Robust optimization of variable-camber continuous trailing-edge flap system action using stochastic kriging

A robust optimization method is described in this paper, focused on the optimization of a Variable-Camber Continuous Trailing-Edge Flap (VCCTEF) system for drag reduction in transonic cruise. The VCCTEF, through the rich combination of shapes it can attain, has the potential to provide greater design and operation freedom than conventional flap systems and greater efficiency in drag reduction and performance improvement. The VCCTEF deformation shape optimization, however, when based on rigorous CFD simulations, presents a significant computational challenge because of the high cost of repetitive analyses required. The construction of surrogate models and their utilization in the optimization process is one common way for tackling this challenge. Here Stochastic Kriging (SK) is used, extending the commonly used Deterministic Kriging (DK). Accounting for the intrinsic uncertainty of data, Stochastic Kriging and the optimization based on it are especially suited for addressing uncertain flight conditions as well as math modeling limitations. An optimization engine is presented that couples geometric shape synthesis with CFD simulations and an automated optimization process focused on the VCCTEF system. A potential for drag reduction is shown even in the presence of uncertainties.