Towards manipulating three-dimensional bluff-body wakes.

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Shifting wind patterns and gusting in the lee of buildings, ground vehicles or exposed pipelines are examples of turbulent bluff-body wakes. The flow impinges on the front of the body and detaches, or separates, along the sides resulting in reverse flow regions. The recirculating region dynamics are characterized by fluctuating velocity and pressure. The fluctuation amplitude depends on the strength and interaction of moving vortices generated in the recirculating region. These dynamics induce deleterious unsteady forces on the body, increase drag and enhance dispersion downstream. In contrast, bluff-body appendages are used in chemical reactors or combustors to enhance mixing and benefit higher product yield or cleaner combustion. Hence, the ability to manipulate bluff-body wakes to suppress or amplify dynamics is of engineering interest. The proposed research program is a framework for understanding and manipulating wake flows. A fundamental understanding the physics underlying the wake dynamics is to be gained. To this end, the influence of the on-coming flow and body shape on the strength of vortices and their interactions will be characterized. From this baseline, changes to the wake dynamics due to local forcing, introduced through pulsating jets along the obstacle surface, will be investigated. How these manipulations affect the unsteady forces, drag and downstream mixing will be characterized. These investigations are enabled by new techniques developed to represent and model the vortex interactions, based on compact mathematical formulations, predict the response to local forcing and optimize the manipulation parameters for suppressing or amplifying wake fluctuations. Optimization will be based on machine learning principles. These techniques are drawn from mathematics, signal processing and artificial intelligence communities, highlighting the interdisciplinary nature of this research. The knowledge and models developed in the program are applicable to a broad class of turbulent separated flows and thus of fundamental interest to the research community. The developed modelling techniques are relevant to industrial applications. These yield new technologies for flow monitoring and early-detection, which are suited for process control and damage mitigation for inaccessible or remote environments, such as chemical reactors and exposed pipelines. The knowledge gained in wake manipulation is anticipated to be significant for: ground transportation, reducing fuel consumption and increasing high-speed stability; and for chemical reactors or combustors, where mixing controls efficiency, product quality and yield. Compact modelling and machine learning can contribute to the design of autonomous systems. Overall, this program thus offers a context for developing skills and training highly qualified personnel for emerging technologies.