| Optimization under uncertainty for wake steering strategies J Quick, J Annoni, R King, K Dykes, P Fleming, A Ning Journal of physics: Conference series 854 (1), 012036, 2017 | 66 | 2017 |
| Wake steering optimization under uncertainty J Quick, J King, RN King, PE Hamlington, K Dykes Wind Energy Science 5 (1), 413-426, 2020 | 35 | 2020 |
| Wind farm turbine type and placement optimization P Graf, K Dykes, G Scott, J Fields, M Lunacek, J Quick, PE Rethore Journal of Physics: Conference Series 753 (6), 062004, 2016 | 21 | 2016 |
| Assessment of wind parameter sensitivity on ultimate and fatigue wind turbine loads AN Robertson, L Sethuraman, J Jonkman, J Quick National Renewable Energy Lab.(NREL), Golden, CO (United States), 2018 | 18 | 2018 |
| Grand challenges in the digitalisation of wind energy A Clifton, S Barber, A Bray, P Enevoldsen, J Fields, AM Sempreviva, ... Wind Energy Science Discussions 2022, 1-42, 2022 | 16 | 2022 |
| PyWake 2.5. 0: An open-source wind farm simulation tool MM Pedersen, AM Forsting, P van der Laan, R Riva, LAA Romàn, ... Denmark: Technical University of Denmark, 2023 | 13 | 2023 |
| Wind turbine optimization with WISDEM KL Dykes, RR Damiani, PA Graf, GN Scott, RN King, Y Guo, J Quick, ... National Renewable Energy Lab.(NREL), Golden, CO (United States), 2018 | 13 | 2018 |
| Optimization under uncertainty of site-specific turbine configurations J Quick, K Dykes, P Graf, F Zahle Journal of Physics: Conference Series 753 (6), 062012, 2016 | 11 | 2016 |
| Multifidelity uncertainty quantification with applications in wind turbine aerodynamics J Quick, PE Hamlington, R King, MA Sprague AIAA Scitech 2019 Forum, 0542, 2019 | 9 | 2019 |
| Systems engineering and optimization of wind turbines and power plants A Ning, K Dykes, J Quick National Renewable Energy Lab.(NREL), Golden, CO (United States), 2019 | 8 | 2019 |
| Assessment of wind parameter sensitivity on extreme and fatigue wind turbine loads A Robertson, L Sethuraman, JM Jonkman 2018 Wind Energy Symposium, 1728, 2018 | 8 | 2018 |
| Gradient-based wind farm layout optimization with inclusion and exclusion zones J Criado Risco, R Valotta Rodrigues, M Friis-Møller, J Quick, ... Wind Energy Science Discussions 2023, 1-24, 2023 | 6 | 2023 |
| Stochastic gradient descent for wind farm optimization J Quick, PE Rethore, M Mølgaard Pedersen, RV Rodrigues Wind Energy Science Discussions 2022, 1-17, 2022 | 6 | 2022 |
| Enabling co-innovation for a successful digital transformation in wind energy using a new digital ecosystem and a fault detection case study S Barber, LAM Lima, Y Sakagami, J Quick, E Latiffianti, Y Liu, R Ferrari, ... Energies 15 (15), 5638, 2022 | 5 | 2022 |
| Exploring optimization opportunities in four-point suspension wind turbine drivetrains through integrated design approaches L Sethuraman, J Quick, K Dykes, Y Guo 2018 Wind Energy Symposium, 1000, 2018 | 5 | 2018 |
| Active subspaces for wind plant surrogate modeling R King, J Quick, C Adcock, K Dykes 2018 Wind Energy Symposium, 2019, 2018 | 4 | 2018 |
| Temporal coherence importance sampling for wind turbine extreme loads estimation PA Graf, R King, K Dykes, J Quick, L Kilcher, J Rinker AIAA Scitech 2019 Forum, 1798, 2019 | 2 | 2019 |
| Speeding up large-wind-farm layout optimization using gradients, parallelization, and a heuristic algorithm for the initial layout R Valotta Rodrigues, MM Pedersen, JP Schøler, J Quick, PE Réthoré Wind Energy Science 9 (2), 321-341, 2024 | 1 | 2024 |
| Speeding up large wind farms layout optimization using gradients, parallelization, and a heuristic algorithm for the initial layout RV Rodrigues, MM Pedersen, JP Schøler, J Quick, P Réthoré Wind Energy Science Discussions 2023, 1-30, 2023 | 1 | 2023 |
| Enabling Co-Innovation for A Successful Digital Transformation in Wind Energy Using the WeDoWind Ecosystem and A Fault Detection Case Study S Barber, L Lima, Y Sakagami, J Quick, E Latiffianti, Y Liu, R Ferrari, ... Preprints, 2022 | 1 | 2022 |
