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

Multi-working-condition frame topological optimization method based on grey clustering algorithm model

A clustering algorithm and topology optimization technology, applied in the direction of constraint-based CAD, design optimization/simulation, CAD numerical modeling, etc., can solve the problems of structural shape extraction and manufacturing difficulties, improve the efficiency and quality of research and development, and improve the reliability. Manufacturability, topological structure force transfer path reasonable effect

Pending Publication Date: 2021-08-10
JIANGSU UNIV
View PDF0 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

This patented technology uses Grey-Based algorithms for optimizing network topologies by eliminating areas near certain points along their length. It also allows for better control over how much space they occupy when transmitting data through them compared with traditional methods like Layered Networks (LN). By doing this, it improves overall performance and reliance between different components within an electronic device's circuitry system.

Problems solved by technology

Technological Problem: The technical problem addressed in this patented text relates to improving the efficiency and effectiveness of vehicles while minimizing their weight without compromising its overall performance. Conventional methods such as strengthening frames have limitations due to factors like fatigue caused by repeated use over time. To address these issues, new solutions called continuous topologyoptimization (CLT) were developed during the past decade. However, current CLT algorithms require multiple objectives and iterative processes, making them hard to interpret even if they provide accurate results.

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
  • Multi-working-condition frame topological optimization method based on grey clustering algorithm model
  • Multi-working-condition frame topological optimization method based on grey clustering algorithm model
  • Multi-working-condition frame topological optimization method based on grey clustering algorithm model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0027] For a better understanding of the present invention, the present invention will be further described below in conjunction with the accompanying drawings and embodiments. The present invention can be embodied in many different forms and is not limited to the examples embodied herein. On the contrary, the purpose of providing these examples is to make the disclosure of the present invention more thorough and comprehensive.

[0028] (1) Attached with the manual figure 2 and 3 Describe the unit clustering process based on the gray clustering algorithm model.

[0029] like image 3 Shown is a typical checkerboard phenomenon after topology optimization, white voids and black cells appear alternately, white represents cells with a density of 0, and black represents cells with a density of 1. According to the clustering index, it will be similar to image 3 The pseudo-density of the units near path 1 that is not the main transmission direction of the force is assigned a va...

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 multi-working-condition frame topological optimization method based on a grey clustering algorithm model, and the method comprises the specific steps: carrying out the initial topological optimization of a structure through employing the grey clustering algorithm model, carrying out the pseudo-density of a unit set A, carrying out the clustering of a sample group in the set A according to the correlation between a unit and the structure, determining a clustering index according to a specific actual engineering condition, and then dividing the set A into a deleted unit set B and a reserved unit set C; and filtering and classifying difficult-to-cluster units in a sample according to a distance selection threshold value from the difficult-to-cluster units to a force transmission path, performing grey clustering analysis, dividing A into a deletion unit set B or a reservation unit set C, and taking a frame as an implementation carrier. According to the method, the grey clustering algorithm is applied to the topological optimization design of the structure, the checkerboard phenomenon is effectively inhibited, the manufacturability of the topological optimization result is improved, the frame structure meeting the dynamic and static characteristics is designed, the design and manufacturing period of a product is shortened, and the research and development efficiency and quality of the product are improved.

Description

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

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
Owner JIANGSU UNIV
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