Research Projects

This page highlights current and past research and engineering projects.

Low-Order Model for Transonic Flutter

In recent years there has been a push for novel commercial transport aircraft concepts which feature large wing spans to increase their fuel effciency. This increase in wing span, however, leads to more flexible wings and therefore more aeroelastic problems. Furthermore, these aircraft fly in the transonic regime, a flow condition for which it is difficult to predict flutter accurately.
To include transonic flutter constraints in the conceptual design phase, we are developing a physical low-order model for two-dimensional unsteady transonic flow.

Opgenoord, M. M. J., Drela, M., and Willcox, K. E., Towards a Low-Order Model for Transonic Flutter Prediction, 8th AIAA Theoretical Fluid Mechanics Conference, Denver, CO, Paper No. AIAA-2017-4340 , June 5–9, 2017.

Design Methodology for Additive Manufacturing

Additive manufacturing allows for unparalleled design freedom, but if you have all the freedom in the world, how do you go about designing a product? And while this design freedom is massive, it is not unlimited, as manufacturing constraints inherent to additive manufacturing still need to be taken into account. We investigate the optimization of lattice structures to be manufactured using 3D printing. Our optimization method leverages techniques from the CFD mesh generation community, and the treatment of manufacturing constraints is inherent to the optimization.

Uncertainty Budgeting in Aircraft Design

Quantification and management of uncertainty are critical in the design of engineering systems, especially in the early stages of conceptual design. We developed a method for defining budgets on the acceptable levels of uncertainty in design quantities of interest, such as the allowable risk in not meeting a critical design constraint and the allowable deviation in a system performance metric. A sensitivity-based method analyzes the effects of design decisions on satisfying those budgets, and a multi-objective optimization formulation permits the designer to explore the tradespace of uncertainty reduction activities while also accounting for a cost budget.

Opgenoord, M. M. J. , Allaire, D. L. and Willcox, K. E., Variance-Based Sensitivity Analysis to Support Simulation-based Design under Uncertainty, ASME Journal of Mechanical Design, Vol. 138, No. 11, pp. 111410-1 - 111410-12, 2016.

Opgenoord, M. and Willcox, K., Sensitivity Analysis Methods for Uncertainty Budgeting in System Design, AIAA Journal, Volume 54, Issue 10, pp. 3134-3148, 2016.