The Zenotech team is proud to have participated in another successful Uncertainty Quantification and Management (UQ&M) study group with industry. These groups bring leading academic researchers and industry figures together to solve real-world problems.

The workshop’s theme was applying machine learning to issues of real value to industry, and we were there, along with CFMS, as part of the SWEPT2 Consortium. The SWEPT2 (Simulated Wake Effects Platform for Turbines) project aims to tackle the UK’s energy trilemma by modelling and simulating more effective predictions of turbine array performance. The project is developing a CFD-based simulation capability, based on our zCFD code.

The wind energy teams were led by Dr Alex Diaz (University of Liverpool) and Dr Peter Brommer (University of Warwick).  We are delighted to have provided secure access to over 320GB of CFD wind flow data via our cloud platform EPIC.  As a result of the collaborations, we have two very credible machine learning prototypes that can support our work with the wind energy sector.

This intensive workshop was hosted by James Kermode and Peter Brommer at the Warwick Centre for Predictive Modelling in December 2017. It is the third workshop in the series, organised by Matt Butchers of the Knowledge Transfer Network. Other challenges were posed by AstraZeneca, HS2, and AWE. These workshops are win-win for industry and academics, challenging both to demonstrate technological solutions within tight deadlines.

For more information about zCFD and how we can work with your business, get in touch.