136 citations · 430 across the 12 of their papers we have counts for
12 papers
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…
Flexible composition and execution of high performance, high fidelity multiscale biomedical simulations
Derek Groen, Joris Borgdorff, Carles Bona-Casas +9
Multiscale simulations are essential in the biomedical domain to accurately model human physiology. We present a modular approach for designing, constructing and executing multisca…
Confined Cubic Blue Phases under Shear
O. Henrich, K. Stratford, D. Marenduzzo +2
We study the behaviour of confined cubic blue phases under shear flow via lattice Boltzmann simulations. We focus on the two experimentally observed phases, blue phase I and blue p…
Prediction of the functional properties of ceramic materials from composition using artificial neural networks
D. J. Scott, P. V. Coveney, J. A. Kilner +2
We describe the development of artificial neural networks (ANN) for the prediction of the properties of ceramic materials. The ceramics studied here include polycrystalline, inorga…
Emergence of rheological properties in lattice Boltzmann simulations of gyroid mesophases
G. Giupponi, J. Harting, P. V. Coveney
We use a lattice Boltzmann (LB) kinetic scheme for modelling amphiphilic fluids that correctly predicts rheological effects in flow. No macroscopic parameters are included in the m…
Efficient numerical integrators for stochastic models
G. De Fabritiis, M. Serrano, P. Español +1
The efficient simulation of models defined in terms of stochastic differential equations (SDEs) depends critically on an efficient integration scheme. In this article, we investiga…