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2304.11405
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Digital Twins in Wind Energy: Emerging Technologies and Industry-Informed Future Directions
16 April 2023
Florian Stadtmann
Adil Rasheed
T. Kvamsdal
K. Johannessen
Omer San
Konstanze Kölle
J. Tande
I. Barstad
A. Benhamou
Thomas Brathaug
Tore Christiansen
Anouk-Letizia Firle
A. Fjeldly
Lars Frøyd
Alexander Gleim
Alexander Hoiberget
C. Meissner
Guttorm Nygård
Jorgen Olsen
Håvard Paulshus
Tore Rasmussen
E. Rishoff
Francesco Scibilia
John Olav Skogås
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Papers citing
"Digital Twins in Wind Energy: Emerging Technologies and Industry-Informed Future Directions"
6 / 6 papers shown
Title
Toward a digital twin of U.S. Congress
Hayden Helm
Tianyi Chen
Harvey McGuinness
Paige Lee
Brandon Duderstadt
Carey E. Priebe
31
0
0
04 Apr 2025
PINN-DT: Optimizing Energy Consumption in Smart Building Using Hybrid Physics-Informed Neural Networks and Digital Twin Framework with Blockchain Security
Hajar Kazemi Naeini
Roya Shomali
Abolhassan Pishahang
Hamidreza Hasanzadeh
Mahdieh Mohammadi
Saeid Asadi
Abbas Varmaghani
Ahmad Gholizadeh Lonbar
AI4CE
35
2
0
01 Mar 2025
Diagnostic Digital Twin for Anomaly Detection in Floating Offshore Wind Energy
Florian Stadtmann
Adil Rasheed
28
0
0
04 Jun 2024
Physics guided machine learning using simplified theories
Suraj Pawar
Omer San
Burak Aksoylu
Adil Rasheed
T. Kvamsdal
PINN
AI4CE
105
106
0
18 Dec 2020
A Probabilistic Graphical Model Foundation for Enabling Predictive Digital Twins at Scale
Michael G. Kapteyn
Jacob V. R. Pretorius
Karen E. Willcox
34
215
0
10 Dec 2020
Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems
J. Willard
X. Jia
Shaoming Xu
M. Steinbach
Vipin Kumar
AI4CE
91
388
0
10 Mar 2020
1