RUI: TRANSPORT OF INERTIAL PARTICLES IN TIME-DEPENDENT AND STOCHASTIC FLOWS
National Science Foundation
MONTCLAIR STATE UNIVERSITY STUDENT GOVERNMENT
In this project computer models of fluid flows and mathematical models of transport and control will be combined to find optimal control strategies for autonomous ocean vehicles, which will be modeled both as inertial and non-inertial objects. Laboratory experiments on precisely tuned flows and magnetically controlled particles will be used both to validate and guide the investigations. The goal is to use experimental and computed flow fields to identify critical transport features and integrate these features into control algorithms that optimally position particles. This project will improve transport control capabilities by developing models for transport and control of inertial objects in canonical flows subject to time-dependent and stochastic perturbations. Flow data will be generated by the numerical simulation of gyre flows, jets, and boundary currents. Inertial particles will be modeled directly using a state-of-the-art interfacial multi-phase numerical code. Laboratory experiments have been designed so that similar flows can be generated by reconfiguring the geometric forcing devices. Through high resolution particle imaging velocimetry (PIV) and particle tracking, experimental flow fields and their transport properties will be correlated with those of the associated model flows. Additionally, control strategies will be implemented using ferromagnetic tracer particles and magnetic pulses. To gain insight into the flow transport properties, flow and tracer data will be analyzed using a variety of geometric and probabilistic methods including finite-time Lyapunov exponents, inertial particle models, almost invariant sets, and finite-time coherent sets. These techniques will directly result in the ability to identify loitering regions and their boundaries and to determine maximal transport rates. This information will be leveraged to develop simple predictive models of transport and trajectory control that can be efficiently adapted to emergent applications.
Country: UNITED STATES
Award Notice Date: 04-Jul-2014
Project Start Date: 15-Jul-2014
Budget Start Date:
Project End Date: 30-Jun-2017
Budget End Date:
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National Science Foundation
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