Erwin R. Gowree

Bio: Erwin R. Gowree is an academic researcher from University of Toulouse. The author has contributed to research in topics: Boundary layer & Turbulence. The author has an hindex of 5, co-authored 20 publications receiving 79 citations. Previous affiliations of Erwin R. Gowree include University of London & City University London.

Destabilisation and modification of Tollmien-Schlichting disturbances by a three dimensional surface indentation

Abstract: We consider the influence of a smooth three-dimensional (3-D) indentation on the instability of an incompressible boundary layer by linear and nonlinear analyses. The numerical work was complemented by an experimental study to investigate indentations of approximately δ99 and δ99 width at depths of 45%, 52% and 60% of δ99 where δ99 indicates 99% boundary layer thickness. For these indentations a separation bubble confined within the indentation arises. Upstream of the indentation, spanwise-uniform Tollmien-Schlichting (TS) waves are assumed to exist, with the objective to investigate how the 3-D surface indentation modifies the 2-D TS disturbance. Numerical corroboration against experimental data reveals good quantitative agreement. Comparing the structure of the 3-D separation bubble to that created by a purely 2-D indentation, there are a number of topological changes particularly in the case of the widest indentation; more rapid amplification and modification of the upstream TS waves along the symmetry plane of the indentation is observed. For the shortest indentations, beyond a certain depth there are then no distinct topological changes of the separation bubbles and hence on flow instability. The destabilising mechanism is found to be due to the confined separation bubble and is attributed to the inflectional instability of the separated shear layer. Finally for the widest width indentation investigated , results of the linear analysis are compared with direct numerical simulations. A comparison with the traditional criteria of using -factors to assess instability of properly 3-D disturbances reveals that a general indication of flow destabilisation and development of strongly nonlinear behaviour is indicated as values are attained. However -factors, based on linear models, can only be used to provide indications and severity of the destabilisation, since the process of disturbance breakdown to turbulence is inherently nonlinear and dependent on the magnitude and scope of the initial forcing.

Experimental Aerodynamics: An Introductory Guide

Abstract: This book presents experimental techniques in the field of aerodynamics, a discipline that is essential in numerous areas, such as the design of aerial and ground vehicles and engines, the production of energy, and understanding the wind resistance of buildings. Aerodynamics is not only concerned with improving the performance and comfort of vehicles, but also with reducing their environmental impact. The book provides updated information on the experimental and technical methods used by aerodynamicists, engineers and researchers. It describes the various types of wind tunnels – from subsonic to hypersonic – as well as the problems posed by their design and operation. The book also focuses on metrology, which has allowed us to gain a detailed understanding of the local properties of flows, and examines current developments toward creating a methodology combining experiments and numerical simulations: the computer-assisted wind tunnel. Lastly, it offers an overview of experimental aerodynamics based on a prospective vision of the discipline, and discusses potential futures challenges. The book can be used as a textbook for graduate courses in aerodynamics, typically offered to students of aerospace and mechanical engineering programs, and as a learning tool for professionals and engineers in the fields of aerodynamics, aeronautics and astronautics automobile.

Influence of Attachment Line Flow on Form Drag

Abstract: Numerical analysis conducted using Callisto, which is Airbus’s three-dimensional momentum integral boundary layer code coupled with Green’s lag-entrainment method has shown that there might be a small but worthwhile form drag reduction through attachment line control, up to about 0:4

Vortices enable the complex aerobatics of peregrine falcons

Abstract: The peregrine falcon (Falco peregrinus) is known for its extremely high speeds during hunting dives or stoop. Here we demonstrate that the superior manoeuvrability of peregrine falcons during stoop is attributed to vortex-dominated flow promoted by their morphology, in the M-shape configuration adopted towards the end of dive. Both experiments and simulations on life-size models, derived from field observations, revealed the presence of vortices emanating from the frontal and dorsal region due to a strong spanwise flow promoted by the forward sweep of the radiale. These vortices enhance mixing for flow reattachment towards the tail. The stronger wing and tail vortices provide extra aerodynamic forces through vortex-induced lift for pitch and roll control. A vortex pair with a sense of rotation opposite to that from conventional planar wings interacts with the main wings vortex to reduce induced drag, which would otherwise decelerate the bird significantly during pull-out. These findings could help in improving aircraft performance and wing suits for human flights.

Boundary Layer Theory

Abstract: The boundary layer equations for plane, incompressible, and steady flow are $$\matrix{ {u{{\partial u} \over {\partial x}} + v{{\partial u} \over {\partial y}} = - {1 \over \varrho }{{\partial p} \over {\partial x}} + v{{{\partial ^2}u} \over {\partial {y^2}}},} \cr {0 = {{\partial p} \over {\partial y}},} \cr {{{\partial u} \over {\partial x}} + {{\partial v} \over {\partial y}} = 0.} \cr }$$

Robust active flow control over a range of Reynolds numbers using an artificial neural network trained through deep reinforcement learning

Abstract: This paper focuses on the active flow control of a computational fluid dynamics simulation over a range of Reynolds numbers using deep reinforcement learning (DRL). More precisely, the proximal policy optimization (PPO) method is used to control the mass flow rate of four synthetic jets symmetrically located on the upper and lower sides of a cylinder immersed in a two-dimensional flow domain. The learning environment supports four flow configurations with Reynolds numbers 100, 200, 300, and 400, respectively. A new smoothing interpolation function is proposed to help the PPO algorithm learn to set continuous actions, which is of great importance to effectively suppress problematic jumps in lift and allow a better convergence for the training process. It is shown that the DRL controller is able to significantly reduce the lift and drag fluctuations and actively reduce the drag by ∼5.7%, 21.6%, 32.7%, and 38.7%, at Re = 100, 200, 300, and 400, respectively. More importantly, it can also effectively reduce drag for any previously unseen value of the Reynolds number between 60 and 400. This highlights the generalization ability of deep neural networks and is an important milestone toward the development of practical applications of DRL to active flow control.

Spectral/hp element methods: recent developments, applications, and perspectives

Abstract: The spectral/hp element method combines the geometric flexibility of the classical h-type finite element technique with the desirable numerical properties of spectral methods, employing high-degree piecewise polynomial basis functions on coarse finite element-type meshes. The spatial approximation is based upon orthogonal polynomials, such as Legendre or Chebychev polynomials, modified to accommodate a C0 - continuous expansion. Computationally and theoretically, by increasing the polynomial order p, high-precision solutions and fast convergence can be obtained and, in particular, under certain regularity assumptions an exponential reduction in approximation error between numerical and exact solutions can be achieved. This method has now been applied in many simulation studies of both fundamental and practical engineering flows. This paper briefly describes the formulation of the spectral/hp element method and provides an overview of its application to computational fluid dynamics. In particular, it focuses on the use of the spectral/hp element method in transitional flows and ocean engineering. Finally, some of the major challenges to be overcome in order to use the spectral/hp element method in more complex science and engineering applications are discussed.

Robust active flow control over a range of Reynolds numbers using an artificial neural network trained through deep reinforcement learning.

Abstract: This paper focuses on the active flow control of a computational fluid dynamics simulation over a range of Reynolds numbers using deep reinforcement learning (DRL). More precisely, the proximal policy optimization (PPO) method is used to control the mass flow rate of four synthetic jets symmetrically located on the upper and lower sides of a cylinder immersed in a two-dimensional flow domain. The learning environment supports four flow configurations with Reynolds numbers 100, 200, 300 and 400, respectively. A new smoothing interpolation function is proposed to help the PPO algorithm to learn to set continuous actions, which is of great importance to effectively suppress problematic jumps in lift and allow a better convergence for the training process. It is shown that the DRL controller is able to significantly reduce the lift and drag fluctuations and to actively reduce the drag by approximately 5.7%, 21.6%, 32.7%, and 38.7%, at $Re$=100, 200, 300, and 400 respectively. More importantly, it can also effectively reduce drag for any previously unseen value of the Reynolds number between 60 and 400. This highlights the generalization ability of deep neural networks and is an important milestone to active flow control.