Xiaodong wind turbine blades

Tags: Xiaodong Wind Turbine

AI-based optical-thermal video data fusion for near real-time blade

We collected a large-scale dataset, i.e., 100 video pairs and over 55,000 images, of optical-thermal videos of blades in operational wind turbines to train and test the method.
2024-DTU Risø Wind Turbine Blade Inpsction Video Dataset Description

Dataset description We captured 29 videos from a wind turbine situated at DTU Risø campus, Roskilde municipality, Denmark. These videos were recorded under diverse circumstances,
Xiaodong Jia (0000-0001-9082-4254)

Currently, he is a postdoc with the Department of Wind and Energy Systems, Technical University of Denmark. His research interests include multi-view learning, multimodal learning, anomaly detection,
Xiaodong Jia

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powerplant81 (xiaodong zhang) · GitHub

A modular Python tool for generating parametric wind turbine blade geometries and fully structured CFD meshes using OpenFOAM''s blockMesh. Includes rotating mesh support.
Unsteady aerodynamic characteristics of a horizontal wind turbine

We found that the unsteady aerodynamic characteristics of the wind turbine blade under yaw considering full 3D rotational effects are still a questionable topic.
Critical review of current wind turbine blades'' design and materials

In this review, the main design features and materials of wind turbine blades are presented and connected to the difficulties and opportunities related to the end-of-life management of
DOISerbia

Wind turbine blades with hybrid fiber composite: Tensile properties and numerical verification. Wind turbine blades are the main component of wind turbines to capture effective wind energy, and require
Xiaodong WANG | Professor | PhD | North China Electric Power

In this paper, a dynamic stall control scheme for vertical-axis wind turbine (VAWT) based on pulsed dielectric-barrier-discharge (DBD) plasma actuation is proposed using computational fluid...
Xiaodong Jia on LinkedIn: I''m thrilled to share that our (Xiaodong Jia

I''m thrilled to share that our (Xiaodong Jia and Xiao CHEN) latest research paper, titled "Unsupervised Wind Turbine Blade Damage Detection with Memory-Aided Denoising Reconstruction,"...