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Power flow (PF) calculations are the backbone of real-time grid operations, across workflows such as contingency analysis (where repeated PF evaluations assess grid security under outages) and topology optimization (which involves PF-based…
This study assesses global offshore wind energy resources, wake-induced losses, array layout optimisation potential and climate change impacts. Global offshore ambient potential is first mapped based on reanalysis data. Wake-induced losses…
Simulating fluid flow around arbitrary shapes is key to solving various engineering problems. However, simulating flow physics across complex geometries remains numerically challenging and computationally resource-intensive, particularly…
Wind energy has become increasingly important for meeting Europe's energy needs. While onshore wind expansion faces public acceptance problems, for offshore wind the European Commission has introduced ambitious goals to increase capacity…
Tool learning has generated widespread interest as a vital means of interaction between Large Language Models (LLMs) and the physical world. Current research predominantly emphasizes LLMs' capacity to utilize tools in well-structured…
The transonic flight regime is often dominated by transonic buffet, a highly unsteady and complex shock-wave/boundary-layer interaction involving major parts of the flow field. The phenomenon is associated with a large-amplitude periodic…
This study investigates the economic and reliability benefits of improved offshore wind forecasting for grid operations along the U.S. East Coast. We introduce and evaluate a state-of-the-art, machine-learning-based offshore wind…
Low-fidelity analytical models of turbine wakes have traditionally been used for wind farm planning, performance evaluation, and demonstrating the utility of advanced control algorithms in increasing the annual energy production. In…
The offshore wind energy is increasingly becoming an attractive source of energy due to having lower environmental impact. Effective operation and maintenance that ensures the maximum availability of the energy generation process using…
Operations and Maintenance (O&M) constitute a major contributor to offshore wind's cost of energy. Due to the harsh and remote environment in which offshore turbines operate, there has been a growing interest in opportunistic maintenance…
This paper describes a multi-region control framework for floating offshore wind farms. Specifically, we propose a novel generator torque controller that regulates rotor speed in Region 2, corresponding to wind speeds between the cut-in and…
Analytical wake models provide a computationally efficient means to predict velocity distributions in wind turbine wakes in the atmospheric boundary layer (ABL). Most existing models are developed for neutral atmospheric conditions and…
With the rising costs of conventional sources of energy, the world is moving towards sustainable energy sources including wind energy. Wind turbines consist of several electrical and mechanical components and experience an enormous amount…
Power curve is widely used in the wind industry to estimate power output for planning and operational purposes. Existing methods for power curve estimation have three main limitations: (i) they mostly rely on wind speed as the sole input,…
In recent years, applying deep learning to solve physics problems has attracted much attention. Data-driven deep learning methods produce fast numerical operators that can learn approximate solutions to the whole system of partial…
This paper implements a recently developed social hierarchy-based distributed economic model predictive control (DEMPC) algorithm in floating offshore wind farms for the purpose of power maximization. The controller achieves this objective…
Wind turbines operating in the atmospheric boundary layer are constantly exposed to time-varying flow conditions. These disturbances often occur on similar time scales to wind-turbine controllers, which may interfere with wind-farm control…
Modern container ships face higher wind loads due to increased windage areas, making accurate predictions of wind loads essential for mooring design. Existing empirical models, largely developed for container ships with smaller windage…
Predicting the elevations of nonlinear wave fields behind floating breakwaters (FBs) is crucial for optimizing coastal engineering structures, enhancing safety, and improving design efficiency. Existing deep learning approaches exhibit…
Data-driven generative models have emerged as promising approaches towards achieving efficient mechanical inverse design. However, due to prohibitively high cost in time and money, there is still lack of open-source and large-scale…