Add to ORKGThis research is supported by the projects GA21-31457S ”Fast flow-field prediction using deep neural networks for solving fluid-structure interaction problems”
This work proposes a novel multi-output neural network for the prediction of the lift coefficient of...
Flow-induced vibration (FIV) is a phenomenon in which the flow passing through a structure exerts pe...
The modeling of complex physical and biological phenomena has long been the domain of computational ...
This research is supported by the projects GA21-31457S ”Fast flow-field prediction using deep neura...
© 2018 Cambridge University Press. Vortex-induced vibrations of bluff bodies occur when the vortex s...
DoctorThe objective of the present study is to investigate capabilities and mechanisms of data-drive...
Computational Fluid Dynamics (CFD) simulations are a numerical tool to model and analyze the behavio...
A study to analyze the efficacy of two novel, state-of-the-art deep learning methods used in flow-fi...
In this study, we propose an encoder–decoder convolutional neural network-based approach for estimat...
Deep learning has been employed to identify flow characteristics from Computational Fluid Dynamics (...
In the field of fluid numerical analysis, there has been a long-standing problem: lacking of a rigor...
Recent advancements have established machine learning’s utility in predicting nonlinear fluid dynami...
New generation combat aircraft are expected to operate over extended flight envelopes, including fli...
Physics-informed machine learning is a novel approach to solving flow problems with physics-informed...
project "Centre of research and experimental development of reliable energy production" TE01020068 o...
This work proposes a novel multi-output neural network for the prediction of the lift coefficient of...
Flow-induced vibration (FIV) is a phenomenon in which the flow passing through a structure exerts pe...
The modeling of complex physical and biological phenomena has long been the domain of computational ...
This research is supported by the projects GA21-31457S ”Fast flow-field prediction using deep neura...
© 2018 Cambridge University Press. Vortex-induced vibrations of bluff bodies occur when the vortex s...
DoctorThe objective of the present study is to investigate capabilities and mechanisms of data-drive...
Computational Fluid Dynamics (CFD) simulations are a numerical tool to model and analyze the behavio...
A study to analyze the efficacy of two novel, state-of-the-art deep learning methods used in flow-fi...
In this study, we propose an encoder–decoder convolutional neural network-based approach for estimat...
Deep learning has been employed to identify flow characteristics from Computational Fluid Dynamics (...
In the field of fluid numerical analysis, there has been a long-standing problem: lacking of a rigor...
Recent advancements have established machine learning’s utility in predicting nonlinear fluid dynami...
New generation combat aircraft are expected to operate over extended flight envelopes, including fli...
Physics-informed machine learning is a novel approach to solving flow problems with physics-informed...
project "Centre of research and experimental development of reliable energy production" TE01020068 o...
This work proposes a novel multi-output neural network for the prediction of the lift coefficient of...
Flow-induced vibration (FIV) is a phenomenon in which the flow passing through a structure exerts pe...
The modeling of complex physical and biological phenomena has long been the domain of computational ...