IABSE Task Group 3.1 Benchmark Results. Numerical Full Bridge Stability and Buffeting Simulations

Diana, Giorgio; Stoyanoff, Stoyan; Allsop, Andrew; Amerio, Luca; Andersen, Michael Styrk; Argentini, Tommaso; Calamelli, Filippo; Montoya, Miguel Cid; Goyet, Vincent de Ville de; Hernández, Santiago; Jurado, J. Á.; Kavrakov, Igor; Larose, Guy L.; Larsen, Allan; Morgenthal, Guido; Rocchi, Daniele; Svendsen, Martin N.; Wu, Teng

doi:10.1080/10168664.2022.2104188

Cited by 7 publications

(3 citation statements)

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“…On the other hand, the aeroelastic performance indicators are the buffeting response of the bridge deck under the action of turbulent wind at four wind mean velocities 𝑈 = [15,30,45,60] m/s. The multimodal buffeting analyses to obtain the RMS of accelerations are performed in the frequency domain following the procedure and wind parameters reported in Diana et al (2022). The modal matrix is built considering 22 modes obtained from the DAs of the bridge FEM after completing the structural size optimization (see Algorithm 1).…”

Section: Application Casesmentioning

confidence: 99%

“…The multimodal buffeting analyses to obtain the RMS of accelerations are performed in the frequency domain following the procedure and wind parameters reported in Diana et al. (2022). The modal matrix is built considering 22 modes obtained from the DAs of the bridge FEM after completing the structural size optimization (see Algorithm 1).…”

Section: Application Casesmentioning

confidence: 99%

“…Extensions of these methods toward multimodal analysis frameworks both in the frequency domain (Ge & Tanaka, 2000; Jain et al., 1996) and the time domain (Beliveau et al., 1977; Caracoglia & Jones, 2003; Chen & Kareem, 2002) showed an excellent performance to model the actual aeroelastic responses of long‐span bridges. They are still nowadays the most widespread methodology used in the industry (Diana et al., 2022), and they have been recently used for the wind‐resistant design optimization of bridges (Cid Montoya et al., 2022).…”

Section: Introductionmentioning

confidence: 99%

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Sequential aero‐structural optimization method for efficient bridge design

Montoya

2023

Computer aided Civil Eng

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The recent development of aero‐structural optimization methods provides a powerful tool to achieve cost‐effective and safe designs for wind‐sensitive structures. However, pursuing holistic formulations involves adopting many design variables and constraints, which increases the computational burden preventing the application of nonlinear methods for accurately assessing aeroelastic responses. This paper proposes a sequential aero‐structural optimization (SASO) method to improve the efficiency of holistic wind‐resistant design optimization of wind‐sensitive structures. The original problem is uncoupled into two standalone optimization problems: a structural size optimization and an aeroelastic shape optimization, linked by an adaptive mapping surrogate and an outer loop. This strategy permits the design‐space dimensionality reduction and avoids the computation of multiple sensitivities with low influence on the design decisions. A long‐span bridge is successfully optimized. The convergence is drastically accelerated by minimizing the number of aeroelastic evaluations, opening the way to implement nonlinear aeroelastic performance‐based design optimization frameworks.

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Section: Application Casesmentioning

confidence: 99%

Section: Application Casesmentioning

confidence: 99%