A Predictive Methodology for Temperature, Heat Generation and Transfer in Gigacycle Fatigue Testing

Autor: Felipe Klein Fiorentin, Luis Reis, Grzegorz Lesiuk, Ana Reis, Abílio de Jesus
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Metals, Vol 13, Iss 3, p 492 (2023)
Druh dokumentu: article
ISSN: 2075-4701
DOI: 10.3390/met13030492
Popis: Recently, a trend in fatigue testing related to increasing excitation frequencies during experiments has been observed. This tendency is a product of both necessity and available technological capabilities. Regarding the last, advances in control and excitation systems made it possible to perform tests at impressive frequencies, beyond the tenths of kHz. Performing fatigue tests much faster is indeed very motivating, representing less time and money spent. On the other hand, such high testing frequencies create some challenges, such as the requirement of measurement systems capable of working with high sample rates and excessive heat generation on the testing samples. The last one is especially critical for fatigue once the mechanical properties, such as the elasticity modulus and yield strength, are highly dependent on the temperature. Therefore, being able to predict and control the sample temperature during fatigue testing is essential. The main goal of the present work is to provide a formulation for estimating the heat generation and specimen temperature during high frequency testing, namely in the ultra-high cycle fatigue (UHCF) regime. Several metallic alloys and specimen geometries were tested, and the model results were compared with experimental temperature measurements. The developed model was able to properly characterize the temperature trend over time. In addition, a script was developed and made publicly available.
Databáze: Directory of Open Access Journals