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Title: Systematic Characterization of the Naval Environment (SCONE) - Deck Motion Characterization

Author(s): Alan Schwartz

Abstract: Recovery of aircraft to ships at sea is a difficult problem unique to Naval operations. A primary challenge is potentially large, difficult to predict deck motions. Researchers addressing various aspects of the aircraft recovery problem require realistic deck motion in order to support development of new technologies such as aircraft guidance and control laws, sensors for relative navigation, and real-time deck motion prediction. The Systematic Characterization of the Naval Environment (SCONE) provides these descriptive data in publically-releasable form for use by researchers in academia, industry, and Government labs. The goal of SCONE is to establish and distribute a concise library of representative deck motion cases and a fast-executing recursive neural network model to model ship motion for specific classes of Naval vessels that cover the range of conditions that are particularly challenging for shipboard recovery of aircraft. 

Presentation will cover:

  • Description of generic ship hullforms used to develop deck motion cases for surface combatants and aircraft carriers
  • Description of seakeeping simulation (LAMP) and range of operating conditions considered
  • Discussion of methodology used to evaluate simulation results and down-select cases for distribution set of time history motions
  • Description of public-release distribution time history data sets for surface combatants and carriers
  • Discussion of Recursive Neural Network (RNN) development for modeling of simulation time histories
  • Discussion of RNN model simulations
  • Summary of status and contact information for SCONE products