Parametric synthesis optimization models for high speed transport aerodynamic design to comply with flight safety and low environmental impact requirements

Preliminary aerodynamic design of a new generation high-speed transport is characterized by epistemic uncertainty in some initial data required for optimization parametric synthesis of aircraft design. In the present paper Liu's uncertainty theory was applied to develop high-speed transport preliminary aerodynamic design under epistemic uncertainty. The theory introduces axiomatics based on measured uncertainty (so-called expert confidence level) and contains analytical expressions for all functions that depend on epistemically uncertain parameters. Such approach provides high computational efficiency when performing optimization procedure compared to statistical modeling. Multicriteria optimization models of aircraft design parametric synthesis, obtained based on uncertainty theory, are presented in the paper. Analytical expressions for numerical characteristics of target functions and constraints with uncertain input and optimized parameters are derived. These ones provide analytical tools for correcting optimized parameters in the iterative high-speed transport designing process that cannot be based on statistical data. Effectiveness of the proposed models is evaluated in the context of the supersonic cruise flight optimization for high-speed transport under epistemic uncertainty and additional requirements for aircraft flight safety and environment low impact.