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Multi-objective optimization using evolutionary algorithms: Application to the control of flow past a circular cylinder

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Thesis (46.00Mb)
Advisor
Martinuzzi, Robert John
Morton, Chris R.
Hu, Yaoping
Author
Bingham, Conrad Cole
Committee Member
Ziadé, Paul
Westwick, David T.
Epstein, Marcelo D.
Accessioned
2018-12-03T16:22:06Z
Available
2018-12-03T16:22:06Z
Issued
2018-11-22
Date
2019-06
Classification
Fluid and Plasma
Computer Science
Engineering--Aerospace
Engineering--Mechanical
Robotics
Subject
Vortex Shedding
Machine learning
Evolutionary Algorithms
Fluid Mechanics
Optimization
Multi-Objective
Type
master thesis
Metadata
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Abstract
Modifications to the vortex shedding dynamics from a circular cylinder of diameter D are investigated experimentally in a free surface water channel. The vortex shedding is modified via the placement of a control cylinder of diameter \textit{D}/8 in the vicinity of the main cylinder. A methodology is presented to link changes in the wake dynamics and loading on the main cylinder. The analysis combines Fourier Modal Decomposition, Proper Orthogonal Decomposition, and phase averaging. Based on differences in the wake dynamics, the influence of the control cylinder can be classified according to its placement: (i) in the free stream outside the main cylinder shear layer; (ii) within the main cylinder shear layer; and (iii) in the recirculation region. While fluctuating lift is significantly reduced in all cases, the mean and fluctuating drag are affected differently. A generalized model-free method to optimize parameters for open-loop and closed-loop control in fluid mechanics applications is then presented. A multi-objective evolutionary algorithm (MOEA) is employed to minimize the oscillating lift caused by vortex shedding from the main cylinder. The control cylinder is prescribed a position as well as a periodic motion in two dimensions. The MOEA efficiently handles the larger optimization parameter space. The first objective of the algorithm is to minimize the fluctuating force coefficient $C_{L_{RMS}}$, while the second objective is to minimize of the actuation power required to drive the control cylinder. The final solution suppresses $C_{L_{RMS}}$ by over 90\% using near-zero actuation power. Further, the MOEA automatically provides a sensitivity study as to the influence of the different parameters and also in which spatial area the greatest influence is expressed.
Faculty
Schulich School of Engineering
Institution
University of Calgary
Doi
http://dx.doi.org/10.11575/PRISM/34666
Uri
http://hdl.handle.net/1880/109214
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