📣 Help Shape the Future of UKRI's Gateway to Research (GtR)

We're improving UKRI's Gateway to Research and are seeking your input! If you would be interested in being interviewed about the improvements we're making and to have your say about how we can make GtR more user-friendly, impactful, and effective for the Research and Innovation community, please email gateway@ukri.org.

AI-Mesh

Lead Participant: ZENOTECH LTD

Abstract

The most commonly referenced bottleneck and process impediment in computational engineering is mesh generation -- defining the discrete elements, lines and points around a geometry (car, aeroplane, turbine) that are required before a solver (computational fluid dynamics, computational structural mechanics or electromagnetics) can be run. AI-Mesh brings together specialist SMEs AlgoLib (AI and machine learning technology) and Zenotech (computational engineering and cloud computing) to create a prototype AI-based meshing system - replacing manual human operations in mesh generation with automation informed by feedback from the quality metrics of each mesh generated.

Lead Participant

Project Cost

Grant Offer

ZENOTECH LTD £65,971 £ 46,180
 

Participant

ALGOLIB LTD £33,938 £ 23,757

Publications

10 25 50