In this study, a neuro-fuzzy-based machine learning method is developed to predict the
multiaxial fatigue life of various metallic materials. First, the fuzzy inference system and …

High-reliability life design process not only can ensure system safety in service, but also can
provide scientific life management during the maintenance period. The objective of the …

In order to investigate the probabilistic damage distribution under creep-fatigue interaction,
machine learning framework with the divide-and-conquer methodology is proposed to …

In power and energy systems, both the aerodynamic performance and the structure
reliability of turbine equipment are affected by utilized blades. In general, the design process …

Engineering components made of ductile cast irons and aluminum alloys, show fatigue lives
which are normally dominated by crack initiation from defects raised by manufacturing …

A numerical process based on crystal plasticity finite element (CPFE) was implemented to
predict creep-fatigue crack initiation life. CPFE-based model can describe the macroscopic …

A series of strain-controlled creep-fatigue tests with various dwell times and strain ratios are
carried out on a nickel-based superalloy at 650° C. Aiming at the mechanical understanding …

Cumulative fatigue damage analysis and life prediction of engineering
structures/components is vital for ensuring their structural integrity and operational reliability …

Notched components with complex configurations are normally designed for engineering
functional requirements. Geometrical discontinuities generally result into stress …

In this article, machine learning is used to predict lifetime under isothermal low-cycle fatigue
and thermo-mechanical fatigue loading, both of which represent the most complex loadings …