:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Pawar, Suraj, San, Omer, Nair, Aditya, Rasheed, Adil, Kvamsdal, Trond
Format:	Preprint
Published:	2021
Subjects:	Computational Physics Fluid Dynamics
Online Access:	https://arxiv.org/abs/2104.04574
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Prospects of federated machine learning in fluid dynamics
by: San, Omer, et al.
Published: (2022)

Enhancing wind field resolution in complex terrain through a knowledge-driven machine learning approach
by: Wold, Jacob Wulff, et al.
Published: (2023)

Classifying acoustic cavitation with machine learning trained on multiple physical models
by: Gatica, Trinidad, et al.
Published: (2024)

Flow control by a hybrid use of machine learning and control theory
by: Ishize, Takeru, et al.
Published: (2023)

Compact representation of transonic airfoil buffet flows with observable-augmented machine learning
by: Fukami, Kai, et al.
Published: (2025)

Drag modelling for flows through assemblies of spherical particles with machine learning: A comparison of approaches
by: Reuter, Julia, et al.
Published: (2025)

A GENERIC-guided active learning SPH method for viscoelastic fluids using Gaussian process regression
by: Dong, Xuekai, et al.
Published: (2025)

twoPhaseInterTrackFoam: an OpenFOAM module for Arbitrary Lagrangian/Eulerian Interface Tracking with Surfactants and Subgrid-Scale Modeling
by: Schwarzmeier, Moritz, et al.
Published: (2024)

Superresolving Non-linear PDE Dynamics with Reduced-Order Autodifferentiable Ensemble Kalman Filtering For Turbulence Modeling and Flow Regulation
by: Dhingra, Mrigank, et al.
Published: (2025)

Physics-informed neural networks for solving moving interface flow problems using the level set approach
by: Mullins, Mathieu, et al.
Published: (2025)

Hierarchy of extreme-event predictability in turbulence revealed by machine learning
by: Yang, Yuxuan, et al.
Published: (2026)

Nonequilibrium Continuous Transition in a Fast Rotating Turbulence
by: Lohani, Chandra Shekhar, et al.
Published: (2025)

Single-snapshot machine learning for super-resolution of turbulence
by: Fukami, Kai, et al.
Published: (2024)

Neural-ISAM: A hybrid in-situ machine learning approach for complex manifold-based combustion models in LES of turbulent flames
by: Fush, S. Trevor, et al.
Published: (2026)

A three-dimensional numerical scheme for modeling three-phase contact line pinning using Smoothed Particle Hydrodynamics
by: Nayak, Subrat Kumar, et al.
Published: (2025)

Optical to infrared mapping of vapor-to-liquid phase change dynamics using generative machine learning
by: Khodakarami, Siavash, et al.
Published: (2025)

An asynchronous discontinuous Galerkin method for combustion simulations
by: Arumugam, Aswin Kumar, et al.
Published: (2025)

A numerical study on the coefficient of restitution of wet collisions
by: Singh, Abhishek Kumar, et al.
Published: (2026)

Machine learning for climate physics and simulations
by: Lai, Ching-Yao, et al.
Published: (2024)

Information-theoretic machine learning for time-varying mode decomposition of separated aerodynamic flows
by: Fukami, Kai, et al.
Published: (2025)

A numerical study on the effect of rolling friction on clogging of pores in particle-laden flows
by: Nayak, Sagar G., et al.
Published: (2026)

Fluid-structure coupled simulation framework for lightweight explosion containment structures under large deformations
by: Narkhede, Aditya, et al.
Published: (2024)

Encoding strategies for quantum enhanced fluid simulations: opportunities and challenges
by: Rathore, Omer, et al.
Published: (2026)

Scalable physics-guided data-driven component model reduction for steady Navier-Stokes flow
by: Chung, Seung Whan, et al.
Published: (2024)

M2C: An Open-Source Software for Multiphysics Simulation of Compressible Multi-Material Flows and Fluid-Structure Interactions
by: Zhao, Xuning, et al.
Published: (2025)

Dominant balance-based adaptive mesh refinement for incompressible fluid flows
by: Kumar, Gaurav, et al.
Published: (2024)

Cost-effective multi-fidelity strategy for the optimization of high-Reynolds number turbine flows guided by LES
by: Matar, Camille, et al.
Published: (2025)

A co-kurtosis based dimensionality reduction method for combustion datasets
by: Jonnalagadda, Anirudh, et al.
Published: (2022)

Accuracy and scalability of asynchronous compressible flow solver for transitional flows
by: Arumugam, Aswin Kumar, et al.
Published: (2025)

Convolutional causal learning for aerodynamic flows
by: Koshikawa, Ryo, et al.
Published: (2026)

SIMR-NO: A Spectrally-Informed Multi-Resolution Neural Operator for Turbulent Flow Super-Resolution
by: Abid, Muhammad, et al.
Published: (2026)

Accelerating Bayesian inverse design in computational fluid dynamics using neural operators
by: Tiwari, Bipin, et al.
Published: (2026)

The Closure Challenge: a benchmark task for machine learning in turbulence modelling
by: McConkey, Ryley, et al.
Published: (2026)

Uncertainty-Aware Spatiotemporal Super-Resolution Data Assimilation with Diffusion Models
by: Ayapilla, Aditya Sai Pranith, et al.
Published: (2026)

Quantum machine learning for efficient reduced order modelling of turbulent flows
by: Li, Han, et al.
Published: (2025)

Modeling the free-surface magnetohydrodynamics of thick liquid metal walls for fusion
by: Giovacchini, Valentina, et al.
Published: (2024)

Data-assisted, physics-informed propagators for recurrent flows
by: Lichtenegger, Thomas
Published: (2023)

Discontinuity-aware KAN-based physics-informed neural networks
by: Lei, Guoqiang, et al.
Published: (2025)

SmartFlow: A CFD-solver-agnostic deep reinforcement learning framework for computational fluid dynamics on HPC platforms
by: Xiao, Maochao, et al.
Published: (2025)

Turbulence model augmented physics informed neural networks for mean flow reconstruction
by: Patel, Yusuf, et al.
Published: (2023)