Atsushi Sekimoto

Associate Professor , Faculty of Environmental and Life Science, Okayama University*Profile is at the time of the award.

2023Inamori Research GrantsScience & Engineering

Research topics
An advanced flow control system based on mathematical and data-driven optimization
Keyword
Summary
Based on a simple turbulence control guideline of using heat, I propose and develop an advanced flow control method based on mathematical optimization theory using the adjoint-based variational method and reinforcement learning. A sensitivity analysis is performed by constructing an adjoint problem for the objective function. The sensitivity is used in the likelihood estimation of Bayesian optimization and the reinforcement learning framework. This enables an efficient automatic search for the globally optimal value of each control parameter. Combined with fast and high-fidelity numerical fluid dynamics techniques using GPUs, I will construct a fluid control system with an eye toward edge computing.

Comment

Turbulent flow phenomena are found in nature and engineering in various situations. For example, approximately half the energy used in the transportation sector is lost as frictional energy between the fluid and the wall. This means that even a reduction in frictional resistance of only a few percent can contribute to improved fuel efficiency and reduced CO2 emissions in automobiles, aircraft, and ships. To achieve this, the nonlinear interaction of vortices of various scales in the vicinity of the wall must be controlled.

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