Biography
Professor Martin Davy is a Mechanical Engineer with somewhat of an unusual background for an Oxford academic.
After leaving school in 1978, he worked variously as: a construction labourer, a storeman and service receptionist in a variety of motorcycle shops and car dealerships, a car valeter and a bodyshop estimator, before finding himself in the early 1990s helping to run a motor racing team in Brazil. He finally decided to consider his late father’s oft repeated advice to “get a proper job” shortly after his 32nd birthday. He subsequently completed his undergraduate degree in Mechanical Engineering at UCL in 1996 and gained his PhD from the same institution in 2000.
Martin joined Oxford and Exeter in 2013 having previously held faculty positions at UCL, the University of British Columbia and Loughborough University. He is still looking for a “proper job”.
Prizes and Awards
- 2001 UnICEG Richard Way Memorial Prize
- 2001 SAE Excellence in Oral Presentation
- 2013 IMechE Dugald Clerk Prize
- 2013 SAE Myers Award
- 2019 SAE Myers Award
Most Recent Publications
A Fundamental Study on the Potential LSPI Promoting Mechanisms of Ca and Mg based Oil Detergents
A Fundamental Study on the Potential LSPI Promoting Mechanisms of Ca and Mg based Oil Detergents
Large eddy simulation of a supersonic lifted hydrogen flame: Impacts of Lewis, turbulent Schmidt and Prandtl numbers
Large eddy simulation of a supersonic lifted hydrogen flame: Impacts of Lewis, turbulent Schmidt and Prandtl numbers
Development of a semi-empirical physical model for transient NOx emissions prediction from a high-speed diesel engine
Development of a semi-empirical physical model for transient NOx emissions prediction from a high-speed diesel engine
Integration and validation of some modules for modelling of high-speed chemically reactive flows in two-phase gas-droplet mixtures
Integration and validation of some modules for modelling of high-speed chemically reactive flows in two-phase gas-droplet mixtures
Extracting vector magnitudes of dominant structures in a cyclic engine flow with dimensionality reduction
Extracting vector magnitudes of dominant structures in a cyclic engine flow with dimensionality reduction
Research Interests
Martin's main research interest is in internal combustion engines, and particularly the combustion processes in compression ignition engines, where his research has a strong focus on pollutant reduction. He also has interests in in-cylinder heat transfer, atomization and sprays, and the use of alternative fuels—including gaseous fuels—for both transportation and stationary applications.
Martin currently leads Oxford’s activities in the EPSRC Prosperity Partnership, "Centre of Excellence for Hybrid Thermal Propulsion Systems", having previously led the joint University of Oxford / Jaguar Land Rover “Centre of Excellence for Compression Ignition Engine Combustion Research”, and Oxford's involvement in the EPSRC sponsored project, “Ultra Efficient Engines and Fuels”.
Most Recent Publications
A Fundamental Study on the Potential LSPI Promoting Mechanisms of Ca and Mg based Oil Detergents
A Fundamental Study on the Potential LSPI Promoting Mechanisms of Ca and Mg based Oil Detergents
Large eddy simulation of a supersonic lifted hydrogen flame: Impacts of Lewis, turbulent Schmidt and Prandtl numbers
Large eddy simulation of a supersonic lifted hydrogen flame: Impacts of Lewis, turbulent Schmidt and Prandtl numbers
Development of a semi-empirical physical model for transient NOx emissions prediction from a high-speed diesel engine
Development of a semi-empirical physical model for transient NOx emissions prediction from a high-speed diesel engine
Integration and validation of some modules for modelling of high-speed chemically reactive flows in two-phase gas-droplet mixtures
Integration and validation of some modules for modelling of high-speed chemically reactive flows in two-phase gas-droplet mixtures
Extracting vector magnitudes of dominant structures in a cyclic engine flow with dimensionality reduction
Extracting vector magnitudes of dominant structures in a cyclic engine flow with dimensionality reduction
DPhil Opportunities
Enquiries from potential research students (graduate and undergraduate) are welcome.
Teaching
In the first year at Exeter, Martin teaches the P4 “Energy” paper, which includes Electricity and Magnetism, Thermodynamics and Fluid Mechanics and Dimensional Analysis. He also teaches elements of the P3 “Structures and Mechanics” paper.
In the second year, he teaches the Applied Fluids, Heat & Mass Transfer, and Thermodynamics content of the A4 “Energy Systems” paper, along with Vibrations and Dynamics of Machines in the A3 paper, “Structures, Materials and Dynamics”.
Within the Department of Engineering Science, Martin lectures the Powertrain module of the Final Year C1 Automotive Engineering course and supervises 1st and 2nd year Thermofluids laboratory classes and a 3rd year project on Chemical Energy Storage.
Most Recent Publications
A Fundamental Study on the Potential LSPI Promoting Mechanisms of Ca and Mg based Oil Detergents
A Fundamental Study on the Potential LSPI Promoting Mechanisms of Ca and Mg based Oil Detergents
Large eddy simulation of a supersonic lifted hydrogen flame: Impacts of Lewis, turbulent Schmidt and Prandtl numbers
Large eddy simulation of a supersonic lifted hydrogen flame: Impacts of Lewis, turbulent Schmidt and Prandtl numbers
Development of a semi-empirical physical model for transient NOx emissions prediction from a high-speed diesel engine
Development of a semi-empirical physical model for transient NOx emissions prediction from a high-speed diesel engine
Integration and validation of some modules for modelling of high-speed chemically reactive flows in two-phase gas-droplet mixtures
Integration and validation of some modules for modelling of high-speed chemically reactive flows in two-phase gas-droplet mixtures
Extracting vector magnitudes of dominant structures in a cyclic engine flow with dimensionality reduction
Extracting vector magnitudes of dominant structures in a cyclic engine flow with dimensionality reduction