© 2022 IIETA. This article is published by IIETA and is licensed under the CC BY 4.0 license (http://creativecommons.org/licenses/by/4.0/).
OPEN ACCESS
Today, the assessment of the safety of long-span bridges relies on wind tunnel testing, although CFD methods are steadily penetrating in research and industrial practice. The evaluation of force coefficients and flutter derivatives presents multiple uncertainties, related with inflow boundary conditions, mechanical and mathematical models or parameter choices. In this work, we focus on one single uncertainty parameter that is the wind angle of incidence, which has been studied for instance in building aerodynamics. The assumed input probability density function adopted for the angle of incidence has been uniform in the range of angles considered. Uncertainty quantification tools, such as the stochastic collocation method, are used to propagate the uncertainty in the wind angle of attack for the force coefficients and flutter derivatives of a twin-box bridge deck. To this end, 5 2D URANS static simulations have been completed to quantify the uncertainty in the force coefficients, and 70 2D URANS forced oscillation simulations have been required to obtain the stochastic mean and standard deviation of the flutter derivatives, applying nested Clenshaw–Curtis quadrature points at level 3. It has been found that for the force coefficients, the stochastic standard deviation has been up to 0.032 for the lift coefficient. Furthermore, for the aeroelastic response, the flutter derivatives H1*, A1*, H2* and A2* show important stochastic standard deviations relative to the stochastic mean value for reduced velocities above 10.
aerodynamic derivatives, flutter, force coefficients, stochastic collocation, twin-box deck, uncertainty quantification
[1] Mannini, C., Soda, A., Voβ, R. & Schewe, G., Unsteady RANS simulations of flowaround a bridge section. Journal of Wind Engineering and Industrial Aerodynamics, 98,pp. 724–753, 2010. https://doi.org/10.1016/j.jweia.2010.06.010
[2] Fang, G., Cao, J., Yang, Y., Zhao, L., Cao, S. & Ge, Y., Experimental uncertainty quantificationof flutter derivatives for a PK section girder and its application on probabilisticflutter analysis. ASCE Journal of Bridge Engineering, 25(7), Article number:04020034, 2020. https://doi.org/10.1061/(asce)be.1943-5592.0001567
[3] Bruno, L. & Fransos, D., Probabilistic evaluation of the aerodynamic properties of abridge deck. Journal of Wind Engineering and Industrial Aerodynamics, 99, pp. 718–728, 2011. https://doi.org/10.1016/j.jweia.2011.03.007
[4] Mariotti, A., Salvetti, M.V., Omrani, P.S. & Witteveen, J.A.S., Stochastic analysis ofthe impact of freestream conditions on the aerodynamics of a rectangular 5:1 cylinder.Computers and Fluids, 136, pp. 170–192, 2016. https://doi.org/10.1016/j.compfluid.2016.06.008
[5] Lamberti, G. & Gorlé, C., Uncertainty quantification for RANS predictions of windloads on buildings. In Proc. INVENTO 2018, LNCE 24, Ricciardelli, F. & Avossa, A.M.eds., pp. 402–412, 2019.
[6] Lamberti, G. & Gorlé, C., Sensitivity of LES predictions of wind loading on a high-risebuilding to the inflow boundary condition. Journal of Wind Engineering and IndustrialAerodynamics, 206, Article number: 104370, 2020. https://doi.org/10.1016/j.jweia.2020.104370
[7] Xu, Y.L.,Wind Effects on Cable-Supported Bridges. John Wiley & Sons; Singapore Pte.Ltd, 2013.
[8] Jurado, J.Á., Hernández, S., Nieto, F. & Mosquera, A., Bridge aeroelasticity. Sensitivityanalysis and optimal design. WITPress,Southampton, UK, 2011.
[9] Scanlan, R.H. & Tomko, J.J., Airfoil and bridge deck flutter derivatives. Journal of theEngineering Mechanics Division, 97(6), pp. 1717–1737, 1971. https://doi.org/10.1061/jmcea3.0001526
[10] Smith, R.C., Uncertainty quantification. Theory, implementation, and applications,SIAM, 2014.
[11] Nieto, F., Cid Montoya, M., Hernández, S., Kusano, I., Casteleiro, A., Álvarez, A.J.,Jurado, J.Á. & Fontán, A., Aerodynamic and aeroelastic responses of short gap twinboxdecks: Box geometry and gap distance dependent surrogate based design. Journalof Wind Engineering and Industrial Aerodynamics, 201, Article 104147, 2020. https://doi.org/10.1016/j.jweia.2020.104147
[12] Sarkar, P.P., Caracoglia, L., Haan, F. Jr., Sato, H. & Murakoshi, J., Comparative andsensitivity study of flutter derivatives of selected bridge deck sections, Part 1: Analysisof inter-laboratory experimental data. Engineering Structures, 31, pp. 158–169, 2009.https://doi.org/10.1016/j.engstruct.2008.07.020
[13] Sarkic, A., Höffer, R. & Brcic, S., Numerical simulations and experimental validationsof force coefficients and flutter derivatives of a bridge deck. Journal of Wind Engineeringand Industrial Aerodynamics, 144, pp. 172–182, 2015. https://doi.org/10.1016/j.jweia.2015.04.017
[14] Nieto, F., Owen, J.S., Hargreaves, D.M. & Hernández, S., Bridge deck flutter derivatives:Efficient numerical evaluation exploiting their interdependence. Journal ofWind Engineering and Industrial Aerodynamics, 136, pp. 138–150, 2015. https://doi.org/10.1016/j.jweia.2014.11.006
[15] Patruno, L., Accuracy of numerically evaluated flutter derivatives of bridge deck sectionsusing RANS: Effects on the flutter onset velocity. Engineering Structures, 89, pp.49–65, 2015. https://doi.org/10.1016/j.engstruct.2015.01.034
[16] Sarkic, A., Fisch, R., Höffer, R. & Bletzinger, K.U., Bridge flutter derivatives based oncomputed, validated pressure fields. Journal of Wind Engineering and Industrial Aerodynamics,104–106, pp. 141–151, 2012. https://doi.org/10.1016/j.jweia.2012.02.033