Neural topology optimization of ship structures under propulsion machinery vibrations
Ship structural vibrations contribute to noise, fatigue, and equipment damage, while dynamic-compliance topology optimization can produce pathological designs near resonance. This study extends neural-reparameterized topology optimization using a convolutional Kolmogorov-Arnold network (KATO) to forced-vibration design with active input power (AIP) as the objective. Applications include a 100 Hz engine-supporting deck panel and an 18 Hz thruster foundation frame. Helmholtz PDE filtering and Heaviside projection control feature sizes and manufacturing tolerance. Across both deck families, all eight optimized layouts reduce AIP relative to size-optimized references and, after finite-depth e...
| Authors | Shengyu Yan, Muhammad Muztahidul Hakim Zareer, Jasmin Jelovica |
|---|---|
| Primary category | cs.CE |
| Published | 29 September 2026 |
| Last updated at source | 29 September 2026 |
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