Physics-agnostic and physics-infused machine learning for thin films flows: modelling, and predictions from small data
From MaRDI portal
Publication:6086911
DOI10.1017/jfm.2023.868arXiv2301.12508OpenAlexW4389051781MaRDI QIDQ6086911
Unnamed Author, George Karapetsas, Ioannis G. Kevrekidis, Eleni D. Koronaki, Unnamed Author
Publication date: 11 December 2023
Published in: Journal of Fluid Mechanics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2301.12508
model calibrationfilm thicknessreduced-order modelasymptotic Kuramoto-Sivashinsky equationgappy diffusion mapNavier-Stokes simulation data
Learning and adaptive systems in artificial intelligence (68T05) Thin fluid films (76A20) Basic methods in fluid mechanics (76M99)
Cites Work
- Unnamed Item
- Discovering governing equations from data by sparse identification of nonlinear dynamical systems
- Falling liquid films.
- Longwave instabilities and patterns in fluids
- Hidden physics models: machine learning of nonlinear partial differential equations
- Parsimonious representation of nonlinear dynamical systems through manifold learning: a chemotaxis case study
- A discrete droplet method for modelling thin film flows
- Stabilized neural ordinary differential equations for long-time forecasting of dynamical systems
- Numerical bifurcation analysis of PDEs from lattice Boltzmann model simulations: a parsimonious machine learning approach
- Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
- A paradigm for data-driven predictive modeling using field inversion and machine learning
- Diffusion maps
- Diffusion maps, spectral clustering and reaction coordinates of dynamical systems
- Diffusion Maps, Reduction Coordinates, and Low Dimensional Representation of Stochastic Systems
- Back in the Saddle Again: A Computer Assisted Study of the Kuramoto–Sivashinsky Equation
- Stability analysis of viscoelastic film flows over an inclined substrate with rectangular trenches
- Nonlinear dynamics of temporally excited falling liquid films
- Fully developed travelling wave solutions and bubble formation in fluidized beds
- Data-driven forecasting of high-dimensional chaotic systems with long short-term memory networks
- Data-Driven Discovery of Closure Models
- Turbulence Modeling in the Age of Data
- From snapshots to manifolds – a tale of shear flows
- Reconstruction of three-dimensional turbulent flow structures using surface measurements for free-surface flows based on a convolutional neural network
- Artificial-neural-network-based nonlinear algebraic models for large-eddy simulation of compressible wall-bounded turbulence
- Viscous damping of steady-state resonant sloshing in a clean rectangular tank
- Efficient prediction of turbulent flow quantities using a Bayesian hierarchical multifidelity model
- Learning black- and gray-box chemotactic PDEs/closures from agent based Monte Carlo simulation data
- Deep learning closure models for large-eddy simulation of flows around bluff bodies
- Double diffusion maps and their latent harmonics for scientific computations in latent space
