Fatigue strength prediction of 410NiMo stainless steel with surrogate weld discontinuities

IF 5.7 2区材料科学 Q1 ENGINEERING, MECHANICAL

International Journal of Fatigue Pub Date : 2025-03-24 DOI:10.1016/j.ijfatigue.2025.108955

C. Constantineau , P.A. Deschênes , R. Dubois , M. Brochu

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Abstract

The fatigue strength of martensitic stainless steel 410NiMo, featuring slag-type discontinuities, was investigated to evaluate the accuracy of fatigue strength prediction models. This study examines the influence of volumetric discontinuities introduced through robotic FCAW on fatigue strength, characterized using advanced techniques. High-resolution CT scanning (20 µm/voxel) enabled precise 3D modelling of the welded zones, supporting finite element simulations of the stress field. These simulations revealed complex distributions, with singularity exponents ranging from 0.27 to 0.45, lower than the typical 0.50 exponent associated with cracks. Fatigue experiments demonstrated that Linear Elastic Notch Mechanics (LENM), applied for the first time in this context, overestimated fatigue resistance by 34 %, whereas Linear Elastic Fracture Mechanics (LEFM), based on maximum discontinuity width, provided more accurate and conservative predictions, with an average deviation of 16 %. Fractographic analyses identified crack initiation sites at flux-filled micro-notches undetectable by CT resolution, while foreign elements from flux residues were observed, suggesting a potential embrittlement effect. These findings indicate that large, rounded discontinuities in welds can behave like cracks due to embedded microscopic cracks or notches. The study highlights the limitations of LENM for volumetric discontinuities in FCAW welds and establishes a framework for improving fatigue strength prediction.

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采用替代焊缝间断的410NiMo不锈钢疲劳强度预测

研究了具有渣型不连续结构的410NiMo马氏体不锈钢的疲劳强度，以评价疲劳强度预测模型的准确性。本研究考察了通过机器人FCAW引入的体积不连续性对疲劳强度的影响，并使用先进的技术进行了表征。高分辨率CT扫描（20 μ m/体素）实现了焊接区域的精确3D建模，支持应力场的有限元模拟。这些模拟显示了复杂的分布，奇点指数在0.27到0.45之间，低于与裂纹相关的典型0.50指数。疲劳实验表明，在这种情况下首次应用的线弹性缺口力学（LENM）高估了34%的疲劳抗力，而基于最大不连续宽度的线弹性断裂力学（LEFM）提供了更准确和保守的预测，平均偏差为16%。断口分析在CT分辨率无法检测到的充满熔剂的微缺口处确定了裂纹起裂位置，而从熔剂残留物中观察到外来元素，表明可能存在脆化效应。这些发现表明，由于嵌入的微观裂纹或缺口，焊缝中的大而圆的不连续可以表现为裂纹。该研究突出了LENM在FCAW焊缝体积不连续方面的局限性，并建立了改进疲劳强度预测的框架。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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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.