Digital twin-driven method for determining wind force coefficients of a bridge deck section

Wind force coefficients are important parameters for aerostatic and aerodynamic analyses in wind-resistant design of a long-span bridge. Wind force coefficients of long-span bridges are currently obtained through wind tunnel tests or computational fluid dynamics (CFD) simulations. Given that limitations and uncertainties exist in both methods, this study proposes a digital twin-driven method for providing more accurate predictions of wind force coefficients of a streamlined bridge deck. The sectional model of the bridge deck tested in a wind tunnel is taken as a physical model, while its virtual model is established using CFD simulation. The test results collected from the physical model are fused with the virtual model using polynomial regression algorithms to update the virtual model into a digital twin. The developed digital twin is employed to conduct an in-depth analysis of blockage effects and provide more accurate wind force coefficients. A global digital twin is then developed based on individual digital twins and Kriging interpolation to provide continuous wind force coefficients within a range of wind attack angles from -12° to 12°. This global digital twin is finally applied for the aerostatic analyses of the bridge. The results show that the digital twin-driven method can provide more accurate prediction than wind tunnel tests or CFD simulations.