Seminars

Controlling Populations of Neural Oscillators

Jeff Moehlis

Professor and Chair, Department of Mechanical Engineering
University of California at Santa Barbara
Santa Barbara, CA

Many challenging problems that consider the analysis and control of neural brain rhythms have been motivated by the advent of deep brain stimulation as a therapeutic treatment for a wide variety of neurological disorders. In a computational setting, neural rhythms are often modeled using large populations of coupled, conductance-based neurons. Control of such models comes with a long list of challenges: the underlying dynamics are nonnegligibly nonlinear, high dimensional, and subject to noise; hardware and biological limitations place restrictive constraints on allowable inputs; direct measurement of system observables is generally limited; and the resulting systems are typically highly underactuated. In this talk, I highlight a collection of recent analysis techniques and control frameworks that have been developed to contend with these difficulties. Particular emphasis is placed on the problem of desynchronization for a population of pathologically synchronized neural oscillators, a problem that is motivated by applications to Parkinson's disease where pathological synchronization is thought to contribute to the associated motor control symptoms.

Jeff Moehlis received a Ph.D. in Physics from UC Berkeley in 2000, and was a Postdoctoral Researcher in the Program in Applied and Computational Mathematics at Princeton University from 2000-2003. He joined the Department of Mechanical Engineering at UC Santa Barbara in 2003, and is currently Chair of this department. He was also recently the Chair of the Program in Dynamical Neuroscience at UC Santa Barbara. He has been a recipient of a Sloan Research Fellowship in Mathematics and a National Science Foundation CAREER Award, and was Program Director of the SIAM Activity Group in Dynamical Systems from 2008-2009. Jeff's current research includes applications of dynamical systems and control techniques to neuroscience, cardiac dynamics, and collective behavior. He has published over 100 journal / conference proceedings articles on these and other topics including shear flow turbulence, microelectromechanical systems, energy harvesting, and dynamical systems with symmetry.

Wednesday, January 18, 2023

3:30 PM

Stauffer Science Lecture Hall, Room 102 (SLH 102)

The Zoom webinar is at https://usc.zoom.us/j/95805178776?pwd=aEtTRnQ2MmJ6UWE4dk9UMG9GdENLQT09.

host: Nguyen

Machine Learning for Scientific Discovery, with Examples in Fluid Mechanics

Steven L. Brunton

Professor of Mechanical Engineering
Department of Mechanical Engineering
University of Washington
Seattle, WA

Accurate and efficient nonlinear dynamical systems models are essential to understand, predict, estimate, and control complex natural and engineered systems. In this talk, I will explore how machine learning may be used to develop these models purely from measurement data. We explore the sparse identification of nonlinear dynamics (SINDy) algorithm, which identifies a minimal dynamical system model that balances model complexity with accuracy, avoiding overfitting. This approach tends to promote models that are interpretable and generalizable, capturing the essential “physics” of the system. We also discuss the importance of learning effective coordinate systems in which the dynamics may be expected to be sparse. This sparse modeling approach will be demonstrated on a range of challenging modeling problems, for example in fluid dynamics. Because fluid dynamics is central to transportation, health, and defense systems, we will emphasize the importance of machine learning solutions that are interpretable, explainable, generalizable, and that respect known physics.

Steven L. Brunton is a Professor of Mechanical Engineering at the University of Washington. He is also Adjunct Professor of Applied Mathematics and Computer science, and a Data Science Fellow at the eScience Institute. Steve received the B.S. in mathematics from Caltech in 2006 and the Ph.D. in mechanical and aerospace engineering from Princeton in 2012. His research combines machine learning with dynamical systems to model and control systems in fluid dynamics, biolocomotion, optics, energy systems, and manufacturing. He received the Army and Air Force Young Investigator Program (YIP) awards and the Presidential Early Career Award for Scientists and Engineers (PECASE). Steve is also passionate about teaching math to engineers as co-author of three textbooks and through his popular YouTube channel, under the moniker “eigensteve”.

Wednesday, January 25, 2023

3:30 PM

Stauffer Science Lecture Hall, Room 102 (SLH 102)

The Zoom webinar is at https://usc.zoom.us/j/95805178776?pwd=aEtTRnQ2MmJ6UWE4dk9UMG9GdENLQT09.

host: Nguyen

Dynamical Weighs: Learning Smooth Latent-Dynamics for Advection-Dominated Systems via Consistency-Constrained Hyper-Networks

Leonardo Zepeda-Núñez

Senior Research Scientist
Google Research
and
Assistant Professor
Department of Mathematics
University of Wisconsin-Madison
Madison, Wisconsin

We present a data-driven, space-time continuous framework to learn surrogate models for complex physical systems described by partial differential equations (PDEs). Our approach involves constructing hypernetwork-based latent dynamical models directly on the parameter space of a compact representation network specially tailored to the state space of the target system. The framework leverages the expressive power of the network with a specially designed consistency-inducing regularization to obtain latent trajectories that are both low-dimensional and smooth. These properties render our surrogate models highly efficient at inference time.

We demonstrate the effectiveness of our approach on advection-dominated systems. These systems have slow-decaying Kolmogorov n-widths that hinders standard methods, including reduced order modeling, from producing high-fidelity simulations at low cost. We show that our method is able to generate accurate multi-step rollout predictions at high efficiency, for several one- and two-dimensional PDEs. The resulting rollouts are shown to be stable and reflect statistics that are consistent with the ground truths.

Leonardo Zepeda-Núñez is a Senior Research Scientist at Google Research and an Assistant Professor of Mathematics at the University of Wisconsin-Madison. He has held postdoctoral positions at Lawrence Berkeley Lab and University of California, working with Lin Lin and Hongkai Zhao respectively. He received a Ph.D. in Mathematics from MIT in 2015 under the direction of Laurent Demanet, an M.Sc. from University of Paris VI in 2010, and a Diploma from École Polytechnique in 2009. His research emcompases scientific machine learning with applications to weather and climate, electronic structure computations, wave-based inverse problems, and fast PDE solvers for wave phenomena.

Wednesday, February 8, 2023

3:30 PM

Stauffer Science Lecture Hall, Room 102 (SLH 102)

The Zoom webinar is at https://usc.zoom.us/j/98775609685?pwd=a2lSd01oY0o2KzA4VWphbGxjWk5Qdz09.

host: Ronney

Strategies to Achieve Order: Colloidal Self-Assembly and Nano-Enhanced Additive Manufacturing

David Doan

Mechanical Engineering Department
Stanford University
Stanford, CA

Achieving order is key to the improvement of materials properties in applications such as mechanics, catalysis, and photonics. Colloidal self-assembly has been a field of interest due to its ability to manipulate nanoscale/microscale particles to create periodic structures. However, a challenge in this field is the ability to expand the possible phase space of crystal structures that can be formed. Here, we explore the fundamentals of shape- or entropy-driven self-assembly to achieve different types of order. I will discuss an experimental framework that allows us to fabricate particles of complex shapes using two-photon lithography and assemble them under a gravitational field. I will present experimental, analytical, and computational results for the self-assembly of truncated tetrahedrons on a 2D interface.

I will also present on enhancing mechanical properties through the addition of atomically precise nanoclusters in polymeric structures to create nanocomposites. This, in conjunction with two-photon lithography, allows us to fabricate strong but lightweight structures of arbitrary shapes. We show that these nanoclusters enhance the overall mechanical properties of the structure, above what is expected from simple composite theory.

David Doan is currently a PhD candidate in Mechanical Engineering at Stanford University under the supervision of Professor Wendy Gu, with a planned graduation in mid-2023. He received his Masters’ degree in Mechanical Engineering at Stanford and Bachelors’ degree in Mechanical Engineering at MIT. He is an NSF Graduate Fellow and Questbridge Scholar. His current research focuses on the fundamentals of self-assembly and mechanics but eventually wants to develop more scalable fabrication techniques that connect the nanoscale to the macroscale.

Wednesday, February 22, 2023

3:30 PM

Stauffer Science Lecture Hall, Room 102 (SLH 102)

The Zoom webinar is at https://usc.zoom.us/j/98775609685?pwd=a2lSd01oY0o2KzA4VWphbGxjWk5Qdz09.

host: Ronney

Humanitarian Engineering: Educating Bold, Responsible, and Innovative Leaders

Janet Ellzey

Professor and Engineering Foundation Centennial Teaching Fellow
Walker Department of Mechanical Engineering
University of Texas at Austin
Austin, TX

Humanitarian engineering, the application of engineering solutions to low-income or marginalized communities, is a growing field in the US and worldwide. Sometimes called development engineering, researchers and practitioners focus on culturally appropriate solutions for resource-constrained environments such as refugee camps or low-income communities. Engineering schools are increasingly recognizing the importance of training students in humanitarian engineering and are developing programs using different approaches, from student organizations to full degree programs. At the University of Texas at Austin, Dr. Janet Ellzey has built an academic certificate that provides students with several pathways to use their engineering skills to positively impact the world, including a design and build program in which student teams partner with local communities and an innovation program to develop new technologies for the International Federation of Red Cross and Red Crescent Societies. In this talk, Dr. Ellzey will discuss this exciting engineering field, describe the programs at UT-Austin with data on the diversity of students enrolled in the program, and present challenges and opportunities for universities wanting to enter this field.

Janet Ellzey is a professor of mechanical engineering and the Engineering Foundation Centennial Teaching Fellow in the Cockrell School of Engineering at the University of Texas at Austin. She received her BS and MS degrees in Mechanical Engineering from The University of Texas at Austin and her PhD from the University of California-Berkeley. After more than 30 years of conducting experimental and computational research in the field of combustion, she pivoted her career to focus on expanding unique educational opportunities for undergraduate students. Recognizing the enthusiasm that the current generation of students has for social justice, she launched a program in humanitarian engineering which she now directs. Through creative partnerships with local communities abroad as well as with major international organizations, she has developed a network to educate the next generation of leaders while positively impacting the world.

Monday, February 27, 2023

3:30 PM

Stauffer Science Lecture Hall, Room 102 (SLH 102)

The Zoom webinar is at https://usc.zoom.us/j/95805178776?pwd=aEtTRnQ2MmJ6UWE4dk9UMG9GdENLQT09.

host: Ronney

Fracture of Highly Entangled Polymer Networks

Junsoo Kim

Postdoctoral Researcher
John A. Paulson School of Engineering and Applied Sciences
Harvard University
Cambridge, MA

Polymers pollute our planet. Part of this pollution comes from tires. Every year, 0.8 kg of rubber particles are shed by tires per capita in the world.¹ A recent study showed that rainstorms wash the rubber particles into rivers, where toxic chemical compounds leach out and kill fish.² Despite its significant impact on the environment, the development of rubbers resistant to fracture has been stagnant for decades. In this talk, I will discuss how to improve the fracture properties of polymer networks, such as rubbers and gels. The key idea is that entanglements stiffen polymers but do not embrittle them, whereas crosslinks stiffen polymers and embrittle them (i.e., stiffness-toughness conflict). Therefore, highly entangled polymer networks in which entanglements greatly outnumber crosslinks can be both stiff and tough. Furthermore, whereas traditional toughening mechanisms are based on sacrificial bonds causing hysteresis and fatigue, highly entangled polymer networks achieve high toughness by stress deconcentration, leading to high strength, elasticity, and fatigue resistance. This toughening mechanism is based on the polymer topology, not chemistry, so it is generally applicable to many other polymer systems, such as various monomers, preexisting polymers,⁴ and filled rubbers.⁵ It is hoped that this work will reactivate the development of wear-resistant tires. Such materials can also be explored in other high-volume applications such as dampers and belts, as well as emerging applications such as soft robots, wearable devices, tissue replacements, bioprinting, and humanoids.

¹ P. J. Kole, A. J. Löhr, F. G. A. J. V. Belleghem, A. M. J. Ragas, Int. J. Environ. Res. Public Health, 14(10), 1265 (2017)
² Z. Tian et. al., Science, 371(6525), 185-189 (2020)
³ J. Kim*, G. Zhang*, M. Shi, Z. Suo, Science, 374(6564), 212-216 (2021)
⁴ G. Nian*, J. Kim*, X. Bao, Z. Suo, Adv. Mat., 34(50), 2206577 (2022)
⁵ J. Steck*, J. Kim*, Y. Kutsovsky, Z. Suo, under review

Junsoo Kim is a postdoctoral researcher at the John A. Paulson School of Engineering and Applied Sciences, Harvard University. He earned his Ph.D. in the Material Science and Mechanical Engineering department at Harvard University in 2022, where he studied fracture of soft materials. Before joining Harvard in 2017, he was a researcher at Electronics Telecommunications Research Institute since 2014. He earned his M.S. in 2013 and B.S. in 2011 at Seoul National University in South Korea. He co-authored 31 papers in peer-reviewed journals, registered six patents, and received fellowships, including the Ilun Science and Technology Foundation (2013) and Kwanjeong Educational Foundation (2017).

Wednesday, March 1, 2023

3:30 PM

Stauffer Science Lecture Hall, Room 102 (SLH 102)

The Zoom webinar is at https://usc.zoom.us/j/95805178776?pwd=aEtTRnQ2MmJ6UWE4dk9UMG9GdENLQT09.

host: Ronney

Additive Manufacturing of Emerging Complex Alloys with Engineered Structures

Wen Chen

Assistant Professor
Department of Mechanical and Industrial Engineering
University of Massachusetts Amherst
Amherst, MA

The increasing demands for materials serving under extreme environments call for the development of emerging classes of metal alloys with increasingly complex compositions. However, synthesis and processing of complex alloys via traditional routes are challenging. Additive manufacturing, also called 3D printing, is a disruptive technology for creating materials and components in a single print. Harnessing the vast compositional space of complex alloys and the far-from-equilibrium processing conditions (e.g., large thermal gradients and high cooling rates) of additive manufacturing provides a paradigm-shifting pathway for material design. In this talk, I will present the potential of utilizing laser additive manufacturing and direct ink writing to produce metal alloys with engineered structural hierarchy across multiple length scales. These unique microstructures give rise to exceptional mechanical and functional properties that extend far beyond those accessible by conventional manufacturing. In addition, I will discuss the abundant opportunities enabled by additive manufacturing for high-throughput materials discovery to accelerate the pace of future materials search for a wide range of applications in aerospace, biomedical, and renewable energy.

Wen Chen is an Assistant Professor in the Department of Mechanical and Industrial Engineering at University of Massachusetts Amherst. He completed his Ph.D. degree in Mechanical Engineering and Materials Science at Yale University in 2016. After his Ph.D., he worked as a postdoctoral research scientist at Lawrence Livermore National Laboratory, where he studied a variety of additive manufacturing techniques such as projection stereolithography, direct ink writing, and laser powder bed fusion. Dr. Chen's current research interests include advanced manufacturing, mechanical behavior of materials, physical metallurgy, and architected materials. He is the recipient of several prestigious awards including the SME Outstanding Young Manufacturing Engineer Award and NSF CAREER Award. He has served as an editorial board member of Scientific Reports since 2018.

Monday, March 6, 2023

3:30 PM

Stauffer Science Lecture Hall, Room 102 (SLH 102)

The Zoom webinar is at https://usc.zoom.us/j/95805178776?pwd=aEtTRnQ2MmJ6UWE4dk9UMG9GdENLQT09.

host: Ronney

Battery Avatar: First-Principles Modeling and Data Analytics

Weiyu Li

PhD Student
Stanford University
Stanford, CA

Rechargeable lithium batteries are electrochemical devices that are widely used in portable electronics and electric-powered vehicles. A breakthrough in battery performance requires advancements in battery cell configurations at the microscale level. This, in turn, places a premium on the ability to accurately predict complex multiphase thermo-electrochemical phenomena, e.g., migration of ions interacting with composite porous materials that constitute a battery cell microstructure. Optimal design of porous cathodes requires efficient quantitative models of microscopic (pore-scale) electrochemical processes and their impact on battery performance. In this talk, I will discuss effective properties (electrical conductivity, ionic diffusivity, reaction parameters) of a composite electrode comprising the active material coated with a mixture of the binder and conductor (the carbon binder domain or CBD). When used to parameterize the industry-standard pseudo-two-dimensional (P2D) models, they significantly improve the predictions of lithiation curves in the presence of CBD. On the lithium anode, dendritic growth is a leading cause of degradation and catastrophic failure of lithium-metal batteries. Deep understanding of this phenomenon would facilitate the design of strategies to reduce, or completely suppress, the instabilities characterizing electrodeposition on the lithium anode. This would improve the safety of lithium-metal batteries with liquid electrolyte and all-solid-state lithium batteries. I will present the results of our analysis, which indicate that the use of anisotropic electrolytes and buffer layers can suppress dendritic growth of lithium metal.

Weiyu Li has received her M.Sc. degree in Mechanical and Aerospace Engineering from Princeton University and is scheduled to obtain her PhD in Energy Science and Engineering from Stanford University in the Spring of 2023. Her research focuses on modeling and simulation of electrochemical transport in energy storage systems, aiming to provide mechanistic insights into the optimal design of porous electrodes, electrolyte, etc. Her other research interests include data assimilation and biomedical modeling. Weiyu Li is the recipient of the Siebel Scholars Award in Energy Science, class of 2023, and of the Princeton University Fellowship in Natural Sciences and Engineering.

Monday, March 20, 2023

3:30 PM

Laufer Conference Room (OHE 406)

The Zoom webinar is at https://usc.zoom.us/j/95805178776?pwd=aEtTRnQ2MmJ6UWE4dk9UMG9GdENLQT09.

host: Ronney

Finding Order in Disorder: Atomic-Scale Understanding of Phase Transformations

Dennis Kim

Research Scientist
University of California Los Angeles
Los Angeles, CA

Crystalline imperfections and their dynamics are essential in phase transformations and structure-property relationships in materials. Classical methods for determining atomic structures average over many unit cells. As a result, such methods cannot correctly capture atomic-level information on amorphous packing, point defects, chemical ordering, strain, and interfaces. I will first present my recent work extending atomic electron tomography (AET) to overcome the limitations of conventional methods to obtain 3D atomic packing information with picometer precision in amorphous materials. With every atom accounted for, we can understand how atoms in amorphous solids arrange in short- to medium-range order and the implications of these findings for metallic glasses. I will then discuss other systems where chemical ordering and crystalline imperfections of point defects, strain, and interfaces play an essential role in phase transformations and atomic-scale structure-property relationships. I will also present recent efforts in developing an electron thermal diffuse scattering method to determine spatially resolved lattice dynamics. The diffuse patterns are highly sensitive to differences in phonon energies. Combining high-reciprocal space sampling and high-dynamic-range imaging methods, and machine-learned interatomic potential-based dynamical simulations, we are able to observe temperature-dependent soft phonon mode dynamics and nuclear quantum effects. These findings have far-reaching implications in understanding heat transport. Finally, I will show how feedback loops powered by experimental coordinates with picometer accuracy, scattering spectroscopy, and ab initio computational methods will guide future materials discovery and design.

Dennis Kim is a research scientist at the University of California Los Angeles and holds a PhD in Materials Science from the California Institute of Technology. Prior to his current position, he was a postdoctoral associate in the Department of Materials Science and Engineering at the Massachusetts Institute of Technology and a STROBE postdoctoral fellow in the Department of Physics and Astronomy at the University of California Los Angeles. His research background is in materials thermodynamics and understanding phase transformations through state-of-the-art scattering, imaging, and quantum mechanical computational techniques. He is interested in developing and optimizing materials for various applications in thermal, energy, and quantum sciences through a fundamental understanding from the atom up.

Monday, March 22, 2023

3:30 PM

Stauffer Science Lecture Hall, Room 102 (SLH 102)

The Zoom webinar is at https://usc.zoom.us/j/95805178776?pwd=aEtTRnQ2MmJ6UWE4dk9UMG9GdENLQT09.

host: Nguyen

Recent Progress on Singularity Formation of 3D Incompressible Euler and Navier-Stokes Equations

Thomas Hou

Charles Lee Powell professor of Applied and Computational Mathematics
Caltech
Pasadena, CA

Whether the 3D incompressible Euler and Navier equations can develop a finite time singularity from smooth initial data is one of the most challenging problems in fluid dynamics. In this talk, I will present a recent result with Dr. Jiajie Chen in which we prove finite time blowup of the 2D Boussinesq and 3D Euler equations with smooth initial data. There are several essential difficulties in establishing such blowup result. We overcome these difficulties by decomposing the solution operator into a leading order operator that enjoys sharp stability estimates plus a finite rank perturbation operator that can be estimated by using computer assisted proof. This enables us to establish nonlinear stability of the approximate self-similar profile and prove nearly self-similar blowup of the 2D Boussinesq and 3D Euler equations. I will also report some recent progress on potentially singular behavior of the 3D incompressible Navier-Stokes equations.

Thomas Yizhao Hou is the Charles Lee Powell professor of applied and computational mathematics at Caltech. His research interests include 3D Euler singularity, interfacial flows, multiscale problems, and adaptive data analysis. He received his Ph.D. from UCLA in 1987, and became a tenure track assistant professor at the Courant Institute in 1989, and a tenured associate professor in 1992. He moved to Caltech in 1993 and was named the Charles Lee Powell Professor in 2004. Dr. Hou has received a number of honors and awards, including Fellow of American Academy of Arts and Sciences in 2011, a member of the inaugural class of SIAM Fellows in 2009 and AMS Fellows in 2012, the SIAM Ralph E. Kleinman Prize in 2023, the SIAM Outstanding Paper Prize in 2018, the SIAM Review SIGEST Award in 2019, the Computational and Applied Sciences Award from USACM in 2005, the Morningside Gold Medal in Applied Mathematics in 2004, the SIAM Wilkinson Prize in Numerical Analysis and Scientific Computing in 2001, the Frenkiel Award from the Division of Fluid Mechanics of American Physical Society in 1998, the Feng Kang Prize in Scientific Computing in 1997, a Sloan fellow from 1990 to 1992. He was also the founding Editor-in-Chief of the SIAM Journal on Multiscale Modeling and Simulation from 2002 to 2007.

Wednesday, March 29, 2023

3:30 PM

Stauffer Science Lecture Hall, Room 102 (SLH 102)

The Zoom webinar is at https://usc.zoom.us/j/95805178776?pwd=aEtTRnQ2MmJ6UWE4dk9UMG9GdENLQT09.

host: Pahlevan

Can't Touch This: Real-Time, Provably Safe Motion Planning and Control for High Dimensional Autonomous Systems

Ram Vasudevan

Associate Professor
Mechanical Engineering and Robotics Departments
University of Michigan
Ann Arbor, MI

A key challenge to the widespread deployment of robotic manipulators is the need to ensure safety in arbitrary environments while generating new motion plans in real-time. This talk describes a technique that constructs a parameterized representation of the forward reachable set that it then uses in concert with predictions to enable certified, collision checking. To improve computational speed, this talk describes how to represent this parameterized reachable set using a neural implicit representation without sacrificing any safety guarantees. This approach, which is guaranteed to generate safe behavior, is demonstrated across a variety of different real-world platforms including ground vehicles, manipulators, and walking robots.

Ram Vasudevan is an associate professor in the Mechanical Engineering and Robotics Departments at the University of Michigan. He received a BS in Electrical Engineering and Computer Sciences, an MS degree in Electrical Engineering, and a PhD in Electrical Engineering all from the University of California, Berkeley. He is a recipient of the NSF CAREER Award, the ONR Young Investigator Award, and the 1938E Award from the University of Michigan. His work has received best paper awards at the IEEE Conference on Robotics and Automation, the ASME Dynamics Systems and Controls Conference, and IEEE International Conference on Biomedical Robotics and Biomechatronics, and has been finalist for best paper at Robotics: Science and Systems.

Wednesday, April 5, 2023

3:30 PM

Stauffer Science Lecture Hall, Room 102 (SLH 102)

The Zoom webinar is at https://usc.zoom.us/j/95805178776?pwd=aEtTRnQ2MmJ6UWE4dk9UMG9GdENLQT09.

host: Nguyen

Large Amplitude Internal Wave Transformation Between 500m and the Surfzone

Kristen Davis

Associate Professor
Civil & Environmental Engineering & Earth System Science
University of California, Irvine
Irvine, CA

Internal waves strongly influence the physical and chemical environment of coastal ecosystems worldwide. We report novel observations from a dense and rapidly-sampling array spanning depths from 500 m to shore near Dongsha Atoll in the South China Sea to track large amplitude internal solitary wave (ISW) shoaling, breaking, and runup. During the observational period incident ISW amplitudes ranged between 78 m and 146 m with propagation speeds between 1.40 m/s and 2.38 m/s. Fissioning ISWs generated larger trailing elevation waves when the thermocline was deep, and evolved into onshore propagating bores in depths near 100 m. Collapsing ISWs contained significant mixing and reduced upslope bore propagation. Bores on the shallow forereef drove bottom temperature variation in excess of 10 degrees Celsius and near-bottom cross-shore currents in excess of 0.4 m/s. Bores decelerated upslope, consistent with upslope two-layer gravity current theory, though runup extent, Xr, was offshore of the predicted gravity current location. Background stratification affected the bore runup, with Xr farther offshore when the Korteweg-de Vries nonlinearity coefficient, α, was negative. Fronts associated with the shoaling local internal tide, but equal in magnitude to the soliton-generated bores, were observed onshore of 20 m depth.

Kristen Davis is an Associate Professor of Civil & Environmental Engineering at the University of California, Irvine. She is an engineer and oceanographer who is interested in studying how physical processes shape coastal waters – combining principles of fluid mechanics, oceanography, and ecology. Kristen uses both field observations and numerical tools to examine circulation in the ocean, its natural variability, and influence on marine ecosystems and human-nature interactions. Kristen earned a Ph.D. in Civil & Environmental Engineering at Stanford University in 2009 and was a postdoctoral researcher at the Woods Hole Oceanographic Institution and the Applied Physics Laboratory at the University of Washington. Her recent research is focused on understanding nonlinear internal wave dynamics and the feasibility of the large-scale, offshore cultivation of macroalgae for the production of biofuels and as a strategy to sequester carbon dioxide.

Wednesday, April 12, 2023

3:30 PM

Stauffer Science Lecture Hall, Room 102 (SLH 102)

The Zoom webinar is at https://usc.zoom.us/j/95805178776?pwd=aEtTRnQ2MmJ6UWE4dk9UMG9GdENLQT09.

host: Spedding

Interactions of Shock Waves and Turbulence Through Numerical Simulations

Ivan Bermejo-Moreno

Assistant Professor
Department of Aerospace & Mechanical Engineering
USC
Los Angeles, CA

Hypersonic flight and propulsion pose fundamental challenges that arise from interactions between shock waves and turbulence. These interactions can be beneficial, enhancing the mixing of fuel and oxidizer in a scramjet engine, but they can also be detrimental, compromising the integrity of the flying vehicle through uncontrolled aerothermostructural coupling. This presentation will highlight recent developments on the prediction and understanding of these phenomena by means of high-fidelity numerical simulations. First, focus will be placed on interactions of shock waves reflecting off turbulent boundary layers that develop along rigid and flexible walls, by loosely coupling a wall-modeled large-eddy simulation solver for the fluid flow with an elastic solid structural solver that accounts for geometric nonlinearities. Strong shock/boundary-layer interactions will be emphasized, resulting in mean flow separation and low-frequency unsteadiness that can couple with natural frequencies of the solid structure. Simulation results will be compared with supersonic wind-tunnel experiments. Second, the enhancement of scalar mixing under canonical shock-turbulence interactions will be addressed by means of shock-capturing direct numerical simulations, evaluating the effects of the shock and turbulence Mach numbers, and the Reynolds number. Statistical analyses will highlight changes along the mean flow direction of scalar variance and dissipation-rate budgets, flow topology, and alignments of the scalar gradient with vorticity and strain-rate eigendirections. A novel methodology to track the time evolution of geometric and physical quantities of turbulent flow structures will be introduced and applied to study the dynamics of isoscalar surfaces across the shock-turbulence interaction.

Ivan Bermejo-Moreno received an engineer's degree from the School of Aeronautics at the Polytechnic University of Madrid, Spain (2001). He then worked for two years in the aerospace industry (GMV) and received a Fulbright Fellowship to pursue M.Sc. (2004) and Ph.D. (2008) degrees in aeronautics from the California Institute of Technology. Afterwards, he held a postdoctoral research fellowship at the Center for Turbulence Research, Stanford University/NASA Ames Research Center (2009-2014). He joined the Aerospace and Mechanical Engineering Department at the University of Southern California as assistant professor in 2015. His research combines numerical methods, physical modeling, and high-performance computing for the simulation and analysis of turbulent fluid flows involving multi-physics phenomena. He is a recipient of the Rolf D. Buhler Memorial Award, the William F. Ballhaus Prize, the Hans G. Hornung Prize, and the NSF CAREER Award.

Wednesday, April 19, 2023

3:30 PM

Stauffer Science Lecture Hall, Room 102 (SLH 102)

The Zoom webinar is at https://usc.zoom.us/j/95805178776?pwd=aEtTRnQ2MmJ6UWE4dk9UMG9GdENLQT09.