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• The damage evolution process based on modulus degradation was obtained by experimental data. DIC technique was used for surface cracks tracking, and SEM was used for fracture surface analysis. • The ductility parameters were used to correlate the lifetime of AA2024-T351 under multiaxial proportional and non-proportional loads. • The life prediction results of AA2024-T351 by the improved FS model were consistent with the experimental data. Multiaxial fatigue has been drawing much attention because it is more applicable to engineering practice. In this paper, an experimental study of aluminum alloy (AA) 2024-T351 was carried out under multiaxial loading with an aim to assess the damage evolution process and failure mechanism under in-phase and out-of-phase loadings. Firstly, fatigue life and stress response under multiaxial cyclic loads were obtained, and it found that although there is non-proportional hardening, the fatigue life subjected to proportional loading is significantly shorter than that of under a nonproportional loading, which was tried to be explained by the ductility of the material. Secondly, a detailed analysis of the damage evolution process based on the degradation of the elastic modulus and the fatigue failure process based on the digital image correlation (DIC) method was provided. Next, a micro-analysis of the specimens' fracture appearance was conducted to obtain the fracture characteristics and found that AA2024-T351 presents a dominant shear fracture mode under proportional loading and a mixed mode of tensile and shear fracture under non-proportional loading. Last but not least, The Fatemi-Socie criterion was modified by considering the material's ductility and the interaction between normal stress and shear stress acting on the critical plane. The multiaxial life prediction results of the modified FS model for AA2024-T351 in this paper were all within the scatter bands of 3 on life. [ABSTRACT FROM AUTHOR]

• A novel framework is established to obtain the distribution characteristics of fatigue parameters {σ f ', ε f '}. • The parameters {σ f ', ε f '} of AA2024-T351 quantified based on the Huffman model all conform to the Weibull distribution. • Based on the distribution of strain life parameters {σ f ', ε f '}, the probability field of Δ γ eq /2-N curves are obtained. • Based on P-Δ γ eq /2-N, a multiaxial fatigue reliability analysis of AA2024-T351 is derived. Various uncertainties are widely presented in engineering problems, such as material properties, loads, geometries, etc. Research has indicated that there is a significant relationship between the dispersion of fatigue life and the material properties. Therefore, it is necessary to study the effect of the parameter distribution of the material on the uncertainty of fatigue life. However, there are very few studies involving the distribution of fatigue performance parameters {σ f ', ε f '} of materials. In this paper, a probability framework of multiaxial fatigue life prediction based on the uncertainty of material parameters {σ f ', ε f '} was established, which focuses on quantifying the distribution of material parameters {σ f ', ε f '} based on the Huffman model. Next, based on the Fatemi-Socie (FS) model and the distribution of strain life parameters {σ f ', ε f '}, the probability field of Δ γ eq /2- N curves were obtained, and experimental data were distributed around the predicted average life. In addition, a time-dependent multiaxial fatigue reliability analysis method based on the Palmgren-Miner rule and P -Δ γ eq /2- N was derived, and the reliability curves were obtained under four multiaxial loading cases. [ABSTRACT FROM AUTHOR]