Dimensional reduction of hull shape using principal component analysis in CAESES.

Introducing the dimensional reduction function based on the drag optimization of KCS ships!

To optimize the hydrodynamic performance of the hull using the parametric modeling and optimization software CAESES, we first extract design variables related to the deformation of the hull's variable geometry. By increasing the number of design variables in this process, we can obtain a wider variety of deformation shapes, which in turn increases the likelihood of achieving better hull design proposals. However, the number of computational cases required for simulations (such as CFD analysis) increases exponentially (recommended number of cases S = 2^N, where N is the number of design variables), leading to significantly larger computational and time costs. To address this issue, CAESES5 offers a dimensionality reduction feature based on Principal Component Analysis (PCA) methods. *For more detailed information, please refer to the related links. For further details, feel free to download the PDF or contact us.*

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