Moderately thick composite cylindrical shells are widely used in submarine pressure-resistant structures. This study employed machine learning to analyse the failure of moderately thick composite cylindrical shells under hydrostatic pressure. Ten moderately thick composite cylindrical shells were fabricated, and their failure behaviour was examined through hydrostatic experiments and finite element analysis (FEA). Subsequently, their failure modes were analysed using FEA. Furthermore, this study trained a TabNet model for predicting the failure pressure of moderately thick composite cylindrical shells, and the model's accuracy and interpretability were validated. The trained TabNet was used to analyse the interaction effects of a shell's length-to-radius ratio (L/R), thickness-to-radius ratio (T/R), and ply angle (θ) on failure pressure. The experimental failure pressures were consistent with the FEA predictions (average error = 1.53 %). The T/R threshold at which the failure mode changes from buckling instability to strength failure varied with the ply angle. The threshold was lowest for shells with ply angles of ±20° and ±30°, and shells with ±10° and 0°/90° ply angles consistently exhibited buckling instability. The TabNet model, which achieved an R2 of 0.986 on the test set, had higher accuracy for failure pressure prediction than benchmark models did. Interpretability analysis revealed that θ and T/R are the dominant factors affecting a shell's failure pressure. Failure pressure increases to the greatest degree as T/R increases for shells with ply angles of ±60° to ±80°. Conversely, failure pressure decreases most markedly with increasing L/R within the same ply angle range. Moreover, if L/R or T/R is increased, the optimal alternating ply angle for maximising failure pressure tends to slightly decrease. The findings of this study offer guidance for the design of pressure-resistant composite shells used in submarine applications.
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