Schedule of Events

ICVFM 2023:


Prof. John Ekaterinaris, Ph.D.
Editor-in-Chief, Aerospace Science and Technology
Professor of Aerospace Engineering, Embry-Riddle Aeronautical University, USA

Title: Construction of Data Driven Surrogate Reduced Order Models for Unsteady Aerodynamic Problems
Abstract: Data-driven modeling techniques are applied to demonstrate reduced order modeling (ROM) of an oscillating prolate spheroid, a single bladed rotor, supersonic store separation, and store separation from a rotorcraft. Proper orthogonal decomposition (POD), dynamic mode decomposition (DMD), and convolutional neural networks (CNN) were compared for their capability to replicate distributed pressure loads of a pitching up prorate spheroid. Results indicated that POD was the most efficient approach for surrogate model generation. The obtained surrogate ROM was shown to provide high-fidelity predictions for new combinations of reduced frequency and amplitude with a very small error of predicted integrated loads. Furthermore, it was shown that a similar surrogate model could be generated to provide accurate store trajectory modeling under subsonic, transonic, and supersonic conditions. In the second demonstration, a POD-based surrogate model is derived from a series of CFD simulations of isolated rotors in hover and forward flight. The derived surrogate models for hover and forward flight were shown to provide very accurate integrated load predictions. The derived surrogate ROM was leveraged to optimize the twist and taper ratio of the rotor such that the efficiency of the rotor was maximized. For the third demonstration scenario, a POD and CNN surrogate model was derived for fixed-wing based supersonic store separation. Results demonstrated that both models were capable of providing high-fidelity predictions of the store’s distributed loads and subsequent trajectory. For the final demonstration scenario, a POD-based surrogate model was derived for the case of a store launching from a rotorcraft. The surrogate model was derived from three CFD simulations while varying ejection force. This surrogate model was then validated against CFD simulation of a new store ejection force. Results indicated that while the surrogate model struggled to provide detailed predictions of store distributed loads, mean load variations could be modeled well at a massively reduced computational cost. Overall, findings from this study indicate that massive CFD generated data-sets can be efficiently leveraged to create effective and accurate surrogate ROM models capable of being deployed to relevant highly iterative design tasks relevant to rotor aerodynamics store separation and other unsteady aerodynamics problems.

Short Vita: Prof. John Ekaterinaris received his M.Sc. in Mechanical Engineering in 1983 and his Ph.D. from the School of Aerospace Engineering in 1987, both at the Georgia Institute of Technology. Between the years 1987 – 1995, he worked at the Numerical Aerodynamics Simulation (NAS) branch of NASA–Ames Research Center at Moffett Field, CA, and at the same time he was faculty at the Naval Postgraduate Scholl at Monterey, CA. He also worked at RISOE/DTU in Denmark since 1995. In Oct. 2000 he took the Research Director position of the Institute of Applied and Computational Mathematics at FORTH, where he remained until 2005. In Sept. 2005, he joined the faculty of Mechanical and Aerospace Engineering at the University of Patras where he continued caring out funded research with the help of PhD students and postdoctoral fellows. Between 2000 and 2012 taught undergraduate and graduate courses both at the school of Applied Mathematics of the University of Crete and the University of Patras. Funded research included Greek national projects, participation in large European research projects, and basic research funded by the London offices of AFOSR, the ARO with the help of a number of postdoctoral fellows. He joined the faculty of Aerospace Engineering of Embry-Riddle Aeronautical University in August 2012 where he is teaching and performing research until now. His interests are computational mechanics (including aerodynamics, magnetogasdynamics, flow control, flow transition, turbulence research, and flow structure interaction), multi-scale phenomena, stochastic PDE’s, and biomechanics. He is author of over 80 journal papers. He is associate editor for the Journal Progress in Aerospace Sciences and editor in chief for the Journal Aerospace Science and Technology.

Prof. Chaoqun Liu, Director of Center for Numerical Simulation and Modeling, Department of Mathematics, University of Texas at Arlington, USA
Title: Liutex and Third Generation of Vortex Definition and Identification
Abstract: Vortex is intuitively recognized as the rotational/swirling motion of fluids. However, a rigorous mathematical definition for vortex was absent for centuries. Liutex is a new physical quantity to represent fluid rotation or vortex, proposed by Liu et al. at University of Texas at Arlington (UTA) in 2018. Since then, they have published over 40 SCI journal papers including 13 PoF papers, many of them are top cited papers. Three professional books on Liutex have been published by Bentham in 2020, Elsevier in 2020 and Springer in 2021. There are three generations of vortex identification methods in history. In 1858, Helmholtz first defined vortex as vortex tube composed by the so-called vortex filaments. It is classified as the first generation of vortex identification that vortex is defined as vorticity tubes. Science and engineering applications have shown that the correlation between vortex and vorticity is very weak, especially in the near-wall region. During the past four decades, many vortex identification criteria including Q-, Lambda_2, Lambda_Ci methods have been developed, which are classified as the second generation of vortex identification. They are all based on the eigenvalues of the velocity gradient tensor. However, they are all scalars and thus strongly threshold-dependent. In addition, they are all obviously contaminated by stretching and shearing. Liutex, as the third generation of vortex definition and identification, is defined as a vector which uses the real eigenvector of velocity gradient tensor as its direction and twice the local angular velocity of the rigid rotation as its magnitude. The major idea of Liutex is to extract the rigid rotation part from fluid motion to represent vortex. After that, a number of new vortex identification methods have been developed by Liu and the UTA Team including Liutex vector, Liutex vector lines, Liutex tubes, Liutex iso-surface, Liutex-Omega methods, Objective Liutex and, more recently, Liutex Core Line methods. Liutex-Omega method is very popular and Liutex-Core-Line method is unique and threshold-free. The Liutex definition, Principal Coordinate, Principal Decomposition in Principal Coordinate, vorticity RS decomposition, velocity gradient tensor UTA R-NR decomposition, and Principal Decomposition of velocity gradient tensor in Cartesian coordinates, proposed by Liu et al., integrate the Liutex theoretic system and pave the foundation for new fluid kinematics, new vortex science and new turbulence research. A new fluid kinematics has been derived in details and a new fluid dynamics is ongoing. 

Short Vita: Dr. Chaoqun Liu received both BS (1968) and MS (1981) from Tsinghua University, Beijing, China and Ph. D. (1989) from University of Colorado at Denver, USA. He is currently the Tenured and Distinguished Professor and the Director of Center for Numerical Simulation and Modeling at University of Texas at Arlington, Arlington, Texas, USA. He has worked on high order direct numerical simulation (DNS) and large eddy simulation (LES) for flow transition and turbulence for over 30 years since 1990. As PI, he has been awarded by NASA, US Air Force and US Navy with 50 federal research grants of over 5.7 million US dollars in the United States. He was Chairman of the First and Third AFOSR International Conference on DNS/LES in 1997 and 2001. He has published 14 professional books, 129 journal papers and 152 conference papers. He is the founder and major contributor of Liutex and the third generation of vortex definition and identification methods including the Omega, Liutex/Rortex, Modified Liutex-Omega, Liutex-Core-Line methods, RS vorticity decomposition and UTA R-NR velocity gradient tensor decomposition. He is also the founder of the new fluid kinematics which is the foundation for new fluid dynamics.

Prof. Dr. Nikolai Kornev, head of the Chair of Modelling and Simulation, University of Rostock, Faculty of Mechanical Engineering and Marine Technology,Germany
Title: VπLES- hybrid vortex and grid based method for simulation of turbulent flows at high Re numbers
Abstract: The lecture presents development and validation of a new computational fluid dynamics (CFD) method using a combination of grid-free (Vortex Particle Method, VPM) and grid-based (Finite Volume Method) techniques.  The Lagrangian particle method VPM is suitable for modeling of fine and fast flow structures whereas the grid-based techniques like FVM have strong advantages in the modeling of large-scale motions. A fundamental  assumption of this novel approach is the decomposition of any physical quantity into the grid based (large scale) and the fine scale parts, whereas large scales are resolved on the grid and fine scales are represented by particles. Dynamics of large and fine scales is calculated from two coupled transport  equations one of which is solved on the grid whereas the second one utilizes the Lagrangian grid free  VPM.  The method is implemented into OpenFOAM in a parallel mode and can be used for computations of complex flows on arbitrary unstructured grids.  The performance of the method is illustrated for the isotropic homogeneous turbulence, free jets, wall bounded flows and mixing.

Short Vita: Prof. Kornev is the head of the Chair of Modelling and Simulation at the Rostock University since 2010. He studied Fluid Mechanics at the Marine Technical University in St. Petersburg, Russia and received his PhD (Candidate of Science) and habilitation (Doctor of Science) degrees from the same university in, respectively, 1988 and 1998. Since 2001 he is working at the Rostock University dealing with fluid dynamics, turbulence research, Computational Fluid Dynamics, mixing, ship hydromechanics and heat transfer. One of his research topics is the development and application of the computational vortex methods.

Prof. New Tze How, Daniel, Nanyang Technological University, Singapore
Title: Recent insights on vortex rings colliding with solid boundaries and density interfaces
Abstract: As highly fundamental flow entities, vortex rings have always intrigued researchers with their simplicity and elegance, not to mention how they shed light upon more complex flow phenomena.  In particular, interactions between vortex rings and solid boundaries, as well as non-solid density interfaces, have roused much interest among researchers in recent years.  This is in no small part due to how such flow scenarios reveal much about vortex-boundary layer and vortex-vortex interactions, which could in turn lead to formulations of novel concepts that could prove to be useful for mitigating flow control issues.  In this presentation, several vortex ring collision, and hence interaction, scenarios studied recently through experimental and numerical means will be elaborated in terms of their key flow and vortex dynamics.  These scenarios will include those associated with various solid geometries and density interfaces, whereby the surprisingly wide range of interaction outcomes demonstrate just how versatile vortex rings are when it comes down to understanding flow mechanisms that bridge real-world applications.

Short Vita: Dr. Daniel T. H. New graduated from the National University of Singapore (NUS) with a PhD in Mechanical Engineering in 2004.  He worked in Temasek Laboratories, NUS as an Associate Scientist and later as a Research Scientist, before he ventured into combustion research at the University of Texas, Arlington as a post-doctoral researcher.  He joined the University of Liverpool, UK as a Lecturer in 2005 and worked on jet flow control strategies with support from EPSRC UK and The Royal Society.  He joined Nanyang Technological University, Singapore in 2010 where he is currently an Associate Professor and was the Associate Chair (Students) of the School of Mechanical and Aerospace Engineering from 2016 to 2018.  He was also a Visiting Professor at ONERA and Monash University in 2018 and 2019 respectively.  His current research interests include vortex-ring and jet vortex dynamics, Light-field camera-based PIV technique, bluff body flows and supersonic flows, among others.  Together with his collaborators, he has edited three books, published nine book chapters, about a hundred journal papers and more than eighty conference articles.


Alan Jeffrey Giacomin, PhD, PE, PEng, FSOR
Editor-in-Chief, Physics of Fluids (IF 4.980)
Corporate Secretary, AIP Publishing
NSERC Tier 1 Canada Research Chair in Physics of Fluids
Professor of Chemical Engineering
Professor of Mechanical and Materials Engineering
Professor of Physics, Engineering Physics and Astronomy
Queen’s University, Canada

Title: Recent Advances in Polymer Viscoelasticity from General Rigid Bead-Rod Theory
Abstract: One good way to explain the elasticity of a polymeric liquid, is to just consider the orientation distribution of the macromolecules. When exploring how macromolecular architecture affects the elasticity of a polymeric liquid, we find general rigid bead-rod theory to be both versatile and accurate. This theory sculpts macromolecules using beads and rods. Whereas beads represent points of Stokes flow resistances, the rods represent rigid separations. In this way, how the shape of the macromolecule affects its rheological behavior in suspension is determined. Our work shows the recent advances in polymer viscoelasticity using general rigid bead-rod theory, including advances applied on the coronavirus. The coronavirus is always idealized as a spherical capsid with radially protruding spikes. However, histologically, in the tissues of infected patients, capsids in cross section are elliptical, and only sometimes spherical. This capsid ellipticity implies that coronaviruses are oblate or prolate or both. We call this diversity of shapes, pleomorphism. Recently, the rotational diffusivity of the spherical coronavirus in suspension was calculated, from first principles, using general rigid bead-rod theory. We did so by beading the spherical capsid, and then also by replacing each of its bulbous spikes with a single bead. In this paper, we use energy minimization for the spreading of the spikes, charged identically, over the oblate or prolate capsids. We use general rigid bead-rod theory to explore the role of such coronavirus cross-sectional ellipticity on its rotational diffusivity, the transport property around which its cell attachment revolves. We learn that coronavirus ellipticity drastically decreases its rotational diffusivity, be it oblate or prolate.