Search

CN-121980940-A - Mold flow behavior virtual simulation design system integrating multiple field characteristics

CN121980940ACN 121980940 ACN121980940 ACN 121980940ACN-121980940-A

Abstract

The invention relates to the technical field of mold design and manufacture, and discloses a mold flow behavior virtual simulation design system integrating multiple field characteristics, which comprises a multi-mode data acquisition module, a multiple field coupling simulation module, a material gene spectrum library, an intelligent optimization engine module and a physical verification closed-loop module; the multi-mode data acquisition module, the multi-field coupling simulation module, the intelligent optimization engine module and the physical verification closed-loop module are arranged, so that the interaction between a temperature field and a stress field of a die is dynamically simulated through a thermal-force coupling equation, the error accumulation of traditional split simulation is avoided, the coupling effect of melt flow and die deformation is predicted through a flow-solid coupling equation, the problem of flow instability in traditional single-field simulation is solved, the cross-scale correlation between millimeter level and micrometer level is realized through coupling the thermal field and the flow field and coupling the force field and the thermal field, and the error accumulation of traditional split simulation is avoided through the thermal-force coupling equation and the flow-solid coupling equation.

Inventors

  • ZENG FEI
  • YUAN JINRUI
  • YAN XIAOZHENG

Assignees

  • 东莞市智尚双色注塑模具有限公司

Dates

Publication Date
20260505
Application Date
20260123

Claims (10)

  1. 1. The die flow behavior virtual simulation design system integrating the multi-field characteristics is characterized by comprising a multi-mode data acquisition module, a multi-field coupling simulation module, a material gene spectrum library, an intelligent optimization engine module and a physical verification closed-loop module; The multi-mode data acquisition module acquires physical signals of a key area of the die in real time through integrating multiple types of sensors, and performs data fusion after preprocessing the data; The multi-field coupling simulation module synchronously simulates melt flow, mold deformation and temperature field distribution by adopting a thermal-force coupling equation and a flow-solid coupling equation to acquire simulation data, and simultaneously introduces a phase change latent heat item to construct a real-time heat exchange model; The material gene spectrum library builds a cross-scale correlation model through the viscosity-temperature-shear rate relation, builds a database for storing material parameters, and receives data of a physical verification closed-loop module to update the parameters of the cross-scale correlation model; the intelligent optimization engine module adopts an improved genetic algorithm to generate an optimal mold design scheme; And the physical verification closed-loop module is used for manufacturing a mould prototype through 3D printing, acquiring actual measurement data by using a three-dimensional scanner, calculating deformation and driving an actuator to compensate.
  2. 2. The virtual simulation design system for the flow behavior of the die integrating the multi-field characteristics, which is disclosed in claim 1, is characterized in that the multi-type sensors comprise a temperature sensor, a pressure sensor, a strain sensor and a vibration sensor, the key areas of the die comprise a die cavity, a runner and a pressure ring, the real-time acquisition is based on the dynamic high-speed sampling frequency of the motion state of the die by a dynamic compensation sampling method, and the data fusion adopts a time alignment algorithm to map scattered data to a unified coordinate system to generate a gridding characteristic data set.
  3. 3. The virtual simulation design system of integrated multi-field feature of claim 2, wherein the time alignment algorithm is formulated as: Wherein, the method comprises the steps of, Representation of Data characteristics after time fusion; represent the first The weights of the sensors are dynamically distributed based on the signal-to-noise ratio; Representing an exponential decay coefficient; represent the first Time when the individual sensors acquired the data; represent the first Personal sensor Data characteristics collected at the moment.
  4. 4. The virtual simulation design system of mold flow behavior integrating multiple field characteristics of claim 3 wherein said thermo-mechanical coupling equation is expressed as: Wherein, the method comprises the steps of, Representing the material density of the mold; Representing the specific heat capacity of the mold; the thermal conductivity of the mold is expressed, and the ability of the material used for the mold to conduct heat is expressed; Representing the term of mechanical work converted heat energy, representing the heat energy converted due to mechanical action and the like; Representing temperature; representing hamiltonian; the flow-solid coupling equation is expressed as: Wherein, the method comprises the steps of, Representing a melt velocity field; Representing the pressure acting on the melt; Representing dynamic viscosity; representing a thermal buoyancy term; Representing the laplace operator.
  5. 5. The virtual simulation design system of mold flow behavior integrating multiple field features of claim 4 wherein said real-time heat exchange model is formulated as: Wherein, the method comprises the steps of, Represents the phase change latent heat term, Represents latent heat; Representing the liquid phase fraction.
  6. 6. The virtual simulation design system for integrated multi-field performance of mold flow behavior of claim 5, wherein the material parameters comprise elastic modulus of the material, viscosity-temperature relation parameters, and the viscosity-temperature-shear rate relation construction cross-scale correlation model is expressed as: Wherein, the method comprises the steps of, Representing the viscosity of the material as a function of temperature and shear rate; Represents the shear rate; representing a reference viscosity; Represents activation energy; Representing the gas constant; Representing a shear rate parameter; representing the change parameters, and taking the values as 。
  7. 7. The virtual simulation design system for integrated multi-field feature die flow behavior of claim 6, wherein said generating an optimal die design scheme using an improved genetic algorithm comprises: step 1, initializing a population, and setting the size of the population as Will make a decision on the variable The encoding is performed as a vector of real numbers, , Represent the first Each decision variable corresponds to a mold design scheme; generating an initial population , , Representing the first of the initial population Individual, i.e. the first A decision variable; step 2, setting an objective function, and sequencing the objective function according to the numerical value; step 3, non-dominant sorting is carried out based on the non-dominant grade; Step 4, calculating the crowding degree; Step 5, generating a offspring population through binary tournament selection, crossover and mutation operation; step 6, combining the current population and the offspring population to form a mixed population, and forming a new generation parent population from the mixed population; And 7, repeating the steps 3 to 6, stopping iteration when the iteration number reaches the maximum iteration number or the fixed convergence condition is met, and outputting the first non-dominant layer in the final population as an optimal solution, wherein the optimal solution is the optimal mould design scheme.
  8. 8. The virtual simulation design system of mold flow behavior integrating multiple field characteristics of claim 7 wherein said objective function is expressed as: Wherein, the method comprises the steps of, Represent the first Objective functions corresponding to individual individuals; representing a first objective function as the first Filling pressure corresponding to individual bodies; Representing a second objective function as the first Filling pressure residual stress corresponding to each individual; 。
  9. 9. the virtual simulation design system for integrated multi-field feature die flow behavior of claim 8, wherein said non-dominant ordering is specifically: Dividing individuals in the population into different dominance classes, for any two individuals And (3) with If it meets Then call it Dominance of Is marked as ; And forming a first layer by the individuals not subjected to any other individuals in the population, removing the individuals in the first layer from the population, repeating the operation, finding out the individuals not subjected to any other individuals in the rest individuals, forming a second layer, and repeating the operation until all the individuals are divided into a certain layer.
  10. 10. The virtual simulation design system for integrated multi-field feature of die flow behavior of claim 9, wherein the computational congestion level is specifically: Wherein, the method comprises the steps of, Represent the first Layer 1 A degree of congestion of the individual; represent the first The normalized range of the individual objective functions, Representing the number of objective functions; And (3) with Represent the first In the layer Is a group of two adjacent individuals.

Description

Mold flow behavior virtual simulation design system integrating multiple field characteristics Technical Field The invention relates to the technical field of mold design and manufacture, in particular to a mold flow behavior virtual simulation design system integrating multiple field characteristics. Background The publication CN119647290A discloses a parameterized simulation model design method and a parameterized simulation model design system for a plastic mold, wherein the method comprises the following steps of finely preparing a target plastic raw material to obtain a homogeneous drying material, carrying out multi-field rheological property scanning on the homogeneous drying material, carrying out viscosity model parameter extraction to obtain a viscosity model initial parameter, carrying out precise thermodynamic property measurement on the plastic material on the homogeneous drying material, carrying out crystallization dynamics behavior analysis to obtain a crystallization dynamics model parameter, and carrying out material gene spectrum integration according to the viscosity model initial parameter and the crystallization dynamics model parameter to obtain a material gene spectrum. According to the invention, through performance-driven parameter optimization and intelligent mold blueprint generation based on material physical properties and micro environments, the efficiency and quality of mold manufacturing are remarkably improved, and the manufacturing cost is reduced. However, in the existing mold design, virtual simulation technologies such as UG motion simulation and injection filling simulation are concentrated in a single physical field such as fluid or structural stress, comprehensive analysis on the coupling effect of multiple fields is lacking, a data island exists, dynamic fusion of data is not realized, so that the deviation between simulation and physical test is large, the simulation result lacks real-time interactive verification with a physical experiment, dynamic correction is difficult, and closed loop verification is lacking. Disclosure of Invention In order to overcome the above-mentioned drawbacks of the prior art, the present invention provides a system for virtual simulation design of flow behavior of a mold integrating multiple-field characteristics, so as to solve the above-mentioned problems in the prior art. The invention provides a die flow behavior virtual simulation design system integrating multiple field characteristics, which comprises a multi-mode data acquisition module, a multiple field coupling simulation module, a material gene spectrum library, an intelligent optimization engine module and a physical verification closed loop module; The multi-mode data acquisition module acquires physical signals of a key area of the die in real time through integrating multiple types of sensors, and performs data fusion after preprocessing the data; The multi-field coupling simulation module synchronously simulates melt flow, mold deformation and temperature field distribution by adopting a thermal-force coupling equation and a flow-solid coupling equation to acquire simulation data, and simultaneously introduces a phase change latent heat item to construct a real-time heat exchange model; The material gene spectrum library builds a cross-scale correlation model through the viscosity-temperature-shear rate relation, builds a database for storing material parameters, and receives data of a physical verification closed-loop module to update the parameters of the cross-scale correlation model; the intelligent optimization engine module adopts an improved genetic algorithm to generate an optimal mold design scheme; And the physical verification closed-loop module is used for manufacturing a mould prototype through 3D printing, acquiring actual measurement data by using a three-dimensional scanner, calculating deformation and driving an actuator to compensate. Preferably, the plurality of types of sensors include a temperature sensor, a pressure sensor, a strain sensor, and a vibration sensor; the method comprises the steps of acquiring a data fusion, wherein the data fusion comprises a data fusion process, a data fusion process and a data fusion process, wherein the data fusion process comprises the steps of acquiring a data fusion process, and acquiring a data fusion process. Preferably, the time alignment algorithm is formulated as: Wherein, the method comprises the steps of, Representation ofData characteristics after time fusion; represent the first The weights of the sensors are dynamically distributed based on the signal-to-noise ratio; Representing an exponential decay coefficient; represent the first Time when the individual sensors acquired the data; represent the first Personal sensorData characteristics collected at the moment. Preferably, the thermo-mechanical coupling equation is expressed as: Wherein, the method comprises the steps of, Representing the material