JP-7857486-B1 - Simulation program, press forming simulation method, and press forming simulation apparatus

JP7857486B1JP 7857486 B1JP7857486 B1JP 7857486B1JP-7857486-B1

Abstract

[Problem] To provide a press forming simulation method that can predict the shape of a press-formed product after springback, regardless of the tensile strength of the blank material. [Solution] Shape data and strain data of the press-formed product at the bottom dead center are calculated by forming simulation based on mold data and blank material shape data. Actual formed outer shape data showing the outer shape after springback is obtained. Based on the shape data at the bottom dead center and the obtained actual formed outer shape data, the stress of the press-formed product at the bottom dead center is calculated. The relationship between the strain data and stress of the press-formed product at the bottom dead center is machine-learned into a learning model. The mold data is corrected. Shape data and strain data of the press-formed product at the bottom dead center are calculated by forming simulation based on the corrected mold. The calculated strain data of the press-formed product is input into the learning model to calculate the stress and calculate the shape after springback. [Selection Diagram] Figure 3

Inventors

武田　雅弘
岡田健二
秋元秀介
山内　和弘

Assignees

株式会社JSOL

Dates

Publication Date: 20260512
Application Date: 20251014

Claims (10)

On the computer, The process involves calculating the shape data and strain data of the press-formed product at the bottom dead center through a forming simulation based on die face shape data, blank material shape data, and material property data related to the blank material. The steps include: acquiring actual formed external shape data showing the external shape of a press-formed product after springback, obtained by actually press-forming the blank material; A stress calculation step that calculates the stress of the press-formed product at the bottom dead center based on the shape data or blank material shape data at the bottom dead center or after springback, and the acquired actual formed outer shape data. The steps include generating a machine learning model that outputs the stress of a press-formed product at the bottom dead center when strain data for the press-formed product at the bottom dead center is input, based on strain data and stress data for the press-formed product at the bottom dead center, and The steps include modifying the die face, The process involves calculating the shape data and strain data of the press-formed product at the bottom dead center through a forming simulation based on the die face modification mold data, blank material shape data, and material property data related to the blank material. The steps include: inputting the calculated strain data of the press-formed product into the learning model to calculate the stress of the press-formed product; A simulation program for executing a springback shape calculation step, which calculates the shape of the press-formed product after springback based on the calculated shape data and stress of the press-formed product at the bottom dead center.
The blank material shape data and the shape data each include data for a mesh structure obtained by dividing the shape of the blank material and the shape of the press-formed product into a plurality of finite elements, The stress calculation step described above is: The steps include creating shape data that includes data for a mesh structure in which the shape of a press-formed product after springback is divided into a plurality of finite elements, by modifying the mesh structure indicated by the shape data or blank material shape data using a mesh morphing method so that the outer shape indicated by the shape data or blank material shape data at the bottom dead center or after springback matches the outer shape indicated by the actual formed outer shape data, A simulation program according to claim 1, comprising the step of calculating the stress that occurs when the shape of a press-formed product after springback is elastically deformed to the shape of the press-formed product at its bottom dead center, based on the shape data of the press-formed product after springback.
The blank material shape data and the shape data each include data for a mesh structure obtained by dividing the shape of the blank material and the shape of the press-formed product into a plurality of finite elements, The stress calculation step described above is: The steps include creating a first actual product mold and a second actual product mold that represent die faces that conform to the first and second press surfaces of an actual press-formed product, respectively, based on actual molding outline data, The steps include creating shape data that includes data for a mesh structure in which the shape of a press-formed product after springback is divided into a plurality of finite elements by sandwiching a press-formed product represented by shape data at the bottom dead center or after springback, or a blank material represented by the blank material shape data, between the first and second actual product molds, thereby changing the mesh structure indicated by the shape data; A simulation program according to claim 1, comprising the step of calculating the stress that occurs when the shape of a press-formed product after springback is elastically deformed to the shape of the press-formed product at its bottom dead center, based on the shape data of the press-formed product after springback.
The shape data includes data for a mesh structure obtained by dividing the shape of a press-formed product into a plurality of finite elements. The data input to the aforementioned learning model is: This includes the vertical strain and shear strain of the upper surface of the finite element and the vertical strain and shear strain of the lower surface of the finite element. The data output from the aforementioned learning model is: A simulation program according to any one of claims 1 to 3, including stress on the upper and lower surfaces of the finite element.
The data input to the aforementioned learning model is: The simulation program according to claim 4, comprising at least one of curvature, pressure, and frictional force on the upper or lower surface of the finite element.
The data input to the aforementioned learning model is: The data output from the learning model includes at least one of the normal strain and shear strain of the neutral plane of the finite element, and the curvature, pressure, and frictional force on the upper or lower surface of the finite element. The simulation program according to claim 4, which includes stress in the neutral plane of the finite element.
The data input to the aforementioned learning model is: The simulation program according to claim 4, comprising at least one of the plate thickness reduction rate, curvature ρ2, minimum principal strain on the upper surface of the finite element, maximum principal strain on the lower surface, first principal strain and second principal strain on the upper surface, and second principal strain on the lower surface.
The data input to the aforementioned learning model is: The simulation program according to claim 4, comprising the vertical strain and shear strain of the upper surface of the peripheral element of the finite element, and the vertical strain and shear strain of the lower surface of the peripheral element.
The process involves calculating the shape data and strain data of the press-formed product at the bottom dead center through a forming simulation based on die face shape data, blank material shape data, and material property data related to the blank material. The steps include: acquiring actual formed external shape data showing the external shape of a press-formed product after springback, obtained by actually press-forming the blank material; A stress calculation step that calculates the stress of the press-formed product at the bottom dead center based on the shape data or blank material shape data at the bottom dead center or after springback, and the acquired actual formed outer shape data. The steps include generating a machine learning model that outputs the stress of a press-formed product at the bottom dead center when strain data for the press-formed product at the bottom dead center is input, based on strain data and stress data for the press-formed product at the bottom dead center, and The steps include modifying the die face, The process involves calculating the shape data and strain data of the press-formed product at the bottom dead center through a forming simulation based on the die face modification mold data, blank material shape data, and material property data. The steps include: inputting the calculated strain data of the press-formed product into the learning model to calculate the stress of the press-formed product; A press forming simulation method comprising a springback shape calculation step, which calculates the shape of the press-formed product after springback based on the calculated shape data and stress of the press-formed product at the bottom dead center.
A press forming simulation apparatus equipped with a processing unit, The aforementioned processing unit, Based on mold data relating to the die face shape, blank material shape data, and material property data relating to the blank material, a forming simulation is performed to calculate the shape data and strain data of the press-formed product at the bottom dead center. Actual formed external shape data is obtained showing the external shape of the press-formed product after springback, obtained by actually press-forming the blank material. Based on the shape data at the bottom dead center or after springback, or the blank material shape data, and the acquired actual molded outer shape data, the stress of the press-formed product at the bottom dead center is calculated. Based on strain and stress data of the press-formed product at the bottom dead center, a machine learning model is generated that outputs the stress of the press-formed product at the bottom dead center when strain data for the press-formed product at the bottom dead center is input. The die face is modified, Based on mold data after die face modification, blank material shape data, and material property data, forming simulations are performed to calculate the shape data and strain data of the press-formed product at the bottom dead center. By inputting the calculated strain data of the press-formed product into the learning model, the stress of the press-formed product is calculated. A press forming simulation device configured to calculate the shape of a press-formed product after springback, based on the calculated shape data and stress of the press-formed product at the bottom dead center.

Description

This disclosure relates to a simulation program, a press forming simulation method, and a press forming simulation apparatus. In press forming of blank materials such as metal sheets, springback can occur due to stress on the molded product at the bottom dead center, sometimes resulting in a product that does not meet the target shape. Springback refers to the phenomenon where, after plastic deformation during press forming, the material attempts to return to its original shape due to stress on the molded product at the bottom dead center when the external force is removed. As a measure against springback, the shape and stress of the press-formed product at the bottom dead center are simulated using finite element method (FEM analysis), and the difference between the target shape of the molded product and the shape after springback is reflected in the mold shape (for example, Patent Document 1). Japanese Patent Publication No. 2013-208622 This is a schematic diagram illustrating an example of the configuration of a press forming simulation apparatus according to Embodiment 1.This flowchart shows the processing procedure for the press forming process simulation according to Embodiment 1.This is a conceptual diagram of the press forming process simulation according to Embodiment 1.This is a flowchart showing the procedure for generating a learning model according to Embodiment 1.This is a conceptual diagram illustrating a method for calculating stress at the bottom dead center during actual press forming.This is a conceptual diagram showing the first example of input and output data for a learning model.This is a conceptual diagram showing a second example of input and output data for a learning model.This is a flowchart showing the procedure for generating a learning model according to Embodiment 2.This is a conceptual diagram illustrating a method for calculating stress at the bottom dead center during actual press forming. A simulation program, press forming simulation method, and press forming simulation apparatus according to embodiments of this disclosure will be described below with reference to the drawings. This disclosure is not limited to these examples, but is intended to include all modifications within the meaning and scope of the claims, as indicated by the claims. Furthermore, at least some of the embodiments described below may be combined in any way. (Embodiment 1) Figure 1 is a schematic diagram illustrating an example configuration of a press forming simulation device 1 according to Embodiment 1. The press forming simulation device 1 is a computer that implements the press forming simulation method according to Embodiment 1, and comprises a processing unit 11, a display unit 12, an operation unit 13, a data input unit 14, and a storage unit 15. Each unit is connected by a bus. The press forming simulation method according to Embodiment 1 is a method that can calculate the shape after springback with sufficient accuracy, even for blank materials with high tensile strength such as high-tensile steel, by learning the relationship between the CAE calculation results of the press forming simulation and the press-formed product obtained using an actual machine. The press forming simulation device 1 may be a standalone computer or a server connected to a network. Furthermore, the press forming simulation device 1 may be a computer in an on-premises environment or a server or other computer in a cloud environment. The press forming simulation device 1 may be configured with multiple computers for distributed processing, implemented using multiple virtual machines within a single server, or implemented using a cloud server. The processing unit 11 is a processor having arithmetic circuits such as a CPU (Central Processing Unit), internal storage devices such as ROM (Read Only Memory) and RAM (Random Access Memory), I/O terminals, a timing unit, etc. Preferably, the processing unit 11 has a configuration with multiple arithmetic cores. The processing unit 11 implements the press forming simulation method according to this embodiment 1 by executing the simulation program (program product) 151 stored in the storage unit 15 described later. Note that each functional unit of the press forming simulation apparatus 1 may be implemented in software, or some or all of them may be implemented in hardware. The display unit 12 is, for example, a display device such as a liquid crystal panel or an organic EL (Electro-Luminescence) display. The operation unit 13 is, for example, an input device such as a hardware keyboard, pointing device, or touch panel. The user of the press forming simulation apparatus 1 can input arbitrary information into the press forming simulation apparatus 1 using the operation unit 13. The operation unit 13 may be configured integrally with the display unit 12. The data input unit 14 is an interface into which data is input externally. The data input unit 14 is, for example, a USB port,