Reduced-Order Modeling for Optimization and Control of Complex Flows.

摘要

The primary objectives of this research were to develop reduced- order modeling methodologies for control and optimization applications. This was achieved through three specific research goals. First of all, we focused on improving the accuracy of reduced-order model simulations by including closure terms (that can be implemented in practical applications). Secondly, we used sensitivity analysis to improve the accuracy of models over ranges of parameters. Finally, we developed a better methodology for using reduced-order modeling methods for feedback control calculations. We made significant advances in each of these three areas.