Long-term wind-induced response of suspension bridges including static response, flutter stability, and parametric effects of turbulence

Parametric effects induced by atmospheric turbulence have emerged as an important factor influencing the aeroelastic behavior and extreme response of long-span suspension bridges. Originating from angle-of-attack fluctuations due to large-scale turbulence, these effects can significantly modify aerodynamic damping and stiffness, particularly for streamlined bridge decks. Long-term analysis, mainly adopted in the field of offshore structures, overcomes some limitations of classical Davenport theory-based approaches for calculating the dynamic response to turbulent wind of flexible structures, such as long-span suspension bridges. Among other aspects, it accounts for the influence of the statistical variability in turbulence parameters on the structural response, which is expected to impact on the actual role played by parametric effects of turbulence. However, accounting for these effects typically requires time-domain simulations, leading to prohibitive computational costs. This study introduces an efficient frequency-domain framework that incorporates the most significant parametric effect of turbulence (the so called "average parametric effect'') into the long-term evaluation of extreme response. The proposed formulation also includes static response and flutter instability, two aspects usually overlooked in previous contributions. The methodology is applied to the Halsafjorden Bridge, a planned 2000-m span suspension bridge in Norway. Three different wind scenarios, in terms of turbulence intensity and mean wind speed, are also considered. Long-term extremes are close to the results of the classical short-term approach if the mean wind speed is the only environmental random variable. In contrast, non-negligibly larger long-term responses are obtained if the randomness in turbulence intensity is also considered. Moreover, results reveal that the parametric effects of turbulence can significantly increase the long-term extreme response, particularly in torsion, where turbulence-induced damping reductions may lead to response increments of up to 41% for a return period of 100 years. Their impact is greater than in classical short-term analyses, where the average parametric effect leads to an increase in the torsional response of about 33%. This behavior is even more pronounced for higher return periods. These findings highlight that the combined influence of parametric effects of turbulence and randomness in the environmental parameters (e.g., turbulence intensity) can properly be assessed only within a long-term analysis.