Education
PhD
M.S.
B.E.
Mechanical and Aerospace Engineering, UC San Diego
Mechanical and Aerospace Engineering, UC San Diego
Engineering Mechanics, Zhejiang University
2005
2002
2001
   
Research Interests
Theoretical and numerical studies of differential equations and dynamical systems in the context of environmental, geophysical and industrial fluid dynamics.
   
Appointments
Assistant Professor
Postdoctoral Associate
Postdoctoral Researcher
Arizona State University
Massachusetts Institute of Technology
UC San Diego
2008-present
2006-2008
2005-2006
   
Awards and Honors
2009-2010 ProjectNExT Fellow
CoPI: "SCREMS: Visualization of Complex Spatio-Temporal Multiscale Fluid Dynamic Phenomena", 2009-2010
CoPI: "CMG: Multiscale Modeling of Urban Atmospheres in a Changing Climate", 2009-2013 (webpage)
   
CV
   
 

 

Fluid Stirring, Coherent Structures
The understanding of a flow system is beyond quantification of ensemble averages. It is in fact very important in applications to identify the patterns with which fluid (and maybe other) particles mix. To understand these patterns, we use Dynamical Systems Methods to extract attractors and repellers in a chaotic flow, and thus find the precise organizing structures of the materials of interest. Some applications include identifying turbulence structures in atmospheric flows and understanding the organizing patterns of bacteria subject to nutrient release in a turbulent ocean environment (also vastly many other applications by different research groups). We are interested in further developing mathematical tools such as individual based models for particles and microorganisms in turbulent flows which will be useful in understanding, e.g., ecology in a chaotic environment. Overall the question that needs to be answered is: Given some resolved flow (from model or observations) what can we tell about the dynamics of different materials of interest and what interesting dynamics will that bring to our understandings of physical/biological processes in the environment?
Gravity Waves
Internal gravity waves (IGW) is the stratified analog to surface waves. Basically it's the distortion of isopycnals due to some global flow over rugged topography. Energy is converted from the global flow to supply wave motion. It's significance in the ocean is such that after the generation at the site IGW can propagate away and break. This could create elevated mixing away from topography in the ocean interior. Experiments, simulations and analytical models have been developed to address the generation of IGW in the lab or in the ocean. Of particular interest are the total rate of energy conversion, modal composition of wave energy and nonlinear waves generated from topography. Analytical models have been developed in 2D and 3D for subcritical topography. Such a theory is only available for supercritical topography in very special cases in 2D. One feature of IGW is that wave reflection over the topography conserve its angle of attack with respect to the vertical axis. For two supercritical topography close by, there could be a configuration such that wave will reflect and form a closed orbit. This leads to the break down of linear inviscid theory. I'm interested in further developing analytical visco-linear models to address such a problem, and also look for extension to 3D configurations.
Irreversible Mixing
We live in a stratified environment where turbulence is ubiquitous. Stratification creates spatial anisotropy which may inhibit (stable stratification) or enhance (unstable stratification) turbulent motion. On the other hand, as opposed to stirring in an unstratified flow, stratification allows fluid particles of different density to mix and irreversibly change the global density profile. Such a process requires extraction of energy from the global flow. One way to quantify stratified mixing is through the flux Richardson number, which is a ratio between buoyancy flux and total energy consumption (B.F.+Dissipation). Measurements and observations suggest that this number is between 0.1-0.5 for strongly turbulent flows, depending on the different driving forces. This could in turn be used in a parameterization for flow models. Using a mathematical tool we can rigorously estabilish that under typical shear forcing and evaluated over long time 0.1-0.5 is the range of accessible flux Richardson numbers, if turbulence manifests itself to maximize buoyancy flux. We are interested in generalizing these results to stratified turbulent flows subject to different forcings and seek the possibility of implementing this quantification in real parameterizations.

 

MAT266(SP12)
Calculus For Engineers II Syllabus Office Hour: 3:00-4:30 TTh & by Appt
Methods of integration, applications of calculus, elements of analytic geometry, improper integrals, Taylor series.
MAT267(SP09)
Calculus For Engineers III Syllabus  
Vector-valued functions of several variables, partial derivatives, multiple integration.
MAT275(FA11) Modern Differential Equations Syllabus  
Introduces differential equations, theoretical and practical solution techniques. Applications. Problem solving using MATLAB. Credit is allowed for only MAT 275 or 274 toward a mathematics degree.
MAT343(SP12)
Applied Linear Algebra Syllabus Office Hour: 3:00-4:30 TTh & by Appt
Solving linear systems, matrices, determinants, vector spaces, bases, linear transformations, eigenvectors, norms, inner products, decompositions, applications. Problem solving using MATLAB.
MAT452(FA09)
Intro Chaos/Nonlinear Dynamics Syllabus  
Properties of nonlinear dynamical systems; dependence on initial conditions; strange attractors; period doubling; bifurcations; symbolic dynamics; Smale-Birkhoff theorem; and applications.
MAT462(FA11)
Applied Partial Differential Equations Syllabus  
Second-order partial differential equations, emphasizing Laplace, wave, and diffusion equations. Solutions by the methods of characteristics, separation of variables, and integral transforms.
APM560(FA10)
Applied Dynamical Systems Methods Syllabus  
Applies modern dynamical systems methods to fluid mechanics: bifurcations, normal forms, nonlinear dynamics, pattern formation, mixing, and Lagrangian chaos.
       

 

In the news

'Finding Order in the Apparent Chaos of Currents', New York Times
'Lagrangian coherent structures rule the world', The Economist

 
Movies from various research topics
1. Finite-size Pollutant Particle Transport in Urban Street Canyon (right click to play flash movie)

Attracting Lagrangian Coherent Structures (LCS) inside an urban street canyon for finite-size inertial particles. The LCS are computed from the slow manifoid velocity derived from simulation data. The forward-time motion shows that an inertial particles is attracted to the local maxima of the Direct Lyapunov Exponent field. The backward-time motion shows the results for inversion of the finite-size particle using different schemes.

Reference: Locating an atmospheric contamination source using slow manifolds (2009), Tang, W., Haller, G., Baik, J.-J. & Ryu, Y.-H., Phys. Fluids, 21, 043302.

2. Lagrangian signatures of a jet stream and balloon measurements

Comparison between the repelling LCS generated from model data and atmospheric characteristics estimated by weather balloon measurements. Color contour is the Forward-time DLE. Black line originating from the big island is the balloon trajectory, green curve is refractive index structure constant Cn2 and blue curve is the dissipation rate.

Reference: Lagrangian Coherent Structures Near a Subtropical Jet Stream (2010), Tang, W., Mathur, M., Haller, G., Hahn, D.C. & Ruggiero, F.H., J. Atmos. Sci., 67, 7, 2307-2319.

3. Turbulent structures near Hong Kong International Airport (right click to play flash movie)

Evolution of radial velocity detected by LIDAR along with backward-time FDFTLE extracted from the retrieved 2D velocity field. Also shown are Hovmoller diagrams at various ranges indicated by the dotted lines in the movies. First movie: recirculation bubble detachment and regeneration next to a mountain peak. Second movie: a persistent ridge of updraft originated inside a mountain gap.

Reference: Lagrangian Coherent Structure analysis of terminal winds detected by LIDAR. Part II: structure evolution and flight data analyses (2011). Tang, W. Haller, G. & Chan, P.W., J. Appl. Meteorol. Clim., 50, 2167-2183

 
   
   

 

Baik, J.-J. Seoul National University  
Calhoun, R. MAE, ASU
Caulfield, C.P. DAMTP, University of Cambridge
Chan, P.W. Hong Kong Observatory
Dimitrova, R., CEE, Notre Dame
Fernando, H.J.S., CEE, Notre Dame
Hahn, D.C. Hanscom AFB
Haller, G. ME, McGill
Kerswell, R.R. Math, University of Bristol
Llewellyn Smith, S.G. MAE, UC San Diego
Mahalov, A. Math, ASU
Peacock, T. ME, MIT
Ruggiero, F.H. Hanscom AFB
Stocker, R. CEE, MIT
Taylor, J.R. EAPS, MIT  
Young, W.R. SIO  

 

Graduate Students   Undergrads  
  Brend Knutson, PhD Candidate, Applied Mathematics   Tim Lai, Undergraduate, Mathematics
  Phillip Walker, PhD Candidate, Applied Mathematics   Christian Wake, Undergraduate, Mathematics
      Angelica Deibel, Undergraduate, Mathematics
      Hershey Kelley, Undergraduate, Mathematics
High School Intern      
       
Alumni
  Phillip Walker, M Sc, Mechanical Engineering, ASU Juan Durazo, Undergraduate, Mathematics
  Inez Ibarra, Biosciences High School Lena Tamrat, Biosciences High School

 

Refereed Journal Publications
1. Reynolds number dependence of an upper bound for the long-time-averaged buoyancy flux in a plane stratified Couette flow (2004) Caulfield, C.P., Tang, W. & Plasting, S.C., J. Fluid Mech. 498, 315-332. [pdf] DOI: 10.1017/S0022112003006797
2. Bounds on dissipation in stress-driven flow (2004) Tang, W., Caulfield, C.P. & Young, W.R., J. Fluid Mech. 510, 333-352. [pdf] DOI: 10.1017/S0022112004009589
3. Bounds on dissipation in stress-driven flow in a rotating frame (2005) Tang, W., Caulfield, C.P. & Young, W.R., J. Fluid Mech. 540, 373-391. [pdf] DOI:10.1017/S0022112005005926
4. Locating an atmospheric contamination source using slow manifolds (2009), Tang, W., Haller, G., Baik, J.-J. & Ryu, Y.-H., Phys. Fluids, 21, 043302. [pdf] URL: http://link.aip.org/link/?PHF/21/043302 DOI: 10.1063/1.3115065
5. A prediction for the optimal stratification for turbulent mixing (2009), Tang, W., Caulfield, C.P. & Kerswell, R.R., J. Fluid Mech., 634, 487-497. [pdf] DOI:10.1017/S0022112009990711
6. Accurate extraction of LCS over finite domains, with applications to flight data analyses over Hong Kong International Airport (2010), Tang, W., Chan, P.W. & Haller, G., Chaos, 20, 017502. [pdf] DOI: 10.1063/1.3276061
7. Lagrangian Coherent Structures and internal wave attractors (2010), Tang, W., Peacock, T., Chaos, 20, 017508. [pdf] DOI:10.1063/1.3273054
8. Lagrangian Coherent Structures near a subtropical jet stream (2010), Tang, W., Mathur, M., Haller, G., Hahn, D.C., Ruggiero, F.H., J. Atmos. Sci.,67, 7, 2307-2319[pdf] DOI: 10.1175/2010JAS3176.1
9. Lagrangian dynamics in stochastic inertia-gravity waves (2010), Tang, W., Taylor, J.E. & Mahalov, A., Phys. Fluids, 22,126601. [pdf] doi:10.1063/1.3518137
10. Lagrangian Coherent Structure analysis of terminal winds detected by LIDAR. Part I: turbulence structures (2011), Tang, W., Haller, G. & Chan, P.W., J. Appl. Meteorol. Clim., 50, 325-338[pdf] DOI:10.1175/2010JAMC2508.1
11. Lagrangian Coherent Structure analysis of terminal winds detected by LIDAR. Part II: structure evolution and flight data analyses, Tang, W., Haller, G. & Chan, P.W., J. Appl. Meteorol. Clim., 50, 2167-2183[pdf] DOI:10.1175/2011JAMC2689.1
   
 
Recent submissions
1. The geometry of inertial particle mixing in urban flows, from deterministic and random displacement models, Tang, W., Knutson, B., Mahalov, A & Dimitrova, R(for Phys. Fluids)
 
To be submitted
1. Modulation of chemical reaction by Lagrangian Coherent Structures, Tang, W., Walker, P. (for J. Fluid Mech.)
   
   

 

Concept based learning workshop for high school students

This workshop is aimed at engaging high-achieving high school students with continued motivation for further mathematical studies. Mathematical models are introduced along with development of physical concepts so the students will learn both simultaneously. Various types of ODE models for natural systems are formed and the concept of dynamics is developed through discussions of the meaning of the models. Students in this workshop get hands-on experience in applying mathematical tools to analyze the dynamical behaviors of the models. Topics such as the Taylor series expansion, vector calculus, linear algebra, differential equations and phase portraits, suitable to the problems presented, are connected so they will not be perceived as disjointed math subjects in future studies.

High school students in this workshop also get the opportunity to visit the ASU campus and collaborate with successful undergraduate students in applied mathematics on problems discussed in workshop. Interactions with college students and faculty help the participating students learn from role models and be informed with career opportunities in STEM fields.

A presentation on applied dynamics can be located here.

Workshop notes can be located here.

Workshop Participants, 2011  
 
 
 

 

Applied Math internship for high school students

High school students can also participate in research activities at our lab. Throughout the course of the internship the students will be exposed to different mathematical concepts linked to solve applied problems in different disciplines. Concept based learning of mathematical topics is further solidified through hands on research questions.

Currently students from BioSciences High School, Phoenix have benefitted from participating in this internship.

 

Last Update: 5/26/2011