Uncertainty Quantification of Compressor Map Using the Monte Carlo Approach Accelerated by an Adjoint-Based Nonlinear Method

Precise and inexpensive uncertainty quantification (UQ) is crucial for robust optimization of compressor blades to control manufacturing tolerances. This study looks into the suitability MC−adj−nonlinear, a nonlinear adjoint-based approach, precisely rapidly assess performance discrepancies transonic blade section, arising from geometric alterations, building upon previous research. In order practicality illustrate benefits its proficiency precision are gauged against two other methodologies, linear approach (MC−adj−linear) high-fidelity Computational Fluid Dynamics (MC−CFD) method. The MC−adj−nonlinear methodology exhibits impressive generalization capabilities. method offers great balance between time efficiency, since it more precise than MC−adj−linear in both design near-stall conditions, yet requires approximately thirtieth MC−CFD Finally, was utilized conduct fast UQ analyses section at four distinct speeds quantify map. It found that aerodynamic sensitive deviations high low speeds. impact generally detrimental mean efficiency.