Abstract
Energy efficiency and process control are critical challenges in scaling sonochemical applications. To address this, we introduce a numerical optimisation framework focused on designing pre-seeded bubble clusters driven by impulse ultrasound to minimise energy consumption. The methodology efficiently handles the large parameter space (bubble sizes) by combining fast, reduced-order modelling of spherical bubbles and chemical kinetics with expensive multi-phase hydrodynamic simulations (ALPACA). The technique is demonstrated on two test cases: ammonia (NH(3)) and hydrogen (H(2)) synthesis, to analyse the effects of different reaction mechanisms. In both cases, the optimal size distribution of a chain of 16 bubbles is found with as few as three multi-phase flow simulations.