preset ±3% error range. Therefore, the preliminary surface heat transfer coefficient is determined to be the effective coefficient. Abnormal data are removed based on a deviation exceeding ±10℃.

[0045] (5) Implementation instructions for alternative solutions 1) Finite element software replacement If Deform-3D software is not used, ABAQUS software can be used to calculate the surface heat transfer coefficient: Establish a 3D model consistent with the actual size of the workpiece, define the temperature boundary conditions for the heating process through ABAQUS's "User Subroutine (DFLUX)," and import the experimentally collected temperature data into the software; using ABAQUS's optimization module, write an optimization script with the objective function of "minimizing the deviation between simulated and measured temperatures," and iteratively solve for the surface heat transfer coefficient. The calculation logic is consistent with Deform-3D, with only slight differences in the operation interface and parameter setting path.

[0046] 2) Temperature measurement technology replacement If a fiber optic grating temperature sensor is used instead of a thermocouple: the sensitive element of the fiber optic grating sensor needs to be fixed to the test location on the workpiece using a high-temperature resistant adhesive (no drilling is required to avoid damaging the integrity of the workpiece). The sensor signal is transmitted to the demodulator via optical fiber. Because the fiber optic grating sensor has strong anti-electromagnetic interference capabilities, it can be used in high-frequency heating environments. However, the temperature response curve of the sensor in the range of 20-1200℃ needs to be calibrated in advance to ensure temperature measurement accuracy. The subsequent surface heat transfer coefficient calculation process is completely consistent with the thermocouple temperature measurement method.

[0047] 3) Algorithm optimization replacement If a genetic algorithm is used to optimize the surface heat transfer coefficient: Based on the core logic of the reverse heat transfer calculation (the reverse heat transfer calculation flowchart shown in Figure 5), the surface heat transfer coefficient is used as the optimization variable, and the root mean square error between the simulated temperature and the measured temperature is used as the fitness function. A genetic algorithm program is written using MATLAB software; the population size is set to 50, the number of iterations is 100, the crossover probability is 0.8, and the mutation probability is 0.05. The surface heat transfer coefficient is optimized, and finally the surface heat transfer coefficient value that minimizes the fitness function is obtained. This method is suitable for multi-parameter reverse calculation under complex heating conditions, and has higher accuracy, but the calculation time is relatively long.

[0048] Example 2: Laboratory determination of the surface heat transfer coefficient of a precipitation-hardening nickel-based superalloy (non-GH4169) during pre-forging heating process. This embodiment uses the same method and steps as Example 1, only adjusting the heating process parameters in step (2) according to the thermophysical properties of the precipitation-hardening nickel-based superalloy (thermal conductivity 10.5-26.8 W / (m・K) at 20-1080℃, specific heat capacity 448-772 J / (kg・K), density 8190 kg / m³): Step heating method: First, heat the workpiece to 650℃ and hold for 4 hours (ensuring the temperature difference between the core and surface of the workpiece is ≤5℃); then raise the temperature to 900℃ at a heating rate of 6℃ / min and hold for 3 hours; finally, raise the temperature to 1080℃ at a heating rate of 6℃ / min and hold for 2.5 hours. Direct heating method: The workpiece is heated from room temperature at a rate of 0.05℃ / s (theoretical rate) for 6 hours to 1080℃ (the actual heating rate deviates from the theoretical rate by 7%), and then held at that temperature for 2 hours. Refer to GB / T 30582-2014 "Heating Process Specification for High Temperature Alloy Forgings".

[0049] The remaining steps are completely consistent with those in Example 1. Finally, the effective surface heat transfer coefficient of the precipitation-hardening nickel-based superalloy before forging heating process is obtained. The maximum error between the simulated temperature and the measured temperature is 2.8%, which is less than the preset error range of ±3%, proving that the method of the present invention can be extended to other superalloys.

[0050] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made by those skilled in the art to the technical solutions of the present invention without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A method for determining the surface heat transfer coefficient of GH4169 alloy during pre-forging heating in a laboratory setting, characterized in that, Includes the following steps: (1) Workpiece preparation: GH4169 alloy workpieces are processed using an electric discharge wire cutting machine. The workpieces are 55-65mm in diameter and 130-150mm in length. Four test locations are selected on the workpieces, and holes of different depths are drilled at each test location. The drilling depths at the four test locations are: 1-3mm at the surface, 4-6mm near the surface, 13.75-16.25mm at the 1 / 2 center, and 27.5-32.5mm at the center. Thermocouples are embedded in each hole, and all thermocouples are connected to the same temperature sensor. (2) Heating and temperature acquisition: Under a controlled laboratory environment, the workpiece is subjected to pre-forging heating treatment using two heating methods, and the transient temperature change data at each test location is recorded synchronously by the thermometer. The two heating methods are as follows: a) Step heating method: First, heat the workpiece to 680-720℃ and hold for no less than 3 hours; then raise the temperature to 950℃ and hold for no less than 2 hours; finally, raise the temperature to 1100℃ and hold for no less than 2 hours. b) Direct heating method: Starting from room temperature, the workpiece is heated to 1100℃ over 4h, 5h or 6h, and held at that temperature for 1-2h. (3) Calculation of surface heat transfer coefficient: Input the transient temperature change data collected in step (2) into the finite element software, and use the reverse heat transfer function module of the finite element software to deduce the surface heat transfer coefficient of the workpiece during the heating process. (4) Result verification: The surface heat transfer coefficient obtained in step (3) is used to simulate the pre-forging heating. The simulated core temperature of the workpiece is compared with the core temperature of the workpiece measured in the laboratory in step (2). If the difference between the two is within the preset error range, the surface heat transfer coefficient is determined to be an effective coefficient.

2. The method for determining the surface heat transfer coefficient of GH4169 alloy during pre-forging heating process in a laboratory according to claim 1, characterized in that, The finite element software mentioned in step (3) is Deform-3D, ABAQUS, or ANSYS.

3. The method for determining the surface heat transfer coefficient of GH4169 alloy during pre-forging heating process in a laboratory according to claim 2, characterized in that, When the finite element software mentioned in step (3) is ABAQUS or ANSYS, the reverse heat transfer calculation is realized by writing the DFLUX user subroutine. The subroutine is constructed based on Fourier's law and boundary condition iterative algorithm, and the furnace gas temperature is defined by a linear interpolation function.

4. The method for determining the surface heat transfer coefficient of GH4169 alloy during pre-forging heating process in a laboratory according to claim 1, characterized in that, The thermocouple in step (1) is a high-temperature resistant thermocouple, and the temperature measuring end of the thermocouple is in close contact with the bottom of the borehole.

5. The method for determining the surface heat transfer coefficient of GH4169 alloy during pre-forging heating process in a laboratory according to claim 1, characterized in that, The calculation logic of the reverse heat transfer function module in step (3) is as follows: taking the measured multi-depth transient temperature data as the target response, the surface heat transfer coefficient boundary conditions in the heat transfer process are inverted and identified.

6. The method for determining the surface heat transfer coefficient of GH4169 alloy during pre-forging heating process in a laboratory according to claim 1, characterized in that, The optimization algorithm used in the reverse heat transfer calculation in step (3) is a genetic algorithm, a particle swarm algorithm, or an iterative algorithm provided by the finite element software.

7. The method for determining the surface heat transfer coefficient of GH4169 alloy during pre-forging heating process in a laboratory according to claim 1, characterized in that, The diameter of the borehole in step (1) is adapted to the outer diameter of the thermocouple. The inner wall of the borehole is polished and fixed with high-temperature resistant ceramic filler material after the thermocouple is embedded.

8. The method for determining the surface heat transfer coefficient of GH4169 alloy during pre-forging heating process in a laboratory according to claim 1, characterized in that, The heating equipment for the controllable laboratory environment in step (2) is a programmable temperature control furnace with a temperature fluctuation range not exceeding ±5℃.

9. The method for determining the surface heat transfer coefficient of GH4169 alloy during pre-forging heating process in a laboratory according to claim 1, characterized in that, The preset error range in step (4) is ±3%.

10. A method for determining the surface heat transfer coefficient of a high-temperature alloy during the pre-forging heating process in a laboratory, characterized in that, The high-temperature alloy is a nickel-based high-temperature alloy or a difficult-to-deform material, and the method steps described in any one of claims 1-9 are adopted, and the heating process parameters in step (2) are adjusted according to the thermophysical properties of the high-temperature alloy.

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