Dr Massoud Tatar

Background

Dr Massoud Tatar is a Research Fellow in Energy Fluid Dynamics at the Centre for Energy Decarbonisation and Recovery, where he contributes to a UK Innovate-funded project focused on CFD modelling of a plasma-assisted waste gasification reactor. His research expertise spans computational fluid dynamics (CFD), aerodynamics, turbomachinery, plasma-assisted processes, and energy systems. Prior to his current role, he worked as a Senior Aerodynamics Research Engineer in the UK, supporting industrial aerodynamic development and analysis. Before moving to the UK, he held postdoctoral positions at Chalmers University of Technology, Sweden. His work included CFD modelling of air plasma reactors for sustainable nitrogen fixation and the development of body-force models for Ultra-High Bypass Ratio (UHBR) fan applications. He holds a PhD in Aerodynamics and continues to pursue research at the intersection of advanced fluid dynamics, reacting flows, and sustainable energy technologies.

Current activities

Dr Massoud Tatar is currently engaged in the numerical modelling of thermal and non-thermal plasma systems and their interaction with complex flow fields, with a particular focus on plasma-assisted waste gasification technologies. His work involves the development of advanced computational fluid dynamics (CFD) models for coupled plasma flow, heat transfer, chemical reactions, and multiphase phenomena within gasifier reactors. Through his research, he contributes to the advancement of sustainable energy conversion and decarbonisation technologies.

His broader research interests span high-temperature reacting flows, thermal and non-thermal plasma modelling for air, hydrogen, and ammonia applications, and aerodynamic flows ranging from subsonic to hypersonic regimes. He is also interested in steady and unsteady aerodynamic modelling, including linear and nonlinear reduced-order models derived from CFD simulations and experimental or flight-test data. Additional areas of interest include hydrodynamic flows such as cavitation, sloshing, and free-surface interactions; transition and turbulence modelling; conjugate heat and mass transfer; and the application of machine learning and reduced-order modelling techniques to complex nonlinear fluid-flow problems.