Dr Amirul Khan
- Position: Lecturer
- Areas of expertise: Computational fluid dynamics; Particle dispersion in turbulent flows; Numerical Optimisation; Lattice Boltzmann Method; GPU based computing using CUDA; Data Assimilation; Medical Flow
- Email: A.Khan@leeds.ac.uk
- Phone: +44(0)113 343 2286
- Location: 4.21 School of Civil Engineering
- Website: Googlescholar | Researchgate
PhD in Applied Mathematics, Wolfson College, University of Cambridge, UK, 2002.
Part III of the Mathematical Tripos, Wolfson College, University of Cambridge, UK, 1998.
MSc in Theoretical Physics, University of Dhaka, Bangladesh, 1997.
BSc (Hons) in Physics with Mathematics and Statistics, University of Dhaka, Bangladesh, 1995.
- Departmental Seminar Organiser
- School Academic Lead for Inclusive Practice
Computational Fluid Dynamics, Particle Dispersion in Turbulent flows, Numerical Optimization, Lattice Boltzmann Method. GPU based computing using CUDA.
My research interests span from the theoretical and experimental investigations into the fundamental aspects of fluid turbulence and turbulent dispersion to nonlinear dynamics in cavity flows, as well as novel computational methods for fluid flow, including:
- Built environment: modelling turbulent flows and investigating its applications in the built and urban environment. Current research topics include:
- Computational fluid dynamics (CFD) modelling of hospital indoor air quality including airborne infection risk.
-CFD-based multi-objective optimisation of hospital ward design to mitigate infection risk while maintaining occupant comfort.
-CFD-based modelling and optimisation in-duct UVC sterilisation systems for healthcare environments.
-Novel sensor supported simulation-based predictive control indoor environment including controlling airborne contamination in hospital wards.
- Multiscale modelling: developing in-house massively parallel GPU-based simulation tools for single and multi-phase fluid modelling for engineering problems. Current projects:
- Novel real-time Lattice Boltzmann (LB) simulation of urban heat and pollution modelling;
- Multiscale LB modelling of coupled hydro- and morphodynamics in environmental flows with applications to land and marine use management and geohazard prediction and mitigation.
- Multiphase flow and heat transfer: including flow in anaerobic digesters (AD) in wastewater treatment plants, ground-source heat exchanger technology, flow and heat transfer, and phase change materials for thermal performance. Current projects:
- Multiphase flow and heat transfer in cooling systems for electronic circuits, built environment and data centres.
- Novel coaxial heat exchanger technology for ground-source heat pumps
- Novel unified radiation transport and turbulent hydrodynamics solver on massively parallel graphics processing units (GPUs) for solving highly coupled multi-physics problems in nuclear engineering.
- Computational modelling of spray carryover in personal care products.
Currently Funded & Completed Research Projects
HECOIRA: Healthcare Environment Control, Optimisation and Infection Risk Assessment (Co-I), 2017-2021, EPSRC Healthcare Impact Partnership in collaboration with two NHS trusts and two industry partners. https://hecoira.leeds.ac.uk/
GEOTECH: Geothermal Technology for Economic Cooling and Heating (CFD-based optimisation,Task Leader), 2015-2019 http://www.geotech-project.eu/
- American Physical Society, USA
- Cambridge Philosophical Society, UK
- International Society of Indoor Air Quality and Climate
Engineering Mathematics Level I & II
Computational Methods Level III
Design Optimisation Level IV
Research groups and institutes
- Centre for Integrated Energy Research
- Energy Leeds
- Computational Science and Engineering
- Cities and Infrastructure
- Energy and Sustainable Buildings
- Water, Public Health and Environmental Engineering
- Centre for Computational Engineering
Current postgraduate researchers
<li><a href="//phd.leeds.ac.uk/project/663-toward-easy-parallel-programming-for-computational-fluid-dynamics">Toward Easy Parallel Programming for Computational Fluid Dynamics</a></li>