A Computational Framework for Full Resolution of Extreme Ship-Motion Statistics
Abstract
Wave-induced extreme platform responses (i.e., motions and loading imposing risk on the platform) are rare events for naval platforms at sea. These large responses can be caused by various sea conditions, for instance the impact of extreme waves or normal waves triggering resonance with the platform. Due to complicated physical causal factors, extreme responses may occur unexpectedly and cause catastrophic damage to naval platforms. The statistical quantification and mitigation of extreme responses in stochastic ocean waves are of vital importance to the survivability and functionality of naval platforms. This is especially important for the next-generation autonomous platforms, which will undergo radical changes in the hull form and must complete missions in harsh sea states. With efforts from the past decades, we now have many tools (e.g., CFD, potential-flow models and data-driven models in addition to experiments) with different fidelity levels to evaluate the platform response for a given incoming wave condition. However, the evaluation of extreme response probability (ERP) requires simulations covering a very long stochastic wave input that is computational infeasible considering the rareness of the extreme events and the high cost of the high-fidelity model. The purpose of this one-year project is to continue the development of methodology for evaluation of ERP and initiate the development of reliability-informed design (RID) capability, i.e., the capability of selecting/optimizing values of design variables to minimize ERP. These tasks are building blocks for the long-term goal of revolutionizing the ship design methodology to combat with extreme loading/motion conditions at sea. The PI#s previous work in the past few years has enabled efficient evaluation of ERP in irregular (especially narrow-band) ocean wave field. We will complete three major tasks in this proposal: (1) extensive validation of our new algorithm for evaluation of ERP in broadband wave fields; (2) development of more efficient sampling algorithm to evaluate ERP; (3) develop the first algorithm to solve RID problem in a simple setting. The completion of this project will lay a more solid foundation on the ERP evaluation and extreme-event mitigation for naval platforms. Approved for Public Release.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- May 15, 2023
- Source ID
- N000142312427
Entities
People
- Yulin Pan
Organizations
- Board of Regents of the University of Michigan
- Office of Naval Research
- United States Navy