CAREER: Controlling Nonlinear Flow Interactions to Suppress Transition to Turbulence

In a wide range of engineering systems (e.g., airplanes, cars, pipelines, and wind turbines), delaying transition of flow from laminar to turbulent can lead to reduced drag and improved efficiency. The research will study complex (nonlinear) flow interactions that will suppress laminar transition to turbulence and achieve drag reduction. Computer simulations of a channel flow incorporating only wall-based sensing and actuation of the flow will be used to demonstrate the delays in transition. The effort closely integrates education and outreach with foundational research that enhances interdisciplinary fluid dynamics, systems modeling, and control theory. The multidisciplinary work will be disseminated to the fluids, dynamical systems, and controls communities to enhance communication between these disciplines. Newly developed courses and undergraduate research initiatives will promote higher education in engineering. A new outreach program will help elementary school teachers introduce engineering into K-6 classrooms.

Nonlinear flow interactions are at the heart of the transition process. Yet, previous studies on transition control have focused on the pre-nonlinear interaction stage and have not exploited a complete description of these interactions for controller synthesis. The proposed effort hinges on the fact that nonlinear flow interactions are dynamically constrained by the Navier-Stokes equations, both at a given time instant and across time instances. Mathematically, these physical constraints can be expressed as a set of integral quadratic constraints, providing a convenient framework for modeling nonlinear flow interactions for transition control synthesis. This project seeks to determine how such representations of nonlinear flow interactions can be exploited to suppress transition within direct numerical simulations of a channel flow, using only wall-based sensing and actuation. The outcomes of this project will provide guidance on how to formally account for nonlinear flow interactions to perform flow control, sensor selection, and model-order reduction in a manner that can be generalized to many complex flow configurations.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.