The aim of this study is to develop a new framework for the prediction of stress intensity
factor (SIF) using newly developed hybrid artificial intelligence (AI) models. To do so, an …

Fatigue life estimation is essential for life safety and cost reasons. Fatigue parameters at low
cycles must be estimated with high accuracy to correctly estimate fatigue life. Conventional …

Artificial neural networks (ANNs) are a widely used machine learning approach for
estimating low‐cycle fatigue parameters. ANN structure has its parameters such as hidden …

Properly modeling the cyclic elastoplastic behavior of structural steels is essential for
establishing accurate analyses of structures subjected to earthquake excitation. However …

The coupling set, exposed to multi-directional severe dynamic loads, is a vital part that
connects the wagons in rail system vehicles. These loads are usually transferred through the …

Turbines, crucial in reusable rocket engines, benefit significantly from precise fatigue life
forecasting in their force‐thermal cyclic loading conditions. Further, low‐cycle fatigue life …

This paper introduces a novel method for estimating the cyclic stress–strain curves of steels
based on their monotonic properties and plastic strain amplitudes, utilizing artificial neural …

Purpose In this manuscript, the authors aimed to demonstrate the influences of influential
parameters in mixed-mode crack propagation phenomenon. The authors attempted to cover …

An elliptical subsurface crack under normal loading may experience mixed fracture modes
due to the non‐symmetrical geometry. This paper investigates the coupling of the modes of …

Normal loading causes mixed fracture modes in an elliptical subsurface crack because of
the nonsymmetrical geometry with respect to the crack face. In this paper, mixed mode …