Reduced order model using convolutional auto-encoder with self-attention

Assessment of unsteady flow predictions using hybrid deep learning based reduced-order models

(2021) Sandeep Reddy Bukka et al.   PHYSICS OF FLUIDS

Convolutional neural network and long short-term memory based reduced order surrogate for minimal turbulent channel flow

(2021) Taichi Nakamura et al.   PHYSICS OF FLUIDS

Reduced-order modeling of advection-dominated systems with recurrent neural networks and convolutional autoencoders

(2021) Romit Maulik et al.   PHYSICS OF FLUIDS

Machine-learning-based reduced-order modeling for unsteady flows around bluff bodies of various shapes

(2020) Kazuto Hasegawa et al.   THEORETICAL AND COMPUTATIONAL FLUID DYNAMICS

Leveraging reduced-order models for state estimation using deep learning

(2020) Nirmal J. Nair et al.   JOURNAL OF FLUID MECHANICS

Deep neural networks for nonlinear model order reduction of unsteady flows

(2020) Hamidreza Eivazi et al.   PHYSICS OF FLUIDS

Convolutional neural network based hierarchical autoencoder for nonlinear mode decomposition of fluid field data

(2020) Kai Fukami et al.   PHYSICS OF FLUIDS

Non-intrusive reduced-order modeling using uncertainty-aware Deep Neural Networks and Proper Orthogonal Decomposition: Application to flood modeling

(2020) Pierre Jacquier et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Unsteady reduced-order model of flow over cylinders based on convolutional and deconvolutional neural network structure

(2020) Jiang-Zhou Peng et al.   PHYSICS OF FLUIDS

A domain decomposition non-intrusive reduced order model for turbulent flows

(2019) D. Xiao et al.   COMPUTERS & FLUIDS

Non-intrusive reduced order modeling of unsteady flows using artificial neural networks with application to a combustion problem

(2019) Qian Wang et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Deep neural network for unsteady aerodynamic and aeroelastic modeling across multiple Mach numbers

(2019) Kai Li et al.   NONLINEAR DYNAMICS

A deep learning enabler for nonintrusive reduced order modeling of fluid flows

(2019) S. Pawar et al.   PHYSICS OF FLUIDS

Memory embedded non-intrusive reduced order modeling of non-ergodic flows

(2019) Shady E. Ahmed et al.   PHYSICS OF FLUIDS

Data-driven reduced order model with temporal convolutional neural network

(2019) Pin Wu et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Model reduction of dynamical systems on nonlinear manifolds using deep convolutional autoencoders

(2019) Kookjin Lee et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Non-intrusive reduced order modeling of nonlinear problems using neural networks

(2018) J.S. Hesthaven et al.   JOURNAL OF COMPUTATIONAL PHYSICS

A reduced-order model for compressible flows with buffeting condition using higher order dynamic mode decomposition with a mode selection criterion

(2018) Jiaqing Kou et al.   PHYSICS OF FLUIDS

Greedy Nonintrusive Reduced Order Model for Fluid Dynamics

(2018) Wang Chen et al.   AIAA JOURNAL

A reduced order model for turbulent flows in the urban environment using machine learning

(2018) D. Xiao et al.   BUILDING AND ENVIRONMENT

Machine learning-based rapid response tools for regional air pollution modelling

(2018) D. Xiao et al.   ATMOSPHERIC ENVIRONMENT

An improved criterion to select dominant modes from dynamic mode decomposition

(2017) Jiaqing Kou et al.   EUROPEAN JOURNAL OF MECHANICS B-FLUIDS

Non-intrusive reduced order modelling of fluid–structure interactions

(2016) D. Xiao et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Non-intrusive reduced-order modelling of the Navier-Stokes equations based on RBF interpolation

(2015) D. Xiao et al.   INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS

Reduced-Order Aeroelastic Models for Dynamics of Maneuvering Flexible Aircraft

(2014) Henrik Hesse et al.   AIAA JOURNAL

Reduced order modelling of an unstructured mesh air pollution model and application in 2D/3D urban street canyons

(2014) F. Fang et al.   ATMOSPHERIC ENVIRONMENT

Optimal mode decomposition for unsteady flows

(2013) A. Wynn et al.   JOURNAL OF FLUID MECHANICS

Dynamic mode decomposition of numerical and experimental data

(2010) PETER J. SCHMID   JOURNAL OF FLUID MECHANICS

Reduced Order Model Based on Principal Component Analysis for Process Simulation and Optimization†

(2009) Yi-dong Lang et al.   ENERGY & FUELS