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20172026
most citedPhysics-Informed Holomorphic Neural Networks (PIHNNs): Solving Linear Elasticity Problems

13 citations · 26 across the 16 of their papers we have counts for

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physics.flu-dyn2026

A high-order polynomial-corrected shifted boundary method for simulating fully nonlinear water waves

Jens Visbech, Allan P. Engsig-Karup, Harry B. Bingham +1

We present a novel unfitted computational framework for simulating fully nonlinear potential flow-based water waves. Focusing on wave propagation, we describe the core methodology,…

physics.flu-dyn2026

Estimating Hydrodynamic Coefficients for Floating Offshore Structures from Movement Data Using Physics-Informed Neural Networks

Anders Schou, Jens Visbech, Allan Peter Engsig-Karup

We present a method for estimating the hydrodynamic coefficients in the Cummins equations using time-series data from a moving body, such as a floating offshore structure. The prop…

physics.flu-dyn2025

Subspace Acceleration for Efficient Nonlinear Water Wave Simulation

Rasmus Kleist Hørlyck Sørensen, Margherita Guido, Allan Peter Engsig-Karup +1

Efficient simulation of nonlinear and dispersive free-surface flows governed by the incompressible Navier-Stokes equations remains a central challenge in ocean and coastal engineer…

physics.flu-dyn2020

The DeRisk database: Extreme Design Waves for Offshore Wind Turbines

Fabio Pierella, Ole Lindberg, Henrik Bredmose +3

The estimation of extreme loads from waves is an essential part of the design of an offshore wind turbine. Standard design codes suggest to either use simplified methods based on r…

physics.flu-dyn2018

Spectral/hp element methods: recent developments, applications, and perspectives

Hui Xu, Chris D. Cantwell, Carlos Monteserin +3

The spectral/hp element method combines the geometric flexibility of the classical h-type finite element technique with the desirable numerical properties of spectral methods, empl…