Method, device, medium and system for optimizing parameters of digital model of casting

Abstract

The present application provides a method, device, medium and system for optimizing parameters of a digital model of a casting. According to the positive or negative value of a first relative deviation, the thermal conductivity and interface heat transfer coefficient of the digital model of the casting are increased, or the thermal conductivity and interface heat transfer coefficient of the digital model of the casting are reduced, so that the optimization direction of the thermal conductivity and interface heat transfer coefficient of the digital model of the casting can be more accurate, thereby improving the optimization efficiency. The acquisition step and the adjustment step are repeatedly performed to continuously optimize in an iterative update manner, and when the current relative deviation is considered to be within an allowable range, the optimal parameters can be determined, thereby solving the problem that in order to improve the simulation accuracy of the digital model of the casting, the existing scheme only relies on historical data for experience summary to optimize the parameters of the digital model, thereby resulting in low optimization efficiency of the parameters of the digital model of the existing scheme.

Description

Technical Field

[0001] The present application relates to the technical field of digital models of castings, and in particular to a method, device, medium and system for optimizing parameters of digital models of castings. Background Art

[0002] In the field of heat exchange between 3D printed sand molds and cast iron interfaces, in order to improve the simulation accuracy of digital models of cast objects (i.e., castings or molds), existing solutions only rely on historical data for experience summary and optimization of digital model parameters, resulting in low optimization efficiency of digital model parameters of existing solutions.

[0003] Since the optimization efficiency of the parameters of the digital model of the existing scheme is low, the efficiency of subsequent experiments based on the digital model is also low, which is not conducive to subsequent experiments. Summary of the invention

[0004] The main purpose of the present application is to provide a method, device, medium and system for optimizing the parameters of a digital model of a casting, so as to at least solve the problem that in order to improve the simulation accuracy of the digital model of the casting, the existing scheme only relies on historical data for experience summary to optimize the parameters of the digital model, which leads to low optimization efficiency of the parameters of the digital model of the existing scheme.

[0005] In order to achieve the above object, according to one aspect of the present application, a method for optimizing parameters of a digital model of a casting is provided, the method comprising:

[0006] Acquisition step: acquiring a first relative deviation, wherein the first relative deviation represents a relative deviation between a measured temperature of the casting and a simulated temperature of a digital model of the casting;

[0007] Adjustment step: increasing the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting, or decreasing the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting according to the positive or negative value of the first relative deviation;

[0008] Processing step: repeatedly executing the acquisition step and the adjustment step to iteratively update the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting until the current number of iterations reaches an iteration number threshold, and / or the current relative deviation of the digital model of the casting is less than or equal to a deviation threshold, wherein the current relative deviation represents a relative deviation between the measured temperature of the casting and the simulated temperature of the digital model of the casting obtained by simulating the casting using the current thermal conductivity and the interface heat transfer coefficient.

[0009] Optionally, increasing the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting, or decreasing the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting according to the positive or negative value of the first relative deviation, comprises:

[0010] When the first relative deviation is a positive number, increasing the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting;

[0011] When the first relative deviation is a negative number, the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting are reduced.

[0012] Optionally, increasing the thermal conductivity of the digital model of the casting, or decreasing the thermal conductivity of the digital model of the casting, comprises:

[0013] according to , determine the updated thermal conductivity;

[0014] Wherein, λ is the updated thermal conductivity, is the first relative deviation, is the initial thermal conductivity, is the first adjustment coefficient.

[0015] Optionally, increasing the interface heat transfer coefficient of the digital model of the casting, or decreasing the interface heat transfer coefficient of the digital model of the casting, comprises:

[0016] according to , determine the updated interface heat transfer coefficient;

[0017] Wherein, h is the updated interface heat transfer coefficient, is the first relative deviation, is the initial interface heat transfer coefficient, is the second adjustment coefficient.

[0018] Optionally, the method further comprises:

[0019] When the current number of iterations reaches the iteration number threshold, obtaining the current optimal thermal conductivity and the current optimal interface heat transfer coefficient;

[0020] The casting is simulated using the current optimal thermal conductivity to obtain a second relative deviation, wherein the second relative deviation represents a relative deviation between the measured temperature of the casting and a simulated temperature of a digital model of the casting obtained by simulating the casting using the current optimal thermal conductivity;

[0021] The casting is simulated using the current optimal interface heat transfer coefficient to obtain a third relative deviation, wherein the third relative deviation represents a relative deviation between the measured temperature of the casting and a simulated temperature of a digital model of the casting obtained by simulating the casting using the current optimal interface heat transfer coefficient;

[0022] When the second relative deviation is less than or equal to the deviation threshold, determining the final optimal thermal conductivity to be the current optimal thermal conductivity;

[0023] When the third relative deviation is less than or equal to the deviation threshold, the final optimal interface heat transfer coefficient is determined to be the current optimal interface heat transfer coefficient.

[0024] Optionally, after determining the final optimal thermal conductivity and the final optimal interface heat transfer coefficient, the method further includes:

[0025] The casting is simulated using the final optimal thermal conductivity and the final optimal interface heat transfer coefficient to obtain a fourth relative deviation, wherein the fourth relative deviation represents a relative deviation between the measured temperature of the casting and a simulated temperature of a digital model of the casting obtained by simulating the casting using the final optimal thermal conductivity and the final optimal interface heat transfer coefficient;

[0026] When the fourth relative deviation is less than or equal to the deviation threshold, it is determined that the optimization work is completed.

[0027] Optionally, obtaining a first relative deviation includes:

[0028] according to , determining the first relative deviation;

[0029] in, is the first relative deviation, is the simulation temperature of the digital model of the casting, is the measured temperature of the casting.

[0030] According to another aspect of the present application, a device for optimizing parameters of a digital model of a casting is provided, the device comprising:

[0031] A first acquisition unit is used to perform an acquisition step: acquiring a first relative deviation, wherein the first relative deviation represents a relative deviation between a measured temperature of the casting and a simulated temperature of the digital model of the casting;

[0032] an adjusting unit, configured to perform an adjusting step: increasing the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting, or decreasing the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting, according to the positive or negative value of the first relative deviation;

[0033] a first processing unit, configured to execute a processing step of repeatedly executing the acquiring step and the adjusting step to iteratively update the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting until a current number of iterations reaches an iteration number threshold, and / or a current relative deviation of the digital model of the casting is less than or equal to a deviation threshold, wherein the current relative deviation represents a relative deviation between the actually measured temperature of the casting and a simulated temperature of the digital model of the casting obtained by simulating the casting using the current thermal conductivity and the interface heat transfer coefficient.

[0034] According to another aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute any one of the methods described.

[0035] According to another aspect of the present application, a parameter optimization system for a digital model of a casting is provided, the system comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include means for executing any one of the methods described.

[0036] By applying the technical solution of the present application, the simulation accuracy is judged based on the relative deviation between the measured temperature and the simulated temperature, thereby improving the reliability of the judgment. According to the positive or negative value of the first relative deviation, the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting are increased, or the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting are reduced, so that the optimization direction of the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting can be more accurate, thereby improving the optimization efficiency. The acquisition step and the adjustment step are repeatedly performed to iteratively update the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting until the current number of iterations reaches the iteration number threshold, and / or the current relative deviation of the digital model of the casting is less than or equal to the deviation threshold, thereby continuously optimizing in an iterative updating manner, and when the current relative deviation is considered to be within the allowable range, the optimal parameters can be determined, thereby solving the problem that in order to improve the simulation accuracy of the digital model of the casting, the existing scheme only relies on historical data for experience summary to optimize the parameters of the digital model, thereby resulting in low optimization efficiency of the parameters of the digital model of the existing scheme. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The drawings constituting part of the present application are used to provide a further understanding of the present application. The exemplary embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0038] Figure 1 A schematic flow chart of a method for optimizing parameters of a digital model of a casting provided in accordance with an embodiment of the present application is shown;

[0039] Figure 2 A schematic diagram showing the positional relationship of a thermocouple, an overflow structure, an upper sand mold, a lower sand mold, and a stepped casting in a casting provided according to an embodiment of the present application is shown;

[0040] Figure 3 Three views showing the structure of a stepped casting and a sand mold provided according to an embodiment of the present application are shown;

[0041] Figure 4 A schematic diagram showing the positional relationship of thermocouples in a casting, a runner, a sprue, an overflow structure, a stepped casting, and a thermocouple in a sand mold provided according to an embodiment of the present application;

[0042] Figure 5 Three views showing the structure of a stepped casting and a pouring and rigging system provided according to an embodiment of the present application;

[0043] Figure 6 A schematic flow chart of another method for optimizing parameters of a digital model of a casting provided in accordance with an embodiment of the present application is shown;

[0044] Figure 7 A structural block diagram of a device for optimizing parameters of a digital model of a casting provided according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0045] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0046] In order to enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this application.

[0047] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0048] As introduced in the background technology, in the field of heat exchange between 3D printed sand molds and cast iron interfaces, in order to improve the simulation accuracy of digital models of castings (i.e., castings or castings), existing solutions only rely on historical data for experience summary to optimize the parameters of the digital model, resulting in low optimization efficiency of the parameters of the digital model of the existing solutions. In order to solve the problem that in order to improve the simulation accuracy of the digital model of the casting, the existing solutions only rely on historical data for experience summary to optimize the parameters of the digital model, resulting in low optimization efficiency of the parameters of the digital model of the existing solutions, the embodiments of the present application provide a parameter optimization method, device, medium and system for a digital model of a casting.

[0049] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0050] In this embodiment, a method for optimizing parameters of a digital model of a casting is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical sequence is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0051] Figure 1 FIG. 1 is a flow chart of a method for optimizing parameters of a digital model of a casting provided in accordance with an embodiment of the present application. Figure 1 As shown, the method comprises the following steps:

[0052] Step S101, an acquisition step: acquiring a first relative deviation, wherein the first relative deviation represents a relative deviation between a measured temperature of a casting and a simulated temperature of a digital model of the casting;

[0053] The casting is a casting or a mold.

[0054] In one embodiment of the present application, obtaining a first relative deviation includes:

[0055] according to , determine the above-mentioned first relative deviation;

[0056] in, is the first relative deviation mentioned above, is the above-mentioned simulation temperature of the above-mentioned casting digital model, is the measured temperature of the above casting.

[0057] Specifically, the relative deviation between the measured temperature and the simulated temperature is used as a benchmark to judge the simulation accuracy, thereby improving the reliability of the judgment.

[0058] Step S102, an adjustment step: increasing the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting, or decreasing the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting according to the positive or negative value of the first relative deviation;

[0059] Specifically, according to the positive or negative value of the above-mentioned first relative deviation, the thermal conductivity and the interface heat transfer coefficient of the above-mentioned digital model of the casting are increased, or the above-mentioned thermal conductivity and the above-mentioned interface heat transfer coefficient of the above-mentioned digital model of the casting are reduced, so that the optimization direction of the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting can be made more accurate, thereby improving the optimization efficiency.

[0060] In one embodiment of the present application, step S102, i.e., increasing the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting, or decreasing the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting according to the positive or negative value of the first relative deviation, comprises:

[0061] When the first relative deviation is a positive number, increasing the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting;

[0062] When the first relative deviation is a negative number, the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting are reduced.

[0063] Specifically, when the first relative deviation is a positive number, it is determined that the thermal conductivity and the interface heat transfer coefficient need to be improved, and the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting are increased;

[0064] When the first relative deviation is a negative number, it is determined that the thermal conductivity and the interface heat transfer coefficient need to be reduced, and the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting are reduced;

[0065] When the first relative deviation is 0, the current thermal conductivity and interface heat transfer coefficient are considered to be optimal values, and the thermal conductivity and interface heat transfer coefficient are maintained unchanged.

[0066] In one embodiment of the present application, increasing the thermal conductivity of the digital model of the casting, or decreasing the thermal conductivity of the digital model of the casting, comprises:

[0067] according to , determine the updated thermal conductivity mentioned above;

[0068] Wherein, λ is the above-mentioned updated thermal conductivity, is the first relative deviation mentioned above, is the initial thermal conductivity, is the first adjustment coefficient.

[0069] In one embodiment of the present application, increasing the interface heat transfer coefficient of the digital model of the casting, or decreasing the interface heat transfer coefficient of the digital model of the casting, comprises:

[0070] according to , determine the updated interface heat transfer coefficient;

[0071] Wherein, h is the above-mentioned updated interface heat transfer coefficient, is the first relative deviation mentioned above, is the initial interface heat transfer coefficient, is the second adjustment coefficient.

[0072] Specifically, if 3%≤| |≤45%, then recommended ∈(0, 0.7), ∈(0,0.6), by setting two adjustment coefficients to optimize the change amount of parameter optimization, and taking the relative deviation between the measured temperature and the simulated temperature into consideration, the optimization adjustment process is made faster and more accurate.

[0073] Step S103, a processing step: repeatedly executing the above-mentioned acquisition step and the above-mentioned adjustment step to iteratively update the above-mentioned thermal conductivity and the above-mentioned interface heat transfer coefficient of the above-mentioned digital model of the casting, until the current number of iterations reaches an iteration number threshold, and / or the current relative deviation of the above-mentioned digital model of the casting is less than or equal to a deviation threshold, and the above-mentioned current relative deviation represents the relative deviation between the above-mentioned measured temperature of the above-mentioned casting and the simulated temperature of the digital model of the casting obtained by simulating the above-mentioned casting using the current above-mentioned thermal conductivity and the above-mentioned interface heat transfer coefficient.

[0074] When the current number of iterations reaches the iteration number threshold, and / or the current relative deviation of the digital model of the casting is less than or equal to the deviation threshold, it is considered that the parameter optimization work has been completed, and the current thermal conductivity and the interface heat transfer coefficient are the optimal values.

[0075] In the above steps, the relative deviation between the measured temperature and the simulated temperature is used as a reference to judge the simulation accuracy, thereby improving the reliability of the judgment. According to the positive or negative value of the above first relative deviation, the thermal conductivity and the interface heat transfer coefficient of the above digital model of the casting are increased, or the above thermal conductivity and the above interface heat transfer coefficient of the above digital model of the casting are reduced, so that the optimization direction of the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting can be more accurate, thereby improving the optimization efficiency. The above acquisition step and the above adjustment step are repeatedly performed to iteratively update the above thermal conductivity and the above interface heat transfer coefficient of the digital model of the casting until the current number of iterations reaches the iteration number threshold, and / or the current relative deviation of the above digital model of the casting is less than or equal to the deviation threshold, so as to continuously optimize in an iterative update manner, and when the current relative deviation is considered to be within the allowable range, the optimal parameters can be determined, thereby solving the problem that in order to improve the simulation accuracy of the digital model of the casting, the existing scheme only relies on historical data for experience summary to optimize the parameters of the digital model, thereby resulting in low optimization efficiency of the parameters of the digital model of the existing scheme.

[0076] In one embodiment of the present application, the above method further includes:

[0077] When the current number of iterations reaches the above-mentioned iteration number threshold, obtaining the current optimal thermal conductivity and the current optimal interface heat transfer coefficient;

[0078] The casting is simulated using the current optimal thermal conductivity to obtain a second relative deviation, wherein the second relative deviation represents a relative deviation between the measured temperature of the casting and a simulated temperature of a digital model of the casting obtained by simulating the casting using the current optimal thermal conductivity;

[0079] The casting is simulated using the current optimal interface heat transfer coefficient to obtain a third relative deviation, wherein the third relative deviation represents a relative deviation between the measured temperature of the casting and a simulated temperature of a digital model of the casting obtained by simulating the casting using the current optimal interface heat transfer coefficient;

[0080] When the second relative deviation is less than or equal to the deviation threshold, determining the final optimal thermal conductivity to be the current optimal thermal conductivity;

[0081] When the third relative deviation is less than or equal to the deviation threshold, the final optimal interface heat transfer coefficient is determined to be the current optimal interface heat transfer coefficient.

[0082] Specifically, the deviation threshold may be 5% to 10%, and when the current number of iterations reaches the iteration number threshold (for example, 20 times), the current optimal thermal conductivity and the current optimal interface heat transfer coefficient are obtained;

[0083] Then, the two parameters are separated, and the casting is simulated using the current optimal thermal conductivity to obtain a relative deviation between the measured temperature of the casting and the simulated temperature of the digital model of the casting obtained by simulating the casting using the current optimal thermal conductivity;

[0084] The casting is simulated by using the current optimal interface heat transfer coefficient to obtain a relative deviation between the measured temperature of the casting and the simulated temperature of a digital model of the casting obtained by simulating the casting by using the current optimal interface heat transfer coefficient;

[0085] The two relative deviations are similar to the first relative deviation. The same steps are used to optimize the two parameters respectively until their respective relative deviations are less than or equal to the deviation threshold. The corresponding number of iterative updates can also be set here, which will not be elaborated here.

[0086] Since the simulation optimization is performed separately, the accuracy of the optimization results of the two parameters is improved compared with the existing solutions.

[0087] In one embodiment of the present application, after determining the final optimal thermal conductivity and the final optimal interface heat transfer coefficient, the method further includes:

[0088] The casting is simulated by using the final optimal thermal conductivity and the final optimal interface heat transfer coefficient to obtain a fourth relative deviation, wherein the fourth relative deviation represents a relative deviation between the measured temperature of the casting and a simulated temperature of a digital model of the casting obtained by simulating the casting by using the final optimal thermal conductivity and the final optimal interface heat transfer coefficient;

[0089] When the fourth relative deviation is less than or equal to the deviation threshold, it is determined that the optimization work is completed.

[0090] Specifically, the casting is simulated using the final optimal thermal conductivity and the final optimal interface heat transfer coefficient to obtain a relative deviation between the measured temperature of the casting and a simulated temperature of a digital model of the casting obtained by simulating the casting using the final optimal thermal conductivity and the final optimal interface heat transfer coefficient;

[0091] When the relative deviation is greater than the deviation threshold, an iterative update may be performed again in the same manner as the first relative deviation;

[0092] When the fourth relative deviation is less than or equal to the deviation threshold, it is determined that the optimization work is completed, and the final optimal thermal conductivity and the final optimal interface heat transfer coefficient are taken as optimal values.

[0093] Various relative deviations can reflect the influence of thermal conductivity and interface heat transfer coefficient on temperature change.

[0094] It is precisely because of the multiple optimizations that the optimization method is more efficient and more accurate than the existing solutions.

[0095] Prepare the digital model of the casting / mold and the physical casting / mold. The digital model of the casting / mold is consistent with the physical casting.

[0096] Thermocouple arrangement: Virtual thermocouples are arranged in the digital model of the casting / mold, and physical thermocouples are arranged in the physical casting / mold. The digital model of the casting / mold and the physical thermocouple arrangement positions are consistent. The thermocouple is d≤10mm away from the casting-coating-mold interface. The thermocouple in the mold is preferably arranged at 3mm≤d≤7mm (if the distance is too close, the molten metal will directly contact the thermocouple when it immerses in the mold; if the distance is too far, the thermocouple's sensitivity to temperature will decrease); the thermocouple in the casting is preferably arranged at 2mm≤d≤10mm.

[0097] Acquisition of casting temperature simulation data: The temperature field of the casting and the mold core is obtained by simulation calculation, and then the temperature-time variation curve of the characteristic point on the simulation geometric model corresponding to the temperature measurement point is obtained;

[0098] On-site temperature measurement of the model: During the on-site casting pouring, filling, solidification and cooling process, the temperature is measured experimentally to collect the temperature variation curve of the casting and mold feature points over time;

[0099] According to the ratio range of the time points corresponding to the two curves, the value range of the first adjustment coefficient and the second adjustment coefficient corresponding to the range is determined.

[0100] Figure 2 The positional relationship of the thermocouple, overflow structure, upper sand mold, lower sand mold and stepped casting in the casting is shown;

[0101] Figure 3 The structure of the stepped casting and sand mold is shown, including the overflow structure, runner structure, thermocouple in the casting, thermocouple in the sand mold, upper sand mold, lower sand mold and L-shaped fit.

[0102] Figure 4 The positional relationship of thermocouples in castings, runners, sprues, overflow structures, stepped castings, and thermocouples in sand molds is shown;

[0103] Figure 5 The structure of the stepped casting and the pouring and rigging system is shown, in which the overflow structure, runner structure and stepped casting are shown.

[0104] In order to enable those skilled in the art to more clearly understand the technical solution of the present application, the implementation process of the parameter optimization method of the digital model of the casting of the present application will be described in detail below in conjunction with specific embodiments.

[0105] This embodiment relates to a specific method for optimizing parameters of a digital model of a casting, such as Figure 6 As shown, the following steps are included:

[0106] Acquisition step: acquiring a first relative deviation, wherein the first relative deviation represents a relative deviation between a measured temperature of the casting and a simulated temperature of a digital model of the casting;

[0107] Adjustment step: when the first relative deviation is a positive number, increase the thermal conductivity and interface heat transfer coefficient of the digital model of the casting; when the first relative deviation is a negative number, reduce the thermal conductivity and interface heat transfer coefficient of the digital model of the casting; when the first relative deviation is 0, determine that the current thermal conductivity and interface heat transfer coefficient are optimal values;

[0108] Processing step: repeatedly executing the acquisition step and the adjustment step to iteratively update the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting until the current number of iterations reaches an iteration number threshold and / or the current relative deviation of the digital model of the casting is less than or equal to the deviation threshold, the current relative deviation representing the relative deviation between the measured temperature of the casting and the simulated temperature of the digital model of the casting obtained by simulating the casting using the current thermal conductivity and the interface heat transfer coefficient;

[0109] When the current number of iterations reaches the iteration number threshold, the current optimal thermal conductivity and the current optimal interface heat transfer coefficient are obtained;

[0110] The casting is simulated using the current optimal thermal conductivity to obtain a second relative deviation, wherein the second relative deviation represents a relative deviation between a measured temperature of the casting and a simulated temperature of a digital model of the casting obtained by simulating the casting using the current optimal thermal conductivity;

[0111] The casting is simulated using the current optimal interface heat transfer coefficient to obtain a third relative deviation, wherein the third relative deviation represents a relative deviation between the measured temperature of the casting and the simulated temperature of the digital model of the casting obtained by simulating the casting using the current optimal interface heat transfer coefficient;

[0112] When the second relative deviation is less than or equal to the deviation threshold, determining the final optimal thermal conductivity as the current optimal thermal conductivity;

[0113] When the third relative deviation is less than or equal to the deviation threshold, the final optimal interface heat transfer coefficient is determined to be the current optimal interface heat transfer coefficient.

[0114] After determining the final optimal thermal conductivity and the final optimal interface heat transfer coefficient, the casting is simulated using the final optimal thermal conductivity and the final optimal interface heat transfer coefficient to obtain a fourth relative deviation, wherein the fourth relative deviation represents a relative deviation between the measured temperature of the casting and the simulated temperature of the digital model of the casting obtained by simulating the casting using the final optimal thermal conductivity and the final optimal interface heat transfer coefficient;

[0115] When the fourth relative deviation is less than or equal to the deviation threshold, it is determined that the optimization work is completed.

[0116] The simulation accuracy is judged based on the relative deviation between the measured temperature and the simulated temperature, thereby improving the reliability of the judgment. According to the positive or negative value of the first relative deviation, the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting are increased, or the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting are reduced, so that the optimization direction of the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting can be more accurate, thereby improving the optimization efficiency. The acquisition step and the adjustment step are repeatedly performed to iteratively update the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting until the current number of iterations reaches the iteration number threshold, and / or the current relative deviation of the digital model of the casting is less than or equal to the deviation threshold, thereby continuously optimizing in an iterative updating manner, and when the current relative deviation is considered to be within the allowable range, the optimal parameters can be determined, thereby solving the problem that in order to improve the simulation accuracy of the digital model of the casting, the existing scheme only relies on historical data for experience summary to optimize the parameters of the digital model, thereby resulting in low optimization efficiency of the parameters of the digital model of the existing scheme.

[0117] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0118] The embodiment of the present application also provides a parameter optimization device for a digital model of a casting. It should be noted that the parameter optimization device for a digital model of a casting in the embodiment of the present application can be used to execute the parameter optimization method for a digital model of a casting provided in the embodiment of the present application. The device is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceived.

[0119] The following is an introduction to the parameter optimization device for the digital model of the casting provided in the embodiment of the present application.

[0120] Figure 7 1 is a structural block diagram of a device for optimizing parameters of a digital model of a casting provided in accordance with an embodiment of the present application. Figure 7 As shown, the device comprises:

[0121] A first acquisition unit 71 is used to perform an acquisition step: acquiring a first relative deviation, wherein the first relative deviation represents a relative deviation between a measured temperature of the casting and a simulated temperature of the digital model of the casting;

[0122] The adjusting unit 72 is used to perform an adjusting step: increasing the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting, or decreasing the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting according to the positive or negative value of the first relative deviation;

[0123] The first processing unit 73 is used to execute a processing step: repeatedly execute the above-mentioned acquisition step and the above-mentioned adjustment step to iteratively update the above-mentioned thermal conductivity and the above-mentioned interface heat transfer coefficient of the above-mentioned digital model of the casting until the current number of iterations reaches an iteration number threshold, and / or the current relative deviation of the above-mentioned digital model of the casting is less than or equal to a deviation threshold, and the above-mentioned current relative deviation represents the relative deviation between the above-mentioned measured temperature of the above-mentioned casting and the simulated temperature of the digital model of the casting obtained by simulating the above-mentioned casting using the current above-mentioned thermal conductivity and the above-mentioned interface heat transfer coefficient.

[0124] In the above device, the relative deviation between the measured temperature and the simulated temperature is used as a reference to judge the simulation accuracy, thereby improving the reliability of the judgment. According to the positive or negative value of the above first relative deviation, the thermal conductivity and the interface heat transfer coefficient of the above digital model of the casting are increased, or the above thermal conductivity and the above interface heat transfer coefficient of the above digital model of the casting are reduced, so that the optimization direction of the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting can be more accurate, thereby improving the optimization efficiency. The above acquisition step and the above adjustment step are repeatedly performed to iteratively update the above thermal conductivity and the above interface heat transfer coefficient of the digital model of the casting until the current number of iterations reaches the iteration number threshold, and / or the current relative deviation of the digital model of the casting is less than or equal to the deviation threshold, so as to continuously optimize in an iterative update manner, and when the current relative deviation is considered to be within the allowable range, the optimal parameters can be determined, thereby solving the problem that in order to improve the simulation accuracy of the digital model of the casting, the existing scheme only relies on historical data for experience summary to optimize the parameters of the digital model, thereby resulting in low optimization efficiency of the parameters of the digital model of the existing scheme.

[0125] In one embodiment of the present application, the adjustment unit includes a first adjustment module and a second adjustment module.

[0126] The first adjustment module is used for increasing the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting when the first relative deviation is a positive number;

[0127] The second adjustment module is used to reduce the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting when the first relative deviation is a negative number.

[0128] In one embodiment of the present application, the adjustment unit includes a first determination module.

[0129] The first determining module is used to , determine the updated thermal conductivity mentioned above;

[0130] Wherein, λ is the above-mentioned updated thermal conductivity, is the first relative deviation mentioned above, is the initial thermal conductivity, is the first adjustment coefficient.

[0131] In one embodiment of the present application, the adjustment unit includes a second determination module.

[0132] The second determining module is used to , determine the updated interface heat transfer coefficient;

[0133] Wherein, h is the above-mentioned updated interface heat transfer coefficient, is the first relative deviation mentioned above, is the initial interface heat transfer coefficient, is the second adjustment coefficient.

[0134] In one embodiment of the present application, the above-mentioned device further includes a second acquisition unit, a third acquisition unit, a fourth acquisition unit, a second processing unit and a third processing unit.

[0135] The second acquisition unit is used to acquire the current optimal thermal conductivity and the current optimal interface heat transfer coefficient when the current number of iterations reaches the above-mentioned iteration number threshold;

[0136] The third acquisition unit is used to simulate the casting by using the current optimal thermal conductivity to obtain a second relative deviation, wherein the second relative deviation represents a relative deviation between the measured temperature of the casting and a simulated temperature of a digital model of the casting obtained by simulating the casting by using the current optimal thermal conductivity;

[0137] The fourth acquisition unit is used to simulate the casting by using the current optimal interface heat transfer coefficient to obtain a third relative deviation, wherein the third relative deviation represents a relative deviation between the measured temperature of the casting and a simulated temperature of a digital model of the casting obtained by simulating the casting by using the current optimal interface heat transfer coefficient;

[0138] The second processing unit is used for determining the final optimal thermal conductivity as the current optimal thermal conductivity when the second relative deviation is less than or equal to the deviation threshold;

[0139] The third processing unit is used to determine that the final optimal interface heat transfer coefficient is the current optimal interface heat transfer coefficient when the third relative deviation is less than or equal to the deviation threshold.

[0140] In one embodiment of the present application, the apparatus further includes a fourth processing unit and a fifth processing unit. After determining the final optimal thermal conductivity and the final optimal interface heat transfer coefficient, the method further includes:

[0141] The fourth processing unit is used to simulate the casting by using the final optimal thermal conductivity and the final optimal interface heat transfer coefficient to obtain a fourth relative deviation, wherein the fourth relative deviation represents a relative deviation between the measured temperature of the casting and a simulated temperature of a digital model of the casting obtained by simulating the casting by using the final optimal thermal conductivity and the final optimal interface heat transfer coefficient;

[0142] The fifth processing unit is used to determine that the optimization work is completed when the fourth relative deviation is less than or equal to the deviation threshold.

[0143] In one embodiment of the present application, the first acquisition unit includes a third determination module.

[0144] The third determination module is used to , determine the above-mentioned first relative deviation;

[0145] in, is the first relative deviation mentioned above, is the above-mentioned simulation temperature of the above-mentioned casting digital model, is the measured temperature of the above casting.

[0146] The above-mentioned parameter optimization device for the digital model of the casting includes a processor and a memory, and the above-mentioned first acquisition unit, adjustment unit and first processing unit are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize the corresponding functions. The above-mentioned modules are all located in the same processor; or, the above-mentioned modules are located in different processors in the form of any combination.

[0147] The processor includes a kernel, and the kernel retrieves the corresponding program unit from the memory. One or more kernels can be set, and the kernel parameters can be adjusted to solve the problem that in order to improve the simulation accuracy of the digital model of the casting, the existing scheme only relies on historical data for experience summary to optimize the parameters of the digital model, which leads to the low optimization efficiency of the parameters of the digital model of the existing scheme.

[0148] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0149] An embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the parameter optimization method of the digital model of the casting.

[0150] The embodiment of the present invention provides a device, the device includes a processor, a memory and a program stored in the memory and can be run on the processor, and the processor implements at least the following steps when executing the program: an acquisition step: acquiring a first relative deviation, the first relative deviation characterizing the relative deviation between the actual measured temperature of the casting and the simulated temperature of the digital model of the casting; an adjustment step: increasing the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting, or reducing the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting according to the positive or negative of the first relative deviation; a processing step: repeatedly executing the acquisition step and the adjustment step to iteratively update the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting until the current number of iterations reaches the iteration number threshold, and / or the current relative deviation of the digital model of the casting is less than or equal to the deviation threshold, the current relative deviation characterizing the relative deviation between the actual measured temperature of the casting and the simulated temperature of the digital model of the casting obtained by simulating the casting using the current thermal conductivity and the interface heat transfer coefficient. The device in this article can be a server, a PC, a PAD, a mobile phone, etc.

[0151] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program initialized with at least the following method steps: an acquisition step: acquiring a first relative deviation, the first relative deviation characterizing the relative deviation between the actual measured temperature of the casting and the simulated temperature of the digital model of the casting; an adjustment step: increasing the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting, or decreasing the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting according to the positive or negative value of the first relative deviation; a processing step: repeatedly executing the acquisition step and the adjustment step to iteratively update the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting until the current number of iterations reaches an iteration number threshold, and / or the current relative deviation of the digital model of the casting is less than or equal to a deviation threshold, the current relative deviation characterizing the relative deviation between the actual measured temperature of the casting and the simulated temperature of the digital model of the casting obtained by simulating the casting using the current thermal conductivity and the interface heat transfer coefficient.

[0152] The present application also provides a parameter optimization system for a digital model of a casting, the system comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include means for executing any one of the above methods. The simulation accuracy is judged based on the relative deviation between the measured temperature and the simulated temperature, thereby improving the reliability of the judgment. According to the positive or negative value of the first relative deviation, the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting are increased, or the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting are reduced, so that the optimization direction of the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting can be more accurate, thereby improving the optimization efficiency. The acquisition step and the adjustment step are repeatedly performed to iteratively update the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting until the current number of iterations reaches the iteration number threshold, and / or the current relative deviation of the digital model of the casting is less than or equal to the deviation threshold, thereby continuously optimizing in an iterative updating manner, and when the current relative deviation is considered to be within the allowable range, the optimal parameters can be determined, thereby solving the problem that in order to improve the simulation accuracy of the digital model of the casting, the existing scheme only relies on historical data for experience summary to optimize the parameters of the digital model, thereby resulting in low optimization efficiency of the parameters of the digital model of the existing scheme.

[0153] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0154] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0155] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0156] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0157] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0158] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0159] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0160] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0161] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0162] From the above description, it can be seen that the above embodiments of the present application achieve the following technical effects:

[0163] 1) The parameter optimization method of the digital model of the casting of the present application uses the relative deviation between the measured temperature and the simulated temperature as a benchmark to judge the simulation accuracy, thereby improving the reliability of the judgment. According to the positive or negative value of the first relative deviation, the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting are increased, or the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting are reduced, so that the optimization direction of the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting can be more accurate, thereby improving the optimization efficiency. Repeat the acquisition step and the adjustment step to iteratively update the casting. The thermal conductivity and the interface heat transfer coefficient of the digital model of the casting are calculated until the current number of iterations reaches the iteration number threshold, and / or the current relative deviation of the digital model of the casting is less than or equal to the deviation threshold, thereby continuously optimizing in an iterative updating manner, and when the current relative deviation is considered to be within the allowable range, the optimal parameters can be determined, thereby solving the problem that in order to improve the simulation accuracy of the digital model of the casting, the existing scheme only relies on historical data for experience summary to optimize the parameters of the digital model, thereby resulting in low optimization efficiency of the parameters of the digital model of the existing scheme.

[0164] 2) The parameter optimization device for the digital model of the casting of the present application uses the relative deviation between the measured temperature and the simulated temperature as a reference to judge the simulation accuracy, thereby improving the reliability of the judgment. According to the positive or negative value of the above-mentioned first relative deviation, the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting are increased, or the above-mentioned thermal conductivity and the above-mentioned interface heat transfer coefficient of the digital model of the casting are reduced, which can make the optimization direction of the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting more accurate, thereby improving the optimization efficiency. Repeat the above-mentioned acquisition step and the above-mentioned adjustment step to iteratively update the above-mentioned casting. The thermal conductivity and the interface heat transfer coefficient of the digital model of the casting are calculated until the current number of iterations reaches the iteration number threshold, and / or the current relative deviation of the digital model of the casting is less than or equal to the deviation threshold, thereby continuously optimizing in an iterative updating manner, and when the current relative deviation is considered to be within the allowable range, the optimal parameters can be determined, thereby solving the problem that in order to improve the simulation accuracy of the digital model of the casting, the existing scheme only relies on historical data for experience summary to optimize the parameters of the digital model, thereby resulting in low optimization efficiency of the parameters of the digital model of the existing scheme.

[0165] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for optimizing parameters of a digital model of a casting, characterized in that: include: Acquisition step: acquiring a first relative deviation, wherein the first relative deviation represents a relative deviation between a measured temperature of the casting and a simulated temperature of a digital model of the casting; Adjustment step: increasing the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting, or decreasing the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting according to the positive or negative value of the first relative deviation; Processing step: repeatedly executing the acquisition step and the adjustment step to iteratively update the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting until the current number of iterations reaches an iteration number threshold, and / or the current relative deviation of the digital model of the casting is less than or equal to a deviation threshold, wherein the current relative deviation represents a relative deviation between the measured temperature of the casting and the simulated temperature of the digital model of the casting obtained by simulating the casting using the current thermal conductivity and the interface heat transfer coefficient; Increasing the thermal conductivity of the digital model of the casting, or decreasing the thermal conductivity of the digital model of the casting, comprises: according to , determine the updated thermal conductivity; Wherein, λ is the updated thermal conductivity, is the first relative deviation, is the initial thermal conductivity, is the first adjustment coefficient; Increasing the interface heat transfer coefficient of the digital model of the casting, or reducing the interface heat transfer coefficient of the digital model of the casting, comprises: according to , determine the updated interface heat transfer coefficient; Wherein, h is the updated interface heat transfer coefficient, is the first relative deviation, is the initial interface heat transfer coefficient, is the second adjustment coefficient; If 3%≤| |≤45%, then ∈(0, 0.7), ∈(0, 0.6).

2. The method according to claim 1, characterized in that Increasing the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting, or decreasing the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting according to the positive or negative value of the first relative deviation, comprises: When the first relative deviation is a positive number, increasing the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting; When the first relative deviation is a negative number, the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting are reduced.

3. The method according to claim 1, characterized in that The method further comprises: When the current number of iterations reaches the iteration number threshold, obtaining the current optimal thermal conductivity and the current optimal interface heat transfer coefficient; The casting is simulated using the current optimal thermal conductivity to obtain a second relative deviation, wherein the second relative deviation represents a relative deviation between the measured temperature of the casting and a simulated temperature of a digital model of the casting obtained by simulating the casting using the current optimal thermal conductivity; The casting is simulated using the current optimal interface heat transfer coefficient to obtain a third relative deviation, wherein the third relative deviation represents a relative deviation between the measured temperature of the casting and a simulated temperature of a digital model of the casting obtained by simulating the casting using the current optimal interface heat transfer coefficient; When the second relative deviation is less than or equal to the deviation threshold, determining the final optimal thermal conductivity to be the current optimal thermal conductivity; When the third relative deviation is less than or equal to the deviation threshold, the final optimal interface heat transfer coefficient is determined to be the current optimal interface heat transfer coefficient.

4. The method according to claim 3, characterized in that After determining the final optimal thermal conductivity and the final optimal interface heat transfer coefficient, the method further includes: The casting is simulated using the final optimal thermal conductivity and the final optimal interface heat transfer coefficient to obtain a fourth relative deviation, wherein the fourth relative deviation represents a relative deviation between the measured temperature of the casting and a simulated temperature of a digital model of the casting obtained by simulating the casting using the final optimal thermal conductivity and the final optimal interface heat transfer coefficient; When the fourth relative deviation is less than or equal to the deviation threshold, it is determined that the optimization work is completed.

5. The method according to any one of claims 1 to 4, characterized in that Obtaining the first relative deviation includes: according to , determining the first relative deviation; in, is the first relative deviation, is the simulation temperature of the digital model of the casting, is the measured temperature of the casting.

6. A device for optimizing parameters of a digital model of a casting, characterized in that: include: A first acquisition unit is used to perform an acquisition step: acquiring a first relative deviation, wherein the first relative deviation represents a relative deviation between a measured temperature of the casting and a simulated temperature of the digital model of the casting; an adjusting unit, configured to perform an adjusting step: increasing the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting, or decreasing the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting, according to the positive or negative value of the first relative deviation; A first processing unit is used to execute a processing step: repeatedly executing the acquiring step and the adjusting step to iteratively update the thermal conductivity and the interface heat transfer coefficient of the digital model of the casting until the current number of iterations reaches an iteration number threshold and / or the current relative deviation of the digital model of the casting is less than or equal to a deviation threshold, wherein the current relative deviation represents a relative deviation between the measured temperature of the casting and a simulated temperature of the digital model of the casting obtained by simulating the casting using the current thermal conductivity and the interface heat transfer coefficient; The adjustment unit includes a first determination module and a second determination module. The first determining module is used to , determine the updated thermal conductivity; Wherein, λ is the updated thermal conductivity, is the first relative deviation, is the initial thermal conductivity, is the first adjustment coefficient; The second determining module is used to , determine the updated interface heat transfer coefficient; Wherein, h is the updated interface heat transfer coefficient, is the first relative deviation, is the initial interface heat transfer coefficient, is the second adjustment coefficient; If 3%≤| |≤45%, then ∈(0, 0.7), ∈(0, 0.6).

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the method according to any one of claims 1 to 5.

8. A parameter optimization system for a digital model of a casting, characterized in that: include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include methods for executing any one of claims 1 to 5.

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