Design coupling tool enables a reduction in the number of design variables, while preserving sufficient design accuracy, resulting in a reduction in total design optimization cost. This project aims to develop design coupling analysis methodologies leveraging various modeling and analysis technologies, such as machine learning, surrogate modeling, and design process framework theories. The demonstration problem will be implemented in the Wind Energy with Integrated Servo-control (WEIS) toolset, based on the OpenMDAO-WEIS framework, and will identify groups of design variables that should be optimized together in a full floating offshore wind turbine (FOWT) control co-design (CCD) optimization.

Related Publications and Presentations

• Athul K. Sundarrajan, Yong Hoon Lee, James T. Allison, Daniel S. Zalkind, Daniel R. Herber, “Open-loop control co-design of semisubmersible floating offshore wind turbines using linear parameter-varying models”, Journal of Mechanical Design, 2024.
• Athul K. Sundarrajan, Yong Hoon Lee, James T. Allison, Daniel R. Herber, “Open-loop control co-design of floating offshore wind turbines using linear parameter-varying models”, in ASME IDETC/CIE Conference, DETC2021-67573, 2021, pp. 1-13.
• Saeid Bayat, Yong Hoon Lee and James T. Allison, “Nested Control Co-design of a Spar Buoy Horizontal-axis Floating Offshore Wind Turbine”, in Applied Energy Symposium: MIT A+B, Cambridge, MA, USA: ICAE, 2022.
• Yong Hoon Lee, Saeid Bayat and James T. Allison, “Control Co-Design Using a Nonlinear Wind Turbine Dynamic Model Based on OpenFAST Linearization”, in Applied Energy Symposium: MIT A+B, Cambridge, MA, USA: ICAE, 2022.
• Saeid Bayat, Yong Hoon Lee and James T. Allison, “Control co-design of horizontal floating offshore wind turbines using a simplified low order model”, in Wind Energy Science Conference, 2021, pp. 9.78.