Prediction of low cycle fatigue life for neutron-irradiated and nonirradiated RAFM steels using their tensile properties

IF 5.7 2区材料科学 Q1 ENGINEERING, MECHANICAL International Journal of Fatigue Pub Date : 2024-09-04 DOI:10.1016/j.ijfatigue.2024.108589

Hussein Zahran , Aleksandr Zinovev , Dmitry Terentyev , Giacomo Aiello , Magd Abdel Wahab

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Abstract

Reduced Activation Ferritic-Martensitic (RAFM) steels are the candidate structural steels for In-Vessel Components of fusion reactors. Since the operation of a tokamak-type fusion reactor is cyclic by its nature, thermomechanical fatigue will be one of the limiting factors defining the life of the plasma-facing components exposed to neutron irradiation. The assessment of fatigue life requires considerable efforts in terms of low cycle fatigue experiments, which is extremely complicated on neutron-irradiated specimens inside the hot cell environment. Performing tensile tests is instead much faster, technically easier and more cost effective than performing fatigue tests especially on neutron-activated specimens. Therefore, a method for predicting fatigue life based on the tensile properties would be an important asset to assess the design of IVC when experimental data on fatigue are not available. Here, several fatigue life prediction methods based on Universal Slopes Equation were assessed based on the fatigue test results of RAFM steels in the irradiated and non-irradiated conditions to choose the best method. Analysis of the available fatigue database showed an effect of test medium and specimen size on the fatigue life. This effect was quantified and added to the selected method by means of scaling factors. The chosen method with the scaling factors was able to predict the fatigue life of irradiated and non-irradiated RAFM steels with an accuracy of 95% within the sleeve of factor three. The modified equations were then used to predict the fatigue life of irradiated RAFM steels at irradiation doses for which the fatigue data is not available.

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利用拉伸特性预测中子辐照和非辐照 RAFM 钢的低循环疲劳寿命

还原活化铁素体-马氏体（RAFM）钢是聚变反应堆舱内部件的候选结构钢。由于托卡马克式聚变反应堆的运行本质上是周期性的，因此热机械疲劳将是决定暴露于中子辐照下的面向等离子体部件寿命的限制因素之一。对疲劳寿命的评估需要进行大量的低循环疲劳实验，而在热室环境中对中子辐照试样进行低循环疲劳实验是极其复杂的。与疲劳试验相比，拉伸试验更快，技术上更简单，成本效益更高，尤其是在中子激活的试样上。因此，在没有疲劳实验数据的情况下，基于拉伸特性的疲劳寿命预测方法将是评估 IVC 设计的重要资产。在此，根据 RAFM 钢在辐照和非辐照条件下的疲劳测试结果，评估了几种基于通用斜坡方程的疲劳寿命预测方法，以选择最佳方法。对现有疲劳数据库的分析表明，试验介质和试样尺寸对疲劳寿命有影响。对这种影响进行了量化，并通过比例因子添加到所选方法中。所选方法与缩放因子能够预测辐照和非辐照 RAFM 钢的疲劳寿命，在因子 3 的套筒内准确率达到 95%。然后使用修改后的公式来预测辐照剂量下 RAFM 钢的疲劳寿命，因为辐照剂量下的 RAFM 钢没有疲劳数据。

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来源期刊

International Journal of Fatigue 工程技术-材料科学：综合

CiteScore

10.70

自引率

21.70%

发文量

619

审稿时长

58 days

期刊介绍： Typical subjects discussed in International Journal of Fatigue address: Novel fatigue testing and characterization methods (new kinds of fatigue tests, critical evaluation of existing methods, in situ measurement of fatigue degradation, non-contact field measurements) Multiaxial fatigue and complex loading effects of materials and structures, exploring state-of-the-art concepts in degradation under cyclic loading Fatigue in the very high cycle regime, including failure mode transitions from surface to subsurface, effects of surface treatment, processing, and loading conditions Modeling (including degradation processes and related driving forces, multiscale/multi-resolution methods, computational hierarchical and concurrent methods for coupled component and material responses, novel methods for notch root analysis, fracture mechanics, damage mechanics, crack growth kinetics, life prediction and durability, and prediction of stochastic fatigue behavior reflecting microstructure and service conditions) Models for early stages of fatigue crack formation and growth that explicitly consider microstructure and relevant materials science aspects Understanding the influence or manufacturing and processing route on fatigue degradation, and embedding this understanding in more predictive schemes for mitigation and design against fatigue Prognosis and damage state awareness (including sensors, monitoring, methodology, interactive control, accelerated methods, data interpretation) Applications of technologies associated with fatigue and their implications for structural integrity and reliability. This includes issues related to design, operation and maintenance, i.e., life cycle engineering Smart materials and structures that can sense and mitigate fatigue degradation Fatigue of devices and structures at small scales, including effects of process route and surfaces/interfaces.