Bow shape modification through multi-objective hydrodynamic optimization: Methodology comparison between CAD-based FreeForm Deformation and Mesh-based Radial Basis Function approach

Author(s):  
Parviz Ghadimi ◽  
Amin Nazemian

Marine industrial engineering face crucial challenges because of environmental footprint of vehicles, global recession, construction, and operation cost. Meanwhile, Shape optimization is the key feature to improve ship efficiency and ascertain better design. Accordingly, the present paper proposes an automated optimization framework for ship hullform modification to reduce total resistance at two cruise and sprint speeds. The case study is a bow shape of a wave-piercing bow trimaran hull. To this end, a multi-objective hydrodynamic problem needs to be solved. A combined optimization strategy using CFD hullform optimization is presented using the software tools STAR-CCM+ and SHERPA algorithm as optimizer. Furthermore, a comparison is made between CAD-based and Mesh-based parametrization techniques. Comparison between geometry regeneration methods is performed to present a practical and efficient parametrization tool. Design variables are control points of FreeForm Deformation (FFD) for CAD-based method and Radial Basis Function (RBF) for Mesh-based method. The optimization results show a 4.77% and 2.47% reduction in the total resistance at cruise and sprint speed, respectively.

2014 ◽  
Vol 577 ◽  
pp. 873-878 ◽  
Author(s):  
Zi Yang ◽  
Ming Rui Chen ◽  
Wei Wu

This paper presents a data fusion method on wireless sensor network based on radial basis function neural networks. In consideration of the hierarchical relationship topology wireless sensor networks, data acquisition, handling and delivery, we proposed a typical classification approach based on radial basis function neural networks. Optimization strategy adopted to process node data for each node indicated different reaction related with energy consumption. Simulation results verify that the method converges fast and effectively.


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