A Computational Framework for Full Resolution of Extreme Ship-Motion Statistics
Abstract
Wave-induced extreme motions are rare events for ships at sea. Large ship motions can be caused by the impact of extreme waves, or s,ome normal waves with certain frequencies that excite the resonances of the ship. Due to the complicated physical causal factors, ex,treme motions may occur unexpectedly and cause catastrophic damage to ships. The physical understanding and statistical quantificati,on of extreme ship motions in a sea state are of vital importance to the survivability and functionality of ships. This is especiall,y important for the next-generation naval vessels, which must complete missions in harsh sea states.The purpose of this project is t,o build a framework to enable efficient and accurate resolution of extreme ship motion statistics. This framework features a few com,ponents: (1) nonlinear wave simulation to resolve the statistics of a wave field; (2) parameterization of wave field to produce a sa,mple space with given probability distributions; (3) sequential sampling coupled with CFD to resolve the extreme motion statistics w,ith minimized computational cost. In the past one and half years, we have implemented this framework (following existing works on wa,ve parameterizationand sequential sampling) and developed additional methods to handle problems such as uncertainty of initial condi,tions in each CFD sample.We propose to further improve and enrich this framework in the next funding period. Inparticular, we propos,e to (1) develop multi-fidelity sampling methods to further reduce the computational cost in sequential sampling; (2) develop parame,terization methods for short-crested wave fields; (3) understand the effect of wave nonlinearity on extreme motion statistics. Final,ly, we plan to apply the well-developed framework to study problems of extreme slamming pressure and multi-DOF ship motions in a thr,ee-dimensional wave field.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jul 08, 2022
- Source ID
- N000142212225
Entities
People
- Yulin Pan
Organizations
- Board of Regents of the University of Michigan
- Office of Naval Research
- United States Navy