1st AIAA Ice Prediction Workshop Workshop in Conjunction with the AIAA AVIATION 2021 Forum All Virtual/Remote Participation 26-29 July 2021
The 1st AIAA Ice Prediction Workshop
The first workshop will focus on ice shape comparisons between the 3D/2D codes for cases where experimental ice shapes are readily available. The ice shapes would be generated on both 2D and 3D geometries for a limited number of configurations and conditions.
The intent is to establish a sound baseline of the current capabilities and use this baseline to target the best topics for the follow-on workshops. This would maximize the number of participants that are potentially interested in such a workshop and minimize the risk of incomplete submissions.
These Ice Prediction Workshops are collaborative in nature, aiming at assessing the icing simulation tools and practices, identify areas of improvement and recommended practices and at sharing knowledge. They should not, therefore, be viewed as competition between codes, groups and/or testing facilities.
Ice accretion is, in most cases, a 3D phenomenon and, therefore, 3D modeling and simulation is usually preferred.
Great effort has been invested in the research, development, and testing of 2D icing simulation. 2D analysis is still widely used and well accepted. It established the groundwork for 3D methods and, hence, it should be used as a valid reference for comparison whenever applicable.
It is important to define a methodology to compare the simulated 3D ice shapes among themselves and with the 3D experimental ice shapes.
Icing simulation typically involves four modules: airflow solver, droplet dynamics solver, surface water mass and energy balance module, and ice accretion geometry module. It is important, to try to understand how each module contributes to discrepancies in the final ice shape prediction.
When comparing numerical simulation results to experimental simulation results, the uncertainty of both types of simulations needs to be considered, as well as the repeatability of the experimental results at a given facility and, if possible, between facilities.
Our intent is to capture best practices in icing simulation, identify current limitations of the 3D tools, and make recommendations about specific areas where more work is needed.