Hydrodynamic Analysis And Optimization Design Of Ducted Propeller

The propulsors of underwater vehicle have various shapes, but conventional type propeller and ducted propeller are the most applied. The paper researches propellers from aspects of numerical simulation and optimization design. Based on viscous fluid dynamics theory, numerical simulation resolves governing equations in whole domain and could simulate real fluid due to taking vortex into account. Optimization design technique is able to find the best plan in many interactional restrictions, which could make efficiency improved and pressure coefficient increased.Two-dimension hydrofoil NACA0012 is firstly studied by CFD code and compared to experimental values. And then iSIGHT platform integrates Fluent software and Fortran program for optimizing hydrofoil shape. The optimization results show that the ration of lift and resistance was improved and min-pressure coefficient increased.The paper simulates conventional type propeller DTRC4119 from four kind grid models with different gird numbers, different turbulence parameters and three kind turbulence models, then obtained conclusion: for four kind gird numbers, more grid ,better simulation results;turbulence parameters defined by formula are better than defined by experience;Two-equation models are better suited to simulate in actual level. A ducted propeller of some a underwater vehicle is simulates by CFD code based on the numerical analysis of DTRC4119.Mixed grids,sliding mesh technique and two-equation model are adopted. The result provided us some active data.Optimizations of panel program for ducted propeller are carried out, which include changed pitches,diameter and fixed pitch,diameter and changed pitched totally three groups. The optimizations take ratio of pitch and diameter as design variables, Latin Hypercube DOE,ASA and NSGA-â…¡as techniques, the thrust no less than original value as constraint, efficiency and pressure coefficient in different radius of the ducted propeller are improved as targets. The optimization results shows efficiency is improved and general evaluation of pressure coefficient is better, and also much time and energy are saved. In addition, the effect of parameters to goal is emerged which could help to reduce parameter range for better optimization.