Conventional CO2 dry-ice blasting is widely used in maintenance for non-destructive cleaning of sensitive industrial components. In dry-ice blasting systems, dry-ice particles serve as cleaning agent. They are accelerated with pressurized air flows through convergent-divergent nozzles. These supersonic flows make the particles impinge and defoul variously fouled targets. The main disadvantages of such systems are high energy consumption by compressed air and massive aeroacoustic emissions, which make them usable under consideration of certain safety restrictions only.
This paper describes an all-encompassing approach to minimize the energy consumption of an automatic cleaning system used to defoul car-tire moulds and to assess and improve this systems aeroacoustic emission. Experiments are made utilizing a high speed camera (HSC) to assess the amount of energy necessary to remove typical fouling layers. Further experiments are conducted with a HSC to measure particle sizes and velocities at the nozzle outlet and the experimental investigation is completed by detailed aeroacoustic emission measurements at the aeroacoustic test-rig. The particle acceleration process is numerically simulated with an Euler-Lagrange approach. Particle outlet velocities, impact properties and mean aeroacoustic emissions of the process are predicted by means of this validated simulation strategy. The simulations are partially compared to experimental measurements where possible.
All these results are used to map and to improve the process for the dry-ice blasting system considered. This is put into practice by adjusting the process parameters and by design and applications of new system-specific silencers. Significant reductions of aeroacoustic emissions and energy consumption are achievable. The study shows that the system can be operated with enhanced energy efficiency and decreased acoustic emissions. The cleaning efficiency is decreased but it is shown that it is still possible to certainly clean the car-tire moulds.