  Digital twinning in structural engineering is a rapidly evolving technology
that aims to eliminate the gap between physical systems and their digital
models through real-time sensing, visualization, and control techniques.
Although digital twins can offer dynamic insights into physical systems, their
accuracy is inevitably compromised by uncertainties in sensing, modeling,
simulation, and controlling. This paper proposes a specialized digital twin
formulation, named Risk Twin, designed for real-time risk visualization and
risk-informed control of structural systems. Integrating structural reliability
and Bayesian inference methods with digital twining techniques, Risk Twin can
analyze and visualize the reliability indices for structural components in
real-time. To facilitate real-time inference and reliability updating, a
"simulation-free" scheme is proposed, leveraging precomputed quantities
prepared during an offline phase for rapid inference in the online phase.
Proof-of-concept numerical and real-world Risk Twins are constructed to
showcase the proposed concepts.
