Handbook of Numerical Simulation of In-Flight Icing

To obtain a type design certification, it must be demonstrated that a commercial aircraft, rotorcraft, or jet engine can sustain safe flight into known or inadvertent icing conditions. The acknowledged three means of compliance with the icing regulations are computational fluid dynamics (CFD), experimental fluid dynamics (EFD), and flight fluid dynamics (FFD). When all equipment has been designed and tested by CFD and/or EFD, it must be shown to be flight-worthy through dry shapes testing and natural icing trials (FFD), with all systems operating simultaneously. A large number of numerical studies are undertaken before reaching this near-final point. CFD-Icing is used throughout the design and tunnel testing phases as well as the natural icing campaign. Examples of such studies include alternate means of compliance where applicable, the down-select of critical ice shapes, ice protection systems design and optimization, similitude analyses, reducing and guiding icing and dry tunnel experiments, and defining dry shapes for testing. CFD-Icing is even used in designing icing tunnels, in mitigating risk during natural icing campaigns, and for supplemental type certification.

Considered for a long time a national advantage to be protected, CFD-Icing tools have remained the private playground of the National Laboratories in leading aerospace countries. In recent years, many new academic and commercial codes have emerged and are making their way into practice. The present Handbook is a testimony to this flurry of international developments and the variety of approaches. The Handbook demonstrates how in-flight icing simulation users are no longer limited in their approaches but can choose from a plethora of methods that are appropriate to their particular needs.

Albeit slowly, but surely, the chasm between the numerical technologies used for aerodynamic design (CFD-Aero) and the ones accepted in the icing certification

(CFD-Icing) is gradually narrowing. OEMs are becoming less hesitant to use tools for icing similar to the advanced ones they already use for their aerodynamics, pushing aside concerns about certification delays when new technologies are introduced.

One only hopes that embracing such technologies will accelerate in the next few years, as simulation methods in general are anticipated to evolve at an unprecedented pace prodded by the advent of artificial intelligence and machine learning. This is a window of opportunity for the icing community to make a big leap, rather than progress through measured steps.