14 citations · 23 across the 20 of their papers we have counts for
5 papers · 1 filter
Reduced Subgrid-Scale Terms for Turbulence Simulations with the Lattice Boltzmann Method
Rik Hoekstra, Xiao Xue, Peter V. Coveney +1
Turbulent flows span a wide range of scales, making direct numerical simulation (DNS) prohibitively expensive at high Reynolds numbers. Large eddy simulation (LES) offers a pragmat…
Explainable quantum-compressed machine learning for complex fluid flows
Xiao Xue, Maida Wang, Mingyang Gao +2
Machine-learning surrogates of physical systems face a paradox: explainable models facing the challenge of expressivity to capture complex nonlinear flows, whereas expressive deep…
Uni-Flow: a unified autoregressive-diffusion model for complex multiscale flows
Xiao Xue, Tianyue Yang, Mingyang Gao +7
Spatiotemporal flows govern diverse phenomena across physics, biology, and engineering, yet modelling their multiscale dynamics remains a central challenge. Despite major advances…
An Uncertainty Visualization Framework for Large-Scale Cardiovascular Flow Simulations: A Case Study on Aortic Stenosis
Xiao Xue, Tushar M. Athawale, Jon W. S. McCullough +5
We present a generalizable uncertainty quantification (UQ) and visualization framework for lattice Boltzmann method simulations of high Reynolds number vascular flows, demonstrated…
A Multi-Component, Multi-Physics Computational Model for Solving Coupled Cardiac Electromechanics and Vascular Haemodynamics
Sharp C. Y. Lo, Alberto Zingaro, Jon W. S. McCullough +5
The circulatory system, comprising the heart and blood vessels, is vital for nutrient transport, waste removal, and homeostasis. Traditional computational models often treat cardia…