Windshield optimization for drag reduction using CFD modelling and genetic algorithm

Wind resistance of the superstructure on container ships has a significant impact on their energy consumption. Adding windshield can effectively reduce the wind resistance of container ships. However, traditional drag reduction design methods based solely on CFD require extensive computational resources and lengthy design cycles, making it difficult to efficiently design high drag-reduction windshield shapes. To address this issue, this work proposes a drag reduction optimization design method that combines a genetic algorithm with computational fluid dynamic analysis. This method enables efficient optimization of windshield shapes, effectively reducing wind resistance and thus lowering energy consumption. The proposed method achieves a 15.97% drag reduction with the installation of the windshield, and a further improvement to 17.02% drag reduction after CFD-GA optimization. This work contributes to energy-saving and emission-reduction in the shipping industry.