Real-time simulation of parameter-dependent fluid flows through deep learning-based reduced order models

10 June 2021

Papers citing "Real-time simulation of parameter-dependent fluid flows through deep learning-based reduced order models"

10 / 10 papers shown

Title
PTPI-DL-ROMs: pre-trained physics-informed deep learning-based reduced order models for nonlinear parametrized PDEs Simone Brivio S. Fresca Andrea Manzoni AI4CE 38 6 0 14 May 2024
Multi-fidelity physics constrained neural networks for dynamical systems Hao Zhou Sibo Cheng Rossella Arcucci AI4CE 27 19 0 03 Feb 2024
Multi-fidelity reduced-order surrogate modeling Paolo Conti Mengwu Guo Andrea Manzoni A. Frangi Steven L. Brunton N. Kutz AI4CE 26 23 0 01 Sep 2023
Multi-fidelity prediction of fluid flow and temperature field based on transfer learning using Fourier Neural Operator Yanfang Lyu Xiaoyu Zhao Zhiqiang Gong Xiao Kang W. Yao AI4CE 29 24 0 14 Apr 2023
Deep Learning Methods for Partial Differential Equations and Related Parameter Identification Problems Derick Nganyu Tanyu Jianfeng Ning Tom Freudenberg Nick Heilenkötter A. Rademacher U. Iben Peter Maass AI4CE 23 34 0 06 Dec 2022
Reduced order modeling of parametrized systems through autoencoders and SINDy approach: continuation of periodic solutions Paolo Conti G. Gobat S. Fresca Andrea Manzoni A. Frangi AI4CE 26 49 0 13 Nov 2022
Multi-fidelity surrogate modeling using long short-term memory networks Paolo Conti Mengwu Guo Andrea Manzoni J. Hesthaven AI4CE 33 48 0 05 Aug 2022
Virtual twins of nonlinear vibrating multiphysics microstructures: physics-based versus deep learning-based approaches G. Gobat S. Fresca Andrea Manzoni A. Frangi AI4CE 8 8 0 12 May 2022
CD-ROM: Complemented Deep-Reduced Order Model Emmanuel Menier M. Bucci Mouadh Yagoubi L. Mathelin Marc Schoenauer 22 7 0 22 Feb 2022
Long-time prediction of nonlinear parametrized dynamical systems by deep learning-based reduced order models Federico Fatone S. Fresca Andrea Manzoni AI4TS 22 16 0 25 Jan 2022