Power prediction of wind turbine in the wake using hybrid physical process and machine learning models

Physics-based smart model for prediction of viscosity of nanofluids containing nanoparticles using deep learning

(2021) Satyasaran Changdar et al.   Journal of Computational Design and Engineering

A novel three-dimensional wake model based on anisotropic Gaussian distribution for wind turbine wakes

(2021) Ruiyang He et al.   APPLIED ENERGY

Advancement of an analytical double-Gaussian full wind turbine wake model

(2021) Aidan Keane   RENEWABLE ENERGY

Wind turbine power prediction considering wake effects with dual laser beam LiDAR measured yaw misalignment

(2021) Xuyang Li et al.   APPLIED ENERGY

PINNeik: Eikonal solution using physics-informed neural networks

(2021) Umair bin Waheed et al.   COMPUTERS & GEOSCIENCES

Convolutional neural networks for classification of Alzheimer's disease: Overview and reproducible evaluation

(2020) Junhao Wen et al.   MEDICAL IMAGE ANALYSIS

Non-invasive inference of thrombus material properties with physics-informed neural networks

(2020) Minglang Yin et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

MIDPhyNet: Memorized infusion of decomposed physics in neural networks to model dynamic systems

(2020) Zhibo Zhang et al.   NEUROCOMPUTING

Probabilistic physics-guided machine learning for fatigue data analysis

(2020) Jie Chen et al.   EXPERT SYSTEMS WITH APPLICATIONS

Numerical investigations on control strategies of wake deviation for large wind turbines in an offshore wind farm

(2019) Yuanbo Wang et al.   OCEAN ENGINEERING

Deep learning and process understanding for data-driven Earth system science

(2019) Markus Reichstein et al.   NATURE

Scene learning: Deep convolutional networks for wind power prediction by embedding turbines into grid space

(2019) Ruiguo Yu et al.   APPLIED ENERGY

Machine learning algorithm validation with a limited sample size

(2019) Andrius Vabalas et al.   PLoS One

A two-dimensional Jensen model with a Gaussian-shaped velocity deficit

(2019) Mingwei Ge et al.   RENEWABLE ENERGY

Grand challenges in the science of wind energy

(2019) Paul Veers et al.   SCIENCE

Investigation and validation of 3D wake model for horizontal-axis wind turbines based on filed measurements

(2019) Xiaoxia Gao et al.   APPLIED ENERGY

Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey

(2018) Naveed Akhtar et al.   IEEE Access

Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data

(2017) Anuj Karpatne et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Optimization of wind turbine layout position in a wind farm using a newly-developed two-dimensional wake model

(2016) Xiaoxia Gao et al.   APPLIED ENERGY

Wake effect modeling: A review of wind farm layout optimization using Jensen׳s model

(2016) Rabia Shakoor et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Support vector regression methodology for wind turbine reaction torque prediction with power-split hydrostatic continuous variable transmission

(2014) Shahaboddin Shamshirband et al.   ENERGY

A new analytical model for wind-turbine wakes

(2014) Majid Bastankhah et al.   RENEWABLE ENERGY

Atmospheric Turbulence Effects on Wind-Turbine Wakes: An LES Study

(2012) Yu-Ting Wu et al.   Energies

Validation of the dynamic wake meander model for loads and power production in the Egmond aan Zee wind farm

(2012) Torben J. Larsen et al.   WIND ENERGY

Wake effect in wind farm performance: Steady-state and dynamic behavior

(2011) F. González-Longatt et al.   RENEWABLE ENERGY

A Survey on Transfer Learning

(2009) Sinno Jialin Pan et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Online wind turbine fault detection through automated SCADA data analysis

(2009) A. Zaher et al.   WIND ENERGY

Numerical simulations of wake characteristics of a wind turbine in uniform inflow

(2009) Niels Troldborg et al.   WIND ENERGY