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physics.flu-dyn2026
Conditional Neural Field based Reduced Order Model for Dynamic Ditching Load Prediction
Henning Schwarz, Pyei Phyo Lin, Jens-Peter M. Zemke +1
Grid-based neural networks such as convolutional autoencoders are widely used in dimension reduction-based surrogate models for computational fluid dynamics. In recent years, the u…
physics.flu-dyn2025
Data-driven pressure field prediction for ships in regular sea states
Malte Loft, Henning Schwarz, Thomas Rung
Merchant shipping is responsible for more than 90% of the global trade and has a significant environmental impact, accounting for over 2% of global greenhouse gas emissions. Theref…
physics.flu-dyn2024
Monolithic 3D numerical modeling of granular cargo movement on bulk carriers in waves
Wibke Düsterhöft-Wriggers, Thomas Rung
A novel monolithic approach for simulating vessels in waves with granular cargo is presented using a Finite Volume framework. This model integrates a three-phase Volume of Fluid me…