Thin-wall section characteristic deformation identification method

A cross-sectional feature and recognition method technology, applied in the direction of instrumentation, geometric CAD, design optimization/simulation, etc., can solve the problems that the deformation mode is difficult to apply to various geometric and boundary conditions, the number of deformation modes is large, and the calculation cost is high, reaching a clear level Sex and physical interpretability, reduce computational cost, and improve computational efficiency

Active Publication Date: 2020-07-14
HOHAI UNIV CHANGZHOU
View PDF1 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, the method of establishing a one-dimensional model is often used for analysis of thin-walled structures, but the one-dimensional model considering the deformation of the section still has some defects in pattern recognition: the number of deformation modes used is too large, which makes the model more complicated and the calculation cost is high ; The deformation mode is difficult to apply to various geometries and boundary conditions

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
  • Thin-wall section characteristic deformation identification method
  • Thin-wall section characteristic deformation identification method
  • Thin-wall section characteristic deformation identification method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0070] by figure 2 The out-of-plane deformation mode of the first-order eigenvector of the thin-walled structure of the prism section shown is the identification object, and the specific implementation steps are as follows:

[0071] Step 1. The thin-walled section node diagram is as follows image 3 As shown, 6 first-level nodes and 4 second-level nodes are used to capture the deformation of the thin-walled section. The out-of-plane deformation corresponds to the axial deformation of the section. There are 10 original out-of-plane deformation modes. The high-order model of the wall structure defines the basis function by applying node displacement interpolation on the thin-walled section, making the basis function capture the section deformation of the thin-walled structure as accurately as possible, considering the bending characteristics of the thin-walled structure, and based on the Kirchhoff thin-plate assumption The three-dimensional displacement field is constructed, a...

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 thin-wall section characteristic deformation identification method, which comprises the following steps of: 1) constructing a thin-wall structure high-order model by considering section deformation, and deriving a control differential equation of a thin-wall structure by adopting a Hamiltonian principle; 2) solving the generalized eigenvalue of the control differential equation and a corresponding eigenvector by using a finite element method; 3) performing order reduction approximation processing on the feature matrix to identify the axial change mode of the basis function; and 4) orthogonally decomposing the feature vector into a component which is collinear with the axial change mode of the primary function to obtain a proportional relation between the componentand the axial change mode, and multiplying the original deformation mode by the corresponding proportionality coefficient to generate a new deformation mode. According to the method, numerical valueimplementation can be carried out in a simple and visual mode, the derived deformation mode has definite hierarchy and physical interpretability, the dynamic behavior of the thin-wall structure can betruly reflected, the calculation efficiency is greatly improved, and the calculation cost is reduced.

Description

technical field [0001] The invention relates to a thin-wall section feature deformation recognition method, which belongs to the field of dynamic analysis of thin-wall structures. Background technique [0002] The thin-walled structure is a structure composed of thin plates, thin shells and slender rods, which can bear large loads with less weight and less materials, and is widely used in various construction machinery. During the working process, thin-walled structures are prone to stretching, bending and other cross-sectional deformations due to external forces, which directly affect the performance of engineering equipment, and even threaten the safety of workers' lives and property. It is important to study the deformation of thin-walled structures. significance. At present, the method of establishing a one-dimensional model is often used for analysis of thin-walled structures, but the one-dimensional model considering the deformation of the section still has some defec...

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): G06F30/23G06F30/17G06F119/14
Inventor 张磊谢瑶唐亚鸣
Owner HOHAI UNIV CHANGZHOU
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products