High-Fidelity Hydrostructural Design & Optimization of Multi-Componet Surface Ship Structures
Abstract
The objective of this work is to develop an efficient, high-fidelity, hydrostructural optimization tool for the modeling and optimization of multi-component surface vessels. It is well-known that the hull, propulsor, rudder, and control surfaces of surface vessels interact and influence each other???s performance, particularly when operating in seaway and in off-design conditions. Traditionally, the various component systems are designed separately and sequentially. Moreover,structural design/analysis is typically conducted after hydrodynamic design/analysis. Consequently, time-consuming design iterations between various design groups are often needed, and the final design may not represent the globally optimal solution. In some cases, the safe operating envelop of the final design may be much more limited than initially desired because ofmaneuvering, stability, and survivability issues caused by complex and unintended interactions between the various component systems. Hence, the objective of this work is to develop a highfidelity, hydrostructural optimization tool that can (1) simulate the complex fluid-structure interactions response and stability between the various components of an advanced surface vessel,including considerations for susceptibility to cavitation and ventilation, structural deformations and maximum stress limits, (2) consider large number of geometry and material variables for realistic optimization of multi-component surface vessels, and (3) consider practical constraints due to manufacturing, handling, and operational limits..The proposed research effort will help the US Navy to achieve its vision to develop agile, fuelefficient, high-performance surface vessels by (1) improving the fundamental understanding of the complex fluid-structure interaction response and stability of multi-component surface vessels, and related scaling effects, (2) provide an efficient, high-fidelity hydrostructural solver for the analysisand optimization multi-component surface vessels, and (3) provide valuable experimental data for validation of future predictive models.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jul 10, 2018
- Source ID
- N000141812333
Entities
People
- Yin Lu Young
Organizations
- Board of Regents of the University of Michigan
- Office of Naval Research
- United States Navy