Physics-Auditable Dryout Recognition in Helical Tubes under Condition Shift

Reliable dryout recognition from sparse wall thermocouples supports thermal-margin assessment in helical tubes. Existing control-based and raw-channel models can confound condition-dependent temperature levels with circumferential film-redistribution patterns. The main bottleneck is condition transfer in the small-sample regime: pressure and mass flux shift the common temperature level, four-side sampling aliases higher-order circumferential modes, and random splits can obscure group dependence. We introduce a physics-auditable hybrid world-model architecture for retrospective report-label recognition. Its primary lane uses an exact four-point harmonic transform to separate the common level from signed circumferential contrasts before fixed-threshold ExtraTrees classification. An anchored residual RSSM and a differentiable FE decoder provide auxiliary rollout and conditional stress-audit branches. On the $3.5\to 7$ MPa pressure-held-out split, the primary lane reaches BA 0.929, compared with 0.786 for raw channels and 0.823 for controls-only ExtraTrees. The five-fold group-held-out BA is 0.957, compared with 0.916 for raw channels. The gain is specific to fixed-threshold BA and does not extend uniformly to AUROC; the focal pressure comparison is not statistically significant. Anchor ablation shows severe rollout drift, although the RSSM remains slightly worse than persistence, and the FE branch remains a conditional structural screen rather than a measured-stress validation. This architecture provides an auditable route from sparse measurements to condition-shifted recognition with explicit evidence boundaries.