Three-dimensional spatiotemporal wind field reconstruction based on physics-informed deep learning

Spatiotemporal wind field prediction based on physics-informed deep learning and LIDAR measurements

(2021) Jincheng Zhang et al.   APPLIED ENERGY

Artificial intelligence velocimetry and microaneurysm-on-a-chip for three-dimensional analysis of blood flow in physiology and disease

(2021) Shengze Cai et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Intelligent wind farm control via deep reinforcement learning and high-fidelity simulations

(2021) Hongyang Dong et al.   APPLIED ENERGY

A novel deep learning ensemble model with data denoising for short-term wind speed forecasting

(2020) Zhiyun Peng et al.   ENERGY CONVERSION AND MANAGEMENT

Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations

(2020) Maziar Raissi et al.   SCIENCE

Feasibility Studies of a Converter-Free Grid-Connected Offshore Hydrostatic Wind Turbine

(2020) Shuyue Lin et al.   IEEE Transactions on Sustainable Energy

High-fidelity simulations and field measurements for characterizing wind fields in a utility-scale wind farm

(2020) Xiaolei Yang et al.   APPLIED ENERGY

Changes in wind turbine power characteristics and annual energy production due to atmospheric stability, turbulence intensity, and wind shear

(2020) Dae-Young Kim et al.   ENERGY

Micro-scale wind resource assessment in complex terrain based on CFD coupled measurement from multiple masts

(2019) Xiao-Yu Tang et al.   APPLIED ENERGY

Load response of a floating wind turbine to turbulent atmospheric flow

(2019) Paula Doubrawa et al.   APPLIED ENERGY

Probabilistic spatiotemporal wind speed forecasting based on a variational Bayesian deep learning model

(2019) Yongqi Liu et al.   APPLIED ENERGY

A Spatiotemporal Estimation Framework for Real-World LIDAR Wind Speed Measurements

(2019) Julian Mercieca et al.   IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY

An Optimized Sensing Arrangement in Wind Field Reconstruction Using CFD and POD

(2019) Shanxun Sun et al.   IEEE Transactions on Sustainable Energy

Use of spatio-temporal calibrated wind shear model to improve accuracy of wind resource assessment

(2018) Jiale Li et al.   APPLIED ENERGY

Static and Dynamic Yaw Misalignments of Wind Turbines and Machine Learning Based Correction Methods Using LiDAR Data

(2018) Daeyoung Choi et al.   IEEE Transactions on Sustainable Energy

Wind Field Reconstruction Using Inverse Process with Optimal Sensor Placement

(2018)   IEEE Transactions on Sustainable Energy

Deep learning of vortex-induced vibrations

(2018) Maziar Raissi et al.   JOURNAL OF FLUID MECHANICS

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

(2018) M. Raissi et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Power Generation Control of a Monopile Hydrostatic Wind Turbine Using an H∞ Loop-Shaping Torque Controller and an LPV Pitch Controller

(2017) Xin Tong et al.   IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY

Observations of offshore wind characteristics by Doppler-LiDAR for wind energy applications

(2016) Z.R. Shu et al.   APPLIED ENERGY

Coupled on-site measurement/CFD based approach for high-resolution wind resource assessment over complex terrains

(2016) B.W. Yan et al.   ENERGY CONVERSION AND MANAGEMENT

Simulation comparison of wake mitigation control strategies for a two-turbine case

(2014) Paul Fleming et al.   WIND ENERGY

Real-time wind field reconstruction from LiDAR measurements using a dynamic wind model and state estimation

(2014) P. Towers et al.   WIND ENERGY

A numerical study of the effects of atmospheric and wake turbulence on wind turbine dynamics

(2012) Matthew J. Churchfield et al.   JOURNAL OF TURBULENCE

A Wind Power Forecasting System to Optimize Grid Integration

(2012) William P. Mahoney et al.   IEEE Transactions on Sustainable Energy

Review of state of the art in smart rotor control research for wind turbines

(2009) T.K. Barlas et al.   PROGRESS IN AEROSPACE SCIENCES