How can fatigue analysis improve mechanical component design?

1 What is fatigue analysis?

Fatigue analysis is the study of how materials and structures behave when they are subjected to cyclic or fluctuating loads over time. Fatigue is a common cause of failure in mechanical components, especially those that operate under dynamic or variable conditions, such as engines, turbines, bridges, and aircraft. Fatigue failure occurs when small cracks initiate and grow due to the repeated application and removal of stress, until they reach a critical size and cause a sudden fracture. Fatigue analysis aims to predict the fatigue life of a component, which is the number of cycles or hours that it can endure before failing.

2 Types of fatigue analysis

There are two main types of fatigue analysis: stress-life (S-N) and strain-life (ε-N). Stress-life analysis is based on the relationship between the applied stress amplitude and the number of cycles to failure for a given material. It is suitable for high-cycle fatigue, where the stress level is low and the number of cycles is high. Strain-life analysis is based on the relationship between the strain amplitude and the number of cycles to failure for a given material. It is suitable for low-cycle fatigue, where the stress level is high and the number of cycles is low. Strain-life analysis also accounts for the effects of plastic deformation, mean stress, and temperature on fatigue life.

3 Methods of fatigue analysis

There are three main methods of fatigue analysis: analytical, experimental, and numerical. Analytical methods use mathematical equations and models to estimate the fatigue life of a component based on its geometry, material properties, and loading conditions. Experimental methods use physical tests and measurements to determine the fatigue life of a component or a specimen under controlled or realistic loading conditions. Numerical methods use computer simulations and software tools to perform fatigue analysis based on finite element models, stress or strain data, and fatigue criteria. Numerical methods can provide more accurate and detailed results than analytical or experimental methods, but they also require more computational resources and data inputs.