Classification of Errors and Uncertainties

The structuring of this work is based upon the distinction between errors and uncer­tainties, for which the definitions given in the BPG for industrial CFD published by ERCOFTAC [1] are adopted.

Errors

The term error is used to refer to problems arising from mis-use of the flow solver or turbulence model and is distinct from the functionality of the applied model. Errors hence lead to different predictions for the same flow using the same model and a prominent example is the use of an insufficiently fine grid. Errors can in theory be avoided through proper solution setup (i. e. by an experienced user and/or through adherence to an appropriate set of BPG). Nonetheless, the problem of errors should not be under-estimated since they are often hard to identify and to avoid, particularly in complex industrial configurations. Furthermore, advanced knowledge of the flow solution is required to correctly generate the grid. Examples include the choice of the skin friction normalised wall-normal cell size at solid boundaries, y+, the wall – normal expansion ratio of the grid inside the boundary layer, the recommendation of wall-normal grid cells and the capturing of the complete boundary layer with prismatic cells.

Uncertainties

In contrast to errors, the term uncertainty is used to refer to loss of predictive ac­curacy that occurs due to lack of knowledge about the true flow physics. In the scope of this work, this implies shortcomings of the RANS models in describing the turbulence. Deviation of an error-free solution with “reality” can hence arise due to uncertainties. The varying reliability of different turbulence models for dif­ferent flow phenomena, e. g. separating/reattaching flows and shock-boundary layer interaction, is primarily considered. Compared to errors, BPG concerning RANS modelling uncertainties are more vague in nature and less accessible to a “Boolean” type of treatment: Simple statements along the lines of “Model A is best for flow type X” have remained elusive.