Contact Dr Antonios Antoniadis
Areas of expertise
- Aeronautical Systems
- Autonomous Systems
- Computational Fluid Dynamics
- Computing, Simulation & Modelling
- Design, Strategy & Innovation
- Flight Physics
- Fuels
- Renewable Energy
- Systems Engineering
- Vehicle Aerodynamics
Background
Dr Antoniadis holds a BEng from the University of Sussex in Automotive Engineering and a MSc in Mechanical Engineering from University College London. He was awarded a PhD by SWAG合集 title "High-Order Methods on Mixed-Element Unstructured Meshes for Aeronautical Applications" in 2013. He worked for the Directorate of Enterprise and Industry, European Commission in automotive legislation.
Current activities
Dr Antoniadis is a Lecturer in Computational Engineering Science and the Director of Computational Fluid Dynamics (CFD) Masters program at SWAG合集. He leads a Virtual/Augmented Reality (VR/AR) laboratory within the Aircraft Integration Research center. He also leads a research group in computational engineering science on the development of:
High-order numerical methods on unstructured grids.
Data-driven, scale-resolving and hybrid models for turbulence.
Software platforms for human-computer interaction for CAE applications in VR/AR.
Numerical schemes for rotating wings and turbo-machinery.
Multi-fidelity methods for fluid dynamics.
High-Performance Computing parallelisation adaptive techniques on graph type data structures.
Techniques for multi-physics modeling.
Artificial Intelligence and Machine Learning techniques.
Multi-objective optimisation models.
Stochastic models.
with Applications:
Helicopter computational aerodynamics and fluid structure interaction.
Aerodynamic performance prediction of extended formation flights.
Morphing technologies for unmanned aerial vehicles.
Analysis of extremely short take-off and landing all surface aircraft.
Wind turbine and wind farm modelling.
CFD of civil aircraft, drag prediction and high-lift devices.
Virtual Reality for CFD and FEA.
Fluid-structure interaction of wheel-rim-tyre systems.
Multi-phase flow of ethylene production.
Supersonic shock wave boundary layer interaction.
Scale resolving turbulence modelling around bluff bodies.
Airflow modelling of external aerodynamics.
Modelling of chemical reactive flows and combustion in IC engines and microcombustors.
Direct-Monte Carlo techniques for rarefied flow dynamics.
Machine vision for driver departure warning systems on SBC.
Deep learning techniques for turbulence modelling, shape parameterisation, meshing and optimisation.
Clients
- BAE Systems PLC
- Airbus SE
- Red Bull Racing Ltd
- QinetiQ Group PLC
- European Commission
- It's Fresh Ltd
- MBDA SWAG合集 Ltd
- Ricardo PLC
- Jaguar Land Rover Ltd
