Prediction of hydrodynamic forces and moments on submarines using neural networks

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Conference21st International Conference on Offshore Mechanics and Arctic Engineering, June 23-28, 2002, Oslo, Norway
Subjectcaptive-model maneuvering tests; hydrodynamic coefficients; hydrodynamic forces and moments; marine dynamics test facility; MDTF; multi-degree-of-freedom maneuvers; neural networks; prediction methods; rigid body motions; stability derivatives; submarines; towing tank experiments
AbstractThis paper describes a parametric identification tool for predicting the hydrodynamic forces acting on a submarine model using its motion history. The tool uses a neural network to identify the hydrodynamic forces and moments; the network was trained with data obtained from multi-degree-of-freedom captive maneuvering tests. The characteristics of the trained network are demonstrated through reconstruction of the force and moment time histories. This technique has the potential to reduce experimental time and cost by enabling a full hydrodynamic model of the vehicle to be obtained from a relatively limited number of test maneuvers.
Publication date
AffiliationNRC Institute for Ocean Technology; National Research Council Canada
Peer reviewedNo
NRC number5504
NPARC number8895516
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Record identifier36309ca3-0918-4f4d-a329-820d84b3a35d
Record created2009-04-22
Record modified2016-05-09
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