Cover Image

DBSCAN in domains with periodic boundary conditions

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	de Wit, Xander M., Gabbana, Alessandro
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Computational Physics Fluid Dynamics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Data-driven Mori-Zwanzig modeling of Lagrangian particle dynamics in turbulent flows
by: de Wit, Xander, et al.
Published: (2025)

Enhancing lattice kinetic schemes for fluid dynamics with Lattice-Equivariant Neural Networks
by: Ortali, Giulio, et al.
Published: (2024)

Flow-driven hysteresis in the transition boiling regime
by: Gabbana, Alessandro, et al.
Published: (2025)

Localization-delocalization transition for light particles in turbulence
by: Wang, Ziqi, et al.
Published: (2024)

Transition to inverse cascade in turbulent rotating convection in absence of the large-scale vortex
by: de Wit, Xander M.
Published: (2025)

Efficient point-based simulation of four-way coupled particles in turbulence at high number density
by: de Wit, Xander M., et al.
Published: (2024)

Physics-informed neural networks for hidden boundary detection and flow field reconstruction
by: Zhu, Yongzheng, et al.
Published: (2025)

Virtual domain extension for imposing boundary conditions in flow simulation using pre-trained local neural operator
by: Ye, Ximeng, et al.
Published: (2025)

Solving nonlinear subsonic compressible flow in infinite domain via multi-stage neural networks
by: Qian, Xuehui, et al.
Published: (2026)

Perfectly Matched Layers and Characteristic Boundaries in Lattice Boltzmann: Accuracy vs Cost
by: Klass, Friedemann, et al.
Published: (2025)

Kinetic data-driven approach to turbulence subgrid modeling
by: Ortali, Giulio, et al.
Published: (2024)

Vielbein Lattice Boltzmann approach for fluid flows on spherical surfaces
by: Ambrus, Victor E., et al.
Published: (2025)

Stochastic resonance of rotating particles in turbulence
by: Wang, Ziqi, et al.
Published: (2025)

Bayesian Reasoning for Physics Informed Neural Networks
by: Graczyk, Krzysztof M., et al.
Published: (2023)

Machine Learning Visualization Tool for Exploring Parameterized Hydrodynamics
by: Jekel, C. F., et al.
Published: (2024)

Reinforcement learning for anisotropic p-adaptation and error estimation in high-order solvers
by: Huergo, David, et al.
Published: (2024)

Inertial rotation of a small oblate spheroid in a simple shear flow
by: Wang, Ziqi, et al.
Published: (2025)

Neural equilibria for long-term prediction of nonlinear conservation laws
by: Benitez, J. Antonio Lara, et al.
Published: (2025)

Data-Driven Reduced-Complexity Modeling of Fluid Flows: A Community Challenge
by: Schmidt, Oliver T., et al.
Published: (2026)

A Numerical Proof of Shell Model Turbulence Closure
by: Ortali, Giulio, et al.
Published: (2022)

Color-gradient lattice Boltzmann modeling of wetting boundary condition on curved solid boundaries
by: Bhattacharya, Malyadeep, et al.
Published: (2026)

Intelligent Optimization of Multi-Parameter Micromixers Using a Scientific Machine Learning Framework
by: Hassanzadeh, Meraj, et al.
Published: (2025)

Differentiable Physics-Neural Models enable Learning of Non-Markovian Closures for Accelerated Coarse-Grained Physics Simulations
by: Xue, Tingkai, et al.
Published: (2025)

Multi-resolution Physics-Aware Recurrent Convolutional Neural Network for Complex Flows
by: Cheng, Xinlun, et al.
Published: (2025)

From Models To Experiments: Shallow Recurrent Decoder Networks on the DYNASTY Experimental Facility
by: Riva, Stefano, et al.
Published: (2025)

Equivariant U-Shaped Neural Operators for the Cahn-Hilliard Phase-Field Model
by: Xue, Xiao, et al.
Published: (2025)

Optimal Lattice Boltzmann Closures through Multi-Agent Reinforcement Learning
by: Fischer, Paul, et al.
Published: (2025)

Predicting The Evolution of Interfaces with Fourier Neural Operators
by: Guida, Paolo, et al.
Published: (2025)

WellPINN: Accurate Well Representation for Transient Fluid Pressure Diffusion in Subsurface Reservoirs with Physics-Informed Neural Networks
by: Walter, Linus, et al.
Published: (2025)

Learning second-order TVD flux limiters using differentiable solvers
by: Huang, Chenyang, et al.
Published: (2025)

Learning Effective Dynamics across Spatio-Temporal Scales of Complex Flows
by: Gao, Han, et al.
Published: (2025)

Reparameterizing 4DVAR with neural fields
by: Oh, Jaemin
Published: (2025)

Graph-Based Learning of Free Surface Dynamics in Generalized Newtonian Fluids using Smoothed Particle Hydrodynamics
by: Kim, Hyo-Jin, et al.
Published: (2025)

From large-eddy simulations to deep learning: A U-net model for fast urban canopy flow predictions
by: Vargiemezis, Themistoklis, et al.
Published: (2025)

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

Jacobian-Scaled K-means Clustering for Physics-Informed Segmentation of Reacting Flows
by: Barwey, Shivam, et al.
Published: (2023)

Physics-enhanced Neural Operator for Simulating Turbulent Transport
by: Chen, Shengyu, et al.
Published: (2024)

AeTHERON: Autoregressive Topology-aware Heterogeneous Graph Operator Network for Fluid-Structure Interaction
by: Kumar, Sushrut
Published: (2026)

Operator Learning for Surrogate Modeling of Wave-Induced Forces from Sea Surface Waves
by: Cai, Shukai, et al.
Published: (2026)

Generative Learning for Forecasting the Dynamics of Complex Systems
by: Gao, Han, et al.
Published: (2024)