Development and validation physical-guided data science models for finite element applications Real-time stress predictions require the continuous interaction of measurements and a complex, refined finite element model that is updated real-time based on measured conditions. Previous work has shown that this interaction can be based on simplified physical relationships that allow quick changes in the model based on actual conditions. However, even when low-fidelity models are used in conjunction with experimental measurements, the resulting computational times are still too large to be feasible with real-time predictions. This complexity has therefore restricted the ability to efficiently monitor the stresses in complex systems during operations without continuous experimental monitoring.