**1. Introduction**

It is well-documented that most of the failures in metallic components are because of fatigue. This makes it vital to analyze and understand the physics behind the fatigue failure and underline a relationship to minimize the chances of failure [1]. Estimation of material fatigue based on multiple experimentation and prediction can have a major role in safe and reliable mechanical design [2]. Several researchers have added their massive effort to devise sound and practical methodologies for fatigue prediction and assess mechanical structures' safety under cyclic mechanical loading [3–5]. It has been affirmed that an accurate forecast of fatigue life is complicated because one must consider several variables to avoid the catastrophic failure of engineering structures while in service [6]. The accuracy of fatigue prediction models is largely based on the capability to predict and model damage under non-zero superimposed mean stresses, range for multi-axiality across the stress regions, and concentration [7]. In case of cyclic and arbitrary loading, it is pretty cumbersome for predicting the fatigue properties because the damage is reliant on major stress components and their deviations while the loading [7].
