7 citations · 8 across the 5 of their papers we have counts for
5 papers
Learning Interface Breakup: A Geometry-Conditioned Latent Surrogate for Spray Formation
Julius H Ramlau, Friedrich Hastedt, Tolga Birdal +3
Designing spray nozzles requires predicting how geometry shapes transient two-phase breakup, but high-fidelity volume-of-fluid (VOF) simulations with adaptive mesh refinement (AMR)…
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…
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…
Deep Gaussian Process-based Multi-fidelity Bayesian Optimization for Simulated Chemical Reactors
Tom Savage, Nausheen Basha, Omar Matar +1
New manufacturing techniques such as 3D printing have recently enabled the creation of previously infeasible chemical reactor designs. Optimizing the geometry of the next generatio…