Multi-field coupling and forward optimization ring piece process parameter determination method and system

Abstract

The invention provides a multi-field coupling and forward optimization ring piece process parameter determination method and system, and is applied to the technical field of ring piece manufacturing. Comprising the steps that the initial blank size and the initial forming path of a ring piece blank and the target blank size of a finish-forged ring piece are obtained; starting from the last forming stage of the multiple forming stages included in the initial forming path, the input blank size of each forming stage is reversely deduced; forming process parameters are determined according to the input blank size and the output blank size of each forming stage, and then an optimal forming path is generated; starting from the first forming stage of the optimal forming path, optimizing the first process parameters to obtain second process parameters according to a plurality of physical fields obtained by simulating the currently traversed forming stage by adopting the first process parameters and key variables which have the maximum influence on the equivalent stress peak value; and determining optimal process parameters according to the respective second process parameters of the plurality of forming stages. And the accuracy and the reliability of the optimal process parameters are ensured.

Description

Technical Field

[0001] This application relates to the field of ring component manufacturing technology, and in particular to a method and system for determining ring component process parameters through multi-field coupling and forward optimization. Background Technology

[0002] Ring forgings (hereinafter referred to as rings) are widely used in high-performance engines and key load-bearing components in the aerospace field due to their excellent comprehensive mechanical properties and structural stability. With the continuous iteration of aerospace equipment, extreme requirements are placed on the structural efficiency and service reliability of rings, which directly depends on the precise design and efficient optimization of forming process parameters.

[0003] However, traditional methods for determining process parameters for ring components rely heavily on the experience-based trial and error of process engineers and repeated physical experiments, which cannot meet the needs of rapid research and development. They are time-consuming and costly. Furthermore, the determination of process parameters lacks a solid scientific basis, making it difficult to guarantee the accuracy and reliability of the final process parameters. Summary of the Invention

[0004] This application provides a method and system for determining process parameters of ring components using multi-field coupling and forward optimization. It employs a process of reverse-engineering the billet dimensions at each forming stage from the final forged ring component, constructing a theoretically geometrically feasible optimal forming path that satisfies constraints. This systematically replaces the experience-based trial-and-error process, improving design efficiency and feasibility from the outset and shortening the R&D cycle. Furthermore, multi-field coupling simulations are performed on each forming stage based on this optimal forming path. By identifying and precisely optimizing key variables most sensitive to the peak equivalent stress, the determination of optimal process parameters is based on solid physical simulation, significantly improving the accuracy and reliability of the final process scheme and reducing reliance on and cost of physical experiments.

[0005] This application provides a method for determining the process parameters of a ring component through multi-field coupling and forward optimization, including: Obtain the initial billet size and initial forming path of the ring blank, and the target billet size of the final forged ring. The initial forming path includes multiple consecutive forming stages. Starting from the last forming stage among the plurality of forming stages, the input billet size for each forming stage is calculated in reverse, wherein the initial billet size is the input billet size of the first forming stage among the plurality of forming stages, and the target billet size is the output billet size of the last forming stage; based on the input and output billet sizes of each forming stage, the forming process parameters for each forming stage are determined; and based on the forming process parameters of each forming stage, the optimal forming path for the final forged ring is generated; Starting from the first forming stage included in the optimal forming path, for the currently traversed forming stage, based on the multiple physical fields obtained after simulating the forming stage using the first process parameters, and the key variables that have the greatest impact on the peak value of the equivalent stress, the first process parameters are optimized to obtain the second process parameters. The optimal process parameters for the final forged ring are determined based on the second process parameters of each of the multiple forming stages.

[0006] According to an embodiment of this application, a method for determining process parameters of a ring component using multi-field coupling and forward optimization is provided. The method involves determining the forming process parameters for each forming stage based on the input and output billet dimensions, and generating the optimal forming path for the final forged ring component based on the forming process parameters for each forming stage. This includes: for the i-th forming stage, determining the input billet dimension of the i-th forming stage based on the output billet dimension and the rib thickening amount of the i-th forming stage; determining the forming process parameters for the i-th forming stage based on the output and input billet dimensions; retaining the i-th forming stage if the forming process parameters meet the constraints; adjusting the initial billet dimension and performing a new reverse calculation starting from the last forming stage until the i-th forming stage is retained; and generating the optimal forming path for the final forged ring component based on the retained forming stages if the reverse calculation returns to the initial billet dimension and the forming process parameters of the retained forming stages all meet the constraints.

[0007] According to an embodiment of this application, a method for determining process parameters of a ring component using multi-field coupling and forward optimization is provided. The forming process parameters include at least the deformation per firing cycle, the wall thickness reduction rate, and the inner diameter expansion ratio. The forming process parameters satisfy the following constraints: the deformation per firing cycle is within a preset deformation range; the wall thickness reduction rate is not greater than a preset reduction rate threshold; and the inner diameter expansion ratio is not greater than a preset expansion threshold.

[0008] According to an embodiment of this application, a method for determining process parameters of a ring component using multi-field coupling and forward optimization is provided. The method involves optimizing the first process parameters to obtain second process parameters based on multiple physical fields obtained after simulating the forming stage using first process parameters, and the key variables that have the greatest impact on the peak equivalent stress. The steps include: simulating the forming stage using the first process parameters and a material model to obtain the multiple physical fields, which at least include a flow field, a temperature field, and a strain field; determining the quality index and the peak equivalent stress of the forming stage based on the flow field, the temperature field, and the strain field; determining the coupling optimization objective corresponding to the quality index, and the key variables that have the greatest impact on the peak equivalent stress; and optimizing the first process parameters based on the key variables to improve the coupling optimization objective, thereby obtaining the second process parameters.

[0009] According to an embodiment of this application, a method for determining process parameters of a ring component using multi-field coupling and forward optimization is provided. The quality indicators include at least the continuity of metal flow lines, the maximum equivalent variable, and the temperature gradient. The improvement of the coupling optimization objective includes at least: ensuring that the continuity of metal flow lines is greater than a preset threshold; ensuring that the maximum equivalent variable is less than a preset variable threshold; and ensuring that the temperature gradient is less than a preset gradient threshold.

[0010] According to an embodiment of this application, a method for determining process parameters of a ring component using multi-field coupling and forward optimization is provided. The first process parameters include at least heating temperature, rolling force, and deformation per pass in each forming stage. The optimization of the first process parameters based on the key variables to obtain the second process parameters includes: optimizing the rolling force and deformation per pass when the key variable is the maximum strain gradient; optimizing the heating temperature and reheating timing through the temperature field when the key variable is metal temperature; dynamically optimizing the rolling force using a variable step size control algorithm when the key variable is metal flow rate difference; and optimizing the deformation per pass when the key variables are material flow direction, maximum temperature rise, and microstructure uniformity.

[0011] According to an embodiment of this application, a method for determining process parameters of a ring component using multi-field coupling and forward optimization is provided. The first process parameters include at least heating temperature, rolling force, stage sequence, and deformation per pass in each forming stage. The material model includes at least a constitutive model, heat conduction parameters, and a friction model. The step of simulating the forming stage based on the first process parameters and the material model to obtain the multiple physical fields includes: constructing a three-dimensional finite element model corresponding to the forming stage based on the heating temperature, rolling force, stage sequence, deformation per pass in each forming stage, constitutive model, heat conduction parameters, and friction model; simulating the three-dimensional finite element model and solving it using an explicit integral and fully coupled solver to simultaneously calculate the multiple physical fields.

[0012] This application also provides a system for determining process parameters of a ring component through multi-field coupling and forward optimization, including: The acquisition module is used to acquire the initial billet size and initial forming path of the ring blank, and the target billet size of the final forged ring. The initial forming path includes multiple consecutive forming stages. The reverse design module is used to reverse engineer the input billet size of each forming stage, starting from the last forming stage among the plurality of forming stages. The initial billet size is the input billet size of the first forming stage, and the target billet size is the output billet size of the last forming stage. Based on the input and output billet sizes of each forming stage, the module determines the forming process parameters for each forming stage. Based on the forming process parameters of each forming stage, the module generates the optimal forming path for the final forged ring. The parameter optimization module is used to traverse from the first forming stage included in the optimal forming path, and for the currently traversed forming stage, optimize the first process parameters based on multiple physical fields obtained after simulating the forming stage using the first process parameters, as well as the key variables that have the greatest impact on the peak value of the equivalent stress, to obtain the second process parameters; and determine the optimal process parameters of the final forged ring based on the second process parameters of each of the multiple forming stages.

[0013] This application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method for determining ring process parameters of multi-field coupling and forward optimization as described above.

[0014] This application also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the method for determining ring process parameters of multi-field coupling and forward optimization as described above.

[0015] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the method for determining ring process parameters of multi-field coupling and forward optimization as described above.

[0016] The method and system for determining ring component process parameters using multi-field coupling and forward optimization provided in this application obtain the initial billet size and initial forming path of the ring component blank, as well as the target billet size of the final forged ring component. The initial forming path includes multiple consecutive forming stages. Starting from the last forming stage, the input billet size of each forming stage is calculated backwards. The initial billet size is the input billet size of the first forming stage, and the target billet size is the output billet size of the last forming stage. Based on the input billet size of each forming stage... The forming process parameters for each forming stage are determined based on the dimensions and output billet dimensions. An optimal forming path for the final forged ring is generated based on these forming process parameters. Starting from the first forming stage included in the optimal forming path, the process is iterated. For each currently traversed forming stage, the first process parameters are optimized based on multiple physical fields obtained after simulating the forming stage using the first process parameters, as well as the key variables that have the greatest impact on the peak equivalent stress, to obtain second process parameters. The optimal process parameters for the final forged ring are determined based on the second process parameters for each of the multiple forming stages. This method employs a reverse engineering approach, working backward from the final forged ring to deduce the billet dimensions for each forming stage. This constructs a theoretically geometrically feasible and constraint-satisfying optimal forming path, systematically replacing the experience-based trial-and-error process. This fundamentally improves design efficiency and feasibility, shortens the R&D cycle, and, based on this optimal forming path, performs multi-field coupled simulations for each forming stage. By identifying the key variables most sensitive to the peak equivalent stress, precise optimization is achieved, establishing the determination of optimal process parameters on a solid physical simulation basis. This significantly improves the accuracy and reliability of the final process scheme, reducing reliance on and cost of physical experiments. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating the method for determining ring process parameters through multi-field coupling and forward optimization provided in the embodiments of this application. Figure 2 This is a schematic diagram of the optimal forming path corresponding to the TC4 ring provided in the embodiments of this application; Figure 3 These are high and low magnification microstructure diagrams of the TC4 ring provided in the embodiments of this application; Figure 4 This is a schematic diagram of the optimal forming path corresponding to the IN718 ring provided in the embodiments of this application; Figure 5 These are high and low magnification microstructure diagrams of the IN718 ring provided in this application embodiment; Figure 6 This is a schematic diagram of the structure of the ring component process parameter determination system with multi-field coupling and forward optimization provided in the embodiments of this application; Figure 7 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0020] To better understand the embodiments of this application, the application scenarios of the method for determining ring process parameters based on multi-field coupling and forward optimization provided in the embodiments of this application are first described: In addition to its application in aerospace technology, it can also be applied in energy equipment (such as wind turbine bearing rings in wind power, nuclear reactor pressure vessel support rings in nuclear power, and magnetic rings for hydropower turbine generator sets), transportation (such as high-speed rail / subway wheels in rail transit, and piston rings and bearing rings for large marine diesel engines in shipbuilding), and defense and heavy machinery (such as slewing bearing rings used in military equipment for manufacturing tanks and armored vehicles), and other scenarios that require rapid R&D while ensuring the accuracy and reliability of the final process parameters.

[0021] It should be noted that the execution entity involved in the embodiments of this application can be a multi-field coupling and forward optimization ring component process parameter determination system, or it can be an electronic device. Optionally, the electronic device may include: computer / laptop, mobile terminal and wearable device, etc.

[0022] The following section uses an electronic device as an example to elaborate on the method for determining ring component process parameters through multi-field coupling and forward optimization provided in the embodiments of this application: Figure 1This is a flowchart illustrating the method for determining ring process parameters through multi-field coupling and forward optimization provided in this application. Figure 1 As shown, the method includes the following steps 101-104.

[0023] Step 101: Obtain the initial billet size and initial forming path of the ring blank, and the target billet size of the final forged ring. The initial forming path includes multiple consecutive forming stages.

[0024] Among them, ring blank refers to the initial metal material that has been cut and heated before being prepared for ring forging. It is usually a solid or hollow forging blank in the shape of a cylinder or near cylinder.

[0025] The initial blank size refers to the geometric dimensions of the ring blank before it undergoes the first forming stage (or the first forming pass). Optionally, the initial blank size may include at least the initial blank volume, the initial blank outer diameter, and the initial blank height.

[0026] The initial forming path refers to the sequence of processing steps that need to be taken from the initial billet to the final forged ring, which is initially planned based on experience. Optionally, the multiple consecutive forming stages may include at least the punching / upsetting punching stage, the pre-rolling stage (such as the rectangular pre-rolling stage, the irregular shape pre-rolling stage, etc.), the final rolling stage, and the bulging stage (that is, the bulging and rounding stage, which may include at least the irregular shape final rolling first fire stage and the irregular shape final rolling second fire stage).

[0027] A final forged ring refers to a ring-shaped forging that meets the requirements of the product drawings after all forming stages of processing have been completed.

[0028] The target billet size refers to the final geometric dimensions of the forged ring after the last forming stage (i.e., the bulging stage). Optionally, the target billet size may include at least the target billet volume, the target billet outer diameter, and the target billet height.

[0029] For example, the ring material can be TC4 ring or IN718 ring. For TC4 ring, the corresponding initial blank size is Φ304.8×603mm, with a chamfer radius of R10-20mm. For IN718 ring, the corresponding initial blank size is Φ300×477mm, with a chamfer radius of R10-20mm. Here, Φ represents the diameter, and R represents the radius.

[0030] It should be noted that for thin-walled, large-diameter rings, rolling passes are usually designed in a 1-to-2 or multi-pass manner to ensure forming stability and wall thickness uniformity.

[0031] Optionally, the process for determining the target billet size is as follows: The electronic device acquires the product drawing of the final forged ring; the electronic device performs three-dimensional geometric modeling on the product drawing to calculate the target billet volume and target billet mass of the final forged ring; based on the law of volume conservation and taking into account the burning loss, flash, and punching allowance during the material hot working process, the electronic device back-calculates the target billet size that the final forged ring should have at the end of the bulging stage.

[0032] It should be noted that the timing of the electronic equipment acquiring the initial blank size, initial forming path, and target blank size is not limited.

[0033] Optionally, prior to step 101, the method may further include: a database of electronic device construction materials and equipment, which may include at least a materials database, an equipment database, and a process rule library.

[0034] Specifically, the materials database can include at least the physical, mechanical, and thermal properties of the ring material, such as density, specific heat, thermal conductivity, yield strength, ultimate tensile strength, coefficient of thermal expansion, and resistance to thermal deformation. Furthermore, this materials data block can also record stress-strain curves and microstructure evolution at different temperatures.

[0035] The equipment database should include at least information such as hydraulic press specifications, maximum pressure, rolling roll diameter, die temperature control capability, heating furnace heating rate and heat preservation capability.

[0036] The process rule library can record the process parameters, allowable strain, maximum rolling force and precautions for each forming pass, such as upsetting and punching, rectangular pre-rolling, irregular pre-rolling, final rolling and bulging, based on typical ring forging process cases, providing rule support for positive process optimization design.

[0037] For example, based on the aforementioned material database, the electronic device can collect high-temperature physical property parameters of more than 20 new materials and difficult-to-deform alloys, such as GH4742, GH4586, GH4065A, TC18, TC21, and C61, covering a temperature range of 850-1250℃ and a strain rate range of 0.001-10s⁻¹, thus supplementing the deficiencies of existing simulation software databases.

[0038] Based on the aforementioned equipment database, this electronic device can record key parameters such as radial / axial rolling force (range 500-3000kN), ring outer diameter (300-3000mm), height (50-800mm), and ring speed during the actual rolling process, thereby achieving a closed-loop comparison between simulation results and actual data.

[0039] Based on the aforementioned process rule library, this electronic device can summarize the stable process rules for different materials and rings of different sizes at each forming stage, including heating temperature (e.g., 950-1180℃), rolling force, deformation amount of each heat treatment (e.g., 10%-35%), and stage sequence.

[0040] Optionally, the database may also include a product model library. Based on this product model library, electronic devices can perform 3D modeling of typical manufactured ring components, along with process paths, defect distributions, and optimization experience, providing direct reference for subsequent ring component process design.

[0041] It should be noted that the aforementioned database enables the structured accumulation and reuse of process experience, which can be directly called upon in the subsequent production of similar complex ring components. It can be used for rapid and repeatable production of different materials and ring component specifications, shortening the process design cycle by more than 40% and significantly improving design efficiency. At the same time, the database can effectively accumulate experience indices, providing complete data support and an experience reuse platform for the future, and has the value for promotion and application.

[0042] Step 102: Starting from the last forming stage among multiple forming stages, work backwards to deduce the input billet size for each forming stage. The initial billet size is the input billet size of the first forming stage among multiple forming stages, and the target billet size is the output billet size of the last forming stage. Based on the input and output billet sizes of each forming stage, determine the forming process parameters for each forming stage. And based on the forming process parameters of each forming stage, generate the optimal forming path for the final forged ring.

[0043] Among them, forming process parameters refer to the core variables used to define and guide the plastic deformation process of the ring in the corresponding forming stage.

[0044] The optimal forming path refers to a coherent and feasible process sequence that has been reverse-engineered and validated by forming constraints. This optimal forming path not only defines the various forming stages required from the initial blank to the final forged ring, but also specifies the input and output blank dimensions for each forming stage, ensuring that the entire ring forming process is controllable and optimal in terms of geometric evolution and mechanical conditions.

[0045] It should be noted that in cases involving multiple forming stages, including punching, pre-rolling, final rolling, and bulging, punching is the first forming stage, and bulging is the last forming stage. Specifically, the input billet size for the punching stage is the initial billet size mentioned above; the output billet size for the punching stage is the input billet size for the pre-rolling stage; the output billet size for the pre-rolling stage is the input billet size for the final rolling stage; the output billet size for the final rolling stage is the input billet size for the bulging stage; and the output billet size for the bulging stage is the target billet size mentioned above.

[0046] In step 102, the electronic device employs a reverse framework to design suitable forming stages. Specifically, starting from the last forming stage (i.e., the bulging stage), the electronic device reverse-engineers the input billet dimensions for each forming stage, i.e., sequentially reverse-engineering the input billet dimensions for the bulging stage, final rolling stage, pre-rolling stage, and punching stage. Then, based on the input and output billet dimensions for each forming stage, the electronic device determines the forming process parameters for each forming stage, thereby generating the optimal forming path for the final forged ring. The entire process, by employing a reverse framework, systematically generates a geometrically feasible and deformation-controllable optimal forming path, fundamentally avoiding the blind spots inherent in traditional forward trial-and-error methods, and significantly improving the success rate and reliability of ring process design.

[0047] In some embodiments, the electronic device determines the forming process parameters for each forming stage based on the input and output billet dimensions of each forming stage; and generates the optimal forming path for the final forged ring based on the forming process parameters of each forming stage. This may include: for the i-th forming stage, the electronic device determines the input billet dimension of the i-th forming stage based on the output billet dimension and the rib thickening amount of the i-th forming stage; the electronic device determines the forming process parameters for the i-th forming stage based on the output and input billet dimensions of the i-th forming stage; if the forming process parameters meet the constraints, the electronic device retains the i-th forming stage; if the forming process parameters do not meet the constraints, the electronic device adjusts the initial billet dimension and performs a new reverse calculation starting from the last forming stage until the i-th forming stage is retained; if the reverse calculation returns to the initial billet dimension and the forming process parameters of the retained forming stages all meet the constraints, the electronic device generates the optimal forming path for the final forged ring based on the retained forming stages.

[0048] The rib thickening refers to the extra material volume, exceeding the outline of the base billet, designed in advance in specific areas of the preformed billet to ensure that the metal can completely fill the irregular cavities such as ribs and ribs on the ring during the subsequent final forging. This extra material volume is calculated using a volume iteration method to ensure that it is slightly larger (usually 1.05-1.1 times) than the volume of the corresponding rib on the final forged ring, in order to compensate for flow losses.

[0049] Constraints are process limits set to ensure that each forming stage is physically feasible and of reliable quality.

[0050] For example, assuming the i-th forming stage is the final rolling stage, the electronic device determines the input billet size for the final rolling stage based on the output billet size and the rib thickening amount. The electronic device then determines the forming process parameters for the final rolling stage based on both the output and input billet sizes. Next, the electronic device determines whether the forming process parameters meet the constraints. If they do, the billet size designed for the final rolling stage is reasonable, and the final rolling stage and related billet size information can be retained. If they do not meet the constraints, the initial billet size designed at the beginning is unreasonable. In this case, the initial billet size can be adjusted, and a complete reverse calculation process starting from the bulging stage can be executed for iterative correction until a reasonable billet size that meets the constraints is found for the final rolling stage, and the final rolling stage and related billet size information are retained. During the reverse calculation process, if the initial billet size is reverse-calculated back to the initial size, and it is determined that the forming process parameters of the retained forming stages all meet the constraints, the electronic device can then generate the optimal forming path for the final forged ring based on the retained forming stages. The entire process adopts a closed-loop logic of "trial → verification → correction → retrial". When the initial design is unreasonable, it can automatically trace back to the root cause (i.e., the initial billet size needs to be adjusted) and make systematic corrections. It ensures that the billet size, rib thickening amount, deformation amount per firing, and forming stage are interconnected through iterative calculations. This ensures that each forming stage generates billet size, rib thickening amount, deformation amount per firing, and forming stage that both meet process constraints and are mutually coordinated. Finally, it efficiently and reliably outputs a coherent and globally optimal forming path.

[0051] Optionally, the electronic device determines the input blank size of the i-th forming stage based on the output blank size and rib thickening amount of the i-th forming stage. This may include: the electronic device back-calculating the blank volume input in the i-th forming stage based on the target blank size; the electronic device calculating the blank outer diameter and height input in the i-th forming stage according to the principle of volume conservation based on the blank outer diameter and height in the target blank size; and the electronic device using a local material replenishment method based on the rib structure and determining the rib thickening amount of the i-th forming stage through a volume iteration method.

[0052] In some embodiments, the forming process parameters may include at least the deformation per firing, the wall thickness reduction rate, and the inner diameter expansion ratio; the forming process parameters satisfy the following constraints: the deformation per firing is within a preset deformation range; the wall thickness reduction rate is not greater than a preset reduction rate threshold; and the inner diameter expansion ratio is not greater than a preset expansion threshold.

[0053] Among them, the deformation per heating cycle refers to the percentage change in the cross-sectional area of ​​the ring blank within a single heating cycle (i.e., one forming stage). It is usually measured by the cross-sectional shrinkage rate and is a core indicator for balancing production efficiency, microstructure performance, and equipment load.

[0054] Wall thickness reduction rate refers to the degree to which the wall thickness of a ring blank is reduced in a single heating cycle.

[0055] The inner diameter expansion ratio refers to the ratio of the inner diameter after deformation to the inner diameter before deformation during the radial deformation stage of the ring blank, such as hole expansion or rolling (e.g., pre-rolling of irregular shapes).

[0056] If the deformation amount per pass is within the preset deformation range (e.g., 20%-35%), it indicates that the deformation degree of the corresponding forming stage is within the ideal range. If it is below 20%, it means that the grains cannot be sufficiently refined, affecting the material's mechanical properties; if it is above 35%, it may lead to equipment overload, overheating inside the forging, or cracks. This 20%-35% range ensures a balance between deformation efficiency and microstructure properties.

[0057] If the wall thickness reduction rate is not greater than a preset reduction rate threshold (e.g., 30%), it indicates that the wall thickness reduction in the corresponding forming stage is controlled within a safe range. However, an excessively large wall thickness reduction rate significantly increases the risk of voids or cracks forming in the core of the ring blank. This constraint is crucial for ensuring the internal quality integrity of the ring blank.

[0058] If the inner diameter expansion ratio is not greater than the preset expansion threshold (e.g., 2.0), it indicates that the tensile deformation of the inner wall material of the ring blank during the irregular pre-rolling is within the permissible range. If the inner diameter expansion ratio is too large, the inner wall of the ring blank may be torn due to excessive tangential tensile stress. This constraint is a direct guarantee to prevent macroscopic tearing failure of the ring blank.

[0059] Step 103: Start traversing from the first forming stage included in the optimal forming path. For the forming stage being traversed, optimize the first process parameters based on the multiple physical fields obtained after simulating the forming stage using the first process parameters, as well as the key variables that have the greatest impact on the peak value of the equivalent stress, to obtain the second process parameters.

[0060] Among them, the physical field refers to the spatial distribution data obtained through numerical simulation calculations, which describes the physical state of the material during the forming process.

[0061] Equivalent stress is a scalar value derived from the principle of deformation energy, used to comprehensively characterize the mechanical response intensity of a material under complex multi-directional stress states (such as the combined action of compressive, tensile, and shear stresses). It can equate a complex stress state to a simple unidirectional stress, making it easier to intuitively assess whether the material has entered plastic yield and the severity of its deformation. Among them, the peak equivalent stress refers to the maximum equivalent stress that appears inside the ring blank during the entire forming stage simulation. This peak equivalent stress is a key indicator for evaluating the safety and feasibility of the process scheme: an excessively high peak equivalent stress indicates the risk of tearing or cracking of the material, and also reflects the magnitude of the load required by the forming equipment (such as the mold) used in the corresponding forming stage.

[0062] Key variables refer to at least one controllable physical quantity or process indicator that is identified through multi-field coupling simulation and has a dominant influence on a specific failure mode or quality target in the ring forming process.

[0063] In step 103, the electronic device employs forward optimization, traversing from the first forming stage included in the optimal forming path, i.e., starting from the punching stage, sequentially traversing the pre-rolling stage, final rolling stage, and bulging stage. For the currently traversed forming stage, it retrieves the first process parameter corresponding to that forming stage from the aforementioned process rule library. Next, the electronic device uses this first process parameter to simulate the forming stage, obtaining multiple physical fields. The coupled simulation of these multiple physical fields improves the simulation accuracy of each forming stage. To accurately pinpoint the optimization direction and efficiently reduce defect risks and forming loads, the key variables with the greatest impact on the equivalent stress peak value can be identified. Then, based on the aforementioned multiple physical fields and key variables, the first process parameter is optimized or adjusted to obtain the second process parameter. The entire forward optimization process, through physical field simulation and key variable identification, achieves precise and directional adjustment of process parameters, thereby significantly improving optimization efficiency and reducing defect risks and equipment loads while ensuring forming quality, thus improving the forming quality of the final forged ring.

[0064] It should be noted that electronic devices are based on reverse engineering and forward optimization, which can reduce the number of experimental iterations, meet the needs of rapid research and development, and have a short cycle and low cost.

[0065] Alternatively, key variables can be identified by the electronic device using sensitivity analysis methods to analyze multiple physical fields.

[0066] In some embodiments, the electronic device optimizes the first process parameters based on multiple physical fields obtained after simulating the forming stage using the first process parameters, and the key variables that have the greatest impact on the peak equivalent stress, to obtain the second process parameters. This may include: the electronic device simulating the forming stage based on the first process parameters and a material model to obtain multiple physical fields, which include at least a flow field, a temperature field, and a strain field; the electronic device determining the quality index and the peak equivalent stress of the forming stage based on the flow field, temperature field, and strain field; the electronic device determining the coupling optimization objective corresponding to the quality index, and the key variables that have the greatest impact on the peak equivalent stress; and the electronic device optimizing the first process parameters based on the key variables with the aim of improving the coupling optimization objective to obtain the second process parameters.

[0067] In this context, a material model refers to a set of physical property parameters and mathematical models used to accurately describe the behavior of materials in numerical simulations.

[0068] The flow field describes the velocity, direction, and trajectory of the plastic flow of metallic materials, and is used to predict filling behavior and identify defects such as folds or incomplete filling. Among them, the simulation of the flow field is used to analyze the flow state of materials during rolling, punching, and bulging processes, and to evaluate the material filling status in each region and possible areas of insufficient or excessive flow.

[0069] The temperature field describes the temperature distribution of the ring blank and the die used in the forming stage at different times. It is used to analyze heat conduction, temperature rise, and heat loss, and is key to controlling material phase transformation, flow stress, and thermal stress. Specifically, the simulation of the temperature field is used to evaluate the impact of the ring blank heating temperature, die temperature, and heat generated by rolling friction on the local temperature distribution, ensuring that the temperature is always above the material recrystallization temperature and below the overheating temperature range.

[0070] The strain field describes the degree and distribution of deformation at various points within a material, and is used to assess the uniformity of the microstructure, the degree of recrystallization, and potential damage. Specifically, strain field simulation is used to monitor the strain distribution at each forming stage, with a focus on strain concentration at sharp corners of inner and outer diameters, ribs, and thin-walled regions to prevent excessive strain from causing cracks or elliptical deformation.

[0071] Quality indicators refer to specific parameters extracted from physical field data and used to quantitatively evaluate the quality of the output results at the corresponding forming stage.

[0072] The coupled optimization objective refers to a comprehensive and quantifiable objective that integrates multiple quality indicators to guide the optimization algorithm. It should be noted that this coupled optimization objective is not a single indicator, but a combination of multiple objectives.

[0073] Alternatively, multiple physical fields can be coupled and simulated by electronic devices using finite element numerical simulation software (such as SimufactForming).

[0074] In this embodiment, the entire process is optimized by multi-field coupled numerical simulation of flow field, temperature field and strain field to optimize the forming process of the final forged ring. Specifically, through physical field simulation and key variable identification, the process parameters are precisely optimized in a directional manner, which improves the forming quality index while effectively controlling the peak value of equivalent stress, thus balancing quality and safety.

[0075] In some embodiments, the first process parameters may include at least heating temperature, rolling force, stage sequence (i.e., pass sequence), and deformation per pass in each forming stage, and the material model may include at least a constitutive model, thermal conductivity parameters, and a friction model.

[0076] Among them, heating temperature refers to the initial temperature that the ring blank needs to reach and be uniformly heated in the heating furnace before entering a specific forming stage for processing. It directly determines the material's flow stress, plasticity, and microstructure evolution, and is the primary variable for controlling the forming difficulty and final performance.

[0077] Rolling force refers to the main process load applied by the mandrel to the inner wall surface of the ring during the ring rolling (pre-rolling of irregular shapes) forming stage, which drives the thinning of the ring wall thickness and the expansion of the diameter. It is the most critical power input parameter, which directly controls the plastic flow rate, strain rate and final deformation degree of the metal.

[0078] The stage sequence refers to the sequential arrangement of a series of forming stages planned according to the shape evolution requirements of the ring from blank to finished product, such as punching stage → pre-rolling stage → final rolling stage → bulging stage.

[0079] Constitutive models describe the flow stress response of materials at different temperatures, strains, and strain rates, i.e., whether the material is "soft" or "hard".

[0080] Thermal conductivity parameters describe a material’s thermal conductivity, specific heat capacity, etc., and determine the rate at which heat is transferred within the ring blank and between the ring blank and the mold and the environment. They are the basis for calculating the temperature field.

[0081] The friction model describes the interaction between the ring blank and the die contact surface, and is used to calculate the frictional force, which directly affects the metal flow pattern and filling behavior.

[0082] The electronic device simulates the forming stage based on the first process parameters and material model to obtain multiple physical fields. These can include: the electronic device constructs a three-dimensional finite element model corresponding to the forming stage based on the heating temperature, rolling force, stage sequence, deformation per firing in each forming stage, constitutive model, heat conduction parameters, and friction model; the electronic device simulates the three-dimensional finite element model and solves it using explicit integration and a fully coupled solver, simultaneously calculating multiple physical fields.

[0083] Among them, the three-dimensional finite element model refers to a mathematical model used for engineering simulation.

[0084] Explicit integration is an algorithm particularly well-suited for simulating high-speed, transient, and large-deformation nonlinear processes (such as forging and impact).

[0085] A fully coupled solver refers to a solver that solves all the physical field governing equations that control the plastic forming process synchronously, rather than sequentially, within the same solution step.

[0086] In this embodiment, the electronic device constructs a calculable digital twin, i.e., a three-dimensional finite element model, that fully corresponds to the forming stage based on heating temperature, rolling force, stage sequence, deformation per pass in each forming stage, constitutive model, heat conduction parameters, and friction model. Then, the electronic device uses explicit integration and a fully coupled solver to simulate and calculate this three-dimensional finite element model, simultaneously solving for multiple physical fields. This improves the prediction accuracy of multiple physical fields, thereby outputting a complete set of physical field data describing the state of the ring blank at any moment during the forming process. The entire process, by constructing a high-fidelity digital twin and employing a fully coupled solution strategy, achieves accurate synchronous prediction of multiple physical fields throughout the ring forging process, providing a reliable data foundation for process optimization. Furthermore, these multiple physical fields can be used to collaboratively predict material flow distribution, local temperature rise, and strain concentration during the process design stage, enabling early identification of risks such as insufficient outer rib material, local overheating, and grain coarsening, making process optimization more targeted and accurate.

[0087] In some embodiments, quality indicators may include at least the continuity of metal flowlines, the maximum equivalent variable, and the temperature gradient; the optimization objective for improving coupling may include at least: Ensure that the continuity of the metal flow lines is greater than a preset threshold. Ensure that the maximum equivalent variable is less than the preset variable threshold; In addition, ensure that the temperature gradient is less than the preset gradient threshold.

[0088] Among them, the continuity of metal flow lines is used to assess whether the material flow produces macroscopic defects such as folding and breakage.

[0089] The maximum equivalent variable is used to assess whether the degree of deformation is sufficient and uniform, which is related to the grain refinement effect.

[0090] Temperature gradients are used to assess whether the ring blank is heated evenly, and to prevent excessive thermal stress and uneven microstructure.

[0091] In this embodiment of the application, ensuring that the continuity of the metal flow lines is greater than a preset threshold (such as 95%) indicates that no macroscopic flow defects such as folding or flow penetration occur during the ring forming process, and the material fiber structure is completely distributed along the shape of the component, which fundamentally guarantees the fatigue performance and service safety of the ring blank.

[0092] Ensuring that the maximum equivalent variable is less than the preset variable threshold (e.g., 1.5) indicates that the degree of plastic deformation of the ring is within the controllable range of the material's microstructure. This satisfies the deformation requirements of dynamic recrystallization to achieve grain refinement, while avoiding internal damage or texture deterioration caused by excessive deformation.

[0093] Ensuring that the temperature gradient is less than the preset gradient threshold (e.g., 200℃) indicates that the heat distribution of the ring blank is uniform during the forming process, effectively suppressing the risk of thermal stress cracking caused by excessive local temperature difference, and ensuring the consistency of deformation coordination and microstructure properties.

[0094] It should be noted that the coupled optimization objectives are "coupled" because optimizing any one process parameter (such as heating temperature) will simultaneously affect all three quality indicators. The process of optimizing the first process parameter to obtain the second process parameter must find the best balance among these interrelated and sometimes even conflicting objectives.

[0095] Furthermore, the objective function corresponding to the above-mentioned coupling optimization objective is defined as a weighted sum function that minimizes the peak equivalent stress, maximizes the continuity of metal flow lines, and minimizes the temperature gradient. The weight coefficients in this weighted sum function are set according to the process priority.

[0096] In some embodiments, the electronic device optimizes the first process parameters based on key variables to obtain the second process parameters, which may include at least one of the following implementation methods: Implementation Method 1: With the maximum strain gradient as the key variable, the electronic equipment optimizes the rolling force and the deformation per firing to obtain the second process parameters.

[0097] The maximum strain gradient refers to the maximum rate of change of the equivalent variable per unit distance within the ring blank, directly reflecting the severity of uneven deformation. Regions with high strain gradients are risk areas for crack initiation and localized structural anomalies.

[0098] In implementation method 1, the electronic equipment identifies strain concentration areas through simulation and executes a local deformation reduction strategy. Specifically, it reduces the rolling force to slow down the deformation rate and adjusts the deformation amount per pass (such as splitting a large deformation pass into two smaller passes) to obtain the second process parameters, so as to make the strain distribution more gradual, thereby directly reducing the maximum strain gradient and eliminating the risk of cracking.

[0099] It should be noted that in implementation method 1, the maximum strain gradient can be controlled within 0.2.

[0100] Implementation Method 2: When the key variable is the metal temperature, the electronic device optimizes the heating temperature and reheating timing through the temperature field to obtain the second process parameters.

[0101] Among them, metal temperature refers to the real-time temperature of the ring blank in the deformation zone, which directly determines the material's plasticity, flow stress, and microstructure evolution dynamics.

[0102] In implementation method 2, the electronic device analyzes the temperature field. If it predicts that the metal temperature will be lower than the lower limit of the plasticity window, it increases the heating temperature or inserts / advances the reheating timing between passes. If it predicts that the temperature is too high, it decreases the heating temperature or optimizes the transmission rhythm to increase heat dissipation, ensuring that the temperature is always within the optimal processing window, so as to optimize the first process parameter and obtain the second process parameter.

[0103] It should be noted that in implementation method 2, the metal temperature can be kept between 940℃ and 1020℃.

[0104] Implementation Method 3: When the key variable is the metal flow rate difference, the electronic equipment uses a variable step size control algorithm to dynamically optimize the rolling force and obtain the second process parameters.

[0105] The metal flow rate difference refers to the absolute value of the difference in metal flow rate between different parts of the ring blank (such as the inner and outer walls, or the upper and lower ends). An excessive flow rate difference is the direct cause of wrinkles (where the faster flow rate compresses the slower flow rate) and incomplete filling (where metals of different flow rates fail to fill the cavity simultaneously).

[0106] In implementation method 3, the electronic device monitors the metal flow rate difference in the simulation in real time. When the metal flow rate difference exceeds the preset flow rate difference threshold, the rolling force is adjusted rapidly with a large step size through a variable step size control algorithm to strongly correct the deviation; when the metal flow rate difference is close to the preset flow rate difference threshold, the rolling force is switched to a small step size for fine adjustment to avoid overshoot oscillation.

[0107] It should be noted that in implementation method 3, the metal flow rate difference can be stably controlled within the allowable range (e.g., ±15%) to avoid wrinkles and material shortages in the ribs.

[0108] Implementation Method 4: With the key variables being material flow direction, maximum temperature rise, and microstructure uniformity, the electronic equipment optimizes the deformation amount per firing cycle to obtain the second process parameters.

[0109] Material flow direction refers to the trajectory of metal particles. Its rationality determines whether the streamline meets the stress requirements of the component and whether it will penetrate the grain boundary to form flow defects.

[0110] Maximum temperature rise refers to the highest local temperature increase of the ring caused by heat mainly converted from plastic work. Excessive temperature rise may lead to local overheating and grain coarsening.

[0111] The uniformity of microstructure refers to the consistency of grain size, morphology and distribution within the ring blank, which is directly related to the uniformity and stability of the mechanical properties of the component.

[0112] In implementation method 4, the electronic device addresses this complex problem by optimizing the deformation amount per firing: increasing the deformation amount per firing can guide the material flow to a more reasonable path and improve the uniformity of the microstructure; however, excessive deformation can lead to excessive maximum temperature rise. Therefore, the optimization goal is to find an optimal deformation amount that ensures correct material flow and uniform microstructure while controlling the maximum temperature rise to within a safe threshold.

[0113] It should be noted that in implementation method 4, the deviation of material flow direction can be reduced from 12.7% in the original process to 4.1%, the maximum temperature rise is reduced by about 38°C, and the uniformity of the structure is improved by about 23%.

[0114] Optionally, the electronic equipment can be optimized iteratively using the above objective function to achieve automatic optimization of heating temperature within an adjustment range of ±10℃, rolling force within an adjustment range of ±5%, and deformation per firing within an adjustment range of ±3%.

[0115] For example, for the TC4 ring, the electronic device can adopt a pre-rolled aggregate strategy to reduce the risk of insufficient outer rib material and optimize the stage sequence to reduce local temperature rise.

[0116] For the IN718 ring, the electronic device can adopt a thin-wall pre-rolling strategy to reduce local strain concentration and temperature rise at the sharp corners of the outer diameter at both ends, thereby improving the uniformity of the microstructure (by about 15%) and mechanical properties.

[0117] Combining the technical solutions described in steps 101-103 above, this electronic device, through multiple iterative simulation optimizations, ensures that the process paths corresponding to the second process parameters of each of the multiple forming stages are repeatable and controllable, and outputs a process parameter table that can be directly used for production. In other words, the entire process of upsetting, punching, pre-rolling, final rolling, and bulging of the ring is optimized through multi-field coupled numerical simulation of flow field, temperature field, and strain field. Based on the simulation results, the billet size, heating temperature, rolling force, stage sequence, and deformation amount of each firing are determined, achieving a positive process design with uniform material flow, moderate strain, and controllable temperature rise.

[0118] For example, the electronic device adopts multi-field coupling modeling and forward process design. For each forming stage, such as the upsetting and punching stage, the heating temperature of the TC4 ring is set to 954℃, the bar stock is upset to H=350mm, the punching diameter is Φ200mm, the punching pressure is about 5000t, and the strain reaches 4. The heating temperature of the IN718 ring is set to 1080℃, the bar stock is upset to H=155±5mm, the punching diameter is Φ220mm, the punching pressure is about 3300t, and the strain reaches the high stress region.

[0119] For example, in the pre-rolling stage, the TC4 ring is pre-rolled in a rectangular shape and then in an irregular shape, with a maximum radial rolling force of about 210t and an outer diameter sharp corner strain of about 3. The IN718 ring is pre-rolled in an irregular shape multiple times, with radial rolling forces ranging from 135t to 200t, a strain range of 5-20, and a temperature rise controlled to not exceed 1200℃.

[0120] For example, in the final rolling stage, the heating temperature of the first heat of the TC4 ring during the irregular final rolling is set to 954℃, and the maximum radial rolling force is about 310t; the maximum force of the second heat is set to 360t, focusing on correcting the uniformity of the outer ribs and thin walls; the heating temperature of the IN718 ring during the irregular final rolling is set to 1010℃, and the radial force range is 180-225t, with uniform flow field, small temperature rise, and ensuring filling of the ribs.

[0121] During the bulging stage, the heating temperature of the TC4 ring is set to 900℃, the bulging force is adjusted to 23t, and the ellipticity is corrected to about 7mm; the IN718 ring is cold-bulged, the bulging force is adjusted to 20-22t, and the ellipticity is controlled at 5-7mm.

[0122] Step 104: Determine the optimal process parameters for the final forged ring based on the second process parameters of each of the multiple forming stages.

[0123] The optimal process parameters refer to a complete, quantifiable, and executable set of process instructions, which is a standardized set of process parameters that can be used for production. These optimal process parameters are not simply a list of the second process parameters corresponding to each forming stage, but rather a globally optimal solution formed by systematically integrating and collaboratively verifying the optimization results of all forming stages.

[0124] Optionally, the above-mentioned optimal process parameters may include at least: the final determined and coherent sequence of forming stages (e.g., punching stage → pre-rolling stage → final rolling stage → bulging stage), and quantitative indicators of each forming stage (e.g., input billet size, output billet size, process window parameters (e.g., heating temperature, rolling force, deformation amount, etc.)).

[0125] In step 104, the electronic device generates globally coordinated optimal process parameters by integrating the optimization parameters of each forming stage, ensuring that the entire process from the initial billet to the final forging is optimal in terms of quality, efficiency and reliability, and realizing a process design with uniform material flow, moderate strain and controllable temperature rise.

[0126] Optionally, after step 104, the method may further include one of the following implementations: Implementation Method 1: The electronic device uses the optimal process parameters to simulate the forming process of the ring blank and obtain simulation results. These simulation results can include at least the uniformity of the microstructure, mechanical properties, and high-temperature performance, so as to realize process verification and performance evaluation.

[0127] For example, during the process of process verification and performance evaluation, for the TC4 ring, the electronic equipment evaluates the microstructure uniformity of the TC4 ring through low-magnification microstructure inspection, verifying that there is no segregation, cracks and forging folds, and that the mechanical properties reach tensile strength of 940-960MPa and yield strength of 875-920MPa.

[0128] For the IN718 ring, the electronic device evaluates the uniformity of the microstructure of the IN718 ring by grain size. The grain size reaches ASTM 6.5-7.5 grade, the room temperature tensile strength is 1460-1470MPa, the yield strength is 1190-1200MPa, the fracture time in the high temperature creep test is improved by about 15% compared with the traditional process, and the high temperature performance is stable.

[0129] It should be noted that in practical applications, simulations revealed a risk of material shortage and localized overheating in the outer rib area of ​​the TC4 ring. A pre-rolling aggregate strategy was adopted to optimize the stage sequence, reducing the risk of material shortage in the outer rib and effectively reducing localized temperature rise by approximately 30°C, ensuring microstructure uniformity. Verification showed that the TC4 ring did not exhibit material shortage in the outer rib area, and its mechanical properties were significantly improved, with the yield strength increasing by approximately 35 MPa and the grain size improving from ASTM 5.5 to ASTM 6.5.

[0130] For IN718 rings, a thin-walled pre-rolling strategy was adopted to avoid strain concentration and local overheating at the sharp corners of the outer diameter at both ends, thereby further improving the uniformity of the microstructure and mechanical properties.

[0131] The entire process compares the numerical simulation results (such as tensile strength) of TC4 ring and IN718 ring with actual production data, verifying the high accuracy of multi-field coupled simulation prediction of flow field, temperature field and strain field, which can provide effective guidance for the forward optimization design of ring forging process.

[0132] Implementation Method 2: The electronic device constructs a process knowledge base based on simulation results and optimal process parameters. This process knowledge base can include at least: detailed data on the process parameters, deformation, heating temperature and rolling passes of each ring material, supporting rapid design of ring forgings of different materials and specifications; and systematically organizes and forms standardized process paths and rules based on simulation data and experimental results to support efficient mass production under the digital manufacturing system.

[0133] The entire process can provide rapid and repeatable production support for ring forgings of different materials and specifications, and can also realize the batch controllable production of high-performance ring forgings under a digital manufacturing system.

[0134] In the embodiments of this application, the technical solutions described in steps 101-104 above adopt the process of reverse-engineering the billet size of each forming stage from the final forged ring to construct a theoretically geometrically feasible optimal forming path that meets the constraints. This systematically replaces the trial-and-error process that relies on experience, improving design efficiency and feasibility from the source and shortening the R&D cycle. In addition, multi-field coupled simulation is performed on each forming stage according to the optimal forming path. By identifying the key variables most sensitive to the peak of equivalent stress, precise optimization is performed, and the determination of the optimal process parameters is based on solid physical simulation. This significantly improves the accuracy and reliability of the final process scheme and reduces the dependence on physical experiments and costs.

[0135] To better understand the embodiments of this application, the following examples illustrate the method for determining ring process parameters through multi-field coupling and forward optimization provided in the embodiments of this application: Example 1: Figure 2 This is a schematic diagram of the optimal forming path corresponding to the TC4 ring provided in the embodiments of this application. From Figure 2As can be seen, the electronic equipment first upsets the bar stock to obtain the first ring blank, then punches the first ring blank to obtain the second ring blank. Then, the electronic equipment can pre-roll the second ring blank using two different process schemes. Specifically, process scheme one: the electronic equipment performs matrix pre-rolling on the second ring blank, followed by sequential irregular final rolling (first and second heats) to obtain the first sub-ring blank, which is then expanded to obtain the first final forged ring. Process scheme two: the electronic equipment performs matrix pre-rolling on the second ring blank, followed by irregular pre-rolling, then sequentially performs irregular final rolling (first and second heats) to obtain the second sub-ring blank, which is then expanded to obtain the second final forged ring.

[0136] It should be noted that the electronic device used multi-field coupled simulations to analyze the streamline distribution, temperature gradient (up to 50℃ / cm), and strain concentration (local strain >0.35) of the ring blank during the forming process for the two aforementioned process schemes. For process scheme one, a significant risk of material shortage was found in the outer rib region, with local temperature rises exceeding 1180℃ and a significant grain growth trend. For process scheme two, the pre-rolling agglomeration strategy and optimized stage sequence resulted in uniform strain distribution, a maximum local temperature reduction of approximately 30℃, and a significant reduction in the risk of material shortage. Finally, through simulation-experiment closed-loop verification, the electronic device ultimately determined process scheme two to be the optimal forming path.

[0137] Figure 3 These are high- and low-magnification microstructure diagrams of the TC4 ring provided in an embodiment of this application. Figure 3 As shown in (a)-(e), the simulation of the electronic equipment using process scheme two confirmed that the TC4 ring did not exhibit any material shortage in the outer rib area. The microstructure was uniform under low magnification, with no segregation, cracks, or forging defects, and the grain size was ASTM 6.0-6.5 grade. The mechanical property test results were a tensile strength of 940-960 MPa, a yield strength of 875-920 MPa, and an elongation of 10%-12%. Compared with process scheme one, the yield strength increased by approximately 35 MPa, and the grain size in the outer rib area was refined from ASTM 5.5 grade to ASTM 6.5 grade.

[0138] Example 2: Figure 4 This is a schematic diagram of the optimal forming path corresponding to the IN718 ring provided in the embodiments of this application. From Figure 4As can be seen from the diagram: The electronic equipment first upsets the bar stock to obtain the first ring blank, then punches the first ring blank to obtain the second ring blank, and then pre-rolls the second ring blank into a rectangle to obtain the third ring blank, the inner diameter of which is Φ340. Then, the electronic equipment can pre-roll the third ring blank using two different process schemes. Specifically, in process scheme three, the electronic equipment performs three separate irregular pre-rolls on the third ring blank, with the inner diameters of the ring blanks obtained after each irregular pre-roll being Φ500, Φ800, and Φ... 1200; The ring blank obtained after the last irregular pre-rolling is then subjected to irregular final rolling to obtain the third sub-ring blank, and then the third sub-ring blank is expanded to obtain the third final forged ring; Process scheme four: The electronic equipment performs irregular pre-rolling on the third ring blank twice in sequence, and the inner diameter of the ring blank obtained after each irregular pre-rolling is Φ700 and Φ1200 respectively; The ring blank obtained after the last irregular pre-rolling is then subjected to irregular pre-rolling again to obtain the fourth sub-ring blank, and then the fourth sub-ring blank is expanded to obtain the fourth final forged ring.

[0139] It should be noted that the electronic equipment obtains stress-strain data from the material database for the two process schemes mentioned above, and sets the heating temperature to 1020-1060℃ and the deformation amount of each heat treatment to 18%-22% in combination with the process rule library. Then, by using multi-field coupling simulation of flow field, temperature field and strain field, the "thin-wall first rolling" path (i.e. process scheme) is selected to avoid strain concentration at the sharp corners of the outer diameter at both ends (reducing it by about 20%) and local overheating.

[0140] Figure 5 These are high- and low-magnification microstructure diagrams of the IN718 ring provided in an embodiment of this application. From... Figure 3 As can be seen from (a)-(c) in the figure: After testing, the electronic equipment was simulated using process scheme three, and it was determined that the low magnification structure of the IN718 ring was uniform, with no inclusions, cracks or other defects, and the grain size was ASTM 6.5-7.5 grade; the room temperature tensile properties were tensile strength 1460-1470MPa, yield strength 1190-1200MPa, and elongation 12%-14%; the fracture time under high temperature creep test (650℃, stress 690MPa) was 134-138h, which is about 15% higher than the average of 118h in the traditional process design.

[0141] The following describes the ring component process parameter determination system with multi-field coupling and forward optimization provided in the embodiments of this application. The ring component process parameter determination system with multi-field coupling and forward optimization described below can be referred to in correspondence with the ring component process parameter determination method with multi-field coupling and forward optimization described above.

[0142] Figure 6This is a schematic diagram of the structure of the ring component process parameter determination system with multi-field coupling and forward optimization provided in the embodiments of this application. Figure 6 As shown, the system includes: an acquisition module 601, a reverse design module 602, and a parameter optimization module 603.

[0143] The acquisition module 601 is used to acquire the initial billet size and initial forming path of the ring blank, and the target billet size of the final forged ring. The initial forming path includes multiple consecutive forming stages. The reverse design module 602 is used to reverse engineer the input billet size of each forming stage, starting from the last forming stage among the plurality of forming stages, wherein the initial billet size is the input billet size of the first forming stage among the plurality of forming stages, and the target billet size is the output billet size of the last forming stage; based on the input and output billet sizes of each forming stage, the forming process parameters of each forming stage are determined; and based on the forming process parameters of each forming stage, the optimal forming path of the final forged ring is generated; The parameter optimization module 603 is used to traverse from the first forming stage included in the optimal forming path, and for the currently traversed forming stage, optimize the first process parameter based on multiple physical fields obtained after simulating the forming stage using the first process parameter, as well as the key variable that has the greatest impact on the peak value of the equivalent stress, to obtain the second process parameter; and determine the optimal process parameter of the final forged ring based on the second process parameter of each of the multiple forming stages.

[0144] Optionally, the reverse design module 602 is specifically used to, for the i-th forming stage, determine the input billet size of the i-th forming stage based on the output billet size and the rib thickening amount of the i-th forming stage; determine the forming process parameters of the i-th forming stage based on the output billet size and the input billet size of the i-th forming stage; retain the i-th forming stage if the forming process parameters meet the constraint conditions; adjust the initial billet size if the forming process parameters do not meet the constraint conditions, and start a new reverse design from the last forming stage until the i-th forming stage is retained; when the reverse design reaches the initial billet size and the forming process parameters of the retained forming stages all meet the constraint conditions, generate the optimal forming path of the final forged ring based on the retained forming stages.

[0145] Optionally, the forming process parameters include at least the deformation per firing, the wall thickness reduction rate, and the inner diameter expansion ratio; the forming process parameters satisfy the following constraints: the deformation per firing is within a preset deformation range; the wall thickness reduction rate is not greater than a preset reduction rate threshold; and the inner diameter expansion ratio is not greater than a preset expansion threshold.

[0146] Optionally, the parameter optimization module 603 is specifically used to simulate the forming stage based on the first process parameters and the material model to obtain the multiple physical fields, which include at least a flow field, a temperature field, and a strain field; determine the quality index and the equivalent stress peak value of the forming stage based on the flow field, the temperature field, and the strain field; determine the coupling optimization objective corresponding to the quality index and the key variable that has the greatest impact on the equivalent stress peak value; and optimize the first process parameters based on the key variable with the aim of improving the coupling optimization objective to obtain the second process parameters.

[0147] Optionally, the quality index includes at least the continuity of the metal streamlines, the maximum equivalent variable, and the temperature gradient; the improvement of the coupled optimization objective includes at least: ensuring that the continuity of the metal streamlines is greater than a preset threshold; ensuring that the maximum equivalent variable is less than a preset variable threshold; and ensuring that the temperature gradient is less than a preset gradient threshold.

[0148] Optionally, the first process parameters include at least heating temperature, rolling force, and deformation per pass in each forming stage; the parameter optimization module 603 is specifically used to optimize the rolling force and deformation per pass when the key variable is the maximum strain gradient, to obtain the second process parameters: when the key variable is metal temperature, the heating temperature and reheating timing are optimized through the temperature field to obtain the second process parameters; when the key variable is metal flow rate difference, the rolling force is dynamically optimized using a variable step size control algorithm to obtain the second process parameters; when the key variables are material flow direction, maximum temperature rise, and microstructure uniformity, the deformation per pass is optimized to obtain the second process parameters.

[0149] Optionally, the first process parameters include at least heating temperature, rolling force, stage sequence, and deformation per pass in each forming stage; the material model includes at least a constitutive model, heat conduction parameters, and a friction model; the parameter optimization module 603 is specifically used to construct a three-dimensional finite element model corresponding to the forming stage based on the heating temperature, rolling force, stage sequence, deformation per pass in each forming stage, constitutive model, heat conduction parameters, and friction model; the three-dimensional finite element model is simulated, and solved using an explicit integral and fully coupled solver, simultaneously calculating the multiple physical fields.

[0150] Figure 7 This is a schematic diagram of the structure of the electronic device provided in an embodiment of this application. For example... Figure 7As shown, the electronic device may include: a processor 710, a communication interface 720, a memory 730, and a communication bus 740, wherein the processor 710, the communication interface 720, and the memory 730 communicate with each other through the communication bus 740. The processor 710 can call logic instructions in the memory 730 to execute a method for determining ring process parameters using multi-field coupling and forward optimization. This method includes: obtaining the initial billet size and initial forming path of the ring blank, and the target billet size of the final forged ring, wherein the initial forming path includes multiple consecutive forming stages; starting from the last forming stage of the multiple forming stages, reverse-engineering the input billet size of each forming stage, wherein the initial billet size is the input billet size of the first forming stage of the multiple forming stages, and the target billet size is the output billet size of the last forming stage; based on each... The input and output billet dimensions of the forming stage are used to determine the forming process parameters for each forming stage. Based on these parameters, the optimal forming path for the final forged ring is generated. Starting from the first forming stage included in the optimal forming path, the process is iterated. For each currently traversed forming stage, the first process parameters are optimized based on multiple physical fields obtained after simulating the forming stage using the first process parameters, as well as the key variables that have the greatest impact on the peak equivalent stress, to obtain second process parameters. The optimal process parameters for the final forged ring are determined based on the second process parameters for each of the multiple forming stages.

[0151] Furthermore, the logical instructions in the aforementioned memory 730 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0152] On the other hand, this application also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the multi-field coupling and forward optimization ring component process parameter determination method provided by the above methods. The method includes: obtaining the initial billet size and initial forming path of the ring component blank, and the target billet size of the final forged ring component, wherein the initial forming path includes multiple consecutive forming stages; starting from the last forming stage among the multiple forming stages, reverse-engineering the input billet size of each forming stage, wherein the initial billet size is the input billet size of the first forming stage among the multiple forming stages. The target billet size is the output billet size of the last forming stage; based on the input and output billet sizes of each forming stage, the forming process parameters of each forming stage are determined; and based on the forming process parameters of each forming stage, the optimal forming path of the final forged ring is generated; starting from the first forming stage included in the optimal forming path, the process is traversed, and for the currently traversed forming stage, based on multiple physical fields obtained after simulating the forming stage using the first process parameters, and the key variables that have the greatest impact on the peak equivalent stress, the first process parameters are optimized to obtain the second process parameters; based on the second process parameters of each of the multiple forming stages, the optimal process parameters of the final forged ring are determined.

[0153] In another aspect, embodiments of this application also provide a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, this computer program implements a method for determining ring process parameters through multi-field coupling and forward optimization provided by the methods described above. This method includes: obtaining an initial billet size and an initial forming path of the ring blank, and a target billet size for the final forged ring. The initial forming path includes multiple consecutive forming stages. Starting from the last forming stage among the multiple forming stages, the input billet size for each forming stage is calculated backwards. The initial billet size is the input billet size of the first forming stage among the multiple forming stages, and the target billet size is the input billet size of the last forming stage. The output billet size of a forming stage; based on the input and output billet sizes of each forming stage, the forming process parameters of each forming stage are determined; and based on the forming process parameters of each forming stage, the optimal forming path of the final forged ring is generated; starting from the first forming stage included in the optimal forming path, the process is traversed, and for the currently traversed forming stage, based on multiple physical fields obtained after simulating the forming stage using the first process parameters, and the key variables that have the greatest impact on the peak equivalent stress, the first process parameters are optimized to obtain the second process parameters; based on the second process parameters of each of the multiple forming stages, the optimal process parameters of the final forged ring are determined.

[0154] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0155] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0156] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method of process parameter determination for a ring part with multi-field coupling and positive optimization, characterized in that, The method comprises the following steps: obtaining an initial blank size and an initial forming path of a ring blank, and a target blank size of a final forged ring, wherein the initial forming path comprises a plurality of forming stages in sequence; starting from a last forming stage in the plurality of forming stages, reversely back-propagating an input blank size of each forming stage, wherein the initial blank size is an input blank size of a first forming stage in the plurality of forming stages, and the target blank size is an output blank size of the last forming stage; determining a forming process parameter of each forming stage according to the input blank size and the output blank size of each forming stage; and generating an optimal forming path of the final forged ring according to the forming process parameter of each forming stage; starting from a first forming stage included in the optimal forming path, for a currently traversed forming stage, optimizing a first process parameter according to a plurality of physical fields obtained after simulating the forming stage by using the first process parameter and a key variable that has the greatest impact on an equivalent stress peak, to obtain a second process parameter; determining an optimal process parameter of the final forged ring according to the second process parameter of each forming stage.

2. The multi-field coupling and forward-optimization ring process parameter determination method of claim 1, wherein, The method of determining the forming process parameter of each forming stage according to the input blank size and the output blank size of each forming stage comprises the following steps: for an i-th forming stage, determining an input blank size of the i-th forming stage according to an output blank size of the i-th forming stage and a rib area thickening amount; determining a forming process parameter of the i-th forming stage according to the output blank size and the input blank size of the i-th forming stage; in a case where the forming process parameter satisfies a constraint condition, retaining the i-th forming stage; in a case where the forming process parameter does not satisfy the constraint condition, adjusting the initial blank size, and starting a new reverse back-propagation from the last forming stage until the i-th forming stage is retained; in a case where the reverse back-propagation reaches the initial blank size and the forming process parameters of the retained forming stages all satisfy the constraint condition, generating an optimal forming path of the final forged ring according to the retained forming stages. The forming process parameter at least comprises a deformation amount per heating, a wall thickness reduction rate and an inner diameter expansion ratio; and the constraint condition satisfied by the forming process parameter is that:

3. The multi-field coupling and forward-optimization ring process parameter determination method of claim 2, wherein, the deformation amount per heating is within a preset deformation degree range; the wall thickness reduction rate is not greater than a preset reduction rate threshold; and the inner diameter expansion ratio is not greater than a preset expansion threshold. The method of optimizing the first process parameter according to the plurality of physical fields obtained after simulating the forming stage by using the first process parameter and the key variable that has the greatest impact on the equivalent stress peak, to obtain the second process parameter, comprises the following steps:

4. The multi-field coupling and forward optimization ring process parameter determination method of claim 1, wherein, simulating the forming stage according to the first process parameter and a material model, to obtain the plurality of physical fields, wherein the plurality of physical fields at least comprise a flow field, a temperature field and a strain field; ​ determine a quality index of the forming stage and the equivalent stress peak value according to the flow field, the temperature field and the strain field; determine a coupling optimization target corresponding to the quality index and a key variable having the greatest influence on the equivalent stress peak value; optimize the first process parameter according to the key variable to obtain the second process parameter, with the purpose of improving the coupling optimization target.

5. The method of claim 4, wherein, The quality index at least includes a metal flow line continuity degree, a maximum equivalent strain variable and a temperature gradient; and the improvement of the coupling optimization target at least includes: ensuring that the metal flow line continuity degree is greater than a preset degree threshold; ensuring that the maximum equivalent strain variable is less than a preset variable threshold; and ensuring that the temperature gradient is less than a preset gradient threshold.

6. The method of claim 4 or 5, wherein, The first process parameter at least includes a heating temperature, a rolling force and a per-pass deformation amount of each forming stage; The optimization of the first process parameter according to the key variable to obtain the second process parameter includes: in a case where the key variable is a maximum strain gradient, optimizing the rolling force and the per-pass deformation amount to obtain the second process parameter; in a case where the key variable is a metal temperature, optimizing the heating temperature and a reheating timing through the temperature field to obtain the second process parameter; in a case where the key variable is a metal flow rate difference, dynamically optimizing the rolling force by using a variable step length control algorithm to obtain the second process parameter; and in a case where the key variable is a material flow direction, a maximum temperature rise and a structure uniformity, optimizing the per-pass deformation amount to obtain the second process parameter.

7. The method of claim 4 or 5, wherein, The first process parameter at least includes a heating temperature, a rolling force, a stage sequence and a per-pass deformation amount of each forming stage, and the material model at least includes a constitutive model, a heat conduction parameter and a friction model; and the simulation of the forming stage according to the first process parameter and the material model to obtain the multiple physical fields includes: constructing a three-dimensional finite element model corresponding to the forming stage according to the heating temperature, the rolling force, the stage sequence, the per-pass deformation amount of each forming stage, the constitutive model, the heat conduction parameter and the friction model; simulating the three-dimensional finite element model and solving by using an explicit integration and a full-coupling solver to synchronously calculate the multiple physical fields.

8. A multi-field coupling and forward optimization ring process parameter determination system, characterized by, The method includes: an acquisition module, configured to acquire an initial blank size and an initial forming path of a ring piece blank and a target blank size of a final-forged ring piece, the initial forming path including a plurality of continuous forming stages; a reverse design module, configured to: starting from a last forming stage of the plurality of forming stages, inversely deduce input blank sizes of each forming stage, wherein the initial blank size is an input blank size of a first forming stage of the plurality of forming stages, and the target blank size is an output blank size of the last forming stage; determine forming process parameters of each forming stage according to the input blank size and the output blank size of each forming stage; and generate an optimal forming path of the final-forging ring piece according to the forming process parameters of each forming stage; a parameter optimization module, configured to: starting from a first forming stage included in the optimal forming path, for a currently traversed forming stage, according to a plurality of physical fields obtained after simulation of the forming stage by using a first process parameter, and a key variable that has the greatest influence on an equivalent stress peak, optimize the first process parameter to obtain a second process parameter; and determine optimal process parameters of the final-forging ring piece according to the second process parameters of the plurality of forming stages.

9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the computer program to implement the ring piece process parameter determination method with multi-field coupling and forward optimization according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the ring piece process parameter determination method with multi-field coupling and forward optimization according to any one of claims 1 to 7.

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