TY - GEN
T1 - System Identification of OSWEC Response Using Physics-Informed Neural Network
AU - Ayyad, Mahmoud
AU - Ahmed, Alaa
AU - Yang, Lisheng
AU - Hajj, Muhammad R.
AU - Datla, Raju
AU - Zuo, Lei
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Optimizing the geometry and increasing the efficiency through PTO control of oscillating surge wave energy converters require the development of effective reduced-order models that can predict their hydrodynamic response. We implement a multi-step approach to identify the coefficients of the equation governing this response. Data from quasi-static, free decay and torque-forced experiments are used to respectively identify and represent the stiffness, the radiation damping, and the added mass and nonlinear damping terms. Particularly, we implement a data-driven system discovery, referred to as Physics-Informed Neural Network, to identify the added mass and nonlinear damping coefficients in the governing equations. Validation is performed via comparing time series predicted by the reduced order model to the measured time series.
AB - Optimizing the geometry and increasing the efficiency through PTO control of oscillating surge wave energy converters require the development of effective reduced-order models that can predict their hydrodynamic response. We implement a multi-step approach to identify the coefficients of the equation governing this response. Data from quasi-static, free decay and torque-forced experiments are used to respectively identify and represent the stiffness, the radiation damping, and the added mass and nonlinear damping terms. Particularly, we implement a data-driven system discovery, referred to as Physics-Informed Neural Network, to identify the added mass and nonlinear damping coefficients in the governing equations. Validation is performed via comparing time series predicted by the reduced order model to the measured time series.
KW - Oscillating Surge Wave Energy Converter (OSWEC)
KW - Physics-Informed Neural Network (PINN)
KW - Reduced-Order Model
KW - System Identification
UR - http://www.scopus.com/inward/record.url?scp=85173648052&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85173648052&partnerID=8YFLogxK
U2 - 10.1109/OCEANSLimerick52467.2023.10244631
DO - 10.1109/OCEANSLimerick52467.2023.10244631
M3 - Conference contribution
AN - SCOPUS:85173648052
T3 - OCEANS 2023 - Limerick, OCEANS Limerick 2023
BT - OCEANS 2023 - Limerick, OCEANS Limerick 2023
T2 - 2023 OCEANS Limerick, OCEANS Limerick 2023
Y2 - 5 June 2023 through 8 June 2023
ER -