Applications of a new magnetic monitoring technique to in situ evaluation of fatigue damage in ferrous components
- Iowa State Univ. of Science and Technology, Ames, IA (United States). Center for Nondestructive Evaluation
This project consisted of research into the use of magnetic inspection methods for the estimation of fatigue life of nuclear pressure vessel steel. Estimating the mechanical and magnetic properties of ferromagnetic materials are closely interrelated, therefore, measurements of magnetic properties could be used to monitor the evolution of fatigue damage in specimens subjected to cyclic loading. Results have shown that is possible to monitor the fatigue damage nondestructively by magnetic techniques. For example, in load-controlled high-cycle fatigue tests, it has been found that the plastic strain and coercivity accumulate logarithmically during the fatigue process. Thus a quantitative relationship between coercivity and the number of fatigue cycles could be established based on two empirical coefficients, which can be determined from the test conditions and material properties. Also it was found that prediction of the onset of fatigue failure in steels was possible under certain conditions. In strain-controlled low cycle fatigue, critical changes in Barkhausen emissions, coercivity and hysteresis loss occurred in the last ten to twenty percent of fatigue life.
- Research Organization:
- US Nuclear Regulatory Commission (NRC), Washington, DC (United States). Div. of Engineering; Iowa State Univ. of Science and Technology, Ames, IA (United States). Center for Nondestructive Evaluation
- Sponsoring Organization:
- Nuclear Regulatory Commission, Washington, DC (United States)
- OSTI ID:
- 10166580
- Report Number(s):
- NUREG/GR-0013; ON: TI94015174
- Resource Relation:
- Other Information: PBD: Jun 1994
- Country of Publication:
- United States
- Language:
- English
Similar Records
Development of Digital Twin Predictive Model for PWR Components: Updates on Multi Times Series Temperature Prediction Using Recurrent Neural Network, DMW Fatigue Tests, System Level Thermal-Mechanical-Stress Analysis
Evaluation of fatigue damage in steel structural components by magnetoelastic Barkhausen signal analysis