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Hamidreza Eivazi
Hamidreza Eivazi
Verified email at tu-clausthal.de
Title
Cited by
Cited by
Year
Physics-informed neural networks for solving Reynolds-averaged Navier–Stokes equations
H Eivazi, M Tahani, P Schlatter, R Vinuesa
Physics of Fluids 34 (7), 2022
2832022
Deep neural networks for nonlinear model order reduction of unsteady flows
H Eivazi, H Veisi, MH Naderi, V Esfahanian
Physics of Fluids 32 (10), 2020
1862020
Towards extraction of orthogonal and parsimonious non-linear modes from turbulent flows
H Eivazi, S Le Clainche, S Hoyas, R Vinuesa
Expert Systems with Applications 202, 117038, 2022
1162022
Recurrent neural networks and Koopman-based frameworks for temporal predictions in a low-order model of turbulence
H Eivazi, L Guastoni, P Schlatter, H Azizpour, R Vinuesa
International Journal of Heat and Fluid Flow 90, 108816, 2021
842021
Physics-informed deep-learning applications to experimental fluid mechanics
H Eivazi, Y Wang, R Vinuesa
Measurement science and technology 35 (7), 075303, 2024
542024
Enhancement of PIV measurements via physics-informed neural networks
G Hasanuzzaman, H Eivazi, S Merbold, C Egbers, R Vinuesa
Measurement Science and Technology 34 (4), 044002, 2023
312023
The sustainable development goals and aerospace engineering: a critical note through artificial intelligence
A Sánchez-Roncero, Ò Garibo-i-Orts, JA Conejero, H Eivazi, F Mallor, ...
Results in Engineering 17, 100940, 2023
282023
New method for dynamic mode decomposition of flows over moving structures based on machine learning (hybrid dynamic mode decomposition)
MH Naderi, H Eivazi, V Esfahanian
Physics of Fluids 31 (12), 2019
282019
Sentiment analysis on Twitter data towards climate action
E Rosenberg, C Tarazona, F Mallor, H Eivazi, D Pastor-Escuredo, ...
Results in Engineering 19, 101287, 2023
262023
The potential of artificial intelligence for achieving healthy and sustainable societies
B Sirmaçek, S Gupta, F Mallor, H Azizpour, Y Ban, H Eivazi, H Fang, ...
The ethics of artificial intelligence for the sustainable development goals …, 2023
152023
Predicting the temporal dynamics of turbulent channels through deep learning
G Borrelli, L Guastoni, H Eivazi, P Schlatter, R Vinuesa
International Journal of Heat and Fluid Flow 96, 109010, 2022
152022
Analysis and prediction of gas turbine performance with evaporative cooling processes by developing a stage stacking algorithm
M Salehi, H Eivazi, M Tahani, M Masdari
Journal of Cleaner Production 277, 122666, 2020
152020
FE² Computations With Deep Neural Networks: Algorithmic Structure, Data Generation, and Implementation
H Eivazi, JA Tröger, S Wittek, S Hartmann, A Rausch
Mathematical and Computational Applications 28 (4), 2023
92023
Assessment of turbulence models for transonic oscillating airfoil
M Tahani, M Masdari, H Eivazi, M Tatar
International Journal of Numerical Methods for Heat & Fluid Flow 27 (11 …, 2017
92017
Thunderstorm prediction during pre-tactical air-traffic-flow management using convolutional neural networks
A Jardines, H Eivazi, E Zea, J García-Heras, J Simarro, E Otero, M Soler, ...
Expert systems with applications 241, 122466, 2024
82024
An experimental study on boundary layer transition detection over a pitching supercritical airfoil using hot-film sensors
A Tabrizian, M Tatar, M Masdari, H Eivazi, M Seddighi
International Journal of Heat and Fluid Flow 86, 108743, 2020
82020
Physics-informed transfer learning strategy to accelerate unsteady fluid flow simulations
J Jeon, J Lee, H Eivazi, R Vinuesa, SJ Kim
arXiv preprint arXiv:2206.06817, 2022
52022
Nonlinear model reduction for operator learning
H Eivazi, S Wittek, A Rausch
The Second Tiny Papers Track at ICLR 2024, 2024
32024
Efficient integration of deep neural networks in sequential multiscale simulations
JA Tröger, H Eivazi, S Hartmann, S Wittek, A Rausch
PAMM 23 (4), e202300052, 2023
12023
DiffBatt: A Diffusion Model for Battery Degradation Prediction and Synthesis
H Eivazi, A Hebenbrock, R Ginster, S Blömeke, S Wittek, C Hermann, ...
arXiv preprint arXiv:2410.23893, 2024
2024
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Articles 1–20