Dr. M. Sergio Campobasso, PhD

Associate Professor (Senior Lecturer) in Renewable Energy Systems and Computational Fluid Dynamics

Department of Engineering, Lancaster University

United Kingdom

E-mail: m.s.campobasso_at_lancaster.ac.uk

NEW: 23 April 2021: SMEs in the Northwest: The Centre for Global Eco-Innovation’s flagship project Eco-I North West at Lancaster University is funding collaborative 12-month Masters by Research projects to develop new low carbon products, processes and services. Project must include an SME business partner with presence in England’s North West. Since October 2020 the Centre has begun 25 PhD and Masters projects spanning a breadth of disciplines and research themes. We have further 12 month Masters by Research project opportunities available, to begin October 2021. If interested, please contact me (m.s.campobasso@lancaster.ac.uk).

My interest in Engineering started at the age of six, with the Japanese Manga Goldrake. Since then, I have moved to more realistic problems. In the past 20 years I have developed and/or used novel high- and low-fidelity simulation technologies for rotary machine analysis and design, including linear, nonlinear and adjoint Navier-Stokes (NS) Computational Fluid Dynamics (CFD) systems for industrial and academic research and development. For more than 10 years, my research work has focused on Renewable Energy Systems. In this framework, one significant achievement of my team has been the development of a novel harmonic balance (HB) compressible NS CFD code (COSA), successfully validated against real turbine data (wind turbine in yawed flow), that we have shown to reduce by up to 50x the run-time of high-fidelity NS CFD based on the conventional time-domain CFD, an accomplishmen that makes CFD more amenable to industrial application. Recently we also extended this technology to tidal stream turbines by developing the ARCTIC incompressible NS CFF code.

New research ideas sometimes arise fortuitously. For example, novel findings on the hydrodynamics of oscillating wings for tidal and estuarine stream power generation (guidelines for the maximization of the hydrodynamic efficiency in real installations and wing end design) were achieved with the COSA code, and published in the International Journal of Marine Energy in 2016. The original impetus for this work arose during a conversation on CFD code validation at the Gala dinner of the Conference on Modelling Fluid Flows 2009 in Budapest, with a researcher who had presented his laminar two-dimensional simulations of an ideal oscillating wing.

The CFD codes we develop and/or use run efficiently both on office desktops and large distributed- and shared-memory computer cluster, such as ARCHER (UK national supercomputing service) using tens of thousands of cores in parallel. Parallelizing our CFD codes in close collaboration with the experts at the Edinburgh Parallel Computing Centre (EPCC), home to ARCHER, we have developed a highly efficient distributed-memory (MPI) infrastructure of our CFD applications, and a novel hybrid parallelization method, based on combining MPI and OpenMP, resulting in an efficient time-parallelization of harmonic balance NS codes.

But it is not all about NS CFD and supercomputing. In collaboration with researchers at the University of Strathclyde, we have produced one of the first demonstrations of a probabilistic multi-disciplinary design optimization technology obtained by integrating state-of-the-art industrial engineering codes for wind turbine development, applying novel uncertainty analysis methods, and steering the robust design process with evolution-based optimization. We have used this technology to minimize the mean and minimize the standard deviation of wind cost of energy accounting for engineering uncertainty (e.g. turbine blade manufacturing and assembly tolerances), and environmental uncertainty (e.g. variability of wind characteristics with installation site).

Our new research projects include a) the analysis of the surface wave-induced unsteady loads on tidal stream current such as those in the MayGen tidal array in the Pentland Firth of the coast of Scotland, b) the analysis of tidal stream turbine wakes and the assessment of power losses due to turbine/wake interactions in the array, c) the investigation of unsteady rotor aerodynamics of utility-scale floating offshore wind turbines like those of the HyWind pilot project in the North Sea (the first utility-scale floating wind farm in the world to date), and d) the development of a wind turbine Annual Energy Prediction Loss Prediction System (ALPS) to assess wind turbine and wind wind farms enery yield losses due to blade leading edge erosion. All of these projects aim at reducing the cost of offshore and marine renewable energy, and are carried out in collaboration with major industrial stake-holders and the UK Engineering and Physical Sciences Research Council.

These pages provide more detail on my research for anyone interested in computing and renewable energy, from prospective postgraduate students to academic and industry colleagues interested in collaborating and exploring the solution to new Renewable Energy challenges to help preserve our planet and its natural environment for present and future generations. We make every effort to keep these pages up-to-date, but some pages are still under construction. Should you be interested in further information, please drop me an email.

M. Sergio Campobasso


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COSA code



Research Data