Richard D. Sandberg

17 papers C 3Journal 13Unranked 1
YearRankTypeTitle / Venue / Authors
2025 J jnl
A Surrogate-Augmented Symbolic CFD-Driven Training Framework for Accelerating Multi-objective Physical Model Development.
CoRR
Yuan Fang, Fabian Waschkowski, Maximilian Reissmann, Richard D. Sandberg, Takuo Oda, Koichi Tanimoto
2025 J jnl
Constraining genetic symbolic regression via semantic backpropagation.
Genet. Program. Evolvable Mach.
Maximilian Reissmann, Yuan Fang, Andrew S. H. Ooi, Richard D. Sandberg
2024 J jnl
Accelerating evolutionary exploration through language model-based transfer learning.
CoRR
Maximilian Reissmann, Yuan Fang, Andrew S. H. Ooi, Richard D. Sandberg
2022 J jnl
Multi-objective CFD-driven development of coupled turbulence closure models.
J. Comput. Phys.
Fabian Waschkowski, Yaomin Zhao, Richard D. Sandberg, Joseph Klewicki
2021 J jnl
Application of Gene Expression Programming to a-posteriori LES modeling of a Taylor Green Vortex.
J. Comput. Phys.
Maximilian Reissmann, Josef Hasslberger, Richard D. Sandberg, Markus Klein
2021 J jnl
Two Dimensional Analysis of Hybrid Spectral/Finite Difference Schemes for Linearized Compressible Navier-Stokes Equations.
J. Sci. Comput.
Raynold Tan, Andrew Ooi, Richard D. Sandberg
2020 J jnl
RANS turbulence model development using CFD-driven machine learning.
J. Comput. Phys.
Yaomin Zhao, Harshal D. Akolekar, Jack Weatheritt, Vittorio Michelassi, Richard D. Sandberg
2019 J jnl
A framework to develop data-driven turbulence models for flows with organised unsteadiness.
J. Comput. Phys.
Chitrarth Lav, Richard D. Sandberg, Jimmy Philip
2018 J jnl
Application of an evolutionary algorithm to LES modelling of turbulent transport in premixed flames.
J. Comput. Phys.
Matthias Schoepplein, Jack Weatheritt, Richard D. Sandberg, Mohsen Talei, Markus Klein
2017 J jnl
The boundary data immersion method for compressible flows with application to aeroacoustics.
J. Comput. Phys.
Stefan C. Schlanderer, Gabriel D. Weymouth, Richard D. Sandberg
2016 J jnl
A novel evolutionary algorithm applied to algebraic modifications of the RANS stress-strain relationship.
J. Comput. Phys.
Jack Weatheritt, Richard D. Sandberg
2016 J jnl
Iterative learning control applied to a non-linear vortex panel model for improved aerodynamic load performance of wind turbines with smart rotors.
Int. J. Control
Mark Blackwell, Owen R. Tutty, Eric Rogers, Richard D. Sandberg
2015 C conf
Iterative learning control for load control of smart turbine blades with variable rotation rates.
ACC
Owen R. Tutty, Mark Blackwell, Eric Rogers, Richard D. Sandberg
2014 C conf
Computational fluid dynamics based iterative learning control for smart rotor enabled fatigue load reduction in wind turbines.
ACC
Mark Blackwell, Owen R. Tutty, Eric Rogers, Richard D. Sandberg
2014 J jnl
Iterative Learning Control for Improved Aerodynamic Load Performance of Wind Turbines With Smart Rotors.
IEEE Trans. Control. Syst. Technol.
Owen R. Tutty, Mark Blackwell, Eric Rogers, Richard D. Sandberg
2013 C conf
Iterative learning control of wind turbine smart rotors with pressure sensors.
ACC
Owen R. Tutty, Mark Blackwell, Eric Rogers, Richard D. Sandberg
2012 — conf
Computational fluid dynamics based iterative learning control of peak loads in wind turbines.
CDC
Owen R. Tutty, Mark Blackwell, Eric Rogers, Richard D. Sandberg