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This research is motivated by the need for effective classification in ice-breaking dynamic simulations, aimed at determining the conditions under which an underwater vehicle will break through the ice. This simulation is extremely…

Methodology · Statistics 2025-06-05 Tian Bai , Dianpeng Wang , Kuangqi Chen , Xu He

We derive a simple algebraic form of the nonlinear wavenumber correction of surface gravity waves in deep water, based on temporal measurements of the water surface and the spatial Zakharov equation. This allows us to formulate an…

Fluid Dynamics · Physics 2022-05-02 Mariano Galvagno , Debbie Eeltink , Raphael Stuhlmeier

We consider the problem of large wave prediction in two-dimensional water waves. Such waves form due to the synergistic effect of dispersive mixing of smaller wave groups and the action of localized nonlinear wave interactions that leads to…

Atmospheric and Oceanic Physics · Physics 2017-04-26 Mohammad Farazmand , Themistoklis P. Sapsis

In the process of the deep learning, we integrate more integrable information of nonlinear wave models, such as the conservation law obtained from the integrable theory, into the neural network structure, and propose a conservation-law…

Pattern Formation and Solitons · Physics 2022-05-04 Yin Fang , Gang-Zhou Wu , Yue-Yue Wang , Chao-Qing Dai

Despite the fact that our physical observations can often be described by derived physical laws, such as the wave equation, in many cases, we observe data that do not match the laws or have not been described physically yet. Therefore…

Geophysics · Physics 2023-09-26 Shijun Cheng , Tariq Alkhalifah

Accurate autoregressive prediction of 3D turbulent flows remains challenging for neural PDE solvers, as small errors in fine-scale structures can accumulate rapidly over rollout. In this paper, we propose FlowRefiner, a flow matching-based…

Fluid Dynamics · Physics 2026-04-28 Yilong Dai , Yiming Sun , Yiheng Chen , Shengyu Chen , Xiaowei Jia , Runlong Yu

Predicting ocean wave behavior is challenging due to the difficulty in choosing suitable numerical models among many with varying capabilities. This review examines the development and performance of numerical wave models in coastal…

Atmospheric and Oceanic Physics · Physics 2025-12-01 Md Meftahul Ferdaus , Nathan Alton Cooper , Austin B. Schmidt , Pujan Pokhrel , Elias Ioup , Mahdi Abdelguerfi , Julian Simeonov

The regularity of solutions to the stochastic nonlinear wave equation plays a critical role in the accuracy and efficiency of numerical algorithms. Rough or discontinuous initial conditions pose significant challenges, often leading to a…

Numerical Analysis · Mathematics 2024-12-20 Jiachuan Cao , Buyang Li , Katharina Schratz

The unsteady flow physics of wind-turbine wakes under dynamic forcing conditions are critical to the modeling and control of wind farms for optimal power density. Unsteady forcing in the streamwise direction may be generated by unsteady…

High-frequency wave propagation in near-inertial wave shear has been considered fundamental in setting the spectral character of the oceanic internal wave continuum and for transporting energy to wave-breaking. We compare idealized ray…

Atmospheric and Oceanic Physics · Physics 2023-10-27 Kurt L Polzin , Yuri V Lvov

Upscaling is central to offshore wind's cost-reduction strategy, with increasingly large rotors and nacelles requiring taller and stronger towers. In Floating Offshore Wind Turbines (FOWTs), this trend amplifies fatigue loads due to coupled…

Computational Engineering, Finance, and Science · Computer Science 2026-01-06 João Alves Ribeiro , Francisco Pimenta , Bruno Alves Ribeiro , Sérgio M. O. Tavares , Faez Ahmed

This paper presents a method developed using techniques from extreme value theory to estimate smooth wind-speed percentiles, allowing us to consider more extreme wind speeds while being less sensitive to the noise that stems from the…

Atmospheric and Oceanic Physics · Physics 2025-05-14 Alexandre Payez , Ad Stoffelen , Cees de Valk , Rianne Giesen

Full Waveform Inversion (FWI) is an important geophysical technique considered in subsurface property prediction. It solves the inverse problem of predicting high-resolution Earth interior models from seismic data. Traditional FWI methods…

Using weak wave turbulence theory analysis, we distinguish three main regimes for 2D stratified fluids in the dimensionless parameter space defined by the Froude number and the Reynolds number: discrete wave turbulence, weak wave…

Fluid Dynamics · Physics 2026-03-30 Vincent Labarre , Michal Shavit

Traditional methods for enhancing tropical cyclone (TC) intensity from climate model outputs or projections have primarily relied on either dynamical or statistical downscaling. With recent advances in deep learning (DL) techniques, a…

Atmospheric and Oceanic Physics · Physics 2025-11-10 Minh-Khanh Luong , Chanh Kieu

Disc winds play a crucial role in many accreting astrophysical systems across all scales. In accreting white dwarfs (AWDs) and active galactic nuclei (AGN), radiation pressure on spectral lines is a promising wind-driving mechanism.…

High Energy Astrophysical Phenomena · Physics 2025-07-08 Amin Mosallanezhad , Christian Knigge , Nicolas Scepi , James H. Matthews , Knox S. Long , Stuart A. Sim , Austen Wallis

The nonlinear dynamics of waves at the sea surface is believed to be ruled by the Weak Turbulence framework. In order to investigate the nonlinear coupling among gravity surface waves, we developed an experiment in the Coriolis facility…

Wave groups can be detected and studied by using the wave envelope. So far, the method used to compute the wave envelope employs the Riesz transform. However, such a technique always produces symmetric envelopes, which is only realistic in…

Atmospheric and Oceanic Physics · Physics 2019-07-16 José Carlos Nieto Borge , Juan Gerardo Alcázar , David Orden , Sara Marazuela Reca , Gerardo Rodríguez

A data-driven and equation-free approach is proposed and discussed to model ships maneuvers in waves, based on the dynamic mode decomposition (DMD). DMD is a dimensionality-reduction/reduced-order modeling method, which provides a linear…

Dynamical Systems · Mathematics 2021-05-28 Matteo Diez , Andea Serani , Emilio F. Campana , Frederick Stern

A data-driven methodology is proposed to model the distribution of multivariate stochastic trajectories from an observed sample. As a first step, each trajectory in the sample is reduced to a vector of features by means of Functional…

Fluid Dynamics · Physics 2026-05-15 Romain Hascoët
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