HARPPP: Autonomous Geometric Design Optimisation of Stirred Tank Reactor Impellers and Baffles

TL;DR

HARPPP is an autonomous optimization framework that uses a programmable geometry model, CFD simulations, and evolutionary search to improve impeller and baffle designs in stirred tank reactors, achieving significant performance gains.

Contribution

It introduces a unified geometry model and an autonomous optimization loop that efficiently explores complex design spaces for industrial equipment.

Findings

Discovered multiple impeller and baffle designs outperforming standard configurations.

Achieved 18-78% improvement in mixing intensity and 16-64% reduction in uniformity CoV.

Demonstrated the method's generalizability to other equipment with credible physics models.

Abstract

Designing and optimising the geometry of industrial process equipment remains slow and still largely ad hoc: engineers make small tweaks to one standard shape at a time, build prototypes, and hope for gains. We introduce HARPPP, an autonomous design loop that couples a compact, programmable geometry model to power-controlled CFD and evolutionary search. The geometry model is a single mathematical description that reproduces every standard impeller as a special case while spanning an unlimited set of manufacturable shapes. Working with Johnson Matthey on an industrial vessel, HARPPP explored a 23-parameter impeller-baffle space at constant power (3024 W), executing 3,000 simulation cycles in 15 days. The search uncovered multiple design families that outperform a Rushton/4-baffle baseline in both mixing intensity and uniformity, including twisted-plate impellers and pitched/curved baffles (intensity +18 to +78 percent; uniformity CoV -16 to -64 percent). A clear intensity-uniformity Pareto frontier emerged, enabling application-specific choices. Because HARPPP treats the simulator as the objective, it generalises to other equipment wherever credible physics models exist.