Jinjun Wang

Bio: Jinjun Wang is an academic researcher from Beihang University. The author has contributed to research in topics: Vortex & Particle image velocimetry. The author has an hindex of 27, co-authored 161 publications receiving 2809 citations.

Proper orthogonal decomposition analysis of vortex dynamics of a circular cylinder under synthetic jet control

Abstract: Vortex dynamics of a circular cylinder controlled by a synthetic jet positioned at the back stagnation point is experimentally investigated using particle image velocimetry (PIV) technique. The proper orthogonal decomposition (POD) method is adopted to present the variations of the POD energy, mode, coefficient, corresponding dominant frequency, and the reconstructed spanwise vorticity. It is found that the dominant dimensionless control parameters should be the synthetic jet stroke length L0/D, where D is the diameter of the experimental circular cylinder, and the equivalent momentum coefficient Cμ. For the same stroke length L0/D=3.3, the states of the wake vortex shedding are determined by the momentum coefficient. They can be categorized into three groups summarizing all the parameters tested: antisymmetric Karman vortex shedding mode (Cμ≤0.027), vortex synchronization with shedding modes varying between the symmetric and antisymmetric ones (0.061≤Cμ≤0.109), and vortex synchronization with symmetric s...

Circular cylinder vortex-synchronization control with a synthetic jet positioned at the rear stagnation point

Abstract: The flow over a circular cylinder controlled by a two-dimensional synthetic jet positioned at the mean rear stagnation point has been experimentally investigated in a water channel at the cylinder Reynolds number Re = 950. This is an innovative arrangement and the particle-image-velocimetry measurement indicates that it can lead to a novel and interesting phenomenon. The synthetic-jet vortex pairs induced near the exit convect downstream and interact with the vorticity shear layers behind both sides of the cylinder, resulting in the formation of new induced wake vortices. The present vortex synchronization occurs when the excitation frequency of the synthetic jet is between 1.67 and 5.00 times the natural shedding frequency at the dimensionless stroke length 99.5. However, it is suggested that the strength of the synthetic-jet vortex pair plays a more essential role in the occurrence of vortex synchronization than the excitation frequency. In addition, the wake-vortex shedding is converted into a symmetric mode from its original antisymmetric mode. The symmetric shedding mode weakens the interaction between the upper and lower wake vortices, resulting in a decrease in the turbulent kinetic energy produced by them. It also has a significant influence on the global flow field, including the velocity fluctuations, Reynolds stresses and flow topology. However, their distributions are still dominated by the large-scale coherent structures.

Review of zero-net-mass-flux jet and its application in separation flow control

Abstract: Since the zero-net-mass-flux (ZNMF) jet was first used as a laboratory flow control method in 1990’s, it has attracted much attention. The ZNMF jet has unique features such as compact actuator, no requirement for external air supply, complex piping, etc., and becomes a hot topic research subject in fluid mechanics. This review introduces the state of the art in the development of ZNMF jet in the quiescent fluid, the interaction of the ZNMF jet with the cross flow and its application in the separation flow control. The evolution of the vortex ring/pair and the spacial flow structure of the ZNMF in quicent fluid or cross flow are presented, as well as the key parameter effects. At last, the applications of ZNMF jet in the wake control of the circular cylinder, the separation control on the airfoil and the aerodynamic force or moment control on MAV/UAV are presented.

The Structure of Turbulent Shear Flow

Abstract: The Structure of Turbulent Shear Flow By Dr. A. A. Townsend. Pp. xii + 315. 8¾ in. × 5½ in. (Cambridge: At the University Press.) 40s.

Random Data Analysis And Measurement Procedures

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Model Reduction for Flow Analysis and Control

Abstract: Advances in experimental techniques and the ever-increasing fidelity of numerical simulations have led to an abundance of data describing fluid flows. This review discusses a range of techniques for analyzing such data, with the aim of extracting simplified models that capture the essential features of these flows, in order to gain insight into the flow physics, and potentially identify mechanisms for controlling these flows. We review well-developed techniques, such as proper orthogonal decomposition and Galerkin projection, and discuss more recent techniques developed for linear systems, such as balanced truncation and dynamic mode decomposition (DMD). We then discuss some of the methods available for nonlinear systems, with particular attention to the Koopman operator, an infinite-dimensional linear operator that completely characterizes the dynamics of a nonlinear system and provides an extension of DMD to nonlinear systems.

Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control

Abstract: Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This textbook brings together machine learning, engineering mathematics, and mathematical physics to integrate modeling and control of dynamical systems with modern methods in data science. It highlights many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy. Aimed at advanced undergraduate and beginning graduate students in the engineering and physical sciences, the text presents a range of topics and methods from introductory to state of the art.