A mini-course on Particle Image Velocimetry

普渡大学Steven T. Wereley教授的PIV短期课程

资料和参考教材:
Particle Image VelocimetryA Practical Guide
Authors: Raffel, M., Willert, C.E., Wereley, S., Kompenhans, J.
http://www.springer.com/gp/book/9783540723073?cm_mmc=sgw-_-ps-_-book-_-978-3-540-72307-3

时间:下午4点 - 6点,Nov. 9, 10, 13 and 14.
地点:TBA
联系人:许超

Thu - Lecture 1 (two hours)

  1. Introduction
  2. Tracer particles, illumination
  3. Particle imaging

Fri - Lecture 2 (two hours) Fri

  1. Statistics of PIV
  2. Recording techniques

Mon - Lecture 3 (two hours)

  1. Eval Techniques I, corr, peak fitting
  2. Eval Techniques II, corr tracking, padding
  3. Eval Techniques III, corr avg, CDIC

Tue - Lecture 4 (two hours)

  1. Image processing, particle ident, part tracking
  2. Data validation, correction, statistics
  3. Resolution, uncertainty
  4. Advanced Topics, stereo, holo, temp

Bio:

Professor Wereley completed his masters and doctoral research at Northwestern University. He joined the Purdue University faculty in August of 1999 after a two-year postdoctoral appointment at the University of California Santa Barbara. During his time at UCSB he worked with a group developing, patenting, and licensing to TSI, Inc., the micro-Particle Image Velocimetry technique. His current research interests include opto/electrokinetics, investigating microscopic biological flows, harnessing diffusion for sensing applications, and developing new ways of measuring flows at the smallest length scales. Professor Wereley is the co-author of Fundamentals and Applications of Microfluidics (Artech House, 2002 and 2006) and Particle Image Velocimetry: A Practical Guide (Springer, 2007). He is on the editorial board of Experiments in Fluids and is an Associate Editor of Springer’s Microfluidics and Nanofluidics. Professor Wereley has edited Springer’s recent Encyclopedia of Microfluidics and Nanofluidics and Kluwer’s BioMEMS and Biomedical Nanotechnology.

Microscopic flow visualization: making the world on your microchip visible

Steve Wereley, Professor of Mechanical Engineering
Purdue University

时间:4 p.m., Nov. 6, 2017(周一)
地点:TBA
联系人:许超,cxu@zju.edu.cn

Abstract:
Fluid flow in the micro and nanoscale world of Lab-on-Chip devices can behave very unusually.  It is essential to have precise experimental tools to see what is happening at these very small length scales. Unfortunately these small length scales also prove challenging for experimental tools. This seminar will explore the tools available for viewing (microscale flow visualization) and measuring (micro-PIV) such small flows.  Numerous examples will be presented in which microscale flows are visualized and measured.  These examples range from flows in Lab-on-Chip devices, in and around mechanical devices, and around biological organisms. In many situations 2D planar measurements are sufficient but in some situations, 3D measurements are required. Several ways of measuring flows in 3D will be discussed.  Furthermore, beyond the fluid’s velocity field, other flow quantities of interest are often needed, such as temperature and pressure.  Methods for imaging or measuring these important scalar fields will also be discussed.

Bio:

Professor Wereley completed his masters and doctoral research at Northwestern University. He joined the Purdue University faculty in August of 1999 after a two-year postdoctoral appointment at the University of California Santa Barbara. During his time at UCSB he worked with a group developing, patenting, and licensing to TSI, Inc., the micro-Particle Image Velocimetry technique. His current research interests include opto/electrokinetics, investigating microscopic biological flows, harnessing diffusion for sensing applications, and developing new ways of measuring flows at the smallest length scales. Professor Wereley is the co-author of Fundamentals and Applications of Microfluidics (Artech House, 2002 and 2006) and Particle Image Velocimetry: A Practical Guide (Springer, 2007). He is on the editorial board of Experiments in Fluids and is an Associate Editor of Springer’s Microfluidics and Nanofluidics. Professor Wereley has edited Springer’s recent Encyclopedia of Microfluidics and Nanofluidics and Kluwer’s BioMEMS and Biomedical Nanotechnology.

ZMART won the IARC First Prize again in 2017

ZJU's aerial robotics team (ZMART) won the First Prize of the International Aerial Robotics Competition (IARC) this year again in 2017. ZMART received the First Prize as well in 2016, and its performance in 2016 was considered the target level for all IARC teams in 2016 to beat in 2017.

Quota from the last sentence of the 2016 IARC Technology Readiness Level: The team demonstrating this level of performance in 2016 was Zhejiang University. .... Zhejiang University has currently set the performance level for all IARC teams to beat in 2017.

According to Robert Michaelson (the creator of the IARC from Georgia Tech), ZMART created the best record of IARC Mission 7 since it was released in 2014. ZMART was successfully to build a fully autonomous drone (shepherd) to drive three ground vehicles (sheep) back the safety region (sheepfold). Comparing to last year, ZMART's drone showed a great improvement in broad region vision and perception capability, machine decision, etc.

ZMART featured in media, including,

Conferences upcoming!

  • The American Control Conference, Philadelphia, PA, USA | July 10-12, 2019
  • The American Control Conference, Denver, CO, USA | July 1-3, 2020
  • The American Control Conference, Milwaukee, WI, USA | June 27-29, 2018
  • AAAI Conference on Artificial Intelligence (AAAI-18), New Orleans, Lousiana, USA |  February 2 - 7, 2018
  • The 10th International Conference on Machine Learning and Computing (ICMLC 2018), Macau, China | February 26 - 28, 2018
  • The 56th IEEE Conference on Decision and Control Melbourne, Australia | December 12-15, 2017
  • Conference on Neural Information Processing Systems (NIPS), Long Beach Convention Center, Long Beach | December 04 - 09, 2017
  • IEEE/RSJ International Conference onIntelligent Robots and Systems, Vancouver, BC, Canada | September 24–28, 2017
  • IEEE International Conference on Robotics and Automation, Brisbane, Australia | May 21 - 25, 2018

Xu Chosen to Attend "China-America Frontiers of Engineering" Symposium

Chao Xu (许超), TRUTH Associate Professor of control science & engineering at Zhejiang University, was recently selected to attend the 2017 China-America Frontiers of Engineering (CAFOE) symposium held on June 22 - 24 in Shanghai.

Sixty of the most promising engineers under the age of 45 from China and the United States met for an intensive 2-1/2 day symposium on developments at the cutting edge of engineering technology in four areas: Intelligent Transportation, Electrochemical Energy Storage, Synthetic Biology, and Robots Everywhere.

Xu was invited to deliver a plenary talk during the CAFOE 2017 on Intelligent Robotic Locomotion: From Dynamic Walking to Autonomous Flight.

The event is intended to facilitate international and cross-disciplinary research collaboration, promote the transfer of new techniques and approaches across disparate engineering fields, and encourage the creation of a transpacific network of world-class engineers. CAFOE is carried out in cooperation with the Chinese Academy of Engineering.

About the Chinese Academy of Engineering(中国工程院)

The Academy is a national and independent organization composed of elected members with the highest honor in the community of engineering and technological sciences of the nation. Its missions are to initiate and conduct strategic studies, provide consultancy services for decision-making of nation’s key issues in engineering and technological sciences and promote the development of the undertaking of engineering and technological sciences in China and devote itself to the benefit and welfare of the society.

中国工程院(Chinese Academy of Engineering)于1994年6月3日在北京成立,是中国工程技术界最高荣誉性、咨询性学术机构,国务院直属事业单位。

About the NAE(美国工程院)

The National Academy of Engineering is a private, independent, nonprofit institution that provides engineering leadership in service to the nation. The mission of the Academy is to advance the well being of the nation by promoting a vibrant engineering profession and by marshaling the expertise and insights of eminent engineers to provide independent advice to the federal government on matters involving engineering and technology. The NAE is part of the National Academies of Sciences, Engineering, and Medicine.

诺贝尔物理学奖得主带你走进量子流体神秘世界!

What can we do with a quantum liquid?

  • 时 间:2017年6月29日(星期四)14:30 - 15:30
  • 地 点:玉泉校区邵逸夫科学馆 117报告厅

Quantum liquids are physical systems which display the effects not only of quantum mechanics but also those of quantum statistics that is of the characteristic indistinguishability of elementary particles. The most spectacular manifestations of quantum statistics are the phenomenon of Bose-Einstein condensation and the closely related one of Cooper pairing; in both cases a finite fraction of all the particles in the system are forced to all do exactly the same thing at the same time, and as a result effects which would normally be obscured by thermal noise may become visible, sometimes spectacularly so.

安东尼·莱格特:英国物理学家,美国科学院院士、美国物理学会会士、英国皇家学会会士。1938年生于伦敦,相继于英国牛津百里奥学院和牛津默顿学院获得文学和物理学学士学位,1964年获牛津大学物理学博士学位,现为美国伊利诺伊大学物理系教授。莱格特教授是国际学术界公认的量子物理学领袖,由于他在超流体理论研究中做出的原创性工作被瑞典皇家科学院授予2003年诺贝尔物理学奖。

媒体报道

Multi-model Predictive Control: Controller formulation and Application to Medical Oxygen Concentrators

Multi-model Predictive Control: Controller formulation and Application to Medical Oxygen Concentrators

Speaker: Mayuresh V. Kothare, PhD, R. L. McCann Professor, Chairman | Department of Chemical and Biomolecular Engineering, Lehigh University

Lecture room: CSC-304 浙江大学玉泉校区智能系统与控制研究所(CSC)304教室

Time: 14:00, June 12 (Monday), 2017

Abstract:

A Multi-Model Predictive Control (M-MPC) algorithm is developed for a novel Rapid Pressure Swing Adsorption (RSPSA) oxygen concentrator system. The RPSA uses a zeolite material to purify oxygen from ambient feed air, and is designed to produce 90% oxygen for medicinal therapies. In previous work, a standard linear MPC algorithm was implemented on the RPSA which rejects disturbances and improves set point tracking in the 90% operating range, but a RPSA can produce a wide range of oxygen purities. The single linear model MPC algorithm is unable to  provide the ability to transition the purity between vastly different values. The M-MPC algorithm uses a collection of linear models each of which corresponds to a different oxygen purity range. The linear models are identified around different operating points, and use Pseudo-Random Binary Signal (PRBS) simulation data in the identification process. With this improved control algorithm, the RPSA can produce a range of oxygen purities, and reject typical RPSA process disturbances. M-MPC switching rules, operating region boundary considerations and set point tracking cases are presented and discussed. General concepts on M-MPC will be presented and ideas on stability analysis will be discussed.

Biosketch:

Dr. M. V. Kothare is currently the Chairman of the Department of Chemical and Biomolecular Engineering and R. L. McCann Professor at Lehigh University. He holds an appointment in Bioengineering at Lehigh University and is a Visiting Professor of Biomedical Engineering at Johns Hopkins School of Medicine. He received his B.Tech. in Chemical Engineering from the Indian Institute of Technology (IIT), Bombay in 1991 and MS/PhD degrees in Chemical Engineering from the California Institute of  Technology in 1995 and 1997. He has held a postdoctoral position at Mobil Oil Corporation and various visiting positions at City College New York, Purdue University, ETH Zurich and East China U. of Science and Technology (ECUST). His interdisciplinary areas of interest span the problems of constrained and optimal predictive control theory, robustness analysis, MEMS and microchemical systems, control of microsystems, embedded control of biomedical systems, neuroengineering and closed-loop neuroprosthetic systems. Kothare is recipient of the Institute Silver Medal from IIT Bombay for ranking first in Chemical Engineering, the Ted Peterson Student Paper Award (2000) and the Outstanding Young Researcher Award (2007) (under 40 years) from the Computing and Systems Technology division of the AIChE for his contributions to the literature of computing in engineering. He has received the US National Science Foundation CAREER award (2002), the Robinson award and Rossin and Hook Professorships at Lehigh University. He was a selected attendee (one of 82 engineers, ages 30-45) at the 2008 Frontiers of Engineering symposium of the US National Academy of Engineering. His interdisciplinary service activities have involved associate editor appointments with AUTOMATICA and the IEEE Transactions on Automatic Control, as well as guest editorial appointments for Journal of Process Control and the IFAC sponsored conference DYCOPS in 2010. In 2011, he was appointed Deputy Editor-in-Chief of IFAC PapersOnLine, an on-line archive of all peer-reviewed conference proceedings sponsored by the International Federation of Automatic Control (IFAC). In 2012, Kothare served as Chair of the CAST division of the AIChE. In 2012, he was elected Fellow of IEEE.

What Machine Learning can do for Science and Engineering?

What Machine Learning can do for Science and Engineering?

2 pm, Tuesday, May 23, 2017; Room 304, Institute for Cyber-systems & Control, Zhejiang University(浙江大学玉泉校区智能系统与控制研究所304教室,联系人:许超,13706711953)

Speaker: Guang Lin(林光), PhD

Associate Professor, Department of Mathematics & School of Mechanical Engineering Purdue University

Web: https://www.math.purdue.edu/~lin491/

Machine learning has attracted a lot attention recently. In this talk, I will use several case studies to demonstrate what machine learning can do for Science and Engineering.

It is observed that birds, bats, insects, and fish can routinely harness unsteady fluid phenomena to improve their propulsive efficiency, maximize thrust and lift, and increase maneuverability. In this talk, I will demonstrate how to use machine learning strategy to characterize the time-varying fluid flows with very limited sensor information in modern engineering, for instance, biological propulsion and bio-inspired engineering design.

In addition, I will also present how to use machine learning techniques to employ very limited satellite data or sensor information to improve the climate model predictive capability or identify the contaminant source locations. Particularly, an adaptive importance sampling technique will be introduced to utilize machine learning method to capture multimodal distribution using a mixture of Gaussian distribution.

Ebola disease has been taking thousands of people’s life. It is critical to develop effective strategy to prevent Ebola’s outbreak. I will present how we can use machine learning techniques to develop more accurate Ebola model using limited data. In addition, we employ this accurate Ebola model to develop and test several different strategies to studies its effectiveness in preventing Ebola’s outbreak.

-----------------

Guang Lin got his bachelor in Zhejiang university in 1997 and PhD from division of applied mathematics at Brown university in 2007. Now he is an associate professor in both department of mathematics and school of mechanical engineering at Purdue University.
Guang Lin received NSF faculty early career development award in recognition of his work on uncertainty quantification and big data analysis in smart grid and other complex interconnected systems. Guang Lin has developed advanced optimization algorithms to calibrate complex global and regional climate models. For this work, he received a Ronald L. Brodzinski Award for Early Career Exception Achievement in 2012. Guang Lin also received 2010ASCR Leadership Computing Challenge (ALCC) award in recognition of his work in analyzing big climate data using extreme-scale supercomputers. Guang Lin has also received Outstanding Performance Award at Pacific Northwest National Laboratory in 2010, and Ostrach Fellowship at Brown University in Fall 2005.

射频脉冲的优化控制方法及其在核磁共振中的应用

题目: 射频脉冲的优化控制方法及其在核磁共振中的应用 (The Radio-Frequency Pulse Optimization Methods: Fundamentals and Applications in Magnetic Resonance)

智能系统与控制研究所223教室,2017年3月29日上午10点

摘要: 射频脉冲可实现自旋体系的精确操控,在核磁共振信号探测中起到关键作用,因此脉冲设计一直是核磁共振领域最活跃的研究前沿之一。报告将从磁共振射频脉冲的基本操控原理及其数学模型出发,介绍基于自旋动力学和优化控制理论的最优脉冲设计方法,通过实例展示优化脉冲在相关领域的应用前景,包括高性能的磁共振动力学模拟平台开发、不依赖于造影剂的对比度增强成像序列、用于伪纯态制备的协作脉冲序列和新型代谢物浓度定量脉冲序列等。

报告人简介: 杨晓冬,男,博士学位。中科院苏州医工所研究员,医学影像技术研究室主任,中科院百人计划获得者,江苏省 “333高层次人才培养工程”中青年科技带头人,江苏省 “高层次创新创业人才”。2005年至2011年,曾先后赴澳大利亚怀特医学国家研究中心和德国慕尼黑工业大学任访问学者和客座研究员。主要从事医学影像技术和系统研发,相关成果在Biochimie, PLOS one, App. Mag. Res.等国际知名SCI/EI学术期刊上发表40余篇论文,引用500余次,拥有专利和软件著作权15项,担任J. Mag. Reson.,Mag. Reson. Imaging等知名国际学术期刊审稿人、国家自然科学基金委评审委员、科技部评审专家。主持和参加了各类应用研究和工程化研究项目21项,完成企业委托项目4项。承担10余项国家级和省部级以上科研项目。培养研究生4名,在培硕士/博士研究生6名。

Teo's Lectures on Optimal Control Problems

  • 14:05 PM, March 29, Lecture 1. Optimal Control in Real-world Practical Applications
  • 15:05 PM, March 29, Lecture 2. Optimal Control Problems with Stopping Constraints
  • Classroom 108: Teaching Building - 7, Yuquan Campus, Zhejiang University
  • 浙江大学玉泉校区教七教学楼-108教室,3月29日周三时间下午2:05

Speaker: Kok Lay Teo, John Curtin Distinguished Professor, Curtin University

Professor Kok Lay Teo received his Ph.D. degree in Electrical Engineering from the University of Ottawa in Canada. Professor Teo was affiliated with University of New South Wales, Australia, National University of Singapore and University of Western Australia. In 1996, He joined the Department of Mathematics and Statistics, Curtin University, Australia, as Professor of Applied Mathematics. He took up the position of Chair Professor of Applied Mathematics and Head of Department of Applied Mathematics at the Hong Kong Polytechnic University, China, from 1999 to 2004. He returned to Australia in 2005 as Professor of Applied Mathematics and Head of Department of Mathematics and Statistics at Curtin University until 2010. Professor Teo has been a John Curtin Distinguished Professor, the highest rank professor at Curtin University, since the beginning of 2011. Professor Teoserved as a member of the Australian Research Council’s Mathematical, Information and Computing Sciences Panel for the 2010 and 2015 Excellence in Research for Australia (ERA) Exercise. He was a Lecturer of the 2010-2011 Texas A&M University at Qatar Distinguished lecture Series, and the winner of the prestigious 2013 John de Laeter Research Leadership Award, Curtin University. Professor Teo is Editor-in-Chief of Journal of Industrial and Management Optimization (JIMO); Cogent Mathematics; and Numerical Algebra, Control and Optimization (NACO). He also serves as an Associate Editor of 12 international journals which include Automatica, Journal of Global Optimization (JOGO), Journal of Optimization Theory and Applications (JOTA), Discrete and Continuous Dynamical Systems (DCDS), Applied Mathematical Modelling, and Optimization Letters (OPTL).

In the last 5 years, Professor Teo has published over 100 refereed journal articles, many in leading international journals such as Automatica, Journal of Global Optimization, Journal of Optimization Theory and Applications, European Journal of Operational Research, and various IEEE journals.

Professor Teo was a Founding Member and member of the working committee of Pacific Optimization Research Activity Group (POP). Pacific optimization Research Activity Group (POP) is an important research organization with over 500 members from 50 different countries and regions. It has an electronic newsletter "Optimization Research Bridge" (ORB), three conference series (International Conference on Optimization: Techniques and Applications; Pacific Optimization Conferences; and International Conference on Optimization and Control with Applications), and two journals ("Pacific Journal of Optimization", and "Journal of Industrial and Management Optimization'' ). Professor Teo has served as the Chair of POP since 2015.

His research interests are optimal control and optimization and their real world applications, such as optimal filter design in signal processing and financial mathematics.