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Optimization of Marine Components Using CFD
Posted Fri May 24, 2002 @03:00PM
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Application The French engineering company Sirehna has been developing and promoting optimal design approaches, especially involving CFD, for a long time. Their current policy is to combine the advantages of the most efficient flow pre- and post-processoring tools (Gridgen and Fieldview) together with Frontier, an advanced tool for design space investigation and optimization, to form an automatic system for design optimization.

The FLUENT flow solver is used in the two following applications, however, the optimization process is independent from the choice of flow solver. Other applications have been developed using ICARE, a dedicated solver for free surface flows in viscous fluid around a ship hull.


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1st Study: SHIP STABILIZING FIN

For their first study, Sirehna chose a very simple case since their interest was not in the parametric modelling or in the solver calculation but in the validation of the optimization chain.

The case of study was the optimization of the profile of a simple fin. This kind of fin is used to stabilize ships by inducing a moment opposite to roll, as shown below.

Stabilizing fin
Stabilizing fins counteract the rolling motion of ship hulls.

The objectives of this optimization process were to:

  • maximize lift
  • minimize drag
  • minimize risk of cavitation

For each design, the process consisted of three parts taking place on different computers and different systems. All computers and systems were running in batch mode and controlled by Frontier:

Frontier sends the four shape control parameters to Gridgen, which then creates a mesh around the new profile. Gridgen Version 14 runs in batch mode using its new Glyph scripting language to control operation. The mesh is created by extrusion from the profile. Gridgen, running on a PC, then exports the mesh in the CFD solver format.

The second step was the flow calculation made on a UNIX station. The solution was then exported in Fieldview format.

Finally, Fieldview was used to integrate to find forces on the profile and to calculate the minimum pressure value.

The Glyph scripting language in Gridgen and the FVX scripting language in FIELDVIEW were essential in forming the optimization loop as shown below.

CFD Optimization Loop
The CFD optimization loop.

A typical optimization process starts with an initial population of 70 designs. The results obtained for these designs are used by Frontier to set up response surfaces using neural networks, which are used by a multi-objective genetic algorithm to mix real calculations and virtual calculations in order to accelerate the process. Finally, multi-criteria decision-making tools provided by Frontier are used to detect the Pareto frontier and to sort the solutions.

2nd Study: OPTIMIZATION OF A SHIP HULL FORM

Once Sirehna validated the optimization chain during the first study, they wanted to test it on a 3D calculation; the integration of an appendage on a ship hull.

The objectives of this optimization process were to:

  • minimize drag
  • minimize variation from a given design

For this case, the parameterization was not done in Gridgen, but in the CAD software. For each design, an IGES file from Pro/ENGINEER was input as geometry for Gridgen. A Glyph script, obtained by journaling, was used to automatically create a 3D structured multi-block mesh, comprising approximately 300,000 cells, around the hull of the vessel. The structured grids benefited from the grid quality improvement provided by the elliptic solver. More than 70 meshes of different designs were generated automatically thanks to this script.

Initial shape
The initial appendage shape.

In order to reduce the computation time in the flow solver, the calculation for each design was started with a flow field already converged on another design. Moreover, the flow field was restricted to a region around the appendage. Boundary conditions were deduced from a solution obtained on a larger flow field. Thanks to these two tricks, the computation time was decreased by 60%.

Response surfaces were used in conjunction with multi-objective genetic algorithm in order to get quick convergence. In less than 110 hours of computing, an optimized design was reached.

Alternate shapes
Some alternate appendage shapes.

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