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We analyze the applicability of convolutional neural network (CNN) architectures for downscaling of short-range forecasts of near-surface winds on extended spatial domains. Short-range wind field forecasts (at the 100 m level) from ECMWF…

Atmospheric and Oceanic Physics · Physics 2020-12-22 Kevin Höhlein , Michael Kern , Timothy Hewson , Rüdiger Westermann

As climate change intensifies, the shift to cleaner energy sources becomes increasingly urgent. With wind energy production set to accelerate, reliable wind probabilistic forecasts are essential to ensure its efficient use. However, since…

Machine Learning · Computer Science 2024-10-08 Jean-Sébastien Giroux , Simon-Philippe Breton , Julie Carreau

The research presents an automated method for determining the trajectory of an unmanned aerial vehicle (UAV) for wind turbine inspection. The proposed method enables efficient data collection from multiple wind installations using UAV…

Accurate models of turbulent wind fields have become increasingly important in the atmospheric sciences, e.g., for the determination of spatiotemporal correlations in wind parks, the estimation of individual loads on turbine rotor and…

Fluid Dynamics · Physics 2022-09-02 Jan Friedrich , Daniela Moreno , Michael Sinhuber , Matthias Waechter , Joachim Peinke

The real-time prediction of floating offshore asset behavior under stochastic metocean conditions remains a significant challenge in offshore engineering. While traditional empirical and frequency-domain methods work well in benign…

Machine Learning · Computer Science 2025-06-23 Michael T. M. B. Morris-Thomas , Marius Martens

Ocean wave climate has a significant impact on near-shore and off-shore human activities, and its characterisation can help in the design of ocean structures such as wave energy converters and sea dikes. Therefore, engineers need long time…

Machine Learning · Statistics 2022-05-27 Said Obakrim , Valérie Monbet , Nicolas Raillard , Pierre Ailliot

Nowadays, wind power is considered as one of the most widely used renewable energy applications due to its efficient energy use and low pollution. In order to maintain high integration of wind power into the electricity market, efficient…

Signal Processing · Electrical Eng. & Systems 2020-10-16 Ephrem Admasu Yekun , Alem Haddush Fitwi , S. Karpaga Selvi , Anubhav Kumar

Aerial operation in turbulent environments is a challenging problem due to the chaotic behavior of the flow. This problem is made even more complex when a team of aerial robots is trying to achieve coordinated motion in turbulent wind…

Robotics · Computer Science 2023-06-09 Diego Patiño , Siddharth Mayya , Juan Calderon , Kostas Daniilidis , David Saldaña

State estimation from limited sensor measurements is ubiquitously found as a common challenge in a broad range of fields including mechanics, astronomy, and geophysics. Fluid mechanics is no exception -- state estimation of fluid flows is…

Fluid Dynamics · Physics 2022-06-01 Taichi Nakamura , Koji Fukagata

Motivated by the pursuit of safe, reliable, and weather-tolerant urban air mobility (UAM) solutions, this work proposes a generative modeling approach for characterizing microweather wind velocities. Microweather, or the weather conditions…

Computational Engineering, Finance, and Science · Computer Science 2025-03-05 Tristan A. Shah , Michael C. Stanley , James E. Warner

The recent years have witnessed increased development of small, autonomous fixed-wing Unmanned Aerial Vehicles (UAVs). In order to unlock widespread applicability of these platforms, they need to be capable of operating under a variety of…

Systems and Control · Computer Science 2019-09-26 Luca Furieri , Thomas Stastny , Lorenzo Marconi , Roland Siegwart , Igor Gilitschenski

This paper presents a novel machine-learning framework for reconstructing low-order gust-encounter flow field and lift coefficients from sparse, noisy surface pressure measurements. Our study thoroughly investigates the time-varying…

Machine Learning · Computer Science 2025-06-25 Hanieh Mousavi , Jeff D. Eldredge

We propose a physics-informed machine-learned framework for sensor-based flow estimation for drone trajectories in complex urban terrain. The input is a rich set of flow simulations at many wind conditions. The outputs are velocity and…

Accurate short-term wind speed forecasting is needed for the rapid development and efficient operation of wind energy resources. This is, however, a very challenging problem. Although on the large scale, the wind speed is related to…

Applications · Statistics 2014-12-08 Xinxin Zhu , Kenneth P. Bowman , Marc G. Genton

This work addresses the challenge of short-term precipitation forecasting by applying Convolutional Long Short-Term Memory (ConvLSTM) neural networks to weather radar data from the Royal Netherlands Meteorological Institute (KNMI). The…

Machine Learning · Computer Science 2023-12-05 Petros Demetrakopoulos

Accurate atmospheric wind field information is crucial for various applications, including weather forecasting, aviation safety, and disaster risk reduction. However, obtaining high spatiotemporal resolution wind data remains challenging…

Machine Learning · Computer Science 2025-10-21 Yuchen Ye , Chaoxia Yuan , Mingyu Li , Aoqi Zhou , Hong Liang , Chunqing Shang , Kezuan Wang , Yifeng Zheng , Cong Chen

Ocean hazardous spills and search and rescue incidents are more prevalent as maritime activities increase across all sectors of society. However, emergency response time remains a factor due to a lack of information to accurately forecast…

Atmospheric and Oceanic Physics · Physics 2021-03-24 Javier Gonzalez-Rocha , Alejandro J. Sosa , Regina Hanlon , Arthur A. Allen , Irina Rypina , David G. Schmale , Shane D. Ross

This paper examines the use of a pitot-static tube array (PSA) to estimate horizontal wind velocity in all directions. This method uses the readings from the PSA as inputs. No flight tests have been done, but this method could potentially…

Fluid Dynamics · Physics 2019-01-31 Matthew Simmons , Carlos Montalvo , Sytske Kimball

Wind resistance control is an essential feature for quadcopters to maintain their position to avoid deviation from target position and prevent collisions with obstacles. Conventionally, cascaded PID controller is used for the control of…

Robotics · Computer Science 2023-08-04 Yu Ishihara , Yuichi Hazama , Kousuke Suzuki , Jerry Jun Yokono , Kohtaro Sabe , Kenta Kawamoto

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…

Machine Learning · Computer Science 2020-01-13 Joyjit Chatterjee , Nina Dethlefs
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