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

Method for predicting low-cycle fatigue life of metallic material under multi-step loading conditions

A low-cycle fatigue and metal material technology, applied in the direction of applying stable tension/pressure to test the strength of materials, can solve the problems of error between prediction results and actual conditions, unreliable life evaluation results, etc., and achieve the effect of convenient engineering application

Inactive Publication Date: 2013-03-20
CENT SOUTH UNIV
View PDF1 Cites 15 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, if the characteristics of material nonlinear fatigue damage accumulation are not fully considered, as well as the impact of the previous loading step on the subsequent loading step, there will be a large error between the predicted results and the actual situation, which directly leads to unreliable life evaluation 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
  • Method for predicting low-cycle fatigue life of metallic material under multi-step loading conditions
  • Method for predicting low-cycle fatigue life of metallic material under multi-step loading conditions
  • Method for predicting low-cycle fatigue life of metallic material under multi-step loading conditions

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0017] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0018] The invention is a method for predicting the low-cycle fatigue life of metal materials under the condition of multi-step loading and asymmetric cyclic stress control. Taking the low-cycle fatigue life prediction of AZ31B magnesium alloy material as an example below, the implementation details of the life prediction method involved in the present invention are introduced in detail, and the method includes:

[0019] Step 1: A low cycle fatigue experiment based on asymmetric cyclic stress control is carried out on AZ31B magnesium alloy material (rolling direction sampling) to obtain the step of low cycle fatigue life of the material; cyclic loading condition parameters include peak stress and stress amplitude, Its values ​​are shown in Tables 1 and 2. The yield limit and tensile limit of the material are obtained by uniaxial tensile test...

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

PropertyMeasurementUnit
fatigue limitaaaaaaaaaa
Login to View More

Abstract

The invention discloses a method for predicting the low-cycle fatigue life of a metallic material under multi-step loading conditions. The method comprises the following steps of: (1) obtaining the low-cycle fatigue life of the metallic material through one-step and multi-step loaded asymmetric cyclic stress control fatigue experiments; (2) according to the working conditions of the fatigue experiments and the fatigue property of the material, determining a fatigue parameter (FP) calculation equation of the material during one-step loading, and establishing a fatigue life prediction model of the material under one-step loading conditions; (3) proposing a fatigue parameter (FP') calculation equation of the material during multi-step loading according to the nonlinear damage accumulation characteristics of the material in a multi-step loading process; and (4) establishing a low-cycle fatigue life prediction model of the metallic material under multi-step loaded asymmetric cyclic stress control conditions, and predicting the fatigue life of the metallic material. According to the method disclosed by the invention, the low-cycle fatigue life of the metallic material under the multi-step loaded asymmetric cyclic stress control conditions can be quickly predicted, thereby providing a theoretical reference for the reliable design and evaluation of parts.

Description

technical field [0001] The invention relates to a method for predicting the life of low-cycle fatigue failure of metal materials under the condition of multi-step loading and asymmetrical stress cycle control. Background technique [0002] Materials / parts are often subjected to cyclic loads during actual service, making fatigue failure one of the main causes of part damage. Especially when the average stress of the metal material / part under cyclic load is not equal to zero, and the load amplitude is constantly changing and large enough (to make the material yield), the plastic strain will continue to accumulate, which seriously reduces the fatigue performance of the material / part . Therefore, to ensure the reliability, durability and safety of such materials / parts during use, the nonlinear fatigue damage accumulation characteristics of materials / parts must be considered in fatigue design and safety assessment. In the actual service process, most of the loads on materials / p...

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): G01N3/08
Inventor 蔺永诚刘正华陈小敏陈明松
Owner CENT SOUTH 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