To mitigate the high cost of integrated ship design, in this paper, we propose an innovative integrated hull design methodology utilizing artificial intelligence-aided design technology. The AIAD methodology leverages a deep neural network model constructed from multiple fidelities datasets to curtail the exponential growth in data requirements resulting from the proliferation of design variables caused by integration. Combining the proposed bump-free deformation method and optimization algorithms with the multi-fidelity deep network, the AIAD-based design approach facilitates the achievement of optimal hull design solutions with remarkable fidelity while minimizing design workload. Utilizing the developed design method, we performed a numerical test on integrated-hull design for container ships.

中文翻译：

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人工智能辅助设计方法辅助的一体化船体设计

为了降低集成船舶设计的高成本，在本文中，我们提出了一种利用人工智能辅助设计技术的创新集成船体设计方法。AIAD 方法利用由多个保真度数据集构建的深度神经网络模型，以抑制因集成而导致的设计变量激增而导致的数据需求的指数增长。基于AIAD的设计方法将所提出的无凹凸变形方法和优化算法与多保真深度网络相结合，有助于实现具有显着保真度的最佳船体设计解决方案，同时最大限度地减少设计工作量。利用所开发的设计方法，我们对集装箱船整体船体设计进行了数值试验。