Potential use of Bayesian Networks for estimating relationship among rotational dynamics of floating offshore wind turbine tower in extreme environmental conditions.
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A Gaussian Bayesian network for the estimation of technical relationships among structural dynamic responses of the tower of a floating spar-type offshore wind turbine. Probabilities were given within the referenced paper. The vertices are:
Platform pitch tilt angular (rotational) displacement;
Platform roll tilt angular (rotational) displacement;
Platform horizontal surge (translational) displacement;
Platform horizontal sway (translational) displacement;
Tower-top/yaw bearing fore-aft (translational) deflection (relative to the undeflected position);
Tower-top/yaw bearing angular (rotational) pitch deflection (relative to the undeflected position);
Tower-top/yaw bearing angular (rotational) roll deflection (relative to the undeflected position);
Tower-top/yaw bearing side-to-side (translation) deflection (relative to the undeflected position);
Tower base fore-aft shear force;
Tower base side-to-side shear force;
Nonrotating tower-top/yaw bearing roll moment;
Nonrotating tower-top/yaw bearing pitch moment;
Tower-top/yaw bearing fore-aft (nonrotating) shear force;
Tower-top/yaw bearing side-to-side (nonrotating) shear force;
Nonrotating tower-top/yaw bearing roll moment;
Nonrotating tower-top/yaw bearing pitch moment;
Rostam-Alilou, A. A., Zhang, C., Salboukh, F., & Gunes, O. (2022). Potential use of Bayesian Networks for estimating relationship among rotational dynamics of floating offshore wind turbine tower in extreme environmental conditions. Ocean Engineering, 244, 110230.