Predicting Fatigue Life of 51CrV4 Steel Parabolic Leaf Springs Manufactured by Hot-Forming and Heat Treatment: A Mean Stress Probabilistic Modeling Approach

• Type: Article in International Scientific Journal
• Date: 2025

Authors

Gomes, VMG (Author) Other; Miguel Figueiredo (Author) FEUP; Correia, JAFO (Author) Other; de Jesus, AMP (Author) Other

Journal

Title: Metals

Final page: 315

Publisher: MDPI

Other information

Authenticus ID: P-018-ADP

DOI: 10.3390/met15030315

Abstract (EN): <jats:p>The longevity of railway vehicles is an important factor in their mechanical and structural design. Fatigue is a major issue that affects the durability of railway components, and, therefore, knowledge of the fatigue resistance characteristics of critical components, such as leaf springs, must be extensively investigated. This research covers the fatigue resistance of 51CrV4 steel under bending and axial tension, for distinct stress ratios, in the low-cycle fatigue regime (LCF), high-cycle fatigue regime (HCF), and very high-cycle fatigue regime (VHCF) using experimental data collected in this work and from previous experiments. Two fatigue models were analyzed: the Walker model (WSN) and the Castillo¿Fernández¿Cantelli model, CFC, adapted for the presence of mean stress (ACFC). According to the analysis carried out, both fatigue resistance prediction models provided good results for the experimental data, with the ACFC model showing good fitting when considering all the failure data and outliers. Additionally, fracture surfaces showed a higher trend for crack initiation on the surface for positive stress ratios despite internal defects also possibly being responsible for some fatigue failures. This investigation aimed to provide a probabilistic fatigue model encompassing the LCF, HCF, and VHCF fatigue regimes for distinct stress ratios for the fatigue design analysis of 51CrV4 steel parabolic leaf springs manufactured by hot-forming processes with subsequent heat treatments.</jats:p>

Language: English

Type (Professor's evaluation): Scientific