Research Interests

Dr Campobasso took up a Senior Lectureship in Renewable Energy Engineering at Lancaster University in January 2013. He gained a Postgraduate Diploma in Turbomachinery from the Von Karman Institute for Fluid Dynamics (Belgium) in 1996, and a PhD in Numerical Analysis from Oxford University in 2004. He worked as aerodynamicist and stress engineer with the German aircraft engine manufacturer BMW-Rolls Royce, and in this period he participated to the development of the Trent 500 turbofan engine. He spent six years at the Rolls-Royce Computational Fluid Dynamics (CFD) University Technology Centre within the Oxford University Computing Laboratory, where he developed crucial parts of the linear and adjoint solvers of the main CFD code of the Rolls-Royce aerodynamic aeroelastic and aeroacoustic turbomachinery design system. At Cranfield University, Dr. Campobasso worked on uncertainty propagation for robust conceptual aircraft design, and at Glasgow University he started a new research programme focusing on wind turbine aerodynamic, aeroelastic and structural design based on nonlinear frequency-domain Navier-Stokes CFD.

The research activities of Dr Campobasso focus on the design, implementation and demonstration of CFD technologies aimed at improving wind and gas turbine design, taking into account stochastic uncertainty sources arising from manufacturing and assembly tolerances, and also the environment variability. His main objectives are to develop accurate and ultra-fast high-fidelity analysis and design methods based on the Navier-Stokes equations. His present research activities include: the development of a harmonic balance NS solver for the rapid analysis of unsteady flows and general fluid/structure interaction problems; the development of low-speed preconditioning methods for the analysis of flows featuring simultaneously high and very-low speeds; the development of novel, more accurate boundary conditions for the analysis of the flow field in complex turbomachinery geometries; and the investigation of hybrid parallelization technologies based on the combination of shared and distributed parallel computing.