An automatic multi-stepping approach to aircraft ice prediction

Abstract

Flying an aircraft in icing conditions may seriously degrade its aerodynamical performance and threaten the flight safety. Over the years, new technologies and improved procedures have limited the potential risks caused by aircraft icing. Experimental studies being very expensive, numerous computer codes have been developed to simulate ice shapes and tackle the problem. Typically in these codes, a flow solution and key icing parameters are evaluated around a clean un-iced geometry and their values remain constant during the entire simulation. This approach may be acceptable for short exposure times or when the ice shape only slightly deforms the initial geometry. However, in other cases, the values of the icing parameters may vary and the simulation will loose its accuracy: for large shapes, the presence of the ice influences the surrounding airflow significantly, altering the value of icing parameters and ultimately the ice accretion. Calculating more accurate ice shapes therefore requires to periodically recompute the flow field around the body during the simulation and determine updated values for icing parameters. This procedure, known as multi-stepping, is investigated in this thesis and adapted to the new threedimensional icing code ICECREMO2. Several multi-step algorithms are presented and tested on cylinders and airfoils. When possible, the ice shapes simulated are compared with experimental results. The first multi-step calculations were generally performed manually. The user had to perform a rather tedious work and inappropriate instructions could lead to severe inaccuracies in the simulations. To avoid these difficulties, a fully automated procedure will be developed including all stages of a multi-step computation. This significantly reduces user interaction and the overall computing time. The present research work forms part of the ICECREMO2 project. ICECREMO2 is a three-dimensional ice accretion and water flow code developed collaboratively by Airbus UK, BAe Systems, Dunlop Aerospace, Rolls-Royce, GKN Westland Helicopters, QinetiQ and Cranfield University under the auspices of the UK Department of Trade and Industry. i