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

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

(2020) Maziar Raissi et al.   SCIENCE

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

(2020) Xiaolei Yang et al.   APPLIED 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

Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data

(2019) Yinhao Zhu et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Adversarial uncertainty quantification in physics-informed neural networks

(2019) Yibo Yang et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Wind Farm Modeling with Interpretable Physics-Informed Machine Learning

(2019) Michael F. Howland et al.   Energies

Adaptive activation functions accelerate convergence in deep and physics-informed neural networks

(2019) Ameya D. Jagtap et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Wake modeling of wind turbines using machine learning

(2019) Zilong Ti et al.   APPLIED ENERGY

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

(2019) Yongqi Liu et al.   APPLIED ENERGY

Physics-informed neural networks for high-speed flows

(2019) Zhiping Mao et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

A composite neural network that learns from multi-fidelity data: Application to function approximation and inverse PDE problems

(2019) Xuhui Meng et al.   JOURNAL OF COMPUTATIONAL PHYSICS

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

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

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

(2018) Jiale Li et al.   APPLIED ENERGY

Bayesian deep convolutional encoder–decoder networks for surrogate modeling and uncertainty quantification

(2018) Yinhao Zhu et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Comparison of wind farm large eddy simulations using actuator disk and actuator line models with wind tunnel experiments

(2018) Richard J.A.M. Stevens et al.   RENEWABLE ENERGY

Turbulence Modeling in the Age of Data

(2018) Karthik Duraisamy et al.   Annual Review of Fluid Mechanics

DGM: A deep learning algorithm for solving partial differential equations

(2018) Justin Sirignano et al.   JOURNAL OF COMPUTATIONAL PHYSICS

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

Data-driven discovery of partial differential equations

(2017) Samuel H. Rudy et al.   Science Advances

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

Reynolds averaged turbulence modelling using deep neural networks with embedded invariance

(2016) Julia Ling et al.   JOURNAL OF FLUID MECHANICS

Discovering governing equations from data by sparse identification of nonlinear dynamical systems

(2016) Steven L. Brunton et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Deep learning

(2015) Yann LeCun et al.   NATURE

Large eddy simulations of the flow past wind turbines: actuator line and disk modeling

(2014) Luis A. Martínez-Tossas et al.   WIND ENERGY

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

Model of the Correlation between Lidar Systems and Wind Turbines for Lidar-Assisted Control

(2013) David Schlipf et al.   JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY

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

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

The upstream flow of a wind turbine: blockage effect

(2011) D. Medici et al.   WIND 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