Real-time structural Digital Twins require numerical models that assimilate measurements while the physical system is being observed without sacrificing response fidelity. This study evaluates a sensor-driven shell finite element synchronization strategy for quasi-static steel applications. A Python-based Digital Twin Environment Application (DTEA) was coupled with ANSYS Mechanical APDL and the ANSYS Data Processing Framework. During three-point bending tests, load, displacement, and strain data were acquired continuously in real time while DTEA updated the FEM online; no post-test replay was used. All reported numerical results refer to SHELL181. For three steel specimens, branch-aware moment-curvature validation gave curvature NRMSE values of 3.4-7.4% and peak-moment errors of -3.8 to -6.3%. In the representative numerical benchmark, mean solver time increased from 1.01 s in the linear-elastic regime to 1.89 s during transition and 2.08 s in the fully plastic regime. The same DTEA benchmark pathway showed increasing equilibrium-iteration demand with nonlinearity. The results demonstrate real-time acquisition with near-real-time shell FEM state assimilation. Reinforced-concrete testing is ongoing and is not evaluated here.