Computational fluid dynamics based iterative learning control of peak loads in wind turbines. - Owen R. Tutty; Mark Blackwell; Eric Rogers; Richard D. Sandberg (CDC, 2012)

Iterative learning control of wind turbine smart rotors with pressure sensors. - Owen R. Tutty; Mark Blackwell; Eric Rogers; Richard D. Sandberg (ACC, 2013)

Computational fluid dynamics based iterative learning control for smart rotor enabled fatigue load reduction in wind turbines. - Mark Blackwell; Owen R. Tutty; Eric Rogers; Richard D. Sandberg (ACC, 2014)

Iterative Learning Control for Improved Aerodynamic Load Performance of Wind Turbines With Smart Rotors. - Owen R. Tutty; Mark Blackwell; Eric Rogers; Richard D. Sandberg (IEEE Trans. Control. Syst. Technol., 2014)

Iterative learning control for load control of smart turbine blades with variable rotation rates. - Owen R. Tutty; Mark Blackwell; Eric Rogers; Richard D. Sandberg (ACC, 2015)

Iterative learning control applied to a non-linear vortex panel model for improved aerodynamic load performance of wind turbines with smart rotors. - Mark Blackwell; Owen R. Tutty; Eric Rogers; Richard D. Sandberg (Int. J. Control, 2016)

A novel evolutionary algorithm applied to algebraic modifications of the RANS stress-strain relationship. - Jack Weatheritt; Richard D. Sandberg (J. Comput. Phys., 2016)

The boundary data immersion method for compressible flows with application to aeroacoustics. - Stefan C. Schlanderer; Gabriel D. Weymouth; Richard D. Sandberg (J. Comput. Phys., 2017)

Application of an evolutionary algorithm to LES modelling of turbulent transport in premixed flames. - Matthias Schoepplein; Jack Weatheritt; Richard D. Sandberg; Mohsen Talei; Markus Klein 002 (J. Comput. Phys., 2018)

A framework to develop data-driven turbulence models for flows with organised unsteadiness. - Chitrarth Lav; Richard D. Sandberg; Jimmy Philip (J. Comput. Phys., 2019)

RANS turbulence model development using CFD-driven machine learning. - Yaomin Zhao; Harshal D. Akolekar; Jack Weatheritt; Vittorio Michelassi; Richard D. Sandberg (J. Comput. Phys., 2020)

Application of Gene Expression Programming to a-posteriori LES modeling of a Taylor Green Vortex. - Maximilian Reissmann; Josef Hasslberger; Richard D. Sandberg; Markus Klein 002 (J. Comput. Phys., 2021)

Two Dimensional Analysis of Hybrid Spectral/Finite Difference Schemes for Linearized Compressible Navier-Stokes Equations. - Raynold Tan; Andrew Ooi; Richard D. Sandberg (J. Sci. Comput., 2021)

Multi-objective CFD-driven development of coupled turbulence closure models. - Fabian Waschkowski; Yaomin Zhao; Richard D. Sandberg; Joseph Klewicki (J. Comput. Phys., 2022)

Accelerating evolutionary exploration through language model-based transfer learning. - Maximilian Reissmann; Yuan Fang; Andrew S. H. Ooi; Richard D. Sandberg (CoRR, 2024)

Constraining genetic symbolic regression via semantic backpropagation. - Maximilian Reissmann; Yuan Fang; Andrew S. H. Ooi; Richard D. Sandberg (Genet. Program. Evolvable Mach., 2025)