August 29^th Introduction

Our first class will be about us. Everyone will have five minutes each to present their research to the class. You can use powerpoint, keynote or a poster as a visual aid. You are also encouraged to ask questions.

September 5^th prof. Bei Fan

Engineered Surfaces for a Sustainable Future

Bio: Dr. Bei Fan received her Ph. D in Mechanical Engineering University of California San Diego in Dec 2019 and completed her postdoc training at Lawrence Berkeley National Laboratory in June 2021. Currently, she is an Assistant Professor in Mechanical Engineering at Michigan State University. Her research interests cover broad areas including thermal fluid science, microfluidic devices, electrokinetics, energy conversion and harvesting, desalination, and micro/nano fabrication. Her work has been published on high-reputation journals such as Nature Communications, Langmuir and Applied Physics Letters and reported by public media including Science Daily, Phys.org, Physics Today, etc. She was awarded with NSF grant awards.

Abstract: Water is ubiquitous on earth and is also a renewable energy source. Electrokinetic flow, which can generate streaming potential and streaming current through the flow of an electrolyte over a charged surface, cab be used for liquid energy harvesting. However, the yielded low energy conversion of electrokinetic flow on flat surface and superhydrophobic surfaces limited its practical applications. Here, I will present the advances of our group in improving the energy conversion via novel engineered surfaces. We showed that an enhanced streaming potential can be obtained through the flow of salt water on slippery liquid-filled surfaces to harness both of the electrolyte slip and associated surface charges. The highest figure of merit, in terms of the voltage generated per unit applied pressure, of 0.043 mV/Pa is obtained. I will also show the tunability of streaming potential by changing the geometry of liquid-filled surface and the properties of filled liquid. These results lay the basis for innovative surface engineering methodology for the study of electrokinetic phenomena at the microscale with possible application in new electrical power sources. Besides, I will also show our recent results of droplet impinging and sustainable drag reduction over other novel rising slippery surfaces.

September 12^th Dr. Chunheng Zhao

Numerical simulation of contact lines

Bio: Dr. Zhao is a postdoctoral research associate working on computational fluid dynamics in Professor Taehun Lee’s group at the City College of New York. He obtained his Ph.D. in Mechanical Engineering from the City College of New York, where he focused on multiphase flow modeling and simulation using the Lattice Boltzmann Method (LBM). He worked as an intern with researchers in Argonne National Laboratory, where he concentrated on large-scale simulation, distributed systems, and GPU acceleration. Following that, he spent a year as a postdoctoral research associate in Paris, collaborating with Professor Stephane Zaleski on Adaptive Mesh Refinement for multiphase flow. He developed a C++ version of IMEXLBM and conducted scaling work on the Theta and Polaris clusters. Currently, he is developing continuous/discontinuous Galerkin lattice Boltzmann methods based on Nek5000 and NekRS.

Abstract: Contact line problems have significant implications in various industrial applications. When two or more fluids or solids come into contact, surface effects can lead to complex morphological deformations. Additionally, fluid-solid interactions often necessitate multi-scale analysis. In the face of these challenges, computational fluid dynamics (CFD) plays a crucial role in both mathematical modeling and experimental analysis. In this seminar, I will present several numerical strategies for addressing contact line problems. I will demonstrate the application of a straightforward explicit precondition-correction finite difference method using the free AMR software, Basilisk. Furthermore, I will introduce a more advanced model, the three-phase VOF, in which I propose a hybrid continuum surface tension force to account for surface effects.

September 19^th PROF. Spencer Zimmerman

Bio: Dr. Zimmerman is an Assistant Professor in the Department of Mechanical Engineering at Stony Brook University. He completed his PhD at the University of Melbourne in 2019, where he focused on multi-component anemometry in wall-bounded flows. In addition to the subject of this talk, his current research involves development of novel conventional and interferometric imaging systems for flow diagnostics.

Abstract: The relationship between high- and low-order statistical moments of the fluctuating velocity is at the heart of the turbulence closure problem. In this talk, we examine joint moments of the streamwise and wall-normal velocities in turbulent wall-bounded flows, and identify consistent relationships that persist throughout the logarithmic layer. These relationships, along with insights gleaned from analysis of the mean momentum balance equation, are then used to model the probability distribution of the instantaneous Reynolds shear stress (RSS). It is argued that this model suggests a particular relationship between the efficiency of momentum transport (i.e. the RSS correlation coefficient) and the magnitude of the mean shear.

September 26^th Prof. Joon Ahn

Unlocking Gas Turbine Efficiency: Advancement in Large Eddy Simulation for Heat Transfer Optimization

Bio: Joon Ahn has received his B.S. (1997), M.S. (1999), and Ph.D. (2003) degrees from Seoul National University, Korea. While in school, his research topic was mainly heat transfer in gas turbines. After graduation, he worked as a postdoctoral researcher at the University of Tokyo, Japan, for two years (2004-2006), mainly conducting turbulence control research. In 2006, he was appointed as a senior researcher at the Korea Institute of Energy Research (KIER) and conducted research on cogeneration and industrial boilers for four years. He has been a professor at Kookmin University in Seoul, South Korea since 2010. His research interests include heat transfer and combustion problems in energy systems.

Abstract: This presentation will explore the application of Large Eddy Simulation (LES) in addressing gas turbine heat transfer challenges. In order to achieve heightened cycle efficiencies by operating turbine blades at temperatures surpassing the thermal limits of materials, active cooling of the blades becomes imperative. This entails the creation of intricate cooling passages within the blade, with cooling air injected onto the outer surface to establish an insulating film. The intricate interplay of flow dynamics and heat transfer involved in this process is not accurately captured by Reynolds-Averaged Navier-Stokes Simulation (RANS). Throughout this presentation, we aim to shed light on instances where LES successfully predicted local heat transfer distributions or turbulence levels that were inadequately captured by RANS. Furthermore, we'll delve into how LES provided insights into information that proved challenging to obtain through
experiments alone.

October 10^th Prof. Lin Dong

Towards Self-Sustaining Biomedical Devices: Energy Solutions and Smart Interfaces

Bio: Lin Dong is an Assistant Professor in the Department of Mechanical & Industrial Engineering at New Jersey Institute of Technology (NJIT). She received her Ph.D. from Stevens Institute of Technology in 2017, where she was honored with the Innovation and Entrepreneurship Doctoral Fellowship. She previously was a Research Associate at Thayer School of Engineering at Dartmouth College, where she was also a recipient of the Arthur L. Irving Institute for Energy and Society Award. Her research focuses on nanomaterials and nanofabrication technology, flexible electronics, soft robotics, and the development of energy harvesting and sensing devices for biomedical applications.

Abstract: Biomedical self-sustainable energy generation, as opposed to invasive battery replacement, represents a groundbreaking advancement in extending the lifespan and effectiveness of implantable biomedical devices such as cardiac pacemakers. However, few in vivo studies have demonstrated energy-harvesting designs that are viable for clinical application. Currently, there is a shortage of technologies capable of efficiently converting the mechanical energy of the heart into electrical power without disrupting cardiovascular functions. In this seminar, I will discuss our recent efforts in addressing these challenges. We have developed integrated piezoelectric-based energy harvesting and sensing systems that can be seamlessly incorporated into existing implantable medical devices, facilitating easier clinical translation. Our in vivo results suggest that this innovative energy harvesting and sensing approach could offer a transformative and practical power and diagnostic solution for cardiac pacemakers and the next generation of implantable biomedical devices. Additionally, I will introduce the application of soft materials with smart mechanical structure designs in biomedical devices, and explore strategies for establishing a synergy between engineered means and biomedical ends. This includes the development of biomechanical energy harvesting systems and advanced human-machine interfaces for prosthetic robotic hands.

October 24^th Prof. Yuki MIURA

Identifying, measuring, and managing socioeconomic impacts of floods amid climate change

Bio: Dr. Yuki Miura is an assistant professor at the Department of Mechanical and Aerospace Engineering and the Center for Urban Science and Progress at New York University. She is also a faculty advisory board member at the Volatility and Risk Institute at NYU Stern School of Business. Previously, she worked at Morgan Stanley in climate risk management and quantitative strategy. She serves as a NYC Panel on Climate Change. Her research is at the intersection of engineering, climate science, finance, and social sciences. She has collaborated with the National Center of Atmospheric Research and the governments of New York State/City. Her work has been recognized through publications in leading journals and featured in The New Yorker and The New York Times. She holds PhD, MPhil, and MS from Columbia University and BE from Keio University.

Abstract: Climate change worsens the impacts of hurricane-induced flooding, making it crucial to develop effective methods for identifying, measuring, and managing these escalating risks. Addressing such risks triggered by climate change and natural hazards is challenging due to inconsistent historical data, unpredictable weather patterns, conflicting stakeholder objectives, and a multitude of potential adaptation solutions. My research offers practical tools for assessing the socioeconomic impacts of floods and other climate-related risks. These tools are designed for real-world application, incorporating feedback from a range of stakeholders—including municipal offices, emergency management teams, and water resource experts. This talk will cover analyses at multiple scales, including local (New York City), national, and global levels.

October 31^th Prof. Indranil Sengupta

Data science-driven improvements of environmental risk management models- applications in Florida rainfall

Bio: Indranil SenGupta is Professor of Mathematics and Statistics at the Hunter College, City University of New York (CUNY). Before joining CUNY, he was a professor of Environmental Finance & Risk Management in the Institute of Environment, and Department of Mathematics and Statistics, at the Florida International University. Before that he was a professor and the graduate program director of the Department of Mathematics at the North Dakota State University. His research areas are stochastic processes and data-science with applications in finance and environmental sciences. His research was supported by internal and external fundings, including DARPA, and Simons Foundation.

Abstract: For this presentation, we implement some "image-based" techniques for estimating rare events in environmental and financial time series. We employ specific neural networks to recognize patterns in time series "photos", followed by a bootstrapped image similarity distribution to predict unusual events. This analysis will show that the suggested technique can identify between "event" (significant) and "non-event" (not so significant) images for an environmental data, and effective even with the access to little and highly imbalanced data. A concrete application will be provided for Florida rainfall.

ME Seminar Lineup, Fall 2024 Bei Fan fluids09|05Chunheng Zhao cfd09|12Spencer Zimmerman fluids09|19Joon Ahn heat transfer09|26Minghao Qiu atmos sci10|10Lin Dong materials10|16Yuki Miura climate10|24Indranil Sengupta climate10|31Pei Te geotech11|07Xianlian Zhou biodynamics11|21 Mech@CCNY

Thursdays 2-3 pm, ME254