65 citations · 367 across the 35 of their papers we have counts for
35 papers
Machine Learning-Assisted Discovery of Flow Reactor Designs
Tom Savage, Nausheen Basha, Jonathan McDonough +3
Additive manufacturing has enabled the fabrication of advanced reactor geometries, permitting larger, more complex design spaces. Identifying promising configurations within such s…
Transition to elasto-capillary thinning dynamics in viscoelastic jets
Konstantinos Zinelis, Thomas Abadie, Gareth H. McKinley +1
We perform simulations of an impulsively-started, axisymmetric viscoelastic jet exiting a nozzle and entering a stagnant gas phase using the open-source code Basilisk. This code al…
Data-driven modelling for drop size distributions
Tullio Traverso, Thomas Abadie, Omar K. Matar +1
The prediction of the drop size distribution (DSD) resulting from liquid atomization is key to the optimization of multi-phase flows, from gas-turbine propulsion, through agricultu…
A machine learning approach to the prediction of heat-transfer coefficients in micro-channels
Tullio Traverso, Francesco Coletti, Luca Magri +2
The accurate prediction of the two-phase heat transfer coefficient (HTC) as a function of working fluids, channel geometries and process conditions is key to the optimal design and…
Discovery of mixing characteristics for enhancing coiled reactor performance through a Bayesian Optimisation-CFD approach
Nausheen Basha, Thomas Savage, Jonathan McDonough +2
Processes involving the manufacture of fine/bulk chemicals, pharmaceuticals, biofuels, and waste treatment require plug flow characteristics to minimise their energy consumption an…
Multi-Fidelity Data-Driven Design and Analysis of Reactor and Tube Simulations
Tom Savage, Nausheen Basha, Jonathan McDonough +2
The development of new manufacturing techniques such as 3D printing have enabled the creation of previously infeasible chemical reactor designs. Systematically optimizing the highl…