Small Sample-Based Fatigue Reliability Analysis Using Non-Intrusive Polynomial Chaos

Abstract

Based on small sample of fatigue test data, a new method to obtain p-S-N curve for fatigue reliability analysis using non-intrusive polynomial chaos (NIPC) is proposed to lower test cost. Parameter C in Basquin S-N model is regarded as random variable. Samples of C are calculated through inverse analysis based on small sample of fatigue test life. Then non-intrusive polynomial chaos expansions of C with respect to fatigue life are constituted under different stress levels. Statistics of C can be calculated directly by polynomial coefficients. A fast large-sample of C can be obtained based on NIPC and probability distribution type can be determined through EDF test. Then samples of C under the stress levels can be obtained and substituted into S-N model to calculate corresponding fatigue life samples. The fatigue life under different reliabilities are calculated for fitting p-S-N curve. Fatigue test of Al 2024-T3 plate with hole is performed. p-S-N curves are obtained by proposed method and compared with that obtained by linear regression based on least square method. Almost all relative errors are less than 5%, which show that the proposed method can predict p-S-N curve effectively.

Keywords

• Fatigue reliability analysis
• non-intrusive polynomial chaos
• p-S-N curve
• small sample
• Basquin S-N model
• aluminium alloy 2024-T3