Fatigue life uncertainty prediction using the Monte Carlo and Latin hypercube sampling techniques under uniaxial and multiaxial cyclic loading

The estimation of uncertainty in fatigue life prediction is a decision-making factor in structural design. The problem is specific in the case of multiaxial loading owing to the complex process involved in life prediction. Numerical algorithms are often required to narrow our choice of uncertainty estimation to stochastic sampling. The Monte Carlo technique is often substituted by Latin hypercubes to reduce the computational cost. However, its effectiveness in the uncertainty of life prediction under multiaxial loading has not been validated. To bridge this gap, these two sampling techniques are tested and compared with the application of several stress-based models to the new results of the experimental test on 16Mo3 steel.

Automated summary

The estimation of uncertainty in fatigue life prediction is an important factor in structural design. In the case of multiaxial loading, numerical algorithms are often used to narrow down the choice of uncertainty estimation to stochastic sampling. This study tests and compares the effectiveness of Latin hypercubes and Monte Carlo technique in the uncertainty of life prediction under multiaxial loading, using the results of experimental tests on 16Mo3 steel.