[HTML][HTML] Identification of Johnson-Cook material model parameters for laser shock peening process simulation for AA2024, Ti–6Al–4V and Inconel 718

R Kuliiev, S Keller, N Kashaev - Journal of Materials Research and …, 2024 - Elsevier
This paper addresses the identification of Johnson-Cook material model parameters for the
simulation of high strain rate processes such as laser shock peening. A combined numerical …

On the prediction of fatigue life of WAAM-processed Ti-6Al-4V under consideration of manufacturing defects

AE Odermatt, L Vázquez, P Álvarez… - International Journal of …, 2024 - emerald.com
Purpose There is still a need for a comprehensive investigation into how wire and arc
manufactured (WAAM) parts fail under cyclic loading. This study investigates the effect of …

[HTML][HTML] Very high cycle fatigue assessment of thermoplastic-based hybrid fiber metal laminate by using a high-frequency resonant testing system

S Mrzljak, M Trautmann, G Wagner, F Walther - International Journal of …, 2024 - Elsevier
The prolonged fatigue lifetime of fiber metal laminates (FML) compared to monolithic metals
is a key aspect for safety-relevant components, where detailed knowledge about the fatigue …

Fatigue cracking behavior and life assessment of TC11 titanium alloy in very high cycle regime at two working temperatures

A Mahmood, C Sun, W Li, G Liu, Z Sun - Engineering Failure Analysis, 2024 - Elsevier
Axial loading fatigue tests were conducted with two stress ratios to investigate fracture
surface behavior and associated failure analysis governing crack nucleation of TC11 …

Microstructure-based interior cracking behavior of α + β titanium alloy under two stress ratios and intermediate temperature in the very high-cycle fatigue regime

A Mahmood, C Sun, MI Lashari, W Li - Journal of Materials Science, 2024 - Springer
Axial loading fatigue tests were conducted for α+ β titanium alloy with two stress ratios to
elucidate the microstructure-based interior cracking behavior at 150° C temperature. The …

Development and assessment of machine learning models for predicting fatigue response in AA2024

JK Jatavallabhula, T Gaonnwe, S Nginda… - Materials Research …, 2025 - iopscience.iop.org
Accurate prediction of fatigue life is vital in the design of aerospace components subjected to
varying stress levels and loading frequencies. In the current research, machine learning …

High Cycle Fatigue Behavior of TIG Welded Joint at Optimum Parametric Condition

SC Moi, PK Pal - International Conference on Nonlinear Dynamics and …, 2024 - Springer
In this study, AISI 316L stainless steel plates are joined together in a square butt joint
arrangement using a semiautomatic tungsten inert gas (TIG) welding process. The research …