Recent developments in estimation of the survivability of a U.S. Navy transport
barge in random seas are extended to improve accuracy. The single Degree-of-Freedom (DOF) model of a extreme roll response of a barge used in previous research
is replaced by a 3-DOF roll-heave-sway model to include linear and nonlinear static and
kinematic coupling between roll, sway and heave. The predominant nonlinearity in the
model arises in an improved approximation of the roll righting moment and heave
buoyant restoring force by coupling roll with heave. Kinematic coupling is introduced
by allowing extreme displacements and rotations in the barge response.
System coefficients in the 3-DOF roll-heave-sway model and a simpler 2-DOF
roll-heave model are identified by comparing time domain simulations with measured
physical model tests of barge motions. Predictions of the 3-DOF and 2-DOF models
are compared to measured test data for the case of random waves.
Monte Carlo simulations of the equations of motions are performed to predict the
reliability of the barge in an operational sea state for a specified mission duration. Use
of parallel computer processing is found to make this a viable option for stability
estimations as we move into the next century. The stochastic nature of the ocean waves
are modeled via filtered white noise. Estimations of the joint probability of the barge responses are presented after application of density estimation kernels. Both the 3-DOF roll-heave-sway model and 2-DOF roll-heave model are tested and compared.
Last, examples are provided of some observed nonlinear behavior of the barge motions for variation in damping or ocean wave amplitude. Transient and intermittent chaotic responses are observed for deterministic input waves and quasiperiodic cases are illustrated. / Graduation date: 1996
| Identifer | oai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/34896 |
| Date | 14 March 1996 |
| Creators | Bartel, Warren A. |
| Contributors | Yim, Solomon C. S. |
| Source Sets | Oregon State University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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