By recasting continuous-forcing immersed boundary problems as composite interior-exterior fields with a smoothed indicator function, the method incorporates neglected terms to achieve second-order convergence in Poisson problems and near-second-order in incompressible Navier-Stokes flows, while also
Bureš, Y
6 Pith papers cite this work. Polarity classification is still indexing.
6
Pith papers citing it
citation-role summary
method 2
citation-polarity summary
years
2026 6roles
method 2polarities
use method 2representative citing papers
A PINN-based periodic CFD solver is shown to reach nearly the same accuracy as traditional transient-to-periodic methods but with substantially lower computational time for 2D heat diffusion and fluid flow cases.
A sharp-interface VOF method for phase-change simulations on unstructured meshes computes evaporation rates from local temperature gradients at geometrically reconstructed interfaces and validates against analytical solutions on Stefan, Sucking, and Scriven problems.
Develops and validates a high-order numerical framework for particle-laden flows in moving domains by coupling DGSEM with Lagrangian tracking, ALE, sliding mesh, and RBF morphing for interface-crossing accuracy.
Systematic benchmark of PINN architectures on 1D stiff PNP system finds BRDR loss weighting competitive with NTK at lower wall-clock time.
Bayesian PINNs with Hamiltonian Monte Carlo sampling deliver the most consistent uncertainty estimates for turbulent flow inverse problems, while repulsive deep ensembles provide a faster but slightly less calibrated alternative.
citing papers explorer
-
A Systematic Benchmark of Physics-Informed Neural Network Architectures for the Stiff Poisson-Nernst-Planck System: Adaptive LossWeighting and Multi-Scale Resolution
Systematic benchmark of PINN architectures on 1D stiff PNP system finds BRDR loss weighting competitive with NTK at lower wall-clock time.