If you travel by plane during the winter, you are used to the de-icing process: The jet taxis to the de-icing station, where technicians spray the it with chemicals to remove any ice that may have built up while it was sitting on the ground. That’s standard procedure. But what about ice that forms when the plane is flying at high altitude in the cold air? Is that ice dangerous, and can the buildup be predicted to avoid problems in-flight?
Prediction is a complicated process, but it can be done. The only way to numerically predict the in-flight icing behavior (aerodynamics, ice shapes, thermal performance) for the wide range of aerospace assemblies and components (wings, empennages, engine inlets, nacelles, sensors, probes, all the way up to the complete aircraft) is by using CFD models that predict performance “as installed.”
Current testing methods can be incomplete. They may deliver less insight than expected or even report misleading results. For example:
- Airfoils or parts of wings are tested individually in icing tunnels, but the flow may be totally different once engines or propellers are mounted on these wings.
- Helicopter icing is analyzed in 2D when only 3D will get the right ice shape.
- Ice protection systems (IPS) systems are designed in 2D, but the flow inside a piccolo tube is “violently” 3D.
- Pitot tubes are tested in wind tunnels mounted against flat walls, but in operation these pitot tubes will experience a different incoming flow once mounted on a fuselage.
- Whole airplanes are certified by analyzing a limited number of natural icing test points, but scientific methods are available to determine the behavior of the aircraft for all points.
- Mathematical methods are well-accepted for optimizing wing performance, but we never apply them to IPS optimization. Designers may produce good and even excellent IPS, but are they optimal? Small performance improvements can have a huge impact over the life of the aircraft.
So, how do you test for ice cracking and tracking?
Industry Needs CFD-Icing Codes that Are Truly Predictive and Not Simply Calibrated
Accuracy in predicting in-flight ice formation must be addressed by developing analytical roughness models that predict ice surface roughness in space (varying all over the 3D body) and in time (roughness is time dependent, increasing asymptotically to a local value as ice accretes). Only in this way can a CFD-Icing code be truly predictive and not simply calibrated.
New 3D CFD-Icing tools permit a more efficient and safer certification method for all types of aircraft by reducing the likelihood of ice-induced hazardous events in service. While dry and icing (wet) wind tunnel testing, flight testing with artificial ice shapes, and flying in natural icing conditions will always play a significant role, advanced simulation tools can shorten the certification process. Simulation can fill important gaps in the data, focus or eliminate the icing tunnel for ice shapes, and predict what will be seen in natural icing testing (calculations and verifications over the entire aircraft with engines, propellers, rotors and turbomachinery stages running, and sensors and probes placed), ultimately increasing safety.
Will further testing be required after using CFD? Of course. But in my experience, final designs created using true 3D CFD will need a lot less tweaking at certification time. Also, safety considerations do not stop when certification is granted but extend to performance during operational life. Incidents and accidents have a high cost in human lives, and can be avoided by a better understanding of the aircraft, engine and appended instruments, as installed.
Learn More at the Simulation Methods for In-Flight Icing Certification Course
My colleagues and I hold an annual International In-flight Icing Course in May. Come see for yourself how CFD-Icing should be pervasive in all stages of analysis, design and certification, from the smallest component to the aircraft itself. Learn from a cross section of experts including code developers, former regulators and an icing lead for a major OEM. You’ll leave with a rigorous, scientifically-based version control, verification and validation dataset that is now widely accepted at all levels. Course details will be posted here when available.