Time:Thursday, Nov 28, 2019
Venue: Morning Session at A310, Afternoon Session at A706
Time |
Topic/Title |
Speaker |
Chair |
09:00~10:20 |
Machine-Learning Based Active Flow Control |
Hui Tang Associate Professor The Hong Kong Polytechnic University |
Prof. Weiwei Zhang |
coffee break |
10:30~11:50 |
Machine-Learningfor Turbulence Modeling |
Richard P. Dwight Professor Delft University of Technology |
14:30~15:00 |
Group Research Introduction Aerodynamics and Fluid-Structure Interaction |
Weiwei Zhang Professor Vice Dean of School of Aeronautics Northwestern Polytechnical University |
Prof. Chen Gang |
15:00~15:30 |
ANew Evolutionary Optimization Framework Based on Model Prediction for Aerodynamic Design |
Xiaojing Wu Lecturer School of Aerospace Science and Technology Xidian University |
15:30~16:00 |
ANovel Spatial-Temporal Prediction Method for Unsteady Wake Flows Based on Hybrid Deep Neural Network |
Renkun Han Doctoral student Xi'an Jiaotong University |
16:00~16:10 |
coffee break |
16:10~16:40 |
Study on High Reynolds Number Turbulence Modeling Based on Machine Learning methods |
Linyang Zhu Doctoral student Northwestern Polytechnical University |
Associate Prof. Li Chunna |
16:40~17:10 |
Airfoil Dynamic Stall Aerodynamic Prediction Method Based on Data Fusion Model |
Xu Wang Doctoral student Northwestern Polytechnical University |
17:10~17:40 |
Adaptive Control of The Transonic Buffet Flow |
Kai Ren Doctoral student Northwestern Polytechnical University |
Invited lecture one
Title:Machine-Learning Based Active Flow Control.
Lecturer:Dr. Hui TANG, the Hong Kong Polytechnic University
Abstract:
In this talk, some recent applications of machine learning (ML) in active flow control (AFC) will be introduced. Here the term AFC means that the control is realized by injecting a small amount of energy into existing flow systems. These applications contain generic-programming (GP) method in vortex-induced vibration (VIV) control, deep reinforcement learning (DRL) for eliminating the velocity deficit, and DRL for finding best drag reduction strategies. Through these ML based AFC studies, some new and unexpected control strategies have been revealed.
Biography:
Dr. Hui Tang is an Associate Professor, Director of Research Center for Fluid-Structure Interactions, and Associate Head of Department of Mechanical Engineering, The Hong Kong Polytechnic University. He received his BEng and MEng degrees from Tsinghua University, and his PhD degree in Aeronautical Engineering from University of Manchester. Prior to joining HK PolyU, he worked in Nanyang Technological University, and University of Michigan - Ann Arbor. His research interests include aerodynamics/hydrodynamics, active flow control, fluid-structure interaction, and heat and mass transfer.
Invited lecture two
Title:Data-driven turbulence modelling with Machine-learning.
Lecturer:Prof Richard P. Dwight, Delft University of technology
Abstract:
Several groups worldwide are investigating numerical and statistical methods for deriving turbulence models directly from this data-corpus - efforts which generally involve some form of machine-learning. We will give an overview of this nascent field, and the key results and observations obtained so far. We discuss our own work in the area, and finally application of our techniques to shape-optimization and to wind-farm wake modelling.
Biography:
Professor Richard P. Dwight received his Ph.D. from the University of Manchester in 2006, worked as an associate professor in the Department of aerodynamics at the school of Aerospace Engineering, Delft University of technology since 2009, and as a visiting professor at the Centrum voor Wiskunde en Informatica (CWI) in The Netherlands since 2017. Professor Richard P. Dwight has made great achievements in computational fluid dynamics, machine learning, aerodynamic design optimization, surrogate-based optimization method, adjoint method, uncertain optimization method and other fields.
This seminar is sponsored by the overseas Expertise Introduction Center for Discipline Innovation on Complex Flow and Its Control (the 111 Center), School of Aeronautics.
