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Shasha Zou

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Shasha Zou is an Associate Professor of Climate and Space Science and Engineering. Her general research interest is about studying the dynamic interaction between the Sun’s extended atmosphere, i.e., solar wind, and the near-Earth space environment. In particular, she is interested in the physical processes of formation and evolution of ionospheric structures and their impact on technology, such as global navigation and communication satellite system (GNSS), during space weather disturbances using multi-instrument observations and numerical models. Numerical models often used include magnetohydrodynamic (MHD) model of the global magnetosphere, and physics-based global ionosphere and thermosphere model.

 

Global ionosphere total electron content distribution and the plasma convection contours from BATSRUS model.

Camille Avestruz

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Dr. Avestruz is a computational cosmologist. She uses simulations to model, predict, and interpret observed large-scale cosmic structures. Her primary focus is to understand the evolution of galaxy clusters. These are the most massive gravitationally collapsed structures in our universe, comprised of hundreds to thousands of galaxies. Other aspects of her work prepare for the next decade of observations, which will produce unprecedented volumes of data. In particular, she is leading software development efforts within the clusters working group of the Large Synoptic Survey Telescope to calibrate galaxy cluster masses from simulation data. Dr. Avestruz also incorporates big data methods, including machine learning, to extract gravitational lensing signatures that probe the mass distribution of massive galaxies and galaxy clusters.

[Click on image to see video] Image projection of various components and properties of a simulated galaxy cluster in its last 8 gigayears of formation. The top left panel shows the underlying dark matter content, the top middle image shows the distribution of stars, and the remaining four panels are properties of the gas content: density, temperature, entropy, and metallicity. To model the evolution of galaxy clusters in a cosmological volume, the simulation uses adaptive refinement in space and time in order to span the relevant dynamic range of the system.

Aaron Towne

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Aaron Towne is an Assistant Professor in the Department of Mechanical Engineering. His research develops simple models that can be used to understand, predict, and control turbulent fluid dynamical systems. His approach focuses on identifying and modeling coherent flow structures, i.e., organized motions within otherwise chaotic flows. These structures provide building blocks for an improved theoretical understanding of turbulence and also contribute significantly to engineering quantities of interest such as drag, heat transfer, and noise emission. Consequently, strategically manipulating coherent structures can potentially lead to vast performance improvements in a wide range of engineering applications. Realizing this potential requires new data mining and analysis methods that can be used to identify and extract these organized motions from the large data sets produced by high fidelity simulations and experiments, as well as new theoretical and computational approaches for modeling and controlling them. Aaron’s research focuses on developing these tools for turbulent flow applications, while also contributing more broadly to the emerging areas of large-scale data mining and machine learning.

Temperature (color) and pressure (gray scale) from a simulation of a turbulent jet. The pressure field exhibits organized patterns (alternating black and white regions) that can be leveraged to understand, predict, and control the noise produced by the jet. Image courtesy of Guillaume Brès.

Yulin Pan

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Yulin Pan is an Assistant Professor in the department of Naval Architecture & Marine Engineering. He received his Ph.D. in mechanical and ocean engineering from MIT in 2016, with a minor in mathematics. His research is primarily concerned with theoretical and computational hydrodynamics, with applications in ocean engineering and science. He has made original contributions in nonlinear ocean wave mechanics, tidal flows, propeller and bio-inspired foil propulsion. Alongside research, he is also an active writer on popular science of fluid mechanics. His active research topics include:

  • Theoretical, computational and experimental investigations to understand the fundamental physics of wave turbulence
  • Prediction and understanding of nonlinear ocean and coastal wave phenomenon
  • Response of ships and offshore structures in wave field
  • Development of computation and optimization methods for propellers and flapping foils
  • Propagation of internal waves/tides at geophysical scales

Richard Rood

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Ricky Rood is a Professor of Climate and Space Sciences and Engineering. His current research and teaching focus is on climate change and its repercussions in society. His research history includes numerical modeling of trace constituents and atmospheric dynamics. He was director of NASA’s Center for Computational Science at Goddard Space Flight Center. He is currently consulting with NOAA on the Next Generation Global Prediction System.

Professor Rood is an active member of the climate science community, working on strategic approaches to the climate-change problem solving. He writes blogs for Wunderground.com and Climatepolicy.org and he is a main contributor of The Climate Workspace project, glisaclimate.org, a site that supports an online community of people working to address climate change questions and problems.

 

Kevin Maki

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Dr. Maki works in the field of fluid mechanics, and his central focus is on developing algorithms for numerical computation of high-Reynolds number external flows that contain an air-water interface. Research interests include investigating free-surface hydrodynamics for analysis and design of high-performance naval craft and renewable-energy devices. Theoretical effort is focused on accurate description of the flow about marine vessels. Numerical research employs finite-volume and boundary element techniques to solve equations appropriate to govern the performance of ships maneuvering in waves, and energy devices and structures that operate in the ocean.

Shravan Veerapaneni

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His research group develops fast and scalable algorithms for solving differential and integral equations on complex moving geometries. Application areas of current interest include large-scale simulations of blood flow through arbitrary confined geometries, electrohydrodynamics of soft particles and heat flow on time-varying domains.

simulation of red blood cells

Snapshot from a hydrodynamic simulation of 40,000 red blood cells with the inset showing the details of a two-body interaction.

Divakar Viswanath

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Divakar Viswanath is a Professor in the Department of Mathematics. His research is at the interface of scientific computation and nonlinear dynamics. The incompressible Navier-Stokes equations are a major point of current interest. Turbulent dynamics is locally unstable and bounded in phase space. In such scenarios, dynamical systems theory predicts the existence of periodic solutions (modulo symmetries). Professor Viswanath has developed algorithms to extract periodic solutions and traveling waves from turbulent dynamics. One goal of current research is to derive, implement, and demonstrate algorithms that simulate turbulent flows at higher Reynolds numbers than is currently possible. It appears that this goal will be met shortly. Professor Viswanath has a general interest in foundational numerical analysis ranging from interpolation theory to the solution of differential equations.

divakarimage

Robert Krasny

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His research goal is to develop accurate and efficient numerical methods for computational problems in science and engineering. The methods he works on typically use the Green’s function to convert the relevant differential equation into an integral equation. Krasny develops treecode algorithms for efficient computation of long-range particle interactions. Topics of interest include fluid dynamics (vortex sheets, vortex rings, Hamiltonian chaos, geophysical flow), and electrostatics (Poisson-Boltzmann model for solvated proteins). He is also interested in modeling charge transport in organic solar cells.

This picture illustrates the instability of a vortex ring. The ring was modeled as a circular disk vortex sheet with an imposed perturbation of azimuthal wavenumber m=8. The ring’s motion was computed using a Lagrangian particle method and a treecode algorithm for fast evaluation of the induced velocity. The picture shows three isosurfaces of vorticity at a late time in the simulation. The results reveal details of the instability, in particular the relation between axial flow and collapse of the vortex core.

This picture illustrates the instability of a vortex ring. The ring was modeled as a circular disk vortex sheet with an imposed perturbation of azimuthal wavenumber m=8. The ring’s motion was computed using a Lagrangian particle method and a treecode algorithm for fast evaluation of the induced velocity. The picture shows three isosurfaces of vorticity at a late time in the simulation. The results reveal details of the instability, in particular the relation between axial flow and collapse of the vortex core.

Brian Arbic

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Brian Arbic is an Associate Professor in the Department of Earth and Environmental Sciences, with an appointment in the Department of Climate and Space Sciences Engineering and affiliations with Applied and Interdisciplinary Mathematics, Applied Physics, and the Center for the Study of Complex Systems. Arbic is a physical oceanographer primarily interested in the dynamics and energy budgets of oceanic mesoscale eddies (the oceanic equivalent of atmospheric weather systems), the large-scale oceanic general circulation, and tides. He has also studied paleotides, tsunamis, and the decadal variability of subsurface ocean temperatures and salinities. His primary tools are numerical models of the ocean. Arbic uses both realistic models, such as the HYbrid Coordinate Ocean Model (HYCOM) being used as a U.S. Navy ocean forecast model, and idealized models. He frequently compares the outputs of such models to oceanic observations, taken with a variety of instruments. Comparison of models and observations helps us to improve models and ideas about how the ocean works. His research has often been interdisciplinary, involving collaborations with scientists outside of my discipline, such as glaciologists, geodynamicists, and marine geophysicists.

The surface expression of the M_2 principal lunar semidiurnal internal tide — the tide that arises due to the stratification of the ocean. The top panel shows analysis of satellite altimetry data, while the bottom shows results from HYCOM, run by collaborators at the Naval Research Laboratory. (Shriver, et al 2012)

The surface expression of the M_2 principal lunar semidiurnal internal tide — the tide that arises due to the stratification of the ocean. The top panel shows analysis of satellite altimetry data, while the bottom shows results from HYCOM, run by collaborators at the Naval Research Laboratory. (Shriver, et al 2012)