Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Dependence-based multi-objective optimization method of integrated phenomenological constitutive model

A multi-objective optimization and dependency technology, which is applied in the fields of mechanical manufacturing, numerical analysis, and material mechanical performance characterization, can solve problems such as increased difficulty in determination, increased uncertainty and non-uniformity, and increased material parameters in characterization constitutive models.

Active Publication Date: 2018-03-09
BEIJING INSTITUTE OF TECHNOLOGYGY
View PDF2 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] There are following problems in the determination of the phenomenological constitutive model in the prior art: (1) a large amount of mechanical tests need to be carried out in a wide range of loads; (2) for a series of explanatory variables (plastic strain, strain rate, deformation temperature and It is difficult to define the coupling relationship between the observable material behavior of the test); (3) it is more difficult to determine as the number of material parameters representing the constitutive model increases; (4) the accurate expression of the constitutive model is often related to the experience of the developer, Increased uncertainty and non-uniformity in constitutive development for the same material

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Dependence-based multi-objective optimization method of integrated phenomenological constitutive model
  • Dependence-based multi-objective optimization method of integrated phenomenological constitutive model
  • Dependence-based multi-objective optimization method of integrated phenomenological constitutive model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0143] The test material is a silicon carbide reinforced aluminum matrix composite material with a volume ratio of 15%. The quasi-static and dynamic mechanical tests were performed on the Gleeble 3500 thermal simulator and the SHPB device, respectively. Gleeble thermal simulation experiment is heated to the specified forming temperature at a rate of 4°C / s in vacuum, and then kept at the forming temperature for three minutes, with a rate of 0.001s -1 Compression tests were carried out at the strain rates, and the test forming temperatures were 25, 100, 200, 300 and 400 °C. SHPB test conditions: nominal forming temperature is 25°C, 100°C, 200°C, nominal strain rate is 1000, 2000s -1 , 5000s -1 and 7000s -1 . figure 1 (a) and figure 1 (b) Quasi-static and dynamic mechanical test data obtained for Gleeble test and dynamic SHPB test, respectively.

[0144] Such as Figure 5 As shown, a dependency-based integrated phenomenological constitutive multi-objective optimization met...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a dependence-based multi-objective optimization method of an integrated phenomenological constitutive model and belongs to the technical field of material mechanics properties,machine manufacturing and numerical analysis. The multi-objective optimization method is constructed by introducing three kinds of weighting factors in consideration of measuring errors and the sameoptimization opportunity of data point number or constitutive parameter number and quasi-static and dynamic states under different loading conditions, a non-coupled strain hardening function under quasi-static deformation, a thermal softening function under quasi-static deformation, a strain hardening function of coupling temperature under quasi-static deformation, a non-coupled strain rate sensitive function under quasi-static and dynamic deformation and a strain rate sensitive function of coupling temperature under quasi-static and dynamic deformation are sequentially determined according tooptimization quality criteria, and the basic form of the phenomenological constitutive model is determined; the specific form of the determined constitutive model is fit according to test data underall loading conditions with the multi-weight and multi-objective optimization method.

Description

technical field [0001] The invention relates to a dependency-based integrated phenomenological constitutive multi-objective optimization method, which belongs to the technical neighborhood of material mechanical performance characterization, mechanical manufacturing and numerical analysis. Background technique [0002] During industrial forming and fabrication, materials undergo complex strain, strain rate, and temperature histories. A good understanding of material flow behavior is important for material forming and manufacturing process planning. Therefore, in order to describe the flow law of materials during deformation, it is necessary to develop and establish a constitutive model, which reflects the mechanical behavior of materials under different deformation rates and temperature loading conditions. The constitutive equation is a mathematical model that expresses the relationship between material flow stress and plastic strain, strain rate and temperature. It describ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06F17/15
CPCG06F17/15G06F30/20G06F2111/06
Inventor 解丽静项俊锋高飞农胡鑫程冠华庞思勤王西彬
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com