Imperial College London

Professor Mehdi Vahdati

Faculty of EngineeringDepartment of Mechanical Engineering

Principal Research Fellow



+44 (0)20 7594 7073m.vahdati




606City and Guilds BuildingSouth Kensington Campus





Mehdi is the Principal Research Fellow in the Thermo-Fluids Division. He has over 30 years of experience in developing numerical models for aerodynamics and aeroelasticity.  His research topics include:

  • Development of CFD algorithms for internal and external flows
  • Development of numerical aeroelasticity (FSI) models
  • Flutter modelling of gas turbine components (Fan, Compressor, Turbine and Seals)
  • Forced response modelling in gas turbines
  • Stall and surge modelling
  • Aeroelastic behaviour of wind turbines
  • Turbulence modelling using Machine Learning
  • Applications of Machine Learning in turbomachinery
  • Aerodynamic and aeroacoustics modelling of drones (UAVs)

One of the main reasons for turbomachinery failure is vibration caused by Fluid-Solid Interaction (FSI). His research has shown that through efficient and accurate numerical modelling, the mitigating causes of engine failures can be identified, which leads to substantial increase in safety and reliability, major costs savings and provides energy-efficient, environmentally friendly benefits. He was a member of Roll-Royce VUTC from 1993-2020 and Head of Aeroelasticity from 2015-2020.  He is the pioneering author of CFD aeroelasticity Code AU3D. In 2001, Mehdi was awarded by Rolls-Royce plc the title of Rolls-Royce Research Fellow at Imperial College, in recognition for his contributions to the company.

He has published extensively in journals and peer reviewed conferences and has won numerous best paper awards.  He is an Associate Editor of the Journal of Turbomachinery (ASME).



Yan C, Wang B, He X, et al., 2024, Extension and Validation of the Turbomachinery Capabilities of SU2 Open Source Computational Fluid Dynamic Code, Journal of Turbomachinery, Vol:146, ISSN:0889-504X

Ba D, Du J, Vahdati M, et al., 2024, Design optimization of a hybrid casing treatment based on axial momentum budget analysis in the tip flow region, Physics of Fluids, Vol:36, ISSN:1070-6631

Zhao F, Moreno J, Dodds J, et al., 2023, Methodology and Validation of Surge Modeling in a Three-Shaft Compression System, Journal of Turbomachinery, Vol:145, ISSN:0889-504X

Zhao F, Chen D, Liu J, et al., 2023, A framework for simulating snow accumulation and ice accretion on high-speed trains, Proceedings of the Institution of Mechanical Engineers Part F-journal of Rail and Rapid Transit, ISSN:0954-4097


Chennuru VYT, Zhao F, Vahdati M, 2024, An Optimal Numerical Strategy for Intake in Crosswind Conditions, ISSN:0742-4795

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