Articles | Volume 4, issue 4
Wind Energ. Sci., 4, 619–632, 2019
https://doi.org/10.5194/wes-4-619-2019
Wind Energ. Sci., 4, 619–632, 2019
https://doi.org/10.5194/wes-4-619-2019
Research article
12 Nov 2019
Research article | 12 Nov 2019

Adjoint-based calibration of inlet boundary condition for atmospheric computational fluid dynamics solvers

Siamak Akbarzadeh et al.

Related authors

A physically interpretable data-driven surrogate model for wake steering
Balthazar Arnoldus Maria Sengers, Matthias Zech, Pim Jacobs, Gerald Steinfeld, and Martin Kühn
Wind Energ. Sci., 7, 1455–1470, https://doi.org/10.5194/wes-7-1455-2022,https://doi.org/10.5194/wes-7-1455-2022, 2022
Short summary
Validation of a coupled atmospheric–aeroelastic model system for wind turbine power and load calculations
Sonja Krüger, Gerald Steinfeld, Martin Kraft, and Laura J. Lukassen
Wind Energ. Sci., 7, 323–344, https://doi.org/10.5194/wes-7-323-2022,https://doi.org/10.5194/wes-7-323-2022, 2022
Short summary
Applying a Random Time Mapping to Mann modelled turbulence for the generation of intermittent wind fields
Khaled Yassin, Arne Helms, Daniela Moreno, Hassan Kassem, Leo Höning, and Laura J. Lukassen
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2021-139,https://doi.org/10.5194/wes-2021-139, 2021
Preprint under review for WES
Short summary
Numerical Investigation of Aerodynamic Performance of Wind Turbine Airfoils with Ice Accretion
Khaled Yassin, Hassan Kassem, Bernhard Stoevesandt, Thomas Klemme, and Joachim Peinke
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2021-3,https://doi.org/10.5194/wes-2021-3, 2021
Revised manuscript not accepted
Short summary
Potential of load and O&M costs reductions of Multi Rotor System for the south Baltic Sea
Maciej Karczewski, Piotr Domagalski, Arnoldus van Wingerde, Bernhard Stoevesandt, Peter Jamieson, and Lars Roar Saetran
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2020-23,https://doi.org/10.5194/wes-2020-23, 2020
Revised manuscript not accepted
Short summary

Related subject area

Wind and turbulence
Evaluation of obstacle modelling approaches for resource assessment and small wind turbine siting: case study in the northern Netherlands
Caleb Phillips, Lindsay M. Sheridan, Patrick Conry, Dimitrios K. Fytanidis, Dmitry Duplyakin, Sagi Zisman, Nicolas Duboc, Matt Nelson, Rao Kotamarthi, Rod Linn, Marc Broersma, Timo Spijkerboer, and Heidi Tinnesand
Wind Energ. Sci., 7, 1153–1169, https://doi.org/10.5194/wes-7-1153-2022,https://doi.org/10.5194/wes-7-1153-2022, 2022
Short summary
Comparing and validating intra-farm and farm-to-farm wakes across different mesoscale and high-resolution wake models
Jana Fischereit, Kurt Schaldemose Hansen, Xiaoli Guo Larsén, Maarten Paul van der Laan, Pierre-Elouan Réthoré, and Juan Pablo Murcia Leon
Wind Energ. Sci., 7, 1069–1091, https://doi.org/10.5194/wes-7-1069-2022,https://doi.org/10.5194/wes-7-1069-2022, 2022
Short summary
Large-eddy simulation of airborne wind energy farms
Thomas Haas, Jochem De Schutter, Moritz Diehl, and Johan Meyers
Wind Energ. Sci., 7, 1093–1135, https://doi.org/10.5194/wes-7-1093-2022,https://doi.org/10.5194/wes-7-1093-2022, 2022
Short summary
Investigation into boundary layer transition using wall-resolved large-eddy simulations and modeled inflow turbulence
Brandon Arthur Lobo, Alois Peter Schaffarczyk, and Michael Breuer
Wind Energ. Sci., 7, 967–990, https://doi.org/10.5194/wes-7-967-2022,https://doi.org/10.5194/wes-7-967-2022, 2022
Short summary
Evaluation of the global-blockage effect on power performance through simulations and measurements
Alessandro Sebastiani, Alfredo Peña, Niels Troldborg, and Alexander Meyer Forsting
Wind Energ. Sci., 7, 875–886, https://doi.org/10.5194/wes-7-875-2022,https://doi.org/10.5194/wes-7-875-2022, 2022
Short summary

Cited articles

Adams, B. M., Ebeida, M. S., Eldred, M. S., Geraci, G., Jakeman, J. D., Maupin, K. A., Monschke, J. A., Swiler, L. P., Stephens, J. A., Vigil, D. M., and Wildey, T. M.: DAKOTA, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis, Tech. rep., Sandia Technical Report SAND2014-4633, Sandia National Laboratories, Albuquerque, NM, 2017. a
Bauweraerts, P. and Meyers, J.: Towards an adjoint based 4D-Var state estimation for turbulent flow, J. Phys.: Conf. Ser., 1037, 072055, https://doi.org/10.1088/1742-6596/1037/7/072055, 2018. a
Chang, C.-Y., Schmidt, J., Dörenkämper, M., and Stoevesandt, B.: A consistent steady state CFD simulation method for stratified atmospheric boundary layer flows, J. Wind Eng. Indust. Aerodynam., 172, 55–67, https://doi.org/10.1016/j.jweia.2017.10.003, 2018. a, b, c
Chen, H., Miao, C., and Lv, X.: Estimation of open boundary conditions for an internal tidal model with adjoint method: a comparative study on optimization methods, Math. Probl. Eng., https://doi.org/10.1155/2013/802136, 2013. a
Davis, L.: Handbook of genetic algorithms, Van Nostrand Reinhold, New York, NY, 1991. a
Download
Short summary
The numerical flow simulation solvers are extensively used for site assessment in the wind energy industry. However, due to the complexity of flow regimes, it is essential to calibrate the important parameters of such algorithms with measurement data. In this paper, we present a computationally cheap (adjoint) solver that can be coupled with any standard gradient-based optimizer to calibrate the inflow boundary of a CFD solver using the wind speed measurements from the interior of a domain.