Probabilistic S-N fields based on statistical distributions applied to metallic and composite materials: State of the art

• Type: Another Publication in an International Scientific Journal
• Date: 2019

Authors

Barbosa, JF (Author) Other; Correia, JAFO (Author) FEUP; Freire Junior, RCS (Author) Other; Zhu, SP (Author) Other; Abilio M P De Jesus (Author) FEUP

Journal

Title: Advances in Mechanical Engineering

Vol. 11

ISSN: 1687-8132

Publisher: SAGE

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 30 Citations

Other information

Authenticus ID: P-00R-05P

DOI: 10.1177/1687814019870395

Abstract (EN): Fatigue life prediction of materials can be modeled by deterministic relations, via mean or median S-N curve approximation. However, in engineering design, it is essential to consider the influence of fatigue life scatter using deterministic-stochastic methods to construct reliable S-N curves and determine safe operation regions. However, there are differences between metals and composites that must be considered when proposing reliable S-N curves, such as distinct fracture mechanisms, distinct ultimate strengths under tension and compression loading, and different cumulative fatigue damage mechanisms including low-cycle fatigue. This study aims at conducting a review of the models used to construct probabilistic S-N fields (P-S-N fields) and demonstrate the methodologies applied to fit the P-S-N fields that are best suited to estimate fatigue life of the selected materials. Results indicate that the probabilistic Stussi and Sendeckyj models were the most suitable for composite materials, while, for metals, only the probabilistic Stussi model presented a good fitting of the experimental data, for all fatigue regimes.7

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 22