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Related papers: Wind-Wave Model with an Optimized Source Function

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Full waveform inversion (FWI) has the potential to provide high-resolution subsurface model estimations. However, due to limitations in observation, e.g., regional noise, limited shots or receivers, and band-limited data, it is hard to…

Geophysics · Physics 2023-11-30 Fu Wang , Xinquan Huang , Tariq Alkhalifah

Travelling wave solutions of reaction-diffusion equations are widely used to model the spatial spread of populations and other phenomena in biology and physics. In this article, we reinterpret the classical variational principle approach…

Analysis of PDEs · Mathematics 2026-03-19 Rebecca M. Crossley , Carles Falco , Ruth E. Baker

The Phase-Field Method (PFM) is employed to simulate two-phase flows with the fully-coupled Cahn-Hilliard-Navier-Stokes (CHNS) equations governing the temporal evolution. The methodology minimizes the total energy functional, accounting for…

Full Waveform Inversion can be made immune to cycle skipping by matching the recorded data arbitrarily well from inaccurate subsurface models. To achieve this goal, the simulated wavefields can be computed in an extended search space as the…

We propose a mathematical formalisation of the ``wave model'' originally developed in historical linguistics but with further applications in human sciences. This model assumes new traits appear in a population and spread to nearby…

Applications · Statistics 2026-04-14 Grégoire Clarté

Wind turbines located in wind farms are operated to maximize only their own power production. Individual operation results in wake losses that reduce farm energy. In this study, we operate a wind turbine array collectively to maximize total…

The resonance mechanism in the initial stage of wind-wave generation proposed by Phillips (J. Fluid Mech., vol. 2, 1957, 417$\unicode{x2013}$445) is a foundation of wind-wave generation theory, but a precise theoretical quantification of…

Fluid Dynamics · Physics 2025-03-12 Tianyi Li , Lian Shen

This Ph.D. thesis deals with the optimization of several renewable energy resources development as well as the improvement of facilities management in oceanic engineering and airports, using computational hybrid methods belonging to AI to…

Machine Learning · Statistics 2018-06-08 L. Cornejo-Bueno

Motivated by the increasing concerns over environmental challenges such as global warming and the exhaustion of fossil-fuel reserves, the renewable energy industry has become the most demanded electrical energy production source worldwide.…

Systems and Control · Electrical Eng. & Systems 2023-08-25 Yashar Mousavi

We put forward a model that describes a decaying and evanescent point source of non-interacting quantum waves in 1D. This point-source assumption allows for a simple description that captures the essential aspects of the dynamics of a wave…

Quantum Physics · Physics 2022-08-31 F. Delgado , J. G. Muga

For a pulsating free surface source in a three-dimensional finite depth fluid domain, the Green function of the source presented by John [F. John, On the motion of floating bodies II. Simple harmonic motions, Communs. Pure Appl. Math. 3…

Fluid Dynamics · Physics 2020-04-29 Zhi-Min Chen

Currents can affect the evolution of waves in nearshore regions through altering their wavenumber and amplitude. Including the effect of ambient currents (e.g., tidal and wind-driven) on waves in phase-resolving wave models is not…

The prediction of the wind wave spectrum of the ocean using numerical models are an important tool for researchers, engineers, and communities living in coastal areas. The governing equation of the wind wave models, the Wave Action Balance…

Fluid Dynamics · Physics 2023-11-07 Mark Loveland , Eirik Valseth , Jessica Meixner , Clint Dawson

Recent studies suggest utilizing generative models instead of traditional auto-regressive algorithms for time series forecasting (TSF) tasks. These non-auto-regressive approaches involving different generative methods, including GAN,…

Machine Learning · Computer Science 2025-03-19 Jiangxuan Long , Zhao Song , Chiwun Yang

A~machine learning framework is developed to estimate ocean-wave conditions. By supervised training of machine learning models on many thousands of iterations of a physics-based wave model, accurate representations of significant wave…

Atmospheric and Oceanic Physics · Physics 2017-09-27 Scott C. James , Yushan Zhang , Fearghal O'Donncha

We apply nested-sampling (NS) Bayesian analysis [AshtonEA22] to a model for the transport of MHD-scale solar wind fluctuations. The dual objectives are to obtain improved constraints on parameters present in the turbulence transport model…

Solar and Stellar Astrophysics · Physics 2024-12-12 Mark Bishop , Sean Ougthon , Tulasi Parashar , Yvette Perrott

We consider some of the methods that can be used to reveal the general features of how wave functions evolve with time in the harmonic oscillator. We first review the periodicity properties over each multiple of a quarter of the classical…

Quantum Physics · Physics 2016-04-20 Mark Andrews

We investigate the reconstruction of the transmission matrix of a time-evolving atmospheric channel with an online recursive optimization routine, using wave-optics simulations. We demonstrate that this estimation technique is able to keep…

Optics · Physics 2025-04-02 Giacomo Sorelli , Douglas McDonald , Szymon Gladysz

Wind power forecasting (WPF), as a significant research topic within renewable energy, plays a crucial role in enhancing the security, stability, and economic operation of power grids. However, due to the high stochasticity of…

Machine Learning · Computer Science 2025-04-16 Mingyi Zhu , Zhaoxin Li , Qiao Lin , Li Ding

Imagine generating a city's electricity demand pattern based on weather, the presence of an electric vehicle, and location, which could be used for capacity planning during a winter freeze. Such real-world time series are often enriched…

Machine Learning · Computer Science 2025-10-31 Sai Shankar Narasimhan , Shubhankar Agarwal , Oguzhan Akcin , Sujay Sanghavi , Sandeep Chinchali