MFOptBF · Multi-fidelity design optimization of long-span bridges considering probabilistic wind-induced instabilities of flutter and buffeting and hydrodynamics

Multi-fidelity design optimization of long-span bridges considering probabilistic wind-induced instabilities of flutter and buffeting and hydrodynamics

Efficient transport structure is considered as fundamental for the economic growth and social cohesion of communities. Long-span suspension bridges have served to cross large physical barriers for decades as one of the most challenging structures in civil engineering. Several major suspension bridges are currently under planning; Coastal Highway E39 Route in Norway, Çanakkale Bridge in Turkey, Tokyo Bay Bridge in Japan to name a few. The span length of suspension bridges has become longer and longer with the advances in construction technologies, yet the bridge structures become more flexible and more prone to wind-induced vibrations, which are key concepts for the bridge design. Among different structural elements for the design, the bridge deck shape is one of the most important factors to determine the structural response under wind. For the construction of long-span bridges, huge material cost is required, and the reduction in material will be of great importance for the sustainable development of the world. In fact, steel production is one of the main industry sources other than power generation to release considerable amount of CO2. The design optimization is a mathematical method of minimizing a cost function while satisfying structural requirements. For carrying out design optimization of bridge structures considering wind-induced vibrations require high computational cost. In general, Computational Fluid Dynamics (CFD) models are used for the estimation of wind forces acted on a particular bridge section. However, performing numerous precise CFD analyses is computational prohibitive. In recent years, the use of surrogate modelling is becoming more popular to alleviate the high computational costs of numerical simulations. Surrogate models provide a structural response (output) from a limited number of data (input). Among such surrogate modelling, the multi-fidelity surrogate modelling uses two types of input data: few numbers of precise numerical simulations and many low-fidelity approximate models results. Since structural response based on few expensive data is complemented by many cheap data, it saves time for simulations. Therefore, the design optimization based on multi-fidelity surrogate modelling is computationally efficient while maintaining the precision of high-fidelity simulations. The purpose of this project is to carry out the shape design optimization of suspension bridge deck using multi-fidelity methods considering wind instabilities. It is multidisciplinary involving in mathematical discipline of design optimization, wind, and structural engineering. This project will help to form efficient transport in the EU by providing method for the sustainable bridge designs. The multi-fidelity optimization method was proven to be feasible and effective from this project. I hope that more and more industries will use optimization methods for their construction/production so that we could contribute to sustainable development.

Data: CORDIS, © European Union