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PurposeAiming at the problems of poor accuracy and limitation in strength assessment of spot welding vehicle body caused by uncertain factors, such as key component size and nugget diameter, the numerical models of strength uncertainty analysis of spot-welded joints were constructed based on evidence theory and fuzzy theory.Design/methodology/approachEvidence theory and fuzzy theory are used to deal with the uncertainty of design parameter, and differential evolution algorithms are used to calculate the propagation process of uncertainty in this model. Furthermore, efficient relationship between the strength of welded joints and each design parameter is constructed by using response surface proxy model, which effectively avoids the problem of repeated complex finite element analysis in uncertainty analysis.FindingsThe results show that the constructed uncertainty numerical model is effective for the multiple uncertainties and give interval results under different probabilities and affiliations, which can more effectively evaluate the strength of the welded body structure to avoid overly conservative estimates for deterministic design.Originality/valueThe evidence theory is improved and combined with differential evolution algorithm and response surface method to effectively improve the computational efficiency. Based on the improved evidence theory and fuzzy algorithm, the numerical models for the uncertainty analysis of solder joint strength of welded structures are constructed and their feasibility is verified.

In fatigue life prediction, many models fail to account for the impact of various factors, such as small load strengthening effect, loading sequence and real-time damage state. In this paper, a new nonlinear fatigue life prediction model has been developed, which a load action factor is introduced into Ye’s toughness dissipation energy model. The action factor combines the small load stress ratio, stress amplitude ratio, and fatigue real-time damage function into an exponential function with multiple powers. This model effectively considers the interaction between loads, loading sequence, real-time damage and the small load strengthening effect. The modified fatigue life prediction model has been tested using data of commonly metal materials, such as 45-gauge steel and 16Mn, under two or more variable amplitude loads. The comparison between experimental and predicted values shows that the new nonlinear fatigue life prediction model can more accurately predict the remaining fatigue life for different materials under multistage variable amplitude loading. Moreover, the model does not require additional parameters and can be easily implemented in practical engineering applications.

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