Active flow control strategy for aerodynamic interference reduction in twin-deck bridges: Upstream-deck wake manipulation via the goose optimization algorithm
Year: 2026
Type: article
Abstract: Aerodynamic interference induced by the construction of a new bridge adjacent to an existing one may adversely affect the aerodynamic performance of the existing structure. To avoid retrofitting the existing structure and traffic control, this study proposes a flow control strategy that optimizes the aerodynamics of the newly constructed (upstream) deck while preserving the original aerodynamic characteristics of the existing (downstream) bridge. Blowing slots were installed along the trailing edge of the upstream deck, and an optimization framework integrating Latin hypercube sampling, Kriging surrogate modeling, and the goose optimization algorithm was developed to efficiently determine the optimal blowing velocities, thereby avoiding conventional trial-and-error procedures. A streamlined twin-deck without wind fairings was adopted as a case study. The aerostatic coefficients, surface pressure distributions, and wake flow structures were examined to evaluate aerodynamic interference and control effectiveness, and a parametric analysis was further conducted to assess the sensitivity of the downstream aerodynamic response to the blowing velocities. The results demonstrate that the proposed strategy can effectively alleviate aerodynamic interference and substantially reduce the deviations of the downstream deck’s aerostatic characteristics from those of the prescribed reference case. These findings suggest that active blowing applied solely to the newly constructed upstream deck provides a promising approach for mitigating aerodynamic interference in parallel bridge systems.
Source: Structures
Authors: Dian-yi Guo, Wen-ming Zhang, Li-ming Zhao
Institution: Southeast University
Language: English
Subfield: Computational Mechanics
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,510
Awards: G2932357873, G8649739537, G9000113113
OpenAlex ID: W7215129680
