Embedding data analytics and CFD into the digital twin concept
type: Item
instance of: scholarly article
title: Embedding data analytics and CFD into the digital twin concept
author: Roberto Molinaro
author: Joel-Steven Singh
author: Sotiris Catsoulis
author: Chidambaram Narayanan
author: Djamel Lakehal
published in: Computers and Fluids
publication date: 2021-05-31T00:00:00Z
Mathematics Subject Classification ID: 76-XX
zbMATH DE Number: 7352792
zbMATH Keywords: fluid flow simulations
zbMATH Keywords: data analytics
zbMATH Keywords: machine learning
zbMATH Keywords: data-driven models
MaRDI profile type: Publication
full work available at URL: j.compfluid.2020.104759
OpenAlex ID: W3091958606
cites work: Machine Learning for Fluid Mechanics
cites work: Model Reduction for Flow Analysis and Control
cites work: Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
cites work: Hidden physics models: machine learning of nonlinear partial differential equations
cites work: Deep learning observables in computational fluid dynamics
cites work: Machine learning control -- taming nonlinear dynamics and turbulence
cites work: On the modelling of multiphase turbulent flows for environmental and hydrodynamic applications
cites work: An Introduction to Statistical Learning
cites work: The elements of statistical learning. Data mining, inference, and prediction
cites work: Multivariate adaptive regression splines
cites work: Q5270493
cites work: A Herschel–Bulkley model for mud flow down a slope
DOI: 10.1016/J.COMPFLUID.2020.104759
description: scientific article; zbMATH DE number 7352792