CN119294173A - A ProCAST-based method for predicting the heating-to-temperature time of large workpieces during heat treatment - Google Patents
A ProCAST-based method for predicting the heating-to-temperature time of large workpieces during heat treatment Download PDFInfo
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Abstract
本发明涉及一种基于ProCAST的大型工件热处理加热到温时间预测方法，属于热处理模拟仿真技术领域，解决了现有技术中没有公开具体采用ProCAST软件模拟预测大型工件热处理加热到温时间的方法。本发明提供了一种基于ProCAST的大型工件热处理加热到温时间预测方法，该方法基于ProCAST软件，准确性高，方法简单，明确了ProCAST软件模拟大型工件热处理的模拟设置方法、模拟参数使用范围、模拟与实际对比方法、模拟准确性定量判断、模拟参数调整方法。模拟与实际情况贴切，该方法时效性强，是在工件生产过程中模拟，根据热处理前期表面的实测温度进一步修正模拟参数，保证模拟的准确性。
The present invention relates to a method for predicting the time of large workpiece heat treatment heating to temperature based on ProCAST, which belongs to the field of heat treatment simulation technology, and solves the problem that there is no public method in the prior art that specifically uses ProCAST software to simulate and predict the time of large workpiece heat treatment heating to temperature. The present invention provides a method for predicting the time of large workpiece heat treatment heating to temperature based on ProCAST, which is based on ProCAST software, has high accuracy, and is simple in method, and clarifies the simulation setting method, simulation parameter usage range, simulation and actual comparison method, simulation accuracy quantitative judgment, and simulation parameter adjustment method of ProCAST software simulating heat treatment of large workpieces. The simulation is close to the actual situation, and the method has strong timeliness. It is simulated in the process of workpiece production, and the simulation parameters are further corrected according to the measured surface temperature in the early stage of heat treatment to ensure the accuracy of the simulation.
Description
Technical Field
The invention relates to the technical field of heat treatment simulation, in particular to a ProCAST-based large-scale workpiece heat treatment heating temperature time prediction method.
Background
In casting or forging processes, heat treatment of the work pieces is generally involved, especially for large forgings, for long periods of time, even up to tens of days. The temperature measurement in the workpiece is inconvenient during heating or cooling of the heat treatment, and the core temperature time is generally judged empirically, but is not accurate. If the heating or cooling time is too short, the interior of the workpiece does not reach the prescribed temperature, which causes quality problems, and if the heating time is too long, the interior of the workpiece reaches the temperature, the production period is prolonged, and energy waste is caused. Therefore, accurate judgment of the temperature condition inside the workpiece during heat treatment is necessary for improving the product quality, improving the production efficiency and reducing the production cost.
Finite element simulation is widely applied to guiding actual production, and a method for predicting temperature change in a heat treatment process by combining the simulation method is a reasonable method. However, the problem of simulation accuracy is also considered, and in order to find the optimal simulation parameters, the simulation and actual comparison should be combined to verify the optimal simulation parameters. The applicable simulation parameters of each heat treatment change, so that the heat treatment time of the large-sized workpiece is long, the simulation parameters can be further corrected according to the actually measured temperature value of the surface in the earlier stage of heat treatment, the time for reaching the temperature inside the workpiece can be accurately predicted, and the furnace outlet time can be judged. And by parameter correction, the influence of on-site complex conditions is reduced, and the simulation accuracy is ensured.
ProCAST software can simulate the processes of filling, solidification, heat treatment and the like, but does not disclose the research on simulation key points and simulation accuracy of a ProCAST heat treatment temperature field, and has little optimization verification combined with measured temperature values.
Disclosure of Invention
In view of the above analysis, the present invention aims to provide a ProCAST-based large workpiece heat treatment temperature field prediction method, which is used for solving the problems that a method for simulating and predicting the heating temperature time of a large workpiece by using ProCAST software is not disclosed in the prior art, the conventional method cannot determine the simulation accuracy, and at least one of the simulation parameter application range, the simulation parameter adjustment method and the like is not defined.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
the ProCAST-based large-scale workpiece heat treatment heating-to-temperature time prediction method specifically comprises the following steps:
S1, establishing a three-dimensional model of workpiece heat treatment;
s2, dividing grids of the three-dimensional model in ProCAST software, setting heat treatment simulation parameters, and starting view angle coefficient calculation;
s3, performing simulation calculation on a temperature field during heat treatment of the workpiece by using ProCAST software to obtain a temperature field simulation result;
S4, extracting an actually measured temperature value, namely, when a workpiece is actually subjected to heat treatment, selecting 1-2 temperature measuring positions for measuring the temperature, and extracting the temperature value of temperature measuring data after the heating time of the workpiece in a heat treatment furnace is more than or equal to 48 hours;
And S5, comparing the temperature value in the simulation result in the step S3 at the same position with the temperature value extracted in the step S4, judging whether the simulation result in the step S3 is reliable, and if not, readjusting the heat treatment simulation parameters in the step S2 until the simulation result in the step S3 is reliable.
Further, in step S1, the simplification process is performed on the heat-treated three-dimensional model, which includes the workpiece, the accessory and the heat treatment furnace.
Further, in step S2, the simulation parameters include material physical property parameters, interface heat exchange coefficients, workpiece surface blackness values, furnace wall blackness values of the heat treatment furnace, convective heat exchange coefficients of the workpiece in the furnace and furnace temperature.
Further, the physical parameters of the material include heat conductivity coefficient, specific heat capacity and density.
Further, in step S4, the temperature measurement data of each temperature measurement point includes temperatures of different heat treatment stages.
Further, the temperature values compared in step S5 are at least 10.
Further, the step S5 specifically comprises comparing the temperature difference and the average value of the temperature difference between the temperature value in the simulation result in the step S3 and the extracted measured temperature value at least 10 corresponding time points, and judging whether the simulation result in the step S3 is credible or not.
Further, if the temperature difference is less than 5% and the average value of the temperature difference is less than 2%, the simulation result of the step S3 is determined to be reliable, otherwise, the heat treatment simulation parameters of the step S2 are readjusted until the simulation result of the step S3 is determined to be reliable.
Further, the readjusting of the heat treatment simulation parameters of step S2 includes workpiece surface blackness values and/or heat treatment furnace wall blackness values.
Further, the prediction method further comprises S6, extracting the temperature reaching time of the slowest temperature rising position point of the workpiece center in the trusted simulation result, and carrying out furnace discharging cooling after reaching the required temperature, wherein the temperature reaching time is the heat treatment furnace discharging time.
Compared with the prior art, the invention has at least one of the following beneficial effects:
The invention provides a ProCAST-based large-scale workpiece heat treatment heating temperature time prediction method, which is based on ProCAST software, has high accuracy and simple method, and defines a simulation setting method, a simulation parameter application range, a simulation and actual comparison method, a simulation accuracy quantitative judgment and a simulation parameter adjustment method for simulating large-scale workpiece heat treatment by the ProCAST software. The simulation method is suitable for actual conditions, has strong timeliness, is used for simulating in the production process of the workpiece, further corrects simulation parameters according to the actually measured temperature of the surface in the earlier stage of heat treatment, ensures the accuracy of simulation, and can provide effective guidance for actual production by using the method for simulation prediction.
In the invention, the technical schemes can be mutually combined to realize more preferable combination schemes. Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention may be realized and attained by the structure particularly pointed out in the written description and drawings.
Drawings
The drawings are only for purposes of illustrating particular embodiments and are not to be construed as limiting the invention, like reference numerals being used to refer to like parts throughout the several views.
FIG. 1 is a flow chart of a method for predicting a thermal treatment temperature field of a large workpiece based on ProCAST according to the invention;
FIG. 2 is a three-dimensional model diagram in example 1 of the present invention;
FIG. 3 is a graph showing the change of the actual heat treatment temperature of the workpiece with time in example 1 of the present invention;
FIG. 4 is a diagram showing the position of an actual temperature measurement point in embodiment 1 of the present invention;
FIG. 5 is a graph showing the comparison of the simulated temperature values and the measured temperature values in example 1 of the present invention;
FIG. 6 is a drawing showing the tapping time of the heat treatment in example 1 of the present invention.
Reference numerals:
1-rotor, 2-sizing block and 3-heat treatment furnace.
Detailed Description
The following detailed description of preferred embodiments of the invention is made in connection with the accompanying drawings, which form a part hereof, and together with the description of the embodiments of the invention, are used to explain the principles of the invention and are not intended to limit the scope of the invention.
In one embodiment of the present invention, as shown in fig. 1, a ProCAST-based method for predicting the heating time to temperature of a large workpiece by heat treatment is disclosed, which specifically comprises the following steps:
S1, establishing a three-dimensional model of workpiece heat treatment;
s2, dividing grids of the three-dimensional model in ProCAST software, setting heat treatment simulation parameters, and starting view angle coefficient calculation;
s3, performing simulation calculation on a temperature field during heat treatment of the workpiece by using ProCAST software to obtain a temperature field simulation result;
S4, extracting an actually measured temperature value, namely, when a workpiece is actually subjected to heat treatment, selecting 1-2 temperature measuring positions for measuring the temperature, and extracting the temperature value of temperature measuring data after the heating time of the workpiece in a heat treatment furnace is more than or equal to 48 hours;
And S5, comparing the temperature value in the simulation result in the step S3 at the same position with the temperature value extracted in the step S4, judging whether the simulation result in the step S3 is reliable, and if not, readjusting the heat treatment simulation parameters in the step S2 until the simulation result in the step S3 is reliable.
The invention provides a ProCAST-based large-scale workpiece heat treatment heating temperature time prediction method, which is based on ProCAST software, has high accuracy and simple method, and defines a simulation setting method, a simulation parameter application range, a simulation and actual comparison method, a simulation accuracy quantitative judgment and a simulation parameter adjustment method for simulating large-scale workpiece heat treatment by the ProCAST software. Simulation is relevant to actual conditions.
In the prior art, the simulation and the actual verification are generally carried out after the actual production is completed, and the proper simulation parameters are determined through the comparison of the simulation and the actual comparison and are used for carrying out the simulation prediction on the subsequent production process, but the actual production condition is complex, and the applicable simulation parameters of each heat treatment are not consistent. The method provided by the invention has strong timeliness, simulation is performed in the production process of the workpiece, simulation parameters are further corrected according to the actually measured temperature of the surface in the earlier stage of heat treatment, and the simulation accuracy is ensured.
The heat treatment temperature field predicted by the method can provide effective guidance for actual production, predicts the temperature change of the heat treatment workpiece, and accurately judges the time required by heating the workpiece to the specified temperature, thereby determining the time for discharging the heat treatment, ensuring that the interior of the workpiece reaches the corresponding temperature and reducing unnecessary energy waste.
In a specific embodiment, step S1 includes performing a simplified process on a three-dimensional model of the heat treatment, where the three-dimensional model includes a workpiece, an accessory, and a heat treatment furnace.
Specifically, the auxiliary tool such as the sizing block models the workpiece and the auxiliary tool according to the actual size, the heat treatment furnace only needs to build an inner wall surface model according to the actual size, and the main structure of the workpiece and the size near the temperature measuring point are required to be ensured to be complete.
Because the data of the temperature measuring points and the temperature reaching time of the slowest temperature rising position of the core are mainly focused, the temperature rising of the core is slow, and small structures such as small chamfers or small fillets which are not focused can be eliminated simply for large workpieces. The heat treatment furnace has a complex structure, but the most main heat exchange is radiation heat exchange between the inner wall of the furnace and the workpiece, and only a model of the inner wall surface is required to be built. Therefore, the modeling efficiency can be improved, the grid division is convenient, the number of grids is reduced, the calculation speed is improved, and the simulation result is not influenced.
The data of the temperature measuring point and the temperature reaching time of the slowest temperature rising position of the core are mainly focused. For large workpieces, the temperature rise of the core is very slow, and small structures, small chamfers or small fillets which are not concerned can be simplified appropriately, so that the result is basically unaffected.
In a specific embodiment, in step S2, the simulation parameters include a physical property parameter of a material, an interface heat exchange coefficient, a surface blackness value of a workpiece, a furnace wall blackness value of a heat treatment furnace, a convective heat exchange coefficient of the workpiece in the furnace, and a furnace temperature.
In the invention, mesh module is divided into meshes, generally, tetrahedron meshes are used, a workpiece and an auxiliary tool (such as a sizing block) are of a solid structure, a surface Mesh and a body Mesh are required to be divided, a heat treatment furnace is of a surface structure, and only the surface Mesh is required to be divided. The smoothness of the model surface needs to be ensured, but the grids are not too much, and for most less complex models, the total number of grids is generally within 100 ten thousand.
Generally, when a workpiece is heated in a heat treatment furnace, convection heat exchange exists between the surface of the workpiece and furnace gas, radiation heat exchange exists between the surface of the workpiece and the wall of the heat treatment furnace, the radiation heat exchange degree is related to angles and distances, and the radiation heat exchange amounts at different positions of the surface of the workpiece are different. When ProCAST software is used for calculation, if the radiation heat exchange condition consistent with the actual condition is expected to be simulated, a heat treatment furnace model needs to be built, the view angle coefficient is started for calculation, and blackness values of the surface of a workpiece and the wall surface of the heat treatment furnace need to be set during simulation.
In the aspect of heat treatment simulation application, in order to simplify a model, the convection heat exchange between the surface of a workpiece and furnace gas and the radiation heat exchange between the surface of the workpiece and a wall of a heat treatment furnace can be simplified into a comprehensive heat exchange coefficient, namely, the value of the convection heat exchange coefficient is improved, or the blackness of the surface of the workpiece and the surface of the wall of the heat treatment furnace can be combined into a blackness value. The simplified model does not consider the influence of the view angle coefficient, namely the heat exchange quantity of any position of the surface of the workpiece is considered to be the same. For a single small workpiece heat treatment of simple shape, the effect of simplifying the model may be small, but for a large workpiece, or for a case of a heat treatment in which a plurality of workpieces are placed simultaneously in a heat treatment furnace, the above simplification cannot be performed, the view angle coefficient must be calculated, otherwise the simulation and actual deviation may be large. The calculation of the opening View angle coefficient (setting View Factor to be ON) in the invention is more in line with the actual situation of a large-sized workpiece.
In one embodiment, the physical properties of the material include thermal conductivity, specific heat capacity, and density.
The physical parameters (thermal conductivity, specific heat and density) of the material required for the heat treatment simulation are obtained in the following order, specifically, if experimental measurement values are available, experimental measurement is selected, if no experimental measurement values are available, JMatPro software calculation is selected, if no JMatPro software is available, proCAST software calculation is selected, but the accuracy is also reduced in sequence:
1. And (5) experimental determination. Aiming at the product materials, the parameters obtained by using experimental tests are the most accurate, and the test method is a general test method.
Jmatpro software calculation. Extended General function calculation using Thermo-Physical Properties module. Before calculation, the heat treatment temperature needs to be set, the phase composition below the heat treatment temperature is unchanged, and the phase composition above the heat treatment temperature is consistent with the equilibrium state. For iron and steel materials, the heat treatment temperature needs to be less than the austenitizing temperature, typically around 600 ℃, and setting too high or too low increases the error.
Procast software calculation. And calculating the thermophysical parameters by using a Lever calculation model in the material database. The software has three thermophysical parameter calculation models of Lever, scheil and Back Diffuse, wherein the calculation result of the Lever model is closest to the actual result.
In a specific embodiment, the interface heat exchange coefficient is a heat exchange coefficient of a contact surface of a component made of different materials.
For a common steel material workpiece and a heat treatment furnace, the interface heat exchange coefficient between metals is 1000-5000W/m 2/K, the surface blackness of the workpiece is 0.4-0.9, the furnace wall blackness is 0.5-0.9, and the convective heat exchange coefficient of the workpiece in the furnace is 0-20W/m 2/K. The surface blackness of the workpiece is related to the surface state, the surface oxidation state and the roughness of the workpiece are changed in the production process of the workpiece, for example, the blackness is different when the oxide scale exists and when the oxide scale does not exist, the surface blackness of the workpiece is a parameter which needs to be adjusted in a key way when the heat treatment is simulated, and the applicable simulation parameters of each time can be changed for different heat treatment processes. The simulation parameters are determined empirically in the past or a value is selected within the above range, and then corrected based on comparison of the simulation results with the measured results.
The initial simulation parameters in the invention are specifically that the interface heat exchange coefficient between the workpiece and the metal sizing block is 2000W/m 2/K, the convection heat exchange coefficient of the workpiece in the furnace is 10W/m 2/K, and the furnace wall blackness is 0.7. The surface blackness of the workpiece is (1) that the surface of the workpiece is not oxidized before heat treatment, the blackness when the surface roughness is low is 0.5, the blackness when the surface roughness is high is 0.7, if the heat treatment temperature is higher than 500 ℃, the surface can be oxidized in the heat treatment process, the blackness value which is set in a simulation mode is changed along with the temperature, and the blackness when the temperature is higher than 500 ℃ is 0.8. (2) The surface of the workpiece before heat treatment was oxidized, the blackness of the scale when the scale was closely adhered to the surface was 0.8, and the blackness of the scale when the scale had evidence of falling off was 0.6.
In one embodiment, in step S4, the total time the workpiece is heated in the heat treatment furnace is greater than 5 days.
In one embodiment, in step S4, the temperature measurement data of each temperature measurement point includes temperatures of different heat treatment stages.
In one embodiment, the different heat treatment stages include a heat treatment warming stage and a constant temperature stage.
Specifically, in step S4, since the workpiece cannot be destroyed, the extracted temperature value can only determine the temperature of the surface position.
The temperature measuring point needs to be far away from the position of the corner angle and the like, which heats up too quickly, and is located at the center of the open surface as much as possible, for example, for a cylindrical workpiece, the temperature measuring point is most reasonable at the center of the side surface. The heat treatment furnace is a gas furnace, and when the gas furnace is used for measuring temperature by using the thermocouple, the placement position of the thermocouple cannot be too close to the position of the nozzle, and the result is influenced by the fact that the temperature near the nozzle is large. For the gas furnace with the nozzle at the bottom of the side surface, the temperature measuring point is arranged at the middle part or the upper part, the thermocouple cost is considered, and one to two temperature measuring point data are acquired.
In one embodiment, the temperature values compared in step S5 are at least 10.
In one embodiment, the step S5 specifically includes comparing the temperature difference and the average value of the temperature difference between the temperature value in the simulation result in the step S3 and the extracted measured temperature value at least 10 corresponding time points, and judging whether the simulation result in the step S3 is reliable.
In a specific embodiment, if the temperature difference is less than 5% and the average value of the temperature differences is less than 2%, the simulation result of the step S3 is determined to be reliable, otherwise, the heat treatment simulation parameters of the step S2 are readjusted until the simulation result of the step S3 is determined to be reliable.
Preferably, the readjusting of the heat treatment simulation parameters of step S2 includes workpiece surface blackness values and/or furnace wall blackness values of the heat treatment furnace.
Specifically, the material parameters are obtained through test measurement or software calculation, so that adjustment is not needed in the follow-up process, the contact between the workpiece and the auxiliary tool is not more, the influence of the interface heat exchange coefficient is smaller, and adjustment is not needed. It is generally only necessary to adjust the workpiece surface blackness value, furnace wall blackness value, and convective heat transfer coefficient.
Simulation parameter correction flow:
After the calculation of the initial simulation parameters is completed, in step S5, the simulation and the actual difference are compared, if the conditions that the temperature difference is less than 5% and the average value of the temperature difference is less than 2% are not satisfied, the simulation parameters are required to be sequentially adjusted according to the following sequence, if part of the simulation parameters have very definite values, the simulation parameters are kept unchanged, and only other parameters are required to be adjusted.
1) If the simulated average temperature difference value is larger than the actual value, returning to the step S2 to reduce the blackness value of the surface of the workpiece by 0.1, and otherwise, increasing the blackness value by 0.1 to restart until the error requirement is met. If the blackness value of the surface of the workpiece is adjusted to the lower limit (0.4) or the upper limit (0.9) and the error requirement is not met, the next simulation parameter is adjusted.
2) If the simulated average temperature difference is larger than the actual temperature difference, returning to the step S2 to reduce the furnace wall blackness value by 0.1 and restarting, otherwise, increasing the furnace wall blackness value by 0.1 and restarting until the error requirement is met. If the furnace wall blackness value is adjusted to the lower limit (0.5) or the upper limit (0.9) and the error requirement is not met, the next simulation parameter is adjusted.
3) If the average value of the simulated temperature difference is larger than the actual value, returning to the step S2 to restart the reduction of the convection heat transfer coefficient by 5W/m 2/K, otherwise, restarting the increase of the convection heat transfer coefficient by 5W/m 2/K until the error requirement is met. If the convection heat transfer coefficient is adjusted to the lower limit (5W/m 2/K) or the upper limit (20W/m 2/K) and the error requirement is not met, ending the parameter adjustment.
4) Under the general condition, the error requirement can be met only by adjusting the surface blackness of the workpiece, and if the error requirement can not be met after the parameters are adjusted, a group of parameters with the minimum error is selected as the final parameters.
The method for comparing the measured temperature value with the simulation result is more accurate and simpler.
In a specific embodiment, the prediction method further comprises S6, extracting the temperature reaching time of the position point of the lowest temperature rising of the workpiece center in the trusted simulation result, and carrying out furnace discharging cooling after reaching the required temperature, wherein the temperature reaching time is the heat treatment furnace discharging time.
The technical scheme of the invention is further explained below by combining specific examples.
Example 1
The method for predicting the heating time of the large workpiece in the heat treatment based on ProCAST comprises the following steps:
s1, establishing a three-dimensional model of heat treatment of a workpiece by using three-dimensional modeling software, wherein the model comprises four rotors 1, sizing blocks 2 and a heat treatment furnace 3, as shown in FIG. 2;
S2, importing a three-dimensional model in an x_t format into finite element simulation software ProCAST, dividing grids, setting heat treatment simulation parameters, specifically, setting rotor and sizing block materials, wherein the parameters of the materials are heat conductivity coefficients, specific heat capacities and densities, which are all actual measurement values, setting initial simulation parameters (1) setting an interface heat exchange coefficient between a contact surface of the rotor and the sizing block to be 2000W/m 2/K, (2) setting the surface of the sizing block to be seriously oxidized and oxide skin to be partially fallen off, setting the surface blackness of the sizing block to be 0.6, (3) setting the surface of the rotor to be oxidized, setting the surface blackness of the rotor to be 0.8, (4) setting a heat treatment furnace to be a gas furnace, setting the blackness of a furnace wall to be 0.7, and (5) setting the convective heat exchange coefficient of a workpiece in the heat treatment furnace to be 10W/m 2/K, and setting the furnace temperature according to the heat treatment temperature and actual measurement data. And (5) starting the view angle coefficient calculation.
S3, performing simulation calculation on a temperature field during heat treatment of the workpiece by using ProCAST software to obtain a temperature field simulation result;
S4, extracting an actual measured temperature value, wherein the total heating time of an actual heat treatment process is about 7 days, the actual heat treatment measured temperature data of the heat treatment for 100 hours before extraction is used for simulation comparison, as shown in FIG. 3, the front 80h is a heating stage, the temperature after 80h is a constant temperature stage, the extracted actual measured temperature comprises the temperature values of the heating stage and the constant temperature stage, and the specific position of a temperature measuring point of the actual measured temperature value is shown in FIG. 4;
S5, corresponding to the actually measured temperature value, selecting a temperature simulation result at the same temperature measuring point position from the simulation result obtained in the step S3, selecting a temperature point every 10 hours, selecting 10 temperature points in total, comparing the temperature difference between the simulation temperature value and the actually measured temperature value at the same time point with the average value of the 10 temperature differences, comparing the simulation temperature value and the actually measured temperature value in the embodiment with each other as shown in FIG. 5, judging that the simulation result in the step S3 is reliable if the temperature difference is less than 5% and the average value of the temperature difference is less than 2%, otherwise, readjusting the heat treatment simulation parameters in the step S2 until the simulation result in the step S3 is reliable;
when the initial simulation parameters are used for simulation, the average value of the simulated temperature difference is larger than the actual value, the step S2 is returned to reduce the blackness value of the surface of the workpiece by 0.1, the workpiece is regulated to be restarted to be 0.7, and the simulated temperature difference is compared with the actual value after the simulation is finished, and the average value of the simulated temperature difference is still larger than the actual value. (2) And returning to the step S2, reducing the blackness value of the surface of the workpiece by 0.1, adjusting to 0.6, restarting, and comparing after the simulation is finished, wherein the average value of the simulation and the actual temperature difference meets the requirement.
The final parameter setting in this example was as follows, the material parameters were measured, the convective heat transfer coefficient was 10W/m 2/K, the interfacial heat transfer coefficient between the workpiece and the sizing block was 2000W/m 2/K, the surface blackness of the workpiece was 0.6, and the furnace wall blackness was 0.7.
The heat treatment simulation result obtained in the step S5 is used for predicting the temperature change in the subsequent heat treatment process, the temperature reaching time of the position point with the slowest temperature rise of the central part is extracted, as shown in figure 6, the temperature reaches the specified requirement at 154h, the heat treatment tapping time can be determined as 154h, the quality problem is not found through the subsequent flaw detection, and the method disclosed by the invention ensures the heat treatment quality of the product, reduces the energy consumption and realizes the accurate simulation prediction of the heat treatment process.
The heat treatment temperature field predicted by the method can guide actual heat treatment production, predict the temperature change of a heat treatment workpiece, accurately judge the time required by heating the workpiece to the specified temperature, and further determine the time for discharging the heat treatment, so as to ensure that the interior of the workpiece reaches the corresponding temperature and reduce unnecessary energy waste.
Those skilled in the art will appreciate that all or part of the flow of the methods of the embodiments described above may be accomplished by way of a computer program to instruct associated hardware, where the program may be stored on a computer readable storage medium. Wherein the computer readable storage medium is a magnetic disk, an optical disk, a read-only memory or a random access memory, etc.
The present invention is not limited to the above-mentioned embodiments, and any changes or substitutions that can be easily understood by those skilled in the art within the technical scope of the present invention are intended to be included in the scope of the present invention.
Claims (10)
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| Application Number | Priority Date | Filing Date | Title |
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| CN202411260264.0A CN119294173A (en) | 2024-09-10 | 2024-09-10 | A ProCAST-based method for predicting the heating-to-temperature time of large workpieces during heat treatment |
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