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Hua-Dong Yao

4 papers hereh-index 218 citations9 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author1
  • last author2

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • physics.flu-dyn3
  • physics.comp-ph1
same name
  • Hua-Dong Yao — 2 papers
  • Hua-Dong Yao — 2 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

physics.flu-dyn2026

Quadrature-Aware Complex-Linear Neural Operator for Boundary-to-Field Prediction in Resonant Acoustics

Muhammad Idrees Khan, Hua-Dong Yao

Repeated prediction of acoustic fields from spatially distributed boundary excitation is computationally expensive when each source realization requires a new wave simulation. This…

physics.comp-ph2026

Deterministic Realization of Classical Dissipation on Quantum Computers

Muhammad Idrees Khan, Sauro Succi, Hua-Dong Yao

Lattice Boltzmann (LB) on quantum devices must reconcile unitary gate evolution with the dissipative \emph{collision} step. In the multiple-relaxation-time (MRT) class, we work in…

physics.flu-dyn2026

Physics-Constrained Neural Closure for Lattice Boltzmann Large-Eddy Simulation

Muhammad Idrees Khan, Sauro Succi, Hua-Dong Yao +1

We present a physics-constrained, data-driven subgrid-scale (SGS) stress closure for large-eddy simulation (LES) in the lattice Boltzmann method (LBM). Trained on filtered-downsamp…

physics.flu-dyn2024

Physics informed data-driven near-wall modelling for lattice Boltzmann simulation of high Reynolds number turbulent flows

Xiao Xue, Shuo Wang, Hua-Dong Yao +2

Data-driven approaches offer novel opportunities for improving the performance of turbulent flow simulations, which are critical to wide-ranging applications from wind farms and ae…

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