Imperial College London


Faculty of EngineeringDepartment of Earth Science & Engineering

Research Associate



c.heaney Website




Royal School of MinesSouth Kensington Campus





I am currently working on the EPSRC-funded "RELIANT project" (Risk EvaLuatIon fAst iNtelligent Tool for COVID19), which aims to identify solutions for the management of people and spaces in the current pandemic and during the easing of restrictions.

Prior to this I have worked on:

• the "MUFFINS project" (MUltiphase Flow-induced Fluid-flexible structure InteractioN in Subsea applications), focusing on reduced order modelling of slug flow in pipes;

• the Newton-funded "Smart GeoWells" project, of which the aim was the numerical prediction of optimal drilling strategies for extracting geo-thermal energy;

• the "Fast Reactor Physics Modelling" project funded by HMS Sultan, which investigated the application of reduced order modelling to problems in reactor physics.

My research interests span several areas including:
(1) reduced order modelling;
(2) calculating error bounds for parameters derived from computational homogenisation;
(3) investigating summation rules for the quasi-continuum method;
(4) error estimation and adaptive mesh refinement;
(5) meshless methods in geomechanics.

Selected Publications

Journal Articles

Obeysekara A, Salinas P, Heaney CE, et al., 2021, Prediction of multiphase flows with sharp interfaces using anisotropic mesh optimisation, Advances in Engineering Software, Vol:160, ISSN:0965-9978, Pages:1-16

Lyu Z, Lei Q, Yang L, et al., 2021, A novel approach to optimising well trajectory in heterogeneous reservoirs based on the fast-marching method, Journal of Natural Gas Science and Engineering, Vol:88, ISSN:1875-5100, Pages:1-12

Phillips T, Heaney C, Tollit B, et al., 2021, Reduced-order modelling with domain decomposition applied to multi-group neutron transport, Energies, Vol:14, ISSN:1996-1073

Heaney CE, Buchan AG, Pain CC, et al., 2021, Reduced-order modelling applied to the multigroup neutron diffusion equation using a nonlinear interpolation method for control-rod movement, Energies, ISSN:1996-1073

Heaney CE, Li Y, Matar OK, et al., 2020, Applying Convolutional Neural Networks to Data on Unstructured Meshes with Space-Filling Curves, Arxiv

Xiao D, Heaney CE, Fang F, et al., 2019, A domain decomposition non-intrusive reduced order model for turbulent flows, Computers & Fluids, Vol:182, ISSN:0045-7930, Pages:15-27

Heaney CE, Pain CC, Buchan AG, et al., 2018, Reactor simulators and reduced order modeling, Nuclear Future, Vol:14, ISSN:1745-2058, Pages:49-54

More Publications