Event Calendar

Mar
6
Fri
Graduate Seminar in Fluid Mechanics @ 213 Hodson Hall
Mar 6 @ 4:00 pm – 5:00 pm

4:10 pm Presentation

A Vortex Sheet as an Interface Retaining Coarsed Model for Multiphase Flow

 Presented by XIANYANG CHEN (Adviser: Prof. Tryggvason)

Multiphase flows are characterized by sharp moving phase boundaries, separating different fluids or phases. In many cases the dynamics of the interfaces determines the behavior of the flow. In a coarse, or reduced order model, either an averaged two-fluid model or a large-eddy-simulation like one, it is therefore critical to retain a sharp interface for the resolved scales. To develop a more general strategy we are experimenting with a particularly simple approach, modeling the interface for a weakly stratified flow using an inviscid vortex sheet with baroclinically generated vorticity, advected using  the Biot-Savart law, and adjustable model parameters to match the results from a full resolved simulation. We start by filtering the fully resolved results, using a filter that we call weighted coordinates smoothing (WCS), that simplifies the interface and concentrates the vorticity at the interface. The model parameters (“vortex blob’’ sizes) are found by optimization, using a cost function that compares the velocity of the filtered interface with the model prediction. Once the model parameters have been found, we plan to use machine learning to develop a strategy to evolve them in time. We discuss the overall work plan, the filtering strategy, and show preliminary results.


4:35 pm Presentation

“Optimal Prediction of Wall Shear Stress from Filtered Velocity Datas

Presented by MENGZE WANG (Adviser: Prof. Zaki)

Resolving near-wall turbulence is difficult in simulations of high-Reynolds-number flows. To mitigate the near-wall resolution requirements and reduce computational cost, wall models are indispensable in practical numerical solvers such as large-eddy simulations (LES). Conventional wall models adopt instantaneous LES velocity as their input and predict a corresponding instantaneous wall shear-stress which is fed back to LES as a boundary condition. Despite the numerous existing wall models, a fundamental question remains unaddressed: given instantaneous filtered off-wall velocity data, what is the highest possible accuracy of predicted wall shear stress? This problem is investigated using an adjoint variational data assimilation approach. By combining a full Navier-Stokes solver with off-wall filtered-velocity data, we reconstruct the initial condition that tracks the full flow state and optimally predicts the spatio-temporal evolution of the wall shear stress. We demonstrate that the optimal prediction is robust to the filter width. As the height of the first available velocity grid point increases, the correlation between the true and optimally predicted wall stresses deteriorates, but remains at least twice as large as that of the true and equilibrium wall-model stresses. Finally, the Reynolds number effect on the optimal prediction is explored.

Mar
13
Fri
Graduate Seminar in Fluid Mechanics @ 213 Hodson Hall
Mar 13 @ 4:00 pm – 5:00 pm

4:10 pm Presentation

Effect of Axial Casing Groove Geometry on Rotor-Groove Interactions in the Tip Region of a Compressor

 Presented by SUBHRA SHANKHA KOLEY (Adviser: Prof. Katz)

The present experimental study expands an ongoing effort to characterize the interactions of axial casing grooves (ACGs) with the flow in the tip region of an axial turbomachine. In recent work, we have tested a series of grooves with the same inlet geometry but with different exit directions. Two geometries have stood out: The U grooves, which have an outflow in the negative circumferential direction (opposing the blade motion) are the most effective in suppressing stall, but cause a decrease in efficiency around the best efficiency point (BEP). In contrast, the S grooves, which have an outflow in the positive circumferential direction, achieve a milder improvement in stall suppression but do not degrade the performance near BEP. Stereo-Particle Image Velocimetry (SPIV) measurements is carried out at various planes to elucidate the flow in the tip region and within the U and S grooves. At low flow rates, the inflow into both grooves peaks periodically when the blade pressure side (PS) faces the entrance (downstream side) to the grooves. This inflow rolls up into a large vortex that remains and lingers within the groove long after the blade clears the groove. The outflow depends on the shape of the groove. For the S groove, the outflow exits at the upstream end of the groove in the positive circumferential direction, as designed. In contrast, for the U grooves, the fast radially and circumferentially negative outflow peaks at the base of the U. The resulting jet causes substantial periodic variations in the flow angle near the leading edge of the rotor blade. Close to the BEP, the chordwise location of primary blade loading moves downstream, as expected. The inflow into the grooves occurs for a small fraction of the blade passing period, and most of the tip leakage vortex remains in the main flow passage. For the S grooves, the rotor-groove interactions seem to be minimal, with little (but not zero) inflow or outflow at both ends, and minimal changes to the flow angle in the passage. In contrast, for the U groove, the inflow into and outflow from the groove reverses direction (compared to the low flowrate trends). The resulting entrainment of secondary flows from the groove into the passage are likely contributors to the reduced efficiency at BEP for the U grooves.


4:35 pm Presentation

“An Input-Output Inspired Method for Permissible Perturbation Amplitude of Transitional Wall-Bounded Shear Flows

Presented by CHANG LIU (Adviser: Prof. Gayme)

Determining the permissible level of perturbation to maintain a laminar flow state is of critical importance in a wide range of applications. Historical approaches to this problem in wall-bounded shear flows focused on linear analysis that is only provably valid in a small neighborhood of the laminar solution and precludes the evaluation of the role of nonlinearity. Extensive simulations or experimental studies allow exploration of the full dynamics, but a finite set cannot provide a definitive bound. This work takes an input-output approach that partitions the dynamics into a feedback interconnection of the linear and nonlinear dynamics (i.e., a Luré system in which the nonlinearity is static feedback). We construct a model of the nonlinear term that is constrained by system physics to be energy conserving (passive) and to have bounded input-output energy. We then formulate computation of the region of attraction of the laminar state (set of safe perturbations) and permissible perturbation amplitude as Linear Matrix Inequalities (LMI), which allows a more computationally efficient solution than prevailing nonlinear approaches based on Sum of Squares (SOS) programming. We apply our approach to low dimensional nonlinear shear flow models for a range of Reynolds numbers. The results from our analytically derived bounds are consistent with the bounds identified through exhaustive simulations. However, our results are obtained at a much lower computational cost and have the benefit of providing a provable guarantee that a certain level of perturbation is permissible.

Apr
2
Thu
Online Mechanical Engineering Spring Seminar Series: Class 530.804 @ Zoom: https://wse.zoom.us/j/560809286
Apr 2 @ 3:00 pm – 4:00 pm

via Zoom: https://wse.zoom.us/j/560809286

“Neuroscience in The Matrix: Closing the loop around the brain to understand how it controls the body”

Presented by Professor Noah Cowan
Department of Mechanical Engineering, Johns Hopkins University

The nervous system is a sophisticated control system, controlling equally sophisticated biomechanical “plant”. Understanding how the nervous system (1) encodes and processes sensory information, (2) transforms it into meaningful intermediate representations in the brain, and (3) computes motor output, therefore, involves decoding a complex closed-loop control system.

This talk will present a research program devoted to developing and applying ideas in engineering to decode closed-loop neuromechanical control in animals (including humans). Central to this program is the ability to wrap artificial feedback systems around freely behaving animals—in some cases by “reading their minds,” i.e. decoding neural activity in real time. Using this approach, the direct neural output is used to adjust sensory inputs on the fly in an effort to disentangle the interactions between the nervous system and the biomechanical plant that it controls.

Noah J. Cowan received a B.S. degree from the Ohio State University, Columbus, in 1995, and M.S. and Ph.D. degrees from the University of Michigan, Ann Arbor, in 1997 and 2001 – all in electrical engineering. Following his Ph.D., he was a Postdoctoral Fellow in Integrative Biology at the University of California, Berkeley for 2 years. In 2003, he joined the mechanical engineering department at Johns Hopkins University, Baltimore, MD, where he is now a Professor. Prof. Cowan’s research interests include mechanics and multisensory control in animals and machines. Prof. Cowan received the NSF PECASE award in 2010, the James S. McDonnell Foundation Scholar Award in Complex Systems in 2012, and two Johns Hopkins Discovery Awards in 2015 and 2016.  In addition, Prof. Cowan received the William H. Huggins Award for excellence in teaching in 2004, and the Dunn Family Award in 2014, conferred for having “. . . an extraordinarily positive impact upon the lives of one or more undergraduate students.”

Apr
3
Fri
Online Graduate Seminar in Fluid Mechanics @ Join on-line via Zoom: https://wse.zoom.us/j/435449376
Apr 3 @ 4:00 pm – 5:00 pm

Join on-line via Zoom: https://wse.zoom.us/j/435449376


“Effect of Axial Casing Groove Geometry on Rotor-Groove Interactions in the Tip Region of a Compressor”

Presented by SUBHRA SHANKHA KOLEY
(Adviser: Prof. Katz)

The present experimental study expands an ongoing effort to characterize the interactions of axial casing grooves (ACGs) with the flow in the tip region of an axial turbomachine. In recent work, we have tested a series of grooves with the same inlet geometry but with different exit directions. Two geometries have stood out: The U grooves, which have an outflow in the negative circumferential direction (opposing the blade motion) are the most effective in suppressing stall, but cause a decrease in efficiency around the best efficiency point (BEP). In contrast, the S grooves, which have an outflow in the positive circumferential direction, achieve a milder improvement in stall suppression but do not degrade the performance near BEP. Stereo-Particle Image Velocimetry (SPIV) measurements is carried out at various planes to elucidate the flow in the tip region and within the U and S grooves. At low flow rates, the inflow into both grooves peaks periodically when the blade pressure side (PS) faces the entrance (downstream side) to the grooves. This inflow rolls up into a large vortex that remains and lingers within the groove long after the blade clears the groove. The outflow depends on the shape of the groove. For the S groove, the outflow exits at the upstream end of the groove in the positive circumferential direction, as designed. In contrast, for the U grooves, the fast radially and circumferentially negative outflow peaks at the base of the U. The resulting jet causes substantial periodic variations in the flow angle near the leading edge of the rotor blade. Close to the BEP, the chord-wise location of primary blade loading moves downstream, as expected. The inflow into the grooves occurs for a small fraction of the blade passing period, and most of the tip leakage vortex remains in the main flow passage. For the S grooves, the rotor-groove interactions seem to be minimal, with little (but not zero) inflow or outflow at both ends, and minimal changes to the flow angle in the passage. In contrast, for the U groove, the inflow into and outflow from the groove reverses direction (compared to the low flowrate trends). The resulting entrainment of secondary flows from the groove into the passage are likely contributors to the reduced efficiency at BEP for the U grooves.


“An Input-Output Inspired Method for Permissible Perturbation Amplitude of Transitional Wall-Bounded Shear Flows”

Presented by CHANG LIU
(Adviser: Prof. Gayme)

Determining the permissible level of perturbation to maintain a laminar flow state is of critical importance in a wide range of applications. Historical approaches to this problem in wall-bounded shear flows focused on linear analysis that is only provably valid in a small neighborhood of the laminar solution and precludes the evaluation of the role of nonlinearity. Extensive simulations or experimental studies allow exploration of the full dynamics, but a finite set cannot provide a definitive bound. This work takes an input-output approach that partitions the dynamics into a feedback interconnection of the linear and nonlinear dynamics (i.e., a Luré system in which the nonlinearity is static feedback). We construct a model of the nonlinear term that is constrained by system physics to be energy conserving (passive) and to have bounded input-output energy. We then formulate computation of the region of attraction of the laminar state (set of safe perturbations) and permissible perturbation amplitude as Linear Matrix Inequalities (LMI), which allows a more computationally efficient solution than prevailing nonlinear approaches based on Sum of Squares (SOS) programming. We apply our approach to low dimensional nonlinear shear flow models for a range of Reynolds numbers. The results from our analytically derived bounds are consistent with the bounds identified through exhaustive simulations. However, our results are obtained at a much lower computational cost and have the benefit of providing a provable guarantee that a certain level of perturbation is permissible.

Apr
9
Thu
Online Mechanical Engineering Spring Seminar Series: Class 530.804 @ https://wse.zoom.us/j/145648770
Apr 9 @ 3:00 pm – 4:00 pm

Via Zoom: https://wse.zoom.us/j/145648770

“Mechanical Regulation of Cell Growth and Proliferation”

Presented by Professor Sean Sun
Department of Mechanical Engineering, Johns Hopkins University

From the point-of-view of engineering, the cell is an extraordinary autonomous system capable of self regulation in a changing environment. One of the critical processes of the cell that require extensive regulation is cell growth and proliferation. Indeed, failure in proper regulation of cell growth is the root cause of many diseases, including cancer. However, studying cell growth control turns out to be difficult, due to measurement problems at the cell single level and inherent noisiness of the growth process. In this talk, I will describe a new AI-based microscopy method to quantitatively measure cell size in real time. Using this method, we can observe single cell growth over multiple rounds of cell division. We find novel signatures of cell growth control and the presence of a cell size checkpoint during the cell cycle. The data clearly shows that cancer cells and normal cells regulate their cell size and growth differently. Moreover, normal cell growth is sensitive to mechanical tension and forces applied to the cell, whereas cancer cells seems to be insensitive to force application. These results suggest that there are redundant control mechanisms of cell growth and cell size regulation in normal cells, and cancer cells can escape normal growth regulation by altering their mechanosensitivity. The implications of these results are important for understanding disease mechanisms, and our method of studying cell growth and proliferation will be useful for further revealing molecular-level control algorithms.

Sean Sun is a faculty member in the Department of Mechanical Engineering and Institute of NanoBioTechnology at JHU. He is interested in the mechanical behavior of the cell and the mechanisms behind cell movement, cell growth and cell size regulation. He uses a combination of microfluidic methods, microscopy, genetic and biophysical techniques, and mathematical modeling to reveal novel mechanisms in cell biomechanics. He is a member of the JHU Physical Sciences in Oncology Center, and a Fellow of the American Physical Society (APS) and the American Institute for Medical and Biological Engineering (AIMBE).

Apr
10
Fri
Graduate Seminar in Fluid Mechanics @ Join on-line via Zoom: https://wse.zoom.us/j/435449376
Apr 10 @ 4:00 pm – 5:00 pm

Join online via Zoom: https://wse.zoom.us/j/435449376


“Scalar Transport in Restricted Nonlinear Wall-Turbulence”

Presented by BENJAMIN MINNICK
(Adviser: Prof. Gayme)

Streamwise coherent structures are inherent in wall-bounded turbulence and their study has given insight into structural features and dynamics of the flow. For example, streamwise vortices have been attributed with redistributing the momentum and developing the blunted mean velocity profile. Numerical and experimental studies of scalars, such as heat or chemical species, transported by wall-bounded turbulent flow have shown scalar fluctuations are highly correlated to streamwise velocity fluctuations, therefore it is likely that the dynamics of streamwise coherent structures also play a key role in scalar transport. We test this hypothesis by simulating scalar transport in the restricted nonlinear (RNL) model, a quasi-two-dimensional representation of wall-turbulence shown to accurately predict low-order statistics and cross-plane features of the momentum field. We have found that restricting both the momentum and scalar fields to streamwise constant mean dynamics interacting with a single non-zero wavenumber perturbation is capable of accurately predicting the expected time-averaged scalar log-law profile for a range of Prandtl numbers. Furthermore, this RNL model is shown to predict similar cross-plane structures in the scalar field to direct numerical simulation (DNS), suggesting streamwise vortices are indeed the structures largely responsible for mixing scalars in wall-bounded turbulent flow. After applying this model to study passive scalar transport, we conclude by investigating buoyancy effects in stably-stratified turbulence.


“Towards a Reduced-Order Model for Finite-Sized Bubbles in Turbulence”

Presented by ASHIK U. M. MASUK
(Adviser: Prof. Ni)

In both natural and industrial turbulent multiphase flows, bubbles are often present as the dispersed second phase controlling many important processes such as ocean-atmosphere gas exchange, heat transfer, and mixing in chemical reactors. For better predictive modeling of such processes, it is essential to understand the contribution of different flow components in determining the shape evolution of bubbles. The shape and relative orientation of a bubble directly control the forces that it experiences in a flow field which eventually determines its dynamics in the flow. In this work, from our unique simultaneous 3D measurements of bubbles and their surrounding flow, we identify the mechanisms that are responsible for the deformation of finite-size bubbles; and based on these mechanisms, we develop a phenomenological model to predict the deformation and orientation of bubbles in turbulence. Finally, the model predictions and experimental measurements are compared.

Apr
16
Thu
Mechanical Engineering Spring Seminar Series: Class 530.804 @ via Zoom: https://wse.zoom.us/j/348258728
Apr 16 @ 3:00 pm – 4:00 pm

3:00pm via Zoom: https://wse.zoom.us/j/348258728

“Mechanics of Granular Materials at “Micro” Length and Time Scales from in-situ X-ray Measurements”

Presented by Professor Ryan Hurley
Department of Mechanical Engineering, Johns Hopkins University

Granular materials are ubiquitous in nature and technology. They include the soils we build structures on, the raw materials we compress and sinter into a vast number of solid products, the foods we love (rice and coffee), and the powders we use in pharmaceuticals and beauty products. Despite their ubiquity, granular materials exhibit very complex behavior that eludes our mechanical models. They size-segregate during flow, exhibit complicated creep behavior when not flowing, demonstrate long-range correlated behavior when compressed, and dissipate an enormous amount of energy due to friction. How can a granular material containing particles that only interact mechanically with their contacting neighbors exhibit such complexity?

In this talk, I will first highlight some interesting behaviors of granular materials with both academic and real-world applications. I will then motivate a need to better experimentally understand granular material behavior: to study their internal structure and response to mechanical loading. I will then describe the portion of my research program that aims to quantitatively measure the behavior of granular materials down to a “microscopic” length scale (the scale of individual particles and their contacts with neighboring particles) and “microscopic” time scales (nanoseconds during dynamic impact). Central to this research program is the use of multiple in-situ X-ray techniques, including X-ray computed tomography (XRCT), 3D X-ray diffraction (3DXRD), and dynamic X-ray phase contrast imaging and radiography. I will describe how we use these techniques and analysis to study how opaque, 3D granular materials develop spatially-correlated inter-particle forces, dissipate energy due to slipping and fracturing, transport wave energy, and dynamically compress due to shock. I will discuss some of our exciting ongoing and future research directions.

Ryan Hurley is an Assistant Professor in the Department of Mechanical Engineering and a Fellow of the Hopkins Extreme Materials Institute, with a Secondary Appointment in the Department of Civil and Systems Engineering, at the Johns Hopkins University (JHU). He received his B.S. in Civil Engineering from the University of Maryland, College Park (2011) and his M.S. (2012) and Ph.D. (2015) in Applied Mechanics from the California Institute of Technology. From 2015 – 2017, Ryan was a postdoctoral researcher in the Computational Geosciences Group at Lawrence Livermore National Laboratory in Livermore, California and an Assistant Research Professor at JHU. He joined JHU full-time as an Assistant Professor in January 2018. He is the recipient of a 2017 Secretary’s Appreciation Award from the U.S. Department of Energy and a 2019 CAREER Award from the U.S. National Science Foundation. In his research, Ryan seeks to see, understand, and predict the mechanical behavior governing a variety of geologic, structural, and composite materials using advanced experimental and numerical techniques.

Apr
17
Fri
Graduate Seminar in Fluid Mechanics @ Join on-line via Zoom: https://wse.zoom.us/j/435449376
Apr 17 @ 4:00 pm – 5:00 pm

Join on-line via Zoom: https://wse.zoom.us/j/435449376

“Generalizing the Coupled Wake Boundary Layer Model for Wind Farm Power Prediction”

Presented by GENEVIEVE STARKE
(Advisers: Profs. Meneveau & Gayme)

During recent years, wind has continued to grow as an electricity provider in the United States. As interest in wind has grown, a need has arisen to be able to accurately predict the effect of turbines on the wind and how this impacts the overall power of the wind farm. Large-scale simulations can predict this accurately, however, they are too expensive and too slow to be used in real-time applications. To achieve faster results, we are working on developing and applying reduced-order models of wind farms that accurately capture key dynamics in the wind farm. Here we present a model that combines two reduced-order models that depend on different scales to improve the overall prediction of the power of the wind farm. The first model is called a wake model, and represents the individual turbines and their effect on the wind. The second model, called the top-down model, works on a larger scale and represents the wind farm as an impediment to the wind in the atmospheric boundary layer, which describes the interaction between the wind in the atmosphere and the ground. This model gives average quantities over the wind farm that are then matched to those obtained from the wake model to obtain a combined prediction of the power. To determine the area over which the average quantities are calculated, the model uses Voronoi tessellation to establish regions of the flow that belong to each turbine. This enables the models to be applied to each turbine and the area around that turbine individually, which allows application to nonuniform wind farms. As a result of our average treatment of the farm, the boundary layer caused by the wind farm in the atmospheric boundary layer is defined to start at the initial line of freestream turbines, rather than on an individual turbine basis. The coupled wake boundary layer model is validated using data from LES simulations for various wind directions from the National Renewable Energy Laboratory, and found to reproduce trends in overall power produced as a function of the inflow direction of the wind.


“LES of Laminar-Turbulent Transition with Turbulent/Non-Turbulent Classification”

Presented by GHANESH NARASIMHAN
(Advisers: Profs. Meneveau & Zaki)

The laminar-turbulent transition in boundary layers and channel flow is usually classified as either orderly (natural) or bypass transition. Natural transition starts with amplification of Tollmien-Schlichting (TS) instability waves which subsequently undergo secondary instability and ultimately break down to turbulence. Often, however, when background disturbances are present, bypass transition takes place instead. It involves initial linear amplification of streamwise perturbations through lift-up mechanism, followed by non-linear evolution and break down into turbulence spots. Direct Numerical Simulation (DNS) of these transition processes is computationally expensive. Therefore, Large Eddy Simulation (LES) is used as an alternative to simulate the laminar-turbulent transition. Wall-Resolved LES (WRLES) using dynamic Smagorinsky Sub-Grid Scale (SGS) model simulates this transition which is comparable to the DNS. However, resolving the inner layer in WRLES demands more grid points thereby making the WRLES of transition computationally expensive. Hence, LES with wall-modeling which models the inner layer rather than resolving it, is used to further decrease the computational cost. Using Wall-Modeled LES (WMLES) to simulate transition is again difficult as the wall model assumes the flow is fully developed. Since a transitional flow has features from both laminar and turbulent states, LES equations with wall-modeling could still be applied in the turbulent regions. Therefore, it is essential to identify the Turbulent/Non-Turbulent (T/NT) regions in the flow. To this end, self-organizing map (SOM), an unsupervised machine learning algorithm is used for the T/NT classification in a transitional channel flow. Firstly, the natural transition is simulated by the WMLES with SOM of the time evolution of channel flow with 2D TS wave and oblique 3D waves as the initial perturbation. Secondly, the case of bypass transition in channel flow is simulated by performing WMLES with SOM of the time evolution of a three-dimensional localized perturbation. The time evolution of the friction Reynolds number from the LES is compared to the DNS. Both the transition scenarios are well predicted by the LES with significantly less computational resources. Thus, the WMLES with T/NT classification using SOM is proposed as a new technique for modeling transitional flows.

Apr
23
Thu
Mechanical Engineering Spring Seminar Series: Class 530.804 @ Join online via Zoom
Apr 23 @ 3:00 pm – 4:00 pm

Zoom: https://wse.zoom.us/j/361732230; password 779781


“On the Breakup and Transport of Crude Oil by Surface Waves and Subsurface Plumes”

Presented by Professor Joseph Katz
Department of Mechanical Engineering, Johns Hopkins University

Nearly a decade after the Deepwater Horizon massive oil spill, this presentation summaries a series of laboratory studies aimed at characterizing interfacial phenomena affecting the breakup of surface slicks and subsurface plumes of crude oil. After entrainment of slicks by surface waves, the droplet size distributions agree with classical turbulence-based scaling, and their subsequent temporal evolution can be modeled by combining effects of turbulent diffusion and buoyant rise.  Pre-mixing the crude oil with dispersant, which drastically reduces the oil-water interfacial tension, causes tip streaming, an interfacial phenomenon that decreases the droplet sizes to the micron range. Aerosolization of oil is caused by the initial splash and by subsequent bubble bursting. Premixing the oil with dispersant increases the concentration of airborne nano-droplets by one to two orders of magnitude, raising health concern. In contrast, the dispersant causes a reduction in concentration of volatile organic compounds. Extended mixing of oil with seawater generates poly-dispersed water-in-oil emulsions with two-orders-of-magnitude higher viscosity. Dispersant partially separates the water, but the viscosity of the remaining sparser emulsion is still higher than that of the original oil. Micro emulsions also form as oil droplets rises and cross an oil-water interface. These droplets do not mix with the bulk oil since they remain coated by submicron water films that persist long after crossing. These films eventually break up owing to droplet deformation induced by electrostatic forces. Below the surface, fragmentation of a vertical buoyant oil jet is elucidated by refractive index matching. Compound oil droplets containing water droplets, some with smaller oil droplets, form regularly. Their fraction increases with droplet diameter, reaching 78% for 2mm droplets. While the exterior surfaces of the oil droplets are deformed by the high shear field, the interior interfaces remain spherical, indicating quiescent domains. In the presence of cross flow, entrainment of small droplets into the core of the counter-rotating vortex pair defines the lower boundary of the plume while large droplets escape and define the upper boundary. Hence, reduction of droplet sizes by dispersant increases the fraction of oil entrained into the vortex pair and lowers the upper boundary of the plume.

Joseph Katz received his B.S. degree from Tel Aviv University, and his M.S. and Ph.D. from California Institute of Technology, all in mechanical engineering. He is the William F. Ward Sr. Distinguished Professor of Engineering, and the director and co-founder of the Center for Environmental and Applied Fluid Mechanics at Johns Hopkins University. He is a Member of the National Academy of Engineering, as well as a Fellow of the American Society of Mechanical Engineers (ASME) and the American Physical Society. He has served as the Editor of the Journal of Fluids Engineering, and as the Chair of the board of journal Editors of ASME. He has co-authored more than 380 journal and conference papers. Dr. Katz research extends over a wide range of fields, with a common theme involving experimental fluid mechanics, and development of advanced optical diagnostics techniques for laboratory and field applications. His group has studied laboratory and oceanic boundary layers, flows in turbomachines, flow-structure interactions, swimming behavior of marine plankton in the laboratory and in the ocean, as well as cavitation, bubble, and droplet dynamics, the latter focusing on interfacial phenomena associated with oil spills.

Apr
24
Fri
Graduate Seminar in Fluid Mechanics @ Join online via Zoom
Apr 24 @ 4:00 pm – 5:00 pm

Join online via Zoom: https://wse.zoom.us/j/435449376


“Large Eddy Simulations of a Developing Turbulent Boundary Layer over Cube Roughened Plate”

Presented by SAMVIT KUMAR
(Advisers: Profs. Meneveau & Mittal)

Turbulent boundary layers are present whenever there is fluid flow over a solid surface or wall. More often than not, these surfaces are rough. The roughness strongly influences flow physics and the drag at the wall. Therefore, it is important to understand the fundamental nature of turbulent boundary layers over rough walls. We first present an improved method for generation of turbulent inflow for simulations of developing boundary layers. The approach is based on prior recycling methods for flow over smooth (Lund et al., 1998) and rough (Yang and Meneveau, 2015) surfaces. In the recycling method, mean and fluctuation velocities on a sample plane are rescaled, combined and recycled back to the inlet, as the inflow velocity. A roughness-length related scale is chosen for rescaling of the inner layer, depending on the surface geometry and the displacement thickness is chosen instead of $\delta_{99}$ as the length scale to rescale the outer layer. The blending function, dependent on both the inner and the outer length scales, is used to combine the two profiles, to obtain the inflow velocity.

We then find an appropriate grid size and use the integral wall model for Large Eddy Simulations of flow over a staggered array of cubes. Results obtained are compared with Direct Numerical Simulations carried out by (Lee et al., 2011) and good agreement is shown. We also set up simulations for flow over multi scale roughness elements.


“The Pressure Field and its Relation to Cavitation Inception in a Turbulent Shear Layer”

Presented by KARUNA AGARWAL
(Adviser: Prof. Katz)

We investigate the unsteady pressure field associated with quasi-streamwise vortices in the shear layer behind a backward facing step. The primary objective is to understand the conditions for cavitation inception, which occurs in the core of these vortices, and appears as 1-2 mm wide and 5-7 mm long cavities. The Reynolds numbers based on the step height are 1.6×10^4 and 5.8×10^4. High speed tomographic imaging followed by 3D particle tracking using the Shake-the-Box method is used for calculating the instantaneous velocity and acceleration fields. The data are interpolated using a constrained cost minimization technique, which establishes a divergence free velocity and curl-free material acceleration fields at a spatial resolution of 200µm. The pressure is then calculated by spatially integrating the material acceleration. Statistical analysis provides the probability density functions of the pressure, strength, size, and straining of the quasi-streamwise vortices. Effects of spatial resolution of the measurements are also discussed. With increasing Reynolds number, the pressure minima are more preferentially located within the quasi streamwise vortices, for longer durations, and appear to be strongly influenced by vortex stretching.

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