Development of Physics-Informed Mathematical Models for Ship Extreme Responses in Ocean Waves
Abstract
Predicting the probability of extreme ship motion events in ocean waves is of increasing importance for the safe operation and survi,vability of ships. Traditionally, ship motions in waves were predicted by using the semi physics-based potential flow solvers whichc,ould partially take into account the nonlinearities involved in wave-induced hydrodynamic loads while some physics such as viscousda,mping must be modeled through empirical formula. Over the last two decades, fully physics-based methods such as CFD (Computational F,luid Dynamics) which entirely resolve nonlinearities demonstrated their outstanding capability in predicting ship responses and hydr,odynamic loads in random waves. However, the large amount of data obtained by such simulations often do not provide any significant, information about the extreme responses, which are located at the tail of the response function. Extremely long computational time, is often required to observe low probable extreme responses, but that is computationally very expensive, especially to evaluate the, ship survivability which requires to run simulations for all essential wave environments in which extreme events are most likely to, occur. One way to enhance the practicality of the nonlinear tools is to develop physics-informed mathematical methods in which thew,ave trail can be designed statistically by the information provided by a limited number of nonlinear simulations. This study aims at, the development of such physics-informed methods to assess extreme ship statistics and ship survivability. The development is forme,d around conditioned wave technique and achieved for both Gaussian and non-Gaussian processes. The method is developed for a single, event as well as a sequence of events. In this proposal, the nonlinear simulation will be conducted by our high-fidelity in-house s,olverCFDFOAM which is built around OpenFOAM and employs both conformal and non-conformal grid techniques to model the ship dynamics., This study supports the Navy s interest in advanced sea platform performance and survivability S&T and naval engineering.The projec,t summary is Approved for Public Release.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Oct 06, 2022
- Source ID
- N000142212778
Entities
People
- Hamid Sadat
Organizations
- Office of Naval Research
- United States Navy
- University of North Texas